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• Published: 08 November 2022

Career feature

Mind the gap: closing the growing chasm between academia and industry

• Alexander J. Spicer   ORCID: orcid.org/0000-0002-7819-1906 1 , 2 ,
• Pierre-Albert Colcomb 3 &
• Ann Kraft 4  

Nature Biotechnology volume  40 ,  pages 1693–1696 ( 2022 ) Cite this article

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Academia and the pharmaceutical industry must unite to offer more comprehensive opportunities for those wanting to stay in research in the field of drug development.

Within the field of drug development, a continued chasm between academia and industry is being exposed. Previous analysis has shown that of the 252 new drugs approved between 1998 and 2007 by the US Food and Drug Administration, a growing majority has been produced by biotechnology companies. Most of these drugs were acquired from university projects; in turn, there is an ever-shrinking number of large pharmaceutical companies developing innovative medicine themselves 1 .

In the United States, a significant amount of public investment funded the development of many drug candidates submitted for approval during the 2010s. Notably, this amount grew substantially from that of previous decades 2 . Among the candidates were blockbuster drugs such as remdesivir from Gilead Sciences, venetoclax from AbbVie and atezolizumab from Roche’s Genentech subsidiary 3 .

Despite the demonstrated success of publicly funded research, spinouts from universities and reliance of big pharma pipelines, research positions at universities are becoming ever harder to fill as the attractiveness of postdoctoral positions wanes 4 . Much of this can be attributed to the lack of career progression 5 and the extremely low pay available for positions at the qualification level 6 .

Developing talent and having access to new drug developers is clearly vital for the success of the field. However, as a result of the previously stated issues and the fact that industrial postdoctoral positions are rare 7 , it is hard to see how industry will fill the void via new postdocs. Moreover, both industry researcher and academic postdoc positions rarely encourage blue-sky thinking and curiosity, with the accompanying prestige in grants, publications and conference appearances. Industry research drives value to its own portfolio and aims solely to return investment to shareholders 7 . As such, it is often considered a failure for a postdoc to move into the area, and academics are hesitating to go 8 .

As a result, there seems to be two sides of a wall that rely on one another, yet seldom share their unique abilities to conquer the others’ shortcomings. If both sides were to come together and amalgamate specialist research, the mentorship and support of talent, and their drug development skills into the next generation of biotech entrepreneurs, it could allow for a new wave of expertise and help reach the goal of creating more drugs that bring about great patient benefits.

Drug developers

Drug developers are often unconventional people, eager to venture into new areas and test their boundaries. Therefore, they can feel out of place within academia 9 . Unfortunately, during their educational journeys from undergraduate to postdoc, they are seldom prepared to take a leap from academia into industry and drug development 10 . Multiple subjects are never taught, including the nuances of topics such as commercial, economic, regulatory, law and intellectual property (IP) skills, as well as knowledge of basic project management. In addition to these hard skills, they also lack training in the vital soft skills such as networking. With such a substantial gap in the education of a new startup generation, it is no wonder that fewer biotech workers are succeeding 10 .

A difference in culture in education and funding

Unsurprisingly, some of the best schools for an education in drug development are located in the European Union (EU), United Kingdom and United States 11 , with curricula ranging from early stage discovery to the regulatory approval process. European academic entities and large pharma companies have had many successful collaborations — one notable example being the collaboration between the University of Oxford and AstraZeneca, which led the development of a COVID-19 vaccine 12 . However, US-based companies and their respective academic groups have formed strong alliances; thus, most drugs that end up reaching the market come from US-based institutions and their subsequently formed biotechs — a trend consistently seen within drug development 1 .

The difference in the financing ecosystem between Europe and the United States can also potentially explain why fundamental education in drug development may be superior in Europe, while the United States does better in translating and commercializing discoveries. European biotech has remained reliant on US funding throughout each biotech’s life cycle. While trends have changed in recent years with later-stage funding limited within the established EU vehicles (as opposed to early stage funding 10 years ago), many EU-based biotechs are turning to US venture capital and public markets such as NASDAQ to access the necessary capital 13 . With a less-risk-averse set of investors in the United States and more of them active in the sector, more inventions can be funded 13 . Nevertheless, if it were possible to generate more aligned science between academia and industry, as well as management teams who are experienced to navigate the intricate maze, it may be possible to also benefit investors as well.

Building relationships with early stage venture capitalists, such as Arch Venture Partners, Flagship Pioneering, Third Rock and now Deerfield Management, as well as RA Capital in the United States and Sofinnova Partners in Europe 13 , and having their involvement in shaping young drug developers careers from an early stage is another aspect to creating a more productive sector.

Within the academic setting

Academia often misses the entire purpose of drug development — understanding how to take a scientific idea, translating it to the clinic and then bringing it to the market in the most timely and cost-effective manner. It cannot be achieved by small-scale projects with minimal funding from one lab in a university setting, but through cooperative work between academia and industry.

Students and early career professionals without any exposure to the industry may not understand the major differences between programs and how they are rooted in different disciplines, and therefore end up on a course that does not align with their career goals. This extends to educators who have not built a program that benefits an early career professional’s overall goal, and it often leads to a financial penalty for those who complete the course 14 .

Despite some differences in programs and modules, they typically contain a research-based project that simulates the real-life expectations of a drug development process. Although the projects will provide some insight, they are often too limited in scope to provide exposure to a comprehensive drug development program. This gives a false impression of industry to students, which further harms their integration from academia to industry 8 . This false sense is further instilled by the fact that these projects are highly unlikely to progress out of the educational environment to become a viable commercial project. Although basic science should be and is necessary to bring about scientific revolutions, focusing drug development projects on discovery and preclinical science generally does not match the industry’s needs.

The overarching theme is that people achieve their degrees within academia and are taught pure science rather than tackling the practical side of the field. This brings us back to the fact that there is a lack of drug developers bringing their knowhow back to students, which further perpetuates the divide. Although professionals not returning to academia is not unique to the pharma and biotech industries, there is a limited number of academics who are well versed in the nuances of day-to-day drug development. In addition, few professional drug developers have the ambition to finalize their careers in the field of education. This leads to educational experiences being heavily entrenched in scientific rhetoric, lacking the translational element to real-life applicability.

The expertise and experience of educators is paramount to the student experience. Moreover, having instructors with real experience would enable them to offer advice on the many career options available in such a broad industry. We have seen educators leave academia and do well in industry, such as David Altshuler (chief scientific officer and executive vice president of global research at Vertex Pharmaceuticals), Sandra Horning (former chief medical officer at Roche and Genentech) and Jay Bradner (former president of Novartis Institutes for BioMedical Research). However, few return to lead a curriculum. This is critical to change because it is important that seasoned drug developers share the lessons that they have learned, as well as their ability to understand and navigate critical decisions in their personal and professional lives.

If professionals are unwilling to return to academia, it would be wise for students to gain hands-on experience via industrial internships in the early stages of the educational process and to open collaborations later in their careers. One notable example is Northeastern University in Boston, where the new Roux Institute integrates research, venture and entrepreneurship. The program has undergraduate programs that span five years instead of four, with students spending six months as interns within the industry. Another example of this integration is the Health Acceleration Challenge and Health Lab Accelerator, which are shared between Harvard schools. However, these are two isolated examples that leave many students without these skills.

Currently, our system does not provide the proper support for students throughout all stages of their academic life. For the drug development field to thrive, it is vital that students are given access to mentors. Fundamental changes are needed to bring together the unique expertise of educational institutes and the knowledge of the private sector to better train the next generation of drug developers, form the next wave of companies and advance the field. However, there seems to be limited cooperation and, even more concerning, limited desire between the two sides to combine their efforts. They understand each other’s survival is dependent on the success of their relationship, but neither seems ready to make the first move to make it better.

Industry flaws

Despite the vital nature of early exposure to industry to develop both necessary practical and technical skills, there are limited opportunities for students to interact with industry professionals 15 . One such example is Immunocore, which recently announced it had taken on 16 students during their undergraduate degrees. This represents around 5% of Immunocore’s total employees, which is a major investment. However, overall, there remains a limited number of positions available in the industry for undergraduate, graduate and master’s degree students. This perpetuates the cycle of these students needing to continue their academic careers in a doctoral program; approximately three-quarters of students who complete their master’s degrees continue to a doctoral program 16 . Notably, a PhD is almost ubiquitously required by any company to progress in the pharma industry. This career path will deepen a person’s scientific understanding, but it is possible that it makes an individual even more distant from roles and duties needed in emerging life science enterprises.

The pharma industry likes to continuously remind the public that it is innovative and forward-thinking. While true — as witnessed through the advent of cell and gene therapies, personalized and digital medicines, and the lightning speed in which the COVID-19 vaccines were developed — despite the ever-expanding need for multiple disciplines to work alongside one another cooperatively, many roles in biotech and in pharma companies require a PhD. Although the industry has never liaised with that person or that PhD program, we nevertheless perpetuate the need for a specific archetype of person to join the field even though it may not answer our problems. As such, both the employee and employer end up facing a financial penalty; the employee’s wage stagnates, and the employer does not receive the desired work potential 8 .

Scientific knowledge is fundamental, but more than that is needed to create the right professional, and for that person to integrate well into a company. This is especially true considering that being able to decide quickly requires an entirely different skill set, and this is necessary should a person choose to start their own biotech. Knowhow and intuition can only be acquired through practice 17 . Educational credentials such as the sought-after MD, PhD, MPH and MBA (or even Juris Doctorate) are a valuable baseline. However, simply acquiring these credentials often overlooks an elementary point: will you be able to work with this person to bring this idea to fruition as effectively as possible? Simon Sinek, an inspirational speaker, points out that trust is a better team selection criterion than performance. Sinek echoes Antoine Papiernik’s point about companies backing the same inventors multiple times. Although weighted metrics toward performance are systemic in all businesses, a middle performer who is also a trusted person brings more to a team than a high performer who has developed low trust. However, these middle performers will likely be skipped in the recruitment for biotech companies due to their lack of apparent qualifications.

The crux of the matter

The culmination of this is that educational establishments and the industry are meant to act in a mutualistic symbiotic relationship, similar to clownfish and sponges, instead of adversarial rivals that cannot admit they need one another. We currently have a system where the R&D comes from the university; however, there is not enough opportunity or progression along this career path. Subsequently, as these people came through a system that never was supported by industry, they move to attain further education, such as working toward a MSc, MPH or a PhD. To ease the current pressures on the job market on both sides, a solution must be found to support early stage career professionals and provide them with a real option to move into industry, while also giving them an understanding of what it takes to develop drugs.

A proposal for change

To bring about real change, all members of the drug development sector — governmental bodies as well as public and private entities — must unite to support the next generation. They need to open a dialog to create multiple opportunities for young drug-developing professionals who can gain expertise from seasoned professionals and apply this knowledge. Here, we suggest programs that could drive such changes and explain how these could benefit the collective.

Develop a curriculum that suits the needs of the students

We need to develop a comprehensive program for all students and postgraduates that is not only pure science but also considers the major skill sets that a drug developer needs, with input directly from the industry. As discussed above, it has been suggested that commercial, law and IP, finance, manufacturing, regulatory, project management and other skills are all necessary for drug developers.

This curriculum can only be created with input from the entire ecosystem. This may mean that courses are taught with modules from different faculties and that basic introduction courses must be developed. Facilities are already available within many establishments; thus, this is a logistical issue rather than a resource one, lowering the bar for change.

Finally, these curricula should be taught by both academics and industry experts, as this will allow for the benefits of both sides to be taught together. These curricula should evolve to align with the changing industry, such as when new technologies and regulations enter the frame. As such, curricula boards must have a changing board of advisors made up of academics and drug development professionals but must include governmental as well as private funds to achieve economic goals such as job opportunities for students and early career professionals, while also providing companies with a return for their enduring efforts in these collaborations.

Establish centers of excellence to serve innovation and education

Pharma companies have become heavily dependent on acquiring or licensing third-party biotech products instead of funding large internal R&D departments. However, there is currently little partnering with academia to fund academic research or to educate future drug developers. We argue that pharma should align with academic institutions to create centers of excellence through long-term research collaborations that allow students to participate in the full drug development process from discovery to preclinical and clinical research. Such collaborations have already seen success.

The high level of rivalry between large pharma companies makes it likely that individual companies would align independently with their chosen institutions to focus on a particular disease state, therapeutic area or even therapy area. In turn, these institutions would become recognized experts in particular fields. The sponsoring company could have an option to acquire the resulting research. As part of the program, they could provide internships for students to work on downstream aspects of the drug development process such as clinical testing, market research, target validation or regulatory strategy.

This would continue to bring new first-in-class assets into the pipeline, create potential future niche pharma players and move drug development away from ‘me too’ development and the dominance of a handful of companies 18 . This could also allow for new drugs to be developed in much-needed areas, such as neglected tropical diseases and other infectious diseases. In this way, it would propel a new wave of pipeline drugs, biotech and entrepreneurs. This benefits research by developing new drugs while also bringing about a more investable group of first-time entrepreneurs that could align with seasoned professional mentors who could pair off into companies. In this system, the innovations, entrepreneurs and startups would have been served by their respective universities, rather than the other way around, which is the case at present 19 .

The curriculum would set out to provide students with the ability to network and to understand the development process. Thus, they would have worked alongside a larger company on their R&D strategy; in turn, this means that venture capitalists would have a lower risk as they would be investing in validated and trusted teams. Finally, this takes a major gripe away from young academics who are under intense pressure to publish and obtain research grants. This vicious cycle ensues where the pressure becomes insurmountable. Instead, the young academics can focus on what academic science is about, disseminating findings via publications and conferences. The new monetary benefit from forging relationships between younger academics and companies will mean that research of greater commercial interest will be conducted. In turn, this will mean that young researchers’ careers will not always be at risk 20 .

Internship and mentorship programs

Currently, students are required to seek internships and mentors, which can be difficult. Often, both parties — industry and student — are willing but they do not know how to reach each other. Efforts have been made in this area, but with some more successful than others. One notable example is VC University, a joint initiative from the University of California–Berkley School of Law, the National Venture Capital Association and Venture Forward, in which students who are typically not represented in venture capital can enter the program to gain valuable connections and experience. The program even includes a specific life science track to hone industry-specific skills. However, initiatives such as this are few and far between, and many students are left behind. More platforms that work in this way would be beneficial as different sectors in pharma often require distinct skill sets. Therefore, teaching students to understand how the sectors work would be an excellent way to support their career development. Furthermore, these programs act as professional leverage for individuals to excel in their careers. Every drug developer remembers when they were at their starting point, and they remember the influential person that supported their career.

Collaborative working groups

With the lingering COVID-19 pandemic and resulting Zoom fatigue, in-person events are back and more popular than ever. These events are necessary for like-minded individuals to come together and discuss everything from life to their ongoing work efforts. It is important to set up collaborative groups whereby scientists of similar disciplines can connect outside of conferences and openly discuss what they are up to, share tips and tricks and work collaboratively. This would also allow new drug developers to take in different perspectives of what it takes to bring ideas from the bench out into the world.

As examples, Deerfield Management and Alexandria Venture Investments are both aiming to bring biotech campuses to New York City. Similarly, the French government has supported a public biocluster for oncology in Paris, with support from Sanofi, Gustave Roussy, Inserm, Institut Polytechnique de Paris and the University of Paris-Saclay. Whether publicly or privately funded, these clusters bring about opportunities for chance interactions, whether sharing ideas or the opportunity to network with people outside of their immediate organization.

Bringing students into the field

Beyond the widening of the curriculum background, it would be valuable for both biotech and pharma companies and academic institutions to propose and implement codirected educational positions, taking place ideally in the labs of both organizations and managed by directors from academia and industry. This has already been successfully implemented in France under the CIFRE status (Industrial Agreements of Training through Research), immersing students who have completed their master’s degree into the realities of R&D in industries within a funded PhD position.

Such a system is a triple-win solution. First, the student gets firsthand details and experience on how pure science translates into development and how patients and end-users benefit. They are exposed to the expertise needed to be a well-rounded drug developer with skills such as non-clinical and chemistry, manufacturing and controls (CMC) development, regulatory and clinical affairs, finance, business development and IP. Second, the academic partner’s relationship with industry is strengthened, which can lead to further long-term collaboration and funding. No matter what the student elects as career choice, building strong relationships with alumni in both academia or industry is valuable. The industrial partners will also usually pay for the PhD position, which provides the academic lab with funding for one more fulltime employees and alleviates worries of funding in smaller groups. Third, the industrial partner sees a wider and more diversified pool of talents nurtured by the research excellence of academia who possess the applicable knowhow to translate science to the patient’s bedside.

Conclusions

Many steps must be taken to facilitate the emergence of new therapeutic alternatives and their translation into lifesaving drugs. Among these, improving the relationship between those in the biopharma industries and academic institutions while also removing some cultural differences would benefit all parties involved. Students would receive knowledge that aligns with current knowhow and that will be necessary for their success; in turn, this would increase job prospects. Universities would have a curriculum that would lead to better business relationships and a more significant revenue stream. In addition, industry could have a pool of new technology to bring into their organizations, as well as a qualified workforce.

We hope that the stakeholders reflect on these ideas and acknowledge that we cannot continue with this divide. Shaping the next generation’s future through academic–industry collaboration is important to continue to propel our industry to new and greater heights. Bringing together mentors, a proper curriculum and initial funding from seasoned partners could give rise to a more successful startup ecosystem, which will finally be properly supported from the first day of education. It would also bring Europe out of its credit risk to venture capitalists and lead to more venture creation, as we see in the United States.

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Acknowledgements

The authors acknowledge A. Papiernik, whose initial piece began the momentum on this manuscript. A. Papiernik’s continued communication throughout the drafting of this has been of great help. He brought the experience and perspectives as one of the leading members of the venture capital communities to drive one of his own lessons: ‘Invest in people’. It has been a pleasure to work with him and the wider Sofinnova Partners team. A.J.S. would like to acknowledge the continued effort of J. Jalkanen, who has put much effort into his education both within this industry and in supporting his academic studies. A.J.S. would also like to thank his fellow students at the University of Turku, E. Louramo, P. Tatsis and B. Berki, for their backing and views in writing the manuscript.

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Alexander J. Spicer

MDP Drug Discovery and Development, Institute of Biomedicine, Faculty of Medicine, University of Turku, Turku, Finland

Genethon, Evry-Courcouronnes, France

Pierre-Albert Colcomb

Oklahoma State University, Center for Health Sciences, Tulsa, OK, USA

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Spicer, A.J., Colcomb, PA. & Kraft, A. Mind the gap: closing the growing chasm between academia and industry. Nat Biotechnol 40 , 1693–1696 (2022). https://doi.org/10.1038/s41587-022-01543-4

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Ready for launch: Reshaping pharma’s strategy in the next normal

As COVID-19 cases continue to spread across the globe, the repercussions in healthcare extend across the value chain from patients and families to clinicians and pharmaceutical companies.

The industry faces a dual challenge. As well as helping to tackle COVID-19 spread by developing and distributing new vaccines and tests, it must continue to deliver innovative therapies and diagnos­tics to clinicians, patients, and healthcare systems—even as R&D, manufacturing, and supply chains are struggling to maintain business as usual.

An earlier McKinsey article considered how pharma companies can reorient their commercial model to respond to the new environment. Below, we focus on launch activities and identify five success factors to consider for commercial launches in the next normal.

Familiar challenges and new complications

Even before the COVID-19 outbreak, launching a new drug was far from straightforward. Forty percent of worldwide drug launches between 2009 and 2017 failed to meet their two-year sales forecasts. 1 McKinsey analysis of pharmaceutical-industry data from Evaluate, August 2020. A successful launch must overcome a series of barriers, including intensifying competition, increasing pricing pressure, growing access challenges, and rising expectations among caregivers and patients. The pandemic and its economic consequences have added further complications to what was already a risky launch environment.

We analyzed 86 launches scheduled for 2018 onward with expected sales in excess of $300 million. We found that between February and August 2020, all of these launches were disrupted through delays, lost revenues, or both. Companies chose to delay launches in 45 percent of cases, regulatory delays affected another 40 percent, and other external factors such as supply-chain problems accounted for the remaining 15 percent of delays. 2 This article draws on insights from a global survey conducted by McKinsey in June 2020 among 101 managers with recently launched drugs that had not reached their peak sales or drugs scheduled for launch between January and June 2020 that had been delayed. In the United States, for instance, the median interval between approval and first scripts had increased more than threefold by May 2020, from 17 to 58 days, although it shrunk back to 21 days by September. 3 McKinsey analyzed products launched from March 2020 or awaiting launch, using data from PHAST (Pharmaceutical Audit Suite) and Evaluate. For products not yet launched, the interval between the FDA-approval date and September 2020 was used as a proxy for the interval between approval and launch.

The pandemic also had a marked impact on the financial performance of the launches we analyzed. In 50 out of the 86 disrupted launches, companies lowered their expectations by more than 25 percent. Overall, we estimate that the changes in analyst consensus expectations between March and August 2020 represent a 9 percent decline in the net present value of the 86 drugs—the equivalent of a total loss of some $10 billion globally. 4 McKinsey used August 2020 data from Evaluate and estimates from March 2020 or earlier to calculate how the net present value of the 86 drugs changed in the months following the outbreak of COVID-19.

Why the traditional launch model is losing effectiveness

It is too soon to evaluate the full impact of the COVID-19 pandemic on drug launches. However, it is clear that major shifts in the way that healthcare professionals (HCPs) interact with pharma companies will present a challenge for the traditional launch model, with its reliance on face-to-face meetings with physicians and its “one size fits all” approach to engagement.

One immediate consequence of the pandemic has been a drastic reduction in pharma companies’ visits to HCPs. A survey conducted by McKinsey in Europe shows that the average number of in-person contacts between HCPs and pharma sales reps was 70 percent lower in September 2020 than before the pandemic. 5 McKinsey COVID-19 Survey: EU Physician Experiences, Expectations, and Perspectives on Pharma Engagement; survey in the field in May and September 2020. In parallel, HCPs’ adoption of digital channels and telemedicine has accelerated for interactions with patients and pharma reps alike. In the same survey, the HCPs who are highly open to remote engagement with sales reps report conducting almost half of their patient consultations remotely as well.

However, this broad overview masks considerable differences in HCPs’ preferences and expectations. A McKinsey survey conducted in May and September 2020 to assess sentiment among more than 900 physicians in five European countries yielded a patchwork of responses (Exhibit 1).

Only 18 percent of the physicians surveyed in May were willing to accept reps’ visits, but by September, that percentage had risen to 31 percent, suggesting that preferences shift over time as infection rates change and HCPs adjust to new circumstances. 6 McKinsey COVID-19 Survey: EU Physician Experiences, Expectations, and Perspectives on Pharma Engagement; survey in the field in May and September 2020. Preferences also vary by country. In the September survey, more than 50 percent of HCPs in France, Germany, and Italy expressed a willingness to accept regular face-to-face visits from reps, but only 11 percent of their UK peers felt the same way.

These findings suggest that the traditional pharma commercial model will likely struggle to adapt to a different world. When reps venture back into the field, they will need to address the plurality and access challenges of the new interaction landscape. To do that, they will need to consider a new approach to launches: one that is digital, local, and personalized.

What next? Five success factors to consider for a launch strategy

For a pharma company looking to reinvent its commercial model, the launch of new products is a golden opportunity to try out new techniques and gauge their impact before rolling them out more widely. Given the uncertainties triggered by the pandemic and the radical changes in physicians’ preferences and behaviors, replicating successful launch strategies from the past is no longer a safe option. Our work with pharma companies indicates that leaders designing a new strategy should consider paying close attention to five success factors: rapidly personalized content, analytics-enabled engagement, innovative patient channels and services, nimble frontline operations, and closed-loop execution (Exhibit 2). We outline each of these five factors in greater detail below.

Rapidly personalized content

With HCPs’ preferences so variable and changeable, pharma companies need clear, up-to-date per­spectives on each physician’s interests and wishes so they can gear messages to individual needs and concerns. Basing communications on an undifferentiated aggregate view of physicians or segments will no longer suffice. For each new product launch, best-practice companies compile a set of marketing and medical modules to cover the full spectrum of HCP needs and then ask reps to use their insight into individual physicians to select the modules that best meet their needs.

While this approach has been true for many years, the difference is that today those new modules need to be created quickly to be relevant. A better way to stay relevant is to engage HCPs on the current hot topics in their field—for example, what best practices are emerging in telemedicine? How are HCPs managing COVID-19 infection risk for patients? What do key opinion leaders think about the potential for drug-to-drug interactions with COVID-19 vaccines?

Familiar product-oriented and company-centered approaches to content may also need rethinking. To reduce development cycles, content creation and review processes need to be streamlined and simplified. With agile approaches, companies can book a meeting with an HCP, gather feedback, and capture it immediately in the next iteration of content development. In that way, content can be approved and refined within approval cycles of no more than two to four weeks.

For a pharma company looking to reinvent its commercial model, the launch of new products is a golden opportunity to try out new techniques and gauge their impact before rolling them out more widely.

Analytics-enabled engagement

If a universal approach is no longer an option for content, the same is true of engagement. The days of casual appointments and conversations in hallways are over. Whether an interaction is face to face or remote, it needs to be scheduled and an agenda shared in advance. A rep needs to have something new and compelling to discuss or risks that the meeting might never happen.

To understand individual physicians’ preferences for interaction frequency and channels, innovative companies are creating data lakes, building predic­tive models, and drawing on unfamiliar data sources—not only customer-relationship-management (CRM) systems, sales records, and quantitative surveys, say, but also claims data for providers at a physician’s office. Innovative approaches can yield surprising results. In the United States, for instance, some pharma com­panies found they can predict physicians’ willingness to engage with reps more accurately from foot traffic and credit-card spend in a given zip code than from local state restrictions or COVID-19 infection rates.

Since relevant historical data on physician prefer­ences on interactions with sales reps is seldom available at launch, the process of generating insights typically begins with field reps reporting on the impressions they gained of HCPs’ preferences during prelaunch interactions with them. As the product launch progresses, important factors such as physi­cian feedback, field insights, and prescription volume are used to flesh out and update this prelimi­nary picture. Through a continual process of refinement, the predictive model on launch success becomes more powerful and its output better aligned with the realities of the market. As a physician’s preferences evolve—both in response to the new product as well as in engagement channels—the model adjusts its recommendations, enabling reps to fine-tune content and channel choices for an audience of one to provide an optimal personalized experience at launch.

To implement an analytics-based approach to engagement, pharma leaders also need to ensure that two critical enablers are in place: a tech and data backbone to enable seamless integration across channels and data sources, and a platform for run­ning advanced-analytics models to enable leaders to distinguish signals from noise, improve deci­sion making in real time, and optimize messages, channels, and timing in individual HCP interactions.

Innovative patient channels and services

In a McKinsey survey of 300 physicians in September 2020, 74 percent of respondents reported noticing their patients delaying necessary care, with conse­quences including an increase in complications from injury or disease, a loss of income from missing work, and a rise in the costs of care. For new product launches, this finding is significant, since patients who have yet to be treated for a new medical condition are often the ones most interested in a new product for treat­ment. However, as patients delay care due to the COVID-19 pandemic, the pool of new patients that may have benefited from being treated with a new product is declining as well. The new hurdles created by the COVID-19 pandemic call for innovative services from pharma companies, as well as from healthcare systems and professionals, to stay connected with patients.

As the survey indicates, the perceived risk of engag­ing with health systems has made many patients wary of face-to-face interactions in all but the most serious cases. Those suffering from nonurgent conditions, such as migraines, insomnia, and depres­sion, are less likely to request appointments with primary-care physicians. Responsive companies have been stepping in to facilitate inter­actions with HCPs by offering telemedicine diagnostic platforms in app form or through the integration of web, text, and voice.

Maintaining or adjusting treatment can also be dif­ficult in today’s circumstances, especially for infusions, injections, and other therapies that require attendance at a hospital or clinic. Innovative companies are developing alternative infusion sites, enabling “at home” infusion, and offering guidance on how to minimize risk when visiting health facilities.

Nimble frontline operations

As pharma companies gear up for remote launch activities, they can help their sales reps build new capabilities that can enhance their impact on launch success. As virtual calls replace in-person visits, reps can foster a sense of proximity with HCPs by learning to make the most of cameras, screen sharing, and other interaction tools. Soft skills such as deep listening will help sales reps gather insights on physicians’ unmet needs and sources of dissatisfaction. Feeding these insights back into CRM systems will enhance their predictive power and enable the organization to rapidly correct course where needed.

As the use of video, interactive content, and multi­person interactions increases, companies will also need to rethink marketing materials so that they are effective in remote settings. Meanwhile, marketing staff will need to further develop their ability to optimize marketing campaigns based on HCP engagement, as well as using CRM data and dashboards to assess the effectiveness of past and future actions. Capability-building programs will equip staff with the soft and hard skills— from empathy to proficiency with advanced digital tools—required for success in a rapidly changing launch environment.

Capabilities aside, launch programs give companies an opportunity to reassess the setup of their field force. With less time spent traveling and waiting to see HCPs, reps have more capacity to pursue value-added opportunities. One example might be expanding physician engagement beyond the treatment network—through referral networks, for instance—especially now that location is no longer a constraint. Building a fuller view of customer-facing roles and interactions should allow launch leaders to allocate frontline capacity in a more effective and granular manner.

Closed-loop execution

Today’s environment makes agile ways of working a necessity. With launches no longer following a common regional or national strategy but tailored to suit local contexts, each initiative must be tracked and redirected in real time as early feedback and results on sales tactics are gathered. This kind of closed-loop execution requires changes in governance and in how decisions are made.

For instance, regional leads should be empowered to fine-tune targeting philosophy and product positioning in response to the feedback they gather locally. Meanwhile, central launch teams can share best practices or make suggestions by aggregating the success rate of different approaches across various target segments and regions. Campaigns that prove effective can be scaled up across broader geographies, while ineffective campaigns can be replaced with new campaigns that are tested and, in turn, refined or replaced as needed based on their results. Consequently, launch plans are updated in rapid iterations at national and regional levels to ensure that insights and opportunities are fully captured. To manage this process and experiment with new methods and ways of working, some companies set up launch situation rooms  that pull together data on sales, volume uptake, and other standard metrics with field insights garnered through rep apps to analyze launch performance in real time. Adopting an agile operating model with processes that support cross-functional collaboration enables launch teams to rapidly create campaigns to address shifting customer needs.

The turbulence of the past few months has made pharma companies keenly aware of the need to rethink their medical education, engagement channels, and platforms—but it has also left some of them paralyzed by uncertainty. Should they invest now in transforming their commercial model or wait to see how things play out? As com­mercial leaders consider their go-to-market plans for new drugs, they have a unique opportunity to experiment with new approaches without disrupting their entire business model. Innovations developed for new drugs that prove valuable for commercial success will reshape the commercial strategy of the whole company.

Arafat Mlika is an associate partner in McKinsey’s Geneva office, Jennifer Mong is a consultant in the Silicon Valley office, Nils Peters  is a partner in the Zurich office, and Pablo Salazar is a partner in the Stamford office.

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Pharmaceutical industry profits and research and development

Subscribe to the brookings center on health policy update, richard g. frank and richard g. frank senior fellow - economic studies , director - center on health policy paul b. ginsburg paul b. ginsburg nonresident senior fellow - economic studies , center on health policy.

November 17, 2017

• 10 min read

Editor’s Note:

This analysis is part of the  USC-Brookings Schaeffer Initiative for Health Policy , which is a partnership between the Center for Health Policy at Brookings and the University of Southern California Schaeffer Center for Health Policy & Economics. The Initiative aims to inform the national health care debate with rigorous, evidence-based analysis leading to practical recommendations using the collaborative strengths of USC and Brookings.

This article originally appeared in Health Affairs  on November 13, 2017.

When the challenge of affording prescription drugs is raised, pharmaceutical manufacturers often argue that steps to reduce prices will lead to less innovation in the future. This response presumably applies to policies that use the market, such as shortening periods of exclusivity and making approvals of generics more rapid, as well as regulatory tools such as price controls.

The manufacturers’ argument has validity in that expectations of lower revenues will lead to less investment in research and development (R&D). But we question the premise that more innovation is always a good thing. A central tenet of economics is the law of diminishing returns. In this case, additional resources going into innovation inevitably yield fewer important breakthroughs. At some point, perhaps already reached, the yield from additional resources going into R&D no longer justifies what society is paying in the form of higher prices to support this.

Basic Economics Of Patent Protection And Pharmaceutical R&D

Pharmaceutical innovation has produced an enormous amount of social value. The evidence on this point is strong and comes from multiple sources. Studies of disease-specific spending on prescription drugs, macro-comparisons in the United States, and international comparisons have all pointed to high social returns with respect to longevity and functional health outcomes. [1]  Those benefits from pharmaceutical innovation stem in great measure from patent policy and the granting of marketing exclusivity to new drug products.

The pharmaceutical industry is what economists call a high-fixed low-cost marginal cost industry. This means that the cost of bringing a new drug to market is very high and the process is risky, while the cost of producing an extra unit of a product that is on the market is frequently “pennies a pill”. There is energetic disagreement about the exact cost of bringing a new drug to market, but there is widespread recognition that the  costs run into at least many hundreds of millions of dollars  per new drug product.

In addition, for many drugs the costs of imitation are low. It is simple and low cost for a firm that did not develop the drug to produce a copy of a new drug. This means that if free competition were permitted, firms spending hundreds of millions of dollars to bring a new drug to market would be unlikely to recoup those investments, as competition would drive prices down to production costs (“pennies a pill”).

It is these features of the economics of new drug development that make the establishment of intellectual property rights through the patent system and regulation of marketing exclusivity so important to promoting innovation in prescription drugs. Establishing temporary monopoly power for makers of new prescription drug products enables innovator companies to raise prices above the level of production costs and realize economic profits to compensate for the investment in pharmaceutical R&D.

The fact that patents are granted and marketing exclusivity for new drugs is established does not mean there in no competition. Competition between patented drugs that treat the same medical conditions does occur, but it is based on the clinical features of the drugs and to a more limited extent on price. This is referred to as “differentiated” product competition. One feature of such competition is that manufacturers of the products can raise prices above production costs.

In the case of differentiated competition, prescription drug manufacturers will tend to pursue R&D investments where the size of markets and the potential price-cost margins are greatest. Because pharmaceutical manufacturers are uncertain about the investments that their rivals are making and long lead times are generally required to bring a new product to market, there are incentives for rival companies to all chase big markets, for example dementia or prevalent cancers, in the hope of realizing large returns.

The result of this type of “arms race” is “overinvestment” in certain clinical areas and lower rates of return on investment than hoped for. This state of affairs can continue indefinitely, eluding normal market self-correction mechanisms, due to prescription drug insurance that has become more common and more generous (see below) and to public-sector drug programs that are often passive purchasers.

Demand Side Developments

In a market economy, with government acting only to provide patent protection and exclusivity to allow innovation to be viable, drug prices would be set by supply and demand. Since much of the cost of producing drugs involves the research and development to create them—as opposed to the cost of manufacturing the pills—the price that can be obtained influences the amount that is invested in development of new drugs. However on the demand side, higher prices lead to fewer units of the drug being sold. This demand constraint leads to investment being sensitive to value—what a drug accomplishes medically for patients compared to what it will cost. To the degree that health insurance pays for a substantial portion of the price of drugs, manufacturers can charge higher prices and likely will invest more to develop new drugs.

But three important developments in recent years have altered the demand constraint. First, more people have coverage for drugs as a result of the implementation of Medicare Part D and the expansion of insurance coverage under the Affordable Care Act. Second, insurance for drugs has become substantially more comprehensive through the spread of benefit designs that set a maximum on the amount of out-of-pocket spending that the enrollee has to pay.

Third, some newer drugs—especially specialty drugs used to treat complex, chronic conditions like cancer, rheumatoid arthritis, and multiple sclerosis—have very high prices, a factor that impacts demand through its interaction with various elements of the insurance benefit design. If a patient is using a $50 drug and a new, perhaps better medication comes along at a price of $100, insurance benefit designs usually allow the patient (with support from a prescribing physician) to use the newer drug, but at an additional cost. While the difference in cost to the patient is usually less than the price difference between the drugs, only patients who perceive better results will switch.

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But this all changes when prices are $100,000 per year or $200,000 per year. For these drugs, most patients who have to pay a substantial part of the cost will not be able to afford the drug at all. However, out-of-pocket maximums make the drugs affordable and in the process make the patient insensitive to price differences. So the $100,000 drug and $200,000 drug cost the patient the same amount—their out-of-pocket maximum. This means that raising prices at this level does not trigger demand restraint on the part of patients.

Thus, the combination of current benefit designs and very expensive drugs means that raising prices even higher may not lead to fewer units. The likely result is higher revenues and more investment in development of new drugs because they promise to be so profitable.

Evidence On Profitability And Innovation

There has been a variety of evidence assembled regarding the relationship between profitability and innovation in the pharmaceutical industry. One major strand of evidence involves natural experiments regarding industry responses to growth in the size of markets. [2]  The logic behind this quasi-experimental approach is simple: Larger markets generate greater revenues that in turn create expectations of more profits to manufacturers, which expand investment in new drugs to pursue those profits.

These studies use factors that cause markets for prescription drugs to differ in size, such as demographic changes like aging of the population ( Acemeglu and Lin ), expansion in insurance coverage ( Blume-Kohout and Sood ;  Dranove, Garthwaite, Hermosilla ), and country-disease prevalence differences in market sizes for specific drugs ( Dubois, de Mouzon, Scott-Morton, Seabright ;  Kyle and McGahan ) to measure differences and changes in market size. They then examine the innovation response from the industry. Innovation is measured in several different ways. Some studies measure the number of clinical trials, R&D spending or the number of new drugs launched; still others attempt to measure the quality of new drugs launched.

Reviews of the literature on the impact of market size differences on innovation suggest two broad conclusions. First, increases in market size and potential profits have a strong positive impact on innovative activity, whether it is measured by clinical trial activity, R&D spending, or number of new drugs launched. The second conclusion is less unanimous but represents the weight of the evidence: innovation increases less than proportionately with market size.

Together, these conclusions are consistent with a couple of interpretations. One is that the science required to produce new drugs in 2017 is harder than it was a decade or two previously and so the “low hanging fruit” has been picked. A second interpretation, mentioned earlier, is that differentiated competition drives excessive entry and duplication of R&D effort, resulting in overinvestment in certain clinical areas. Both forces can be at work.

A third conclusion has recently emerged but it reflects only one research effort. Using changes in market size stemming from insurance expansion,  Dranove and colleagues  examined both the number of new drugs brought to market and the degree to which new drugs are “truly innovative,” as measured by being aimed at an under treated illness or being rated by the U.S. Food and Drug Administration (FDA) as high priority. Like prior researchers, they found that as markets grow the number of new products increases; the vast majority of increases occur in markets where there are already five or more products being sold. Dranove and colleagues found no meaningful increases in the number of drugs rated by the FDA as high priority as market size grew.

These latter two results are consistent with a conception of the pharmaceutical market that exhibits differentiated competition and a tendency to overinvest in a limited number of clinical areas. It is important to note that the evidence on this point remains limited and more work is needed. Nevertheless the mix of research findings, alongside the institutional changes in the prescription drug markets, raises fresh questions about the trade-off between high prices and profits on the one hand and innovation on the other.

Looking Forward

Reactions on the part of the pharmaceutical industry to proposals that would lead to lower drug prices, either through market forces (e.g. faster generic approvals) or regulation (e.g. price controls), have emphasized reductions in future innovation. The relationship between prices and innovations is real, but that is only part of the needed analysis. Innovation, like everything else, is constrained by the law of diminishing returns.

Indeed, it is possible that the current magnitude of innovation in pharmaceuticals is already too high in the sense that resources going into it might be better used for infrastructure, education, housing and other priorities. For those concerned about the growing role of government in the economy, since a large portion of higher drug prices are paid either directly (Medicare, Medicaid) or indirectly (tax subsidies for insurance) by government, higher drug prices inevitably lead to either higher taxes or cuts in spending for other priorities.

The authors did not receive financial support from any firm or person for this article or from any firm or person with a financial or political interest in this article. They are currently not an officer, director, or board member of any organization with an interest in this article.

[1]  See, for example, Cremieux P-Y, D Jarvinen, G Long, P Merrigan,  Pharmaceutical Spending and Health Outcomes , in FA Sloan and CR Hsieh  Pharmaceutical Innovation: Incentives, Competition and Cost-Benefit Analysis in International Perspective , Cambridge: Cambridge University press, 2007

[2]  See for example  Acemoglu and Lin ;  Blume-Kohout and Sood ;  Dubois, de Mouzon, Scott-Morton, Seabright ;  Dranove, Garthwaite, Hermosilla ;  Kyle and McGahan

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• UNC Chapel Hill

Understanding Pharmaceutical Research Studies

Medical researchers are constantly looking for new or better ways to treat illness or disease. If they discover something that may be helpful, it cannot be put into general use until years of careful testing has been done. Research studies are what link medical research to a drug becoming available to physicians and patients. Research studies may also be called clinical trials, drug trials or drug studies.

What are Research Studies?

• Research studies are designed to test the effect of a medication or treatment in a group of volunteers, measure a drug’s ability to treat the medical condition, monitor the drug’s safety, and possible side effects.
• Pharmaceutical companies or other health organizations may sponsor research studies by providing funding and designing the protocol, which is a set of detailed guidelines. A study that is conducted at several different locations is called a multi-center study.
• Trained doctors, nurses and researchers conduct research studies. The study coordinator is in charge of the day-to-day running of the study. The principal investigator (usually a physician) has overall responsibility for carrying out the protocol.

How Are Study Subjects’ Rights and Safety Protected?

• The Food and Drug Administration (FDA) is the government agency that is responsible for research studies. It regulates the conduct of research studies, enforces the laws on the use of drugs, and must approve all new drugs before they are available to the general public.
• In every university or medical center, the Institutional Review Board (IRB) reviews any study that may be done in that location. The IRB is composed of physicians and lay people. They review the study protocol to make sure patients’ rights are protected and that there are no unnecessary risks in the study. Any physician awarded a research study must get approval from the IRB before beginning the study.
• Participants are required to sign an “informed consent” form, which is also signed by the investigator (the doctor conducting the study). It details the nature of the study, the risks involved and what will happen throughout the study. It informs study subjects that they have a right to leave the study at any time and who to call if they have questions. Finally, since the patient is under a doctor’s supervision, the same laws and ethics that normally regulate the medical profession protect the study subject.

What Are the Different Types of Pharmaceutical Research Studies?

There are three phases, or steps, in doing research studies. All three of these steps must be successfully completed and all results known before a new drug can be approved for public use.

• Phase I studies are done on healthy volunteers who agree to take the study drug to help the doctors determine how safe the drug is and if there are any side effects. Studies are also done to determine how the drug is absorbed, metabolized and excreted. Usually a small number of subjects (20-100) participate in Phase I studies. Approximately 70% of new drugs will pass this phase.
• Phase II studies measure the effect of the new drug in patients with the disease or disorder to be treated. The main purpose is to determine safety and effectiveness of the new drug. Usually several hundred patients participate. These studies are usually “Double-blinded, randomized and controlled”. In controlled studies, the effect of the active drug is compared to the effect of a placebo (inactive or “sugar” pill). In double blinded studies neither the investigator nor the study subject knows who is getting active drug and who is receiving placebo medication. One third of studied drugs complete both Phase I and II.
• Phase III studies also use patients with the disorder to be treated by the new drug. These studies are done to gain a more thorough understanding of the effectiveness, benefits and side effects of the study drug. These studies use a large numbers of subjects, several hundred to several thousand. Of the new drugs that enter Phase III studies, 70 to 90% of drugs successfully complete this phase. If the results show a good effect and safety profile, the company will submit the data and request FDA approval for marketing the drug.

Who Is Eligible to Be in a Research Study?

Almost anyone can be in some type of research study. Each study has certain requirements about health, medications or age depending on what specific questions are being asked. You must meet the requirements of a particular study to be an eligible volunteer

What Is Involved in Participating in a Research Study?

• Participating in a research study is much like a regular visit to a clinic or doctor’s office, but with even greater personal attention. The study subject may be referred by their doctor or may have heard about the study elsewhere.
• Preliminary screening for the study is usually done over the phone. Basic criteria of age, symptoms, and medical history are reviewed and the details of the study are discussed. If the caller seems to qualify for the study and is interested, they are asked to come in for the initial, or screening, visit.
• The screening visit is done in the a clinic, office or hospital. After reviewing the information gathered over the phone, the informed consent form is signed by the subject and the supervising physician. A copy is given to the subject. A physical exam, blood, and other tests may be done. Following this, in most studies, there is a period, usually a few weeks, where baseline information is collected, for example severity and frequency of symptoms.
• At the end of the screening period the patient returns to the clinic for the randomization visit. If the patient’s baseline information shows that they qualify for the study, they are then randomized (usually by computer) to receive placebo or active drug.
• During the treatment period the subjects are taking the study medication on a regular basis, and recording their symptoms. There are regular visits with the study coordinator during the treatment period. At the end of the treatment period, medication use and symptoms are reviewed. Possible side effects from the study medication are recorded. After completion of the treatment period, many studies have a follow up period to assess how symptoms and possible side effects have changed. There may be one additional visit or a telephone call to assess how the subject has been doing since stopping the study drug.

What Are the Risks of Participating in a Study?

Risks vary from study to study. Researchers expect certain results but since the treatment is new and is still being studied it is impossible to say exactly what the risks may be. If a side effect or adverse event does occur, it is generally temporary and will go away as soon as the treatment is stopped.

Why Think About Participating in a Research Study

• To help yourself, as you might have a beneficial effect from the study drug.
• You will receive a great deal of personal medical attention generally at no cost to you.
• To help others, as a great deal of information is gathered during studies, making new treatments available.

Deciding to Participate in a Research Study

• Think it over carefully, weigh possible benefits against risks.
• Make sure all your questions are answered by the study personnel.
• Discuss the study with your own doctor to see what their feelings may be about it.
• If you decide to enter a study, do not do so just out of curiosity. It is important to make a commitment to try to finish the study, unless you develop serious problems.
• Remember participation in a research study is always voluntary.
• You may refuse to participate, or withdraw your consent at any time, and for any reason, without jeopardizing your future care at this institution or your relationship with your doctor.
• If you are a patient with an illness, you do not have to participate in research in order to receive treatment.

Resources for Studies

• Current On-going Studies at the UNC Center for Functional GI & Motility Disorders
• International Foundation for Functional GI Disorders: www.iffgd.org
• IBS Self Help Group: www.ibsgroup.org

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• What Is R&D?
• R&D Spending in Pharma

Who Are the Big Spenders?

Spending during covid-19.

• R&D Spending by Industry

The Bottom Line

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What Are the Average Research and Development Costs for Pharmaceutical Companies?

Thomas J Catalano is a CFP and Registered Investment Adviser with the state of South Carolina, where he launched his own financial advisory firm in 2018. Thomas' experience gives him expertise in a variety of areas including investments, retirement, insurance, and financial planning.

What Is Research and Development (R&D)?

Businesses put a lot of time and energy into developing the products and services they put on the market. This gives them a competitive advantage over their peers. These efforts require an investment in what the financial industry calls research and development (R&D). It's a series of activities that companies undertake to innovate and introduce new products and services.

R&D is often the first stage in the development process. The goal is to take new products and services to market and add to the company's  bottom line . Companies don't conduct their R&D to make an immediate profit and that makes it different from other corporate activities. It helps companies achieve their long-term growth potential and this can lead to copyrights, patents , and trademarks.

Some industries spend more on R&D than others, including telecoms, computing, health care, chemicals, and software.

Key Takeaways

• Research and development is often the first stage in the development process.
• The goal of R&D is to take new products and services to market and add to the company's bottom line.
• Pharmaceutical companies account for nearly half of the top 20 largest R&D spenders.
• Pharmaceutical companies rely on R&D to develop new drugs.
• Johnson & Johnson spent $82.6 billion in R&D in 2020 while Merck laid out 28.3% of its revenue on R&D in 2020.

Research and Development (R&D) Spending in the Pharmaceutical Industry

The pharmaceutical industry is responsible for discovering, producing, and marketing drugs for use in the healthcare sector. These drugs are used to treat and cure short- and long-term medical conditions. This is considered to be one of the largest sectors in the global economy.

According to research, the pharma industry recorded more than $1.23 trillion in sales in 2020, with about 46% of sales coming from North America. Sales are expected to grow to $1.7 trillion in 2025. Getting to this point doesn't happen without R&D.

R&D is the pharmaceutical industry's lifeblood. The success of major drug companies almost wholly depends upon the discovery and development of new medicines and their allocation of capital expenditures (capex) reflects this fact. The average spending is over 25% of revenues but some companies spend substantially more.

No other industry other than the semiconductor industry spends more on R&D. The pharmaceutical industry makes up nearly half the list of the 20 largest R&D spending industries in the world.

The largest pharmaceutical companies in the industries in 2020 included:

• Johnson & Johnson: $82.6 billion
• Roche: $26.9 billion
• Novartis: $48.7 billion
• Merck: $48 billion
• Pfizer: $41.9 billion

As noted above, many of these firms spend as much as 25% of their revenue on R&D. But just how much did these firms spend on R&D? Here's a breakdown of how much they spent in 2020:

• Johnson & Johnson: $12.2 billion (14.8% of revenue)
• Roche: $6.5 billion (24.1% of revenue)
• Novartis: $9 billion (18.5% of revenue)
• Merck: $13.6 billion (28.3% of revenue)
• Pfizer: $9.4 billion (22.4% of revenue)

Some of the other major names in the industry include AstraZeneca, which spent $6 million in R&D compared to $26.6 million in revenue (22.6%), and Eli Lilly, which earned $24.5 billion in revenue and spent $6 billion in R&D (24.5%).

Pharmaceutical companies determine their R&D expenses by estimating their revenue earned by developing and marketing a new drug.

The global COVID-19 pandemic forced pharmaceutical companies to reevaluate their R&D activities. Not only did a number of companies have to interrupt the clinical trials for some of their drugs, but many found themselves rushing to step up to help the general public. A number of these corporations helped by providing medical supplies to health care providers and patients.

Some major pharma companies ramped up their R&D efforts to develop vaccines, according to a report by McKinsey & Company. The study reported that 90% of the companies polled executed emergency protocols under their business plans, with more than 50% of these companies pausing existing clinical trials until things return to normal. As much as 50% of the industry was operating under normal capacity with productivity dropping by as much as 75% because of telecommuting.

Research and Development (R&D) Spending by Industry

R&D is an important component of any business model, regardless of the industry. R&D in the pharmaceutical sector, though, continues to have a great impact on global spending in this business area. Health care, which includes the pharmaceuticals sector came in second with a total of 21.7% in spending. The computing and electronics sector spent the most on R&D in 2018 with a total of 22.5% of its total revenue.

Spending by technology and internet companies is closer to that of pharmaceutical firms. Total spending during the 2018 fiscal year amounted to 22.5%. The chemicals sector, one of the larger R&D sectors, spends an average of 4.1%. Aerospace and defense firms only dedicated about 2.8% of revenues to R&D spending in 2018.

Research and development is a pivotal component of any company's success, whether that's a chemical, energy, computer, or pharmaceutical company. Companies that fall into the latter sector are among the top spenders when it comes to R&D. The high level of R&D expenditures in this industry is easy to understand given the cost of developing a new drug and bringing it to market. The average R&D to marketplace cost for a new medicine is nearly $4 billion, and can sometimes exceed $10 billion.

The Business Research Company. " Pharmaceuticals Global Market Report 2021: COVID-19 Impact and Recovery to 2030 ," Summary.

Congressional Budget Office. " Research and Development in the Pharmaceutical Industry ."

Roche. " Year In Review ," Page 60.

Novartis. " Novartis delivered sales growth and margin expansion. Continued to progress its next wave of medicines in 2020 ."

Merck. " Merck Announces Fourth-Quarter and Full-Year 2020 Financial Results ."

Pfizer. " PFIZER REPORTS FOURTH-QUARTER AND FULL-YEAR 2020 RESULTS AND RELEASES 5-YEAR PIPELINE METRICS ."

Johnson & Johnson. " 2020 Annual Report ," Page 3.

Roche. " Roche Holdings, Inc. Annual Report 2020 ," Page 6.

Novartis. " Annual Review 2020 ," Page 24.

Pfizer. " FINANCIAL PERFORMANCE ."

AstraZeneca PLC. " Full-year 2020 results ," Pages 1-2.

Eli Lilly. " Key Facts ."

McKinsey & Company. " COVID-19 implications for life sciences R&D: Recovery and the next normal ."

Statista. " Percentage of global research and development spending in 2018, by industry ."

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Top 20 Pharmaceutical Market Research Companies

What are pharmaceutical market research companies.

Pharmaceutical market research companies provide services to help pharma, healthcare, and related industries gain insights into how to best market in today's complex healthcare landscape. They inform on marketing for prescription and over-the-counter (OTC) drugs, vaccines, and other pharma products as well as some medical devices.

The top pharmaceutical market research companies offer market research services related to prescription medicines and certain types of healthcare marketing. These vendors conduct research projects for prescription drug development and marketing needs, and their services go hand-in-hand with overarching pharmaceutical research, healthcare research, and other niche aspects of pharma research.

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Emerging Drug Trends

• Emerging drugs, which include designer drugs and new psychoactive substances , are substances that have appeared or become more popular in the drug market in recent years.
• Emerging drugs have unpredictable health effects . They may be as powerful or more powerful than existing drugs, and may be fatal.
• Because drug markets change quickly, NIDA supports the National Drug Early Warning System (NDEWS) , which tracks emerging substances. NIDA also advances the science on emerging drugs by supporting research on their use and on their health effects.

What are emerging drugs?

Emerging drugs are mind-altering substances that have become more common in recent years. They may be sold in drug markets or at convenience stores and online. Since 2013, the United Nations Office on Drugs and Crime has identified more than 1,000 emerging drugs worldwide. 1

These substances, which include designer drugs and new psychoactive substances , come from many sources. Some were first developed as potential treatments or research chemicals. Others originate in illicit labs and are created to mimic the effects of drugs regulated under the Controlled Substances Act . These emerging substances often produce similar effects and/or are chemically similar to illegal or prescription opioids, stimulants, benzodiazapines (“benzos”), or other existing types of drugs.

People may seek out these drugs for recreation or use them to self-medicate without medical supervision. They may also be added to other drugs without a buyer knowing it. As a result, the health effects of emerging drugs are largely unknown, potentially posing a public health threat and contributing to the overdose crisis . 2,3

NIDA monitors emerging drug trends through its Designer Drug Research Unit and through support for the National Drug Early Warning System (NDEWS) , which tracks drug-related emergency calls.

What are the effects of emerging drugs?

An emerging drug’s effects depend on the type of substance it is—for instance, if it is a new type of opioid , depressant , synthetic cannabinoid , psychedelic , or stimulant. Its effects may be unpredictable and unwanted, especially if it is an unknown ingredient in another drug. A person may not know what substance or substances they have really taken. And because these substances are new to the drug market, clinicians or researchers may not know their effects or how potent (powerful) they are until people begin to visit emergency departments or clinics with symptoms of negative health effects. 4

In addition, emerging substances are usually not included in emergency department drug tests and are not routinely included in the toxicology tests used after a fatal overdose. The delay in this data means there is also a delay in understanding how widespread use of the drug is, why and how these drugs have their effects, and how to care for people who experience negative effects of those substances.

NIDA researchers and grantees collaborate to identify how these emerging drugs work and their potential health effects, including those that have the potential to impact the overdose crisis. NIDA also supports the National Drug Early Warning System (NDEWS) to track emerging substances and their impact on drug-related emergency calls.

What are nitazenes?

Nitazenes are a class of lab-made (synthetic) opioids that may be as powerful or more powerful than fentanyl. 4   They were developed in research labs in the 1950s as potential pain relievers but never marketed. Nitazenes are most often sold as a white powder or tablets. People may not be aware that they have taken nitazenes, as they may be added to other substances, including fentanyl, heroin, and benzodiazepines. 5

Nitazenes began to re-emerge in the drug supply in 2019, after the U.S. Drug Enforcement Administration banned fentanyl-related substances. 6,7 Researchers and authorities are monitoring nitazenes, including isotonitazene, protonitazene, etonitazene, N-piperidinyl etonitazene, and metonitazene. Many nitazenes are listed as Schedule 1 drugs under the Controlled Substances Act. 

Like all opioids , nitazenes can slow breathing, blood pressure, and heart rate to dangerously low levels, potentially contributing to overdose . Preliminary NIDA-supported research shows that the opioid overdose reversal medication naloxone is effective with isonitazene, metonitazene, and etonitazene, though it may require repeated doses. More research is needed to confirm these findings with additional nitazenes and in larger groups of people. Fentanyl test strips do not detect nitazenes.

What is tianeptine?

Tianeptine is an antidepressant medication that is not approved for use in the United States. NIDA-funded research suggests that most people take tianeptine in dietary supplements marketed as cognitive enhancers or nootropics, often sold in convenience stores and online. It may be blended with or taken at the same time as other nootropics (like phenibut and racetams) and is also used with substances such as kratom , kava, and gabapentin.

Tianeptine is not an opioid but at high doses it can have opioid-like effects, such as dangerous drops in blood pressure, heart rate, or breathing rate. Research shows that other effects include problems with brain, heart, and digestive function.

Research has shown that tianeptine can cause symptoms of a substance use disorder, including tolerance—which is when you need to take more of a drug for it to have the same level of effect—and withdrawal. Withdrawal from tianeptine has been associated with pain and problems with brain, heart, and digestive function. Early evidence suggests that tianeptine-related substance use disorder can be treated with medications for opioid use disorder , such as buprenorphine. 8

What are new psychoactive substances?

“New psychoactive substances” is a term used to describe lab-made compounds created to skirt existing drug laws . The category may include medications created by pharmaceutical companies or researchers that were never meant to reach the public .

These substances belong to a number of drug classes:

• Synthetic opioids. These drugs are chemically different from existing lab-made opioids like fentanyl . They include brorphine and U-47700. Researchers first identified brorphine in the unregulated drug supply in 2018. New synthetic opioids may slow breathing, blood pressure, and heart rate to dangerously low levels, potentially contributing to overdose. Emerging opioids can be as powerful or more powerful than fentanyl, which itself is 50 to 100 times more powerful than morphine.
• Synthetic cannabinoids , sometimes called “K2” or “Spice.” Lab-made cannabinoids are chemically similar to the cannabis plant but may have very different effects. Newer synthetic cannabinoids include ADMB-5,Br-BUTINACA and MDMB-4en-PINACA. MDMB-4en-PINACA has been associated with hallucinations, paranoia, and confusion. These substances have been found in people who died from accidental overdose. 9
• Synthetic cathinones , also known as “Bath Salts.” Lab-made cathinones are stimulants that are chemically related to, but not derived from, the khat plant. People sometimes take synthetic cathinones as a less expensive alternative to other stimulants, but cathinones have also been found as an added ingredient in other recreational drugs. Emerging cathinones include eutylone, N,N-dimethylpentylone (dipentylone), and pentylone. These substances have been found in people who died from overdose. 10
• Synthetic benzodiazapines. Benzodiazapenes are a class of lab-made depressants that include prescription medications such as diazepam (sometimes sold as Valium), alprazolam (sometimes sold as Xanax), and clonazepam (sometimes sold as Klonopin). Recent data show that new versions of recreationally manufactured bezodiazapines include bromazolam, disalkylgidazepam, and flubromazepam. 11

How does NIDA support research into emerging drugs?

NIDA supports research tracking the emergence of new drugs into the unregulated drug supply, including via the National Drug Early Warning System (NDEWS) , collaboration with other researchers, partners around the world, and social media. The Institute studies or supports research on changes in the lab-made drug supply and how these emerging substances work in the brain, as well as their health effects and potential as therapeutic treatments.

NIDA also researches ways to prevent substance use and misuse , and studies whether and how harm reduction methods may prevent, reverse, or reduce rates of overdose.

Latest from NIDA

Law enforcement seizures of psilocybin mushrooms rose dramatically between 2017-2022

Can science keep up with designer drugs?

Xylazine appears to worsen the life-threatening effects of opioids in rats

Find more resources on emerging drugs.

• See recent data on Overdose Rates from the Centers for Disease Control and Prevention (CDC). 
• Stay up to date on new and emerging substances at the National Drug Early Warning System website
• Early warning advisory on new psychoactive substances. United Nations Office on Drugs and Crime. Accessed April 15, 2024. https://www.unodc.org/LSS/Page/NPS
• Singh VM, Browne T, Montgomery J. The emerging role of toxic adulterants in street drugs in the US illicit opioid crisis . Public Health Rep . 2020;135(1):6-10. doi:10.1177/0033354919887741
• Gladden RM, Chavez-Gray V, O'Donnell J, Goldberger BA. Notes from the field: overdose deaths involving eutylone (psychoactive bath salts) - United States, 2020 . MMWR Morb Mortal Wkly Rep . 2022;71(32):1032-1034. Published 2022 Aug 12. doi:10.15585/mmwr.mm7132a3
• Pergolizzi J Jr, Raffa R, LeQuang JAK, Breve F, Varrassi G. Old drugs and new challenges: A narrative review of nitazenes . Cureus . 2023;15(6):e40736. Published 2023 Jun 21. doi:10.7759/cureus.40736
• Ujváry I, Christie R, Evans-Brown M, et al. DARK classics in chemical neuroscience: Etonitazene and related benzimidazoles . ACS Chem Neurosci . 2021;12(7):1072-1092. doi:10.1021/acschemneuro.1c00037
• Benzimidazole opioids, other name: nitazenes. Drug Enforcement Agency. Issued January 2024. Accessed April 15, 2024. https://www.deadiversion.usdoj.gov/drug_chem_info/benzimidazole-opioids.pdf
• Papsun DM, Krotulski AJ, Logan BK. Proliferation of novel synthetic opioids in postmortem investigations after core-structure scheduling for fentanyl-related substances . Am J Forensic Med Pathol . 2022;43(4):315-327. doi:10.1097/PAF.0000000000000787
• Trowbridge P, Walley AY. Use of buprenorphine-naloxone in the treatment of tianeptine use disorder . J Addict Med . 2019;13(4):331-333. doi:10.1097/ADM.0000000000000490
• Simon G, Kuzma M, Mayer M, Petrus K, Tóth D. Fatal overdose with the cannabinoid receptor agonists MDMB-4en-PINACA and 4F-ABUTINACA: A case report and review of the literature . Toxics . 2023;11(8):673. Published 2023 Aug 5. doi:10.3390/toxics11080673
• Ehlers PF, Deitche A, Wise LM, et al. Notes from the field: Seizures, hyperthermia, and myocardial injury in three young adults who consumed bromazolam disguised as alprazolam - Chicago, Illinois, February 2023 . MMWR Morb Mortal Wkly Rep . 2024;72(5253):1392-1393. Published 2024 Jan 5. doi:10.15585/mmwr.mm725253a5

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Oncologists' meetings with drug reps don't help cancer patients live longer

Sydney Lupkin

Drug companies often do one-on-one outreach to doctors. A new study finds these meetings with drug reps lead to more prescriptions for cancer patients, but not longer survival. Chris Hondros/Getty Images hide caption

Drug companies often do one-on-one outreach to doctors. A new study finds these meetings with drug reps lead to more prescriptions for cancer patients, but not longer survival.

Pharmaceutical company reps have been visiting doctors for decades to tell them about the latest drugs. But how does the practice affect patients? A group of economists tried to answer that question.

When drug company reps visit doctors, it usually includes lunch or dinner and a conversation about a new drug. These direct-to-physician marketing interactions are tracked as payments in a public database, and a new study shows the meetings work. That is, doctors prescribe about five percent more oncology drugs following a visit from a pharmaceutical representative, according to the new study published by the National Bureau of Economic Research this month.

But the researchers also found that the practice doesn't make cancer patients live longer.

"It does not seem that this payment induces physicians to switch to drugs with a mortality benefit relative to the drug the patient would have gotten otherwise," says study author Colleen Carey , an assistant professor of economics and public policy at Cornell University.

For their research, she and her colleagues used Medicare claims data and the Open Payments database , which tracks drug company payments to doctors.

While the patients being prescribed these new cancer drugs didn't live longer, Carey also points out that they didn't live shorter lives either. It was about equal.

The pharmaceutical industry trade group, which is known as PhRMA, has a code of conduct for how sales reps should interact with doctors. The code was most recently updated in 2022, says Jocelyn Ulrich, the group's vice president of policy and research .

"We're ensuring that there is a constant attention from the industry and ensuring that these are very meaningful and important interactions and that they're compliant," she explains.

The code says that if drug reps are buying doctors a meal, it must be modest and can't be part of an entertainment or recreational event. The goal should be education.

Ulrich also points out that cancer deaths in the U.S. have declined by 33 percent since the 1990s , and new medicines are a part of that.

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Profitability of Large Pharmaceutical Companies Compared With Other Large Public Companies

Fred d. ledley.

1 Center for Integration of Science and Industry, Department of Natural & Applied Sciences, Bentley University, Waltham, Massachusetts

2 Department of Management, Bentley University, Waltham, Massachusetts

Sarah Shonka McCoy

3 Department of Accountancy, Bentley University, Waltham, Massachusetts

4 Department of Accounting, University of New Mexico, Albuquerque, New Mexico

Gregory Vaughan

5 Department of Mathematical Sciences, Bentley University, Waltham, Massachusetts

Ekaterina Galkina Cleary

6 Center for Integration of Science and Industry, Department of Mathematical Sciences, Bentley University, Waltham, Massachusetts

Accepted for Publication: January 14, 2020.

Author Contributions : Dr Ledley had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ledley, McCoy.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Ledley, McCoy.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: All authors.

Obtained funding: Ledley.

Administrative, technical, or material support: Ledley, McCoy.

Supervision: Ledley.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by the National Biomedical Research Foundation.

Role of the Funder/Sponsor: The National Biomedical Research Foundation had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The funder did not have the right to veto publication or to control the decision regarding to which journal the manuscript was submitted.

Disclaimer: The Center for Integration of Science and Industry at Bentley University does not receive corporate support.

Additional Contributions: The authors thank Steve Wasserman, MBA (Bentley University); Michael Boss, PhD (executive in residence, Bentley University); and Nancy Hsiung, PhD (executive in residence, Bentley University), for advice and critical reading of the manuscript. Mr Wasserman is faculty at Bentley University. Drs Boss and Hsiung received no compensation for their work at Bentley University or their role in this study. The authors also thank Bentley University undergraduate researchers Liam Fitzgerald, Jeremy Holden, and John Reddington for assistance in data collection and Danielle Solar, BA, for assistance in preparation of the manuscript.

Data Sharing Statement: All data used in this study are publicly available.

Associated Data

eTable 1. Companies included in datasets with identifying information. Panel A: Companies in pharmaceutical dataset. Panel B: Companies in the S&P 500 dataset. Panel C: Companies in the healthcare dataset.

eTable 2. Summary statistics on pharmaceutical and S&P 500 datasets, 2000-2018

eTable 3. Median and IQR of profit margins for pharmaceutical companies and other sectors of the S&P 500, 2000–2018.

eTable 4. Median profit margins of selected large technology companies, 2000-2018

eTable 5. Median and IQR of profit margins for pharmaceutical companies and subsectors of the healthcare dataset, 2000–2018.

eTable 6. Median and IQR difference between profit margins of pharmaceutical companies and subsectors of the healthcare dataset, 2000–2018.

eTable 7. Differential profit margins of pharmaceutical and S&P 500 companies, complete results

eTable 8. Differential profit margins of pharmaceutical companies and sectors within the S&P 500, complete results

eFigure 1A-F. Distribution of expense and profit metrics as a fraction of revenue in the pharmaceutical and S&P 500 datasets

eReferences

How do the profits of large pharmaceutical companies compare with those of other companies from the S&P 500 Index?

In this cross-sectional study that compared the profits of 35 large pharmaceutical companies with those of 357 large, nonpharmaceutical companies from 2000 to 2018, the median net income (earnings) expressed as a fraction of revenue was significantly greater for pharmaceutical companies compared with nonpharmaceutical companies (13.8% vs 7.7%).

Large pharmaceutical companies were more profitable than other large companies, although the difference was smaller when controlling for differences in company size, research and development expense, and time trends.

Understanding the profitability of pharmaceutical companies is essential to formulating evidence-based policies to reduce drug costs while maintaining the industry’s ability to innovate and provide essential medicines.

To compare the profitability of large pharmaceutical companies with other large companies.

Design, Setting, and Participants

This cross-sectional study compared the annual profits of 35 large pharmaceutical companies with 357 companies in the S&P 500 Index from 2000 to 2018 using information from annual financial reports. A statistically significant differential profit margin favoring pharmaceutical companies was evidence of greater profitability.

Large pharmaceutical vs nonpharmaceutical companies.

Main Outcomes and Measures

The main outcomes were revenue and 3 measures of annual profit: gross profit (revenue minus the cost of goods sold); earnings before interest, taxes, depreciation, and amortization (EBITDA; pretax profit from core business activities); and net income, also referred to as earnings (difference between all revenues and expenses). Profit measures are described as cumulative for all companies from 2000 to 2018 or annual profit as a fraction of revenue (margin).

From 2000 to 2018, 35 large pharmaceutical companies reported cumulative revenue of $11.5 trillion, gross profit of $8.6 trillion, EBITDA of $3.7 trillion, and net income of $1.9 trillion, while 357 S&P 500 companies reported cumulative revenue of $130.5 trillion, gross profit of $42.1 trillion, EBITDA of $22.8 trillion, and net income of $9.4 trillion. In bivariable regression models, the median annual profit margins of pharmaceutical companies were significantly greater than those of S&P 500 companies (gross profit margin: 76.5% vs 37.4%; difference, 39.1% [95% CI, 32.5%-45.7%]; P  < .001; EBITDA margin: 29.4% vs 19%; difference, 10.4% [95% CI, 7.1%-13.7%]; P  < .001; net income margin: 13.8% vs 7.7%; difference, 6.1% [95% CI, 2.5%-9.7%]; P  < .001). The differences were smaller in regression models controlling for company size and year and when considering only companies reporting research and development expense (gross profit margin: difference, 30.5% [95% CI, 20.9%-40.1%]; P  < .001; EBITDA margin: difference, 9.2% [95% CI, 5.2%-13.2%]; P  < .001; net income margin: difference, 3.6% [95% CI, 0.011%-7.2%]; P  = .05).

Conclusions and Relevance

From 2000 to 2018, the profitability of large pharmaceutical companies was significantly greater than other large, public companies, but the difference was less pronounced when considering company size, year, or research and development expense. Data on the profitability of large pharmaceutical companies may be relevant to formulating evidence-based policies to make medicines more affordable.

This study uses data from annual financial reports to compare the profitability of large pharmaceutical companies vs other large companies in the S&P 500 Index from 2000 to 2018, measured via gross profit; earnings before interest, taxes, depreciation, and amortization; and net income (earnings).

Introduction

Policy makers face growing pressure to reduce the cost of drugs in the United States. 1 , 2 , 3 , 4 , 5 , 6 This pressure arises from concern that essential drugs are increasingly unaffordable and that excessive pharmaceutical company profits contribute to high drug prices. 1 , 5 , 7 , 8 , 9 , 10 , 11

Large, for-profit companies play a central role in providing medicines to the public. Virtually all of the US Food and Drug Administration–approved medicines in the United States were developed by for-profit corporations. 12 The 25 largest pharmaceutical companies accounted for 73% of all pharmaceutical sales in 2015. 5 As such, it has been argued that pharmaceutical companies have an obligation to balance their responsibility to patients and the profit expectations of their shareholders. 1 , 2 , 3 , 4 , 5 , 6 , 7 , 10 , 13

Thus, evidence-based policy aimed at reducing the cost of medicines requires a detailed understanding of both drug costs and company profits. While there is extensive literature on the adverse consequences of high drug prices, there has been little research on industry profits. 1 The objective of this study was to compare the profitability of large, publicly traded companies engaged in the research, development, manufacture, marketing, and sale of pharmaceutical products with that of other large, publicly traded companies.

This cross-sectional study compared the profitability of large pharmaceutical companies with companies in the S&P 500 Index from 2000 to 2018 using information from annual financial reports.

Audited financial data for fiscal years 2000 to 2018 were retrieved from Compustat (Wharton Research Data Services), including end of fiscal year stock price; common shares outstanding; revenue; gross profit; net income; research and development expense; in-process research and development expense; selling, general, and administrative expense; and earnings before interest, taxes, depreciation, and amortization (EBITDA). Calculated data included market capitalization (end of fiscal year stock price × common shares outstanding); cost of goods sold (revenue − gross profit); research and development expense (research and development expense [Compustat variable] + in-process research and development expense); selling, general, and administrative expense (selling, general, and administrative expense [Compustat variable] − research and development expense [Compustat variable]); gross profit margin (gross profit/revenue); EBITDA margin (EBITDA/revenue); and net income margin (net income/revenue). Financial terms are described in the Box and the eAppendix in the Supplement . Financial metrics are presented in US dollars adjusted for inflation to 2016 using the Consumer Price Index for All Urban Consumers data.

Accounting and Finance Terms a

Total amount of sales after discounts, credits, or rebates.

Market capitalization

A measure of company size calculated as the stock price multiplied by the number of shares outstanding.

Expense metrics

Cost of goods sold.

Costs of producing or purchasing products that are sold.

Research and development expense

Costs of both basic research and development.

Selling, general, and administrative expense

Costs of marketing and sales as well as administration and management.

Profit metrics

Gross profit.

The difference between revenue and cost of goods sold. Gross profit margin is gross profit as a percentage of revenue.

Earnings before interest, tax, depreciation, and amortization (EBITDA)

The difference between revenue and expenses related to the core business, but not expenses related to interest, taxes, or the reduction in the value of assets over time. EBITDA margin is EBITDA as a percentage of revenue.

The difference between all revenues and expenses, often referred to as the bottom line or earnings . Net income margin is net income as a percentage of revenue.

Pharmaceutical, S&P 500, and Health Care Data Sets

The pharmaceutical data set comprised companies involved in research, development, manufacture, marketing, and sale of pharmaceutical products from the S&P 500 Index or PharmaExpert “top 50” in 2018. Companies without data in Compustat were excluded.

The S&P 500 data set comprised companies listed in the S&P 500 Index in 2018, excluding (1) companies categorized as pharmaceutical, biotechnology, or health care products; (2) companies with data in the financial services format (mostly banks, savings and loans, insurance, or real estate investment trust); and (3) fiscal years without necessary data in Compustat. S&P 500 companies were classified by the Bloomberg Industry Classification System as communications, consumer discretionary, consumer staples, energy, health care (excluding companies in the pharmaceutical data set), industrials, materials, technology, utilities, or other. “Other” included primarily banks, savings and loans, insurance, or real estate investment trust with data in the industrial format.

The health care data set combined the pharmaceutical data set and the health care sector of the S&P 500 data set. These companies were subclassified as pharmaceutical; distribution, retail, information; insurance, health services; or other products. The list of companies and sector classifications is provided in eTable 1 in the Supplement .

Subset analyses included (1) data from fiscal years with reported research and development expense (research and development >0), (2) data from fiscal years that companies were listed in the S&P 500 Index, and (3) data only from the years 2014 to 2018. Sector analysis compared pharmaceutical companies with companies in each sector and to a set of the largest technology companies: Alphabet (Google), Amazon, Apple, and Microsoft.

The primary outcome was the difference between the profits of companies in the pharmaceutical data set and the S&P 500 data set from 2000 to 2018 expressed as percent of revenue (margin) and calculated by median regression. Three distinct measures of corporate profit were examined: gross profit, representing the difference between revenue and cost of goods sold; EBITDA, representing the pretax profit from the core business activities of the company; and net income (earnings), representing the difference between all revenue and expenses. Financial terms are described in the Box and defined in the eAppendix in the Supplement .

Statistical Analyses

Cumulative financial metrics were calculated as the sum of annual values from 2000 to 2018. Normality of data was assessed using the Kolmogorov-Smirnov test. Descriptive analysis included calculation of median and interquartile range, Mann-Whitney tests of significance, and Hodges-Lehman estimator of median difference. The Hodges-Lehman estimator accounts for variation within data sets and is not equivalent to the difference of the medians. Because this analysis involved 20 comparisons, significance was interpreted with a Bonferroni correction of 20, meaning that P  < .0025 was considered significant.

The profit margins of pharmaceutical companies were compared with subsectors of the health care data set by Mann-Whitney tests and the Hodges-Lehman estimator. Because this analysis involved 3 comparisons, significance was interpreted with a Bonferroni correction of 3, meaning that P  < .016 was considered significant.

As the normality of residuals of classic linear regression estimated by the Shapiro-Wilk W test was rejected ( P  < .001), primary outcomes were examined by median regression. 14 The linearity and additivity of explanatory variables in the median regression model were assessed via residual vs fitted values plots, and no evidence of a violation of the median regression assumption was found. Pseudo R 2 value was calculated to assess the explanatory power of the model.

The median and 95% CI of the difference in profit margins of pharmaceutical and S&P 500 companies were estimated by bivariable regressions for each profit measure. Two similar bivariable models with a single indicator variable (PHARMA) were used. In the first model, with PHARMA = 0 for pharmaceutical companies, the intercept estimated the median pharmaceutical profit margin and the coefficient estimated the median difference between pharmaceutical and S&P 500 companies. In the second model, with PHARMA = 1 for pharmaceutical companies, the intercept estimated the median S&P 500 profit margin and the coefficient estimated the median difference between S&P 500 and pharmaceutical companies.

The multivariable model included the PHARMA indicator variable set to 0 for S&P 500 companies and 1 for pharmaceutical companies, market capitalization as a proxy for company size, and year fixed effects to account for time trends. The model specification was as follows: PROFIT METRIC i,t  =   β 0 i,t  +   β 1 PHARMA i   +   β 2 Market Capitalization i,t   +   β (Year Fixed Effects)   +   ε i,t .

Standard errors were estimated using the bootstrapping method (10 000 bootstrap replications; initial seed set equal to 495) with samples drawn from company clusters with replacement to address time-series correlation in the residual. 15 Bonferroni correction was unnecessary for these analyses.

Secondary analyses were the difference between pharmaceutical and S&P 500 profit margins in subsets of the data including (1) years with reported research and development expense (research and development >0), (2) years when these companies were listed in the S&P 500 Index, and (3) the years 2014 to 2018.

For sector analysis, the multivariable model eliminated the PHARMA indicator and included an indicator for each of the 10 industrial sectors (industry fixed effects): PROFIT METRIC i,t  =   β 0 i,t  +   β 1 Market Capitalization i,t  +   β (Year Fixed Effects)   +   β (Industry Fixed Effects)   +   ε i,t .

In this model, the coefficients for each sector indicator represented the difference in profit between pharmaceutical companies and that sector. Because 10 sectors were examined, significance was interpreted with a Bonferroni correction of 10, meaning that P  < .005 was considered significant.

All tests were 2-tailed. Except where previously noted, a 2-sided P  value less than .05 was considered significant. Kolmogorov-Smirnov and Mann-Whitney tests, as well as the Hodges-Lehman estimator, were performed using SPSS version 26. Median regression was performed using Stata/SE version 15.

Data Description

The pharmaceutical data set comprised 35 companies and 631 fiscal years of data, the S&P 500 data set comprised 357 companies and 6258 fiscal years of data, and the health care data set comprised 87 companies and 1552 fiscal years of data.

From 2000 to 2018, the cumulative revenue of companies in the pharmaceutical data set was $11.5 trillion, with gross profit of $8.6 trillion (74.5% of cumulative revenue), EBITDA of $3.7 trillion (32.2% of cumulative revenue), and net income of $1.9 trillion (16.2% of cumulative revenue) (eTable 2 in the Supplement ). The cumulative revenue of companies in the S&P 500 data set was $130.5 trillion, with gross profit of $42.1 trillion (32.3% of cumulative revenue), EBITDA of $22.8 trillion (17.5% of cumulative revenue), and net income of $9.4 trillion (7.2% of cumulative revenue) (eTable 2 in the Supplement ).

The Kolmogorov-Smirnov test rejected the null hypothesis that corporate profit data was normally distributed ( P  < .001), indicating that statistical tests comparing mean values were not appropriate, so analyses were performed using tests of median values.

Comparison of Pharmaceutical and S&P 500 Profits

Figure 1 A shows the distribution of annual financial metrics for companies in the pharmaceutical and S&P 500 data sets. There was no significant difference between the median annual revenue of pharmaceutical and S&P 500 companies ($10.6 billion vs $8.4 billion; median difference, −$289 million [95% CI, −$971 million to $569 million]; P  = .47). However, pharmaceutical companies were significantly larger than S&P 500 companies as measured by median market capitalization ($36.1 billion vs $12.2 billion; median difference, $15.6 billion [95% CI, $12.0 billion to $19.7 billion]; P  < .001) ( Table 1 ).

Box plot lines represent the 25th percentile, median, and 75th percentile. Whiskers are 1.5 times the interquartile ranges. Financial terms are defined in the Box . A, Annual financial metrics in millions of US dollars inflation adjusted to 2016. B, Annual financial metrics as a percentage of annual revenue. Gross profit; earnings before interest, taxes, depreciation, and amortization (EBITDA); and net income expressed as a percent of revenues represent gross profit margin, EBITDA margin, and net income margin, respectively.

Abbreviations: EBITDA, earnings before interest, tax, depreciation, and amortization; NA, not applicable.

Figure 1 B shows the distribution of annual expenses and profit metrics as a fraction of annual revenue. Pharmaceutical companies had significantly lower median cost of goods sold as a fraction of revenues than S&P 500 companies (23.5% vs 62.6%; median difference, –32.6% [95% CI, −34.5% to −30.6%]; P  < .001), but significantly higher median research and development expense as a fraction of revenue (16.2% vs 0%; median difference, 14.5% [95% CI, 14.0%-14.9%]; P  < .001) and median sales, general, and administrative expense as a fraction of revenue (28.2% vs 16.6%; median difference, 10.7% [95% CI, 9.8%-11.5%]; P  < .001) ( Table 1 ). Distributions of these data are illustrated in eFigure 1 in the Supplement .

Pharmaceutical companies had significantly higher annual profit margins than S&P 500 companies for the 3 primary outcome measures of gross profit, EBITDA, and net income ( P  < .001) ( Table 1 ). These results were confirmed using bivariable median regression ( Table 2 ). For pharmaceutical companies, the median gross profit margin was 76.5% (95% CI, 70.3%-82.7%), the median EBITDA margin was 29.4% (95% CI, 26.3%-32.5%), and the median net income margin was 13.8% (95% CI, 10.2%-17.4%). For S&P 500 companies, the median gross profit margin was 37.4% (95% CI, 35.2%-39.6%), the median EBITDA margin was 19% (95% CI, 17.8%-20.3%), and the median net income margin was 7.7% (95% CI, 7.2%-8.2%) ( Table 2 ). In bivariable median regression, the difference in median gross profit margin was 39.1% ([95% CI, 32.5%-45.7%]; P  < .001), the difference in EBITDA margin was 10.4% ([95% CI, 7.1%-13.7%]; P  < .001), and the difference in net income margin was 6.1% ([95% CI, 2.5%-9.7%]; P  < .001).

Controls and Subset Analysis

The difference in annual profit margins for pharmaceutical and S&P 500 companies was estimated with controls for company size (market capitalization) and time trends (year fixed effects) using median multivariable regression ( Table 2 ). Complete results of the regression analyses are available in eTable 7 in the Supplement . With these controls, pharmaceutical companies were significantly more profitable, although there was less of a difference between pharmaceutical and S&P 500 companies. The difference in gross profit margin was 34.6% ([95% CI, 25.3%-44.0%]; P  < .001), the difference in EBITDA margin was 8.6% ([95% CI, 4.7%-12.5%]; P  < .001), and the difference in net income margin was 4.1% ([95% CI, 0.6%-7.5%]; P  = .02) ( Table 2 ).

While pharmaceutical companies reported research and development expense in every year from 2000 to 2018, S&P 500 companies reported research and development expense in less than half of those years ( Table 1 ). Considering a subset of data with nonzero research and development expense and controls for company size and time trends, pharmaceutical companies were significantly more profitable than S&P 500 companies, although the difference in net income margin was reduced. In this analysis, the difference in gross profit margin was 30.5% ([95% CI, 20.9%-40.1%]; P  < .001), the difference in EBITDA margin was 9.2% ([95% CI, 5.2%-13.2%]; P  < .001), and the difference in net income margin was 3.6% ([95% CI, 0.01%-7.2%]; P  = .05) ( Table 2 ). These estimates of the differential profit were not outside the 95% CI for the complete data set.

Both the pharmaceutical and S&P 500 data sets included data from companies such as Incyte, Gilead, Vertex, Amazon, Salesforce, and Twitter in the years before they were listed in the S&P 500 Index. To assess whether the inclusion of data from these years biased estimates of differential profit, the profits of pharmaceutical and S&P 500 companies were compared using a subset of data comprising years that companies were listed in the S&P 500 Index along with controls for company size and time trends. In this analysis, the difference in gross profit margin was 37.2% ([95% CI, 25.4%-49.0%]; P  < .001); EBITDA margin, 11.1% ([95% CI, 5.4%-16.8%]; P  < .001); and net income margin, 6.8% ([95% CI, 3.5%-10.1%]; P  < .001) ( Table 2 ). While these estimates of the differential profit were higher than those calculated with the complete data set, they were not outside the 95% CI of the complete data set.

The profit margins of pharmaceutical and S&P 500 companies over the past 5 years were compared using a subset of data from 2014 to 2018 with controls for company size and time trends. Over this interval, the median gross profit and EBITDA margins of pharmaceutical companies were significantly higher than S&P 500 companies, but there was no significant difference in the median net income margin. The difference in gross profit margin was 35.8% ([95% CI, 28.3%-43.4%]; P  < .001); EBITDA margin, 9.0% ([95% CI, 2.9%-15.1%]; P  = .004); and net income margin, 2.3% ([95% CI, −1.0% to 5.6%]; P  = .17) ( Table 2 ).

Comparison of Pharmaceutical Companies and S&P 500 Sectors

The profit margins of pharmaceutical companies and companies in 10 sectors of the S&P 500 (eTable 3 in the Supplement ) were compared. Medians and interquartile ranges are shown in Figure 2 A and median regression with controls for company size and time trends is shown in Table 3 . Complete results of regression analysis are available in eTable 8 in the Supplement . In this analysis, the median gross profit margin of pharmaceutical companies was significantly higher than that of companies in each of the S&P 500 sectors. The median EBITDA margin of pharmaceutical companies was significantly greater than that of companies in the consumer staples, materials, industrials, consumer discretionary, and health care sectors, but not companies in the technology, other, utilities, communications, or energy sectors. The net income margin of pharmaceutical companies was higher than that of companies in each sector except for technology and other, although the difference was only significant for the consumer discretionary and health care sectors.

Box plot lines represent the 25th percentile, median, and 75th percentile. Whiskers are 1.5 times the interquartile ranges. Financial terms are defined in the Box . Annual profit margins are expressed as a percentage of annual revenue. A, Comparison of pharmaceutical companies with 10 industrial sectors in the S&P 500 data set. B, Comparison of pharmaceutical companies with 3 other subsectors of the health care data set. EBITDA indicates earnings before interest, taxes, depreciation, and amortization.

Considering 4 of the largest S&P 500 companies, Amazon, Alphabet (Google), Apple, and Microsoft, the median annual gross profit margins of Alphabet (65.8%) and Microsoft (83.1%) were similar to those of pharmaceutical companies, while those of Apple (40.8%) and Amazon (26.8%) were lower. The median annual EBITDA margin of Apple was 29.0%; Alphabet, 33.0%; Microsoft, 41.7%; and Amazon, 6.0%. The median annual net income margin of Apple was 19.2%; Alphabet, 21.9%; Microsoft, 27.6%; and Amazon, 1.7% (eTable 4 in the Supplement ).

The profit margins of pharmaceutical companies were compared with 3 other subsectors of the health care data set ( Figure 2 B and eTable 5 in the Supplement ). Pharmaceutical companies had significantly higher median gross profit margins and EBITDA margins than companies in other health care sectors. Pharmaceutical companies also had significantly higher median net income margins than companies in distribution, retail, and information and insurance and health services ( P  < .001), but not higher than other product companies (median difference, −1.6% [95% CI, −3.1% to −0.1%]; P  = .035) (eTable 6 in the Supplement ).

In this study, the profitability of a set of large, fully integrated pharmaceutical companies, which generate revenue primarily from the sale of pharmaceutical products, was shown to be significantly greater than that of other large, nonpharmaceutical companies in the S&P 500 Index from 2000 to 2018. Three metrics for profitability were examined.

The greatest difference between pharmaceutical and S&P 500 companies was in the gross profit margin, a measure of the difference between the cost of goods sold and total revenue. This profit measure does not take into account expenses related to research and development or the costs of selling a product or managing the company. Pharmaceutical companies also had a significantly greater EBITDA margin, a measure of pretax profits from the company’s core operations, which does not consider nonoperational expenses, including interest, taxes, or the accounting expense associated with reductions, in the value of company assets over time (depreciation or amortization). In addition, pharmaceutical companies had significantly greater net income margin, a measure of posttax profit accounting for all revenue and expenses. Net income, also called earnings , represents a company’s “bottom line” and is used to calculate earnings per share, an important measure of profit for shareholders.

These analyses also showed that there was considerable complexity underlying the differential profitability of pharmaceutical companies. The estimated differential profitability of pharmaceutical companies was lower when controlling for company size and time trends, and was even lower when the analysis was restricted to years of data with reported research and development expense. In contrast, the estimated differential profit of pharmaceutical companies was larger when the analysis was restricted to years when companies were listed in the S&P 500 Index. Moreover, sector analysis showed considerable overlap between the EBITDA margins and net income margins of pharmaceutical companies and those in certain other industrial sectors.

The differential profitability of pharmaceutical companies was also markedly lower over the past 5 years (2014 to 2018), and there was no significant difference between the net income margin of pharmaceutical and S&P 500 companies during this interval. Further research is required to assess whether the lower differential net income of pharmaceutical companies over the past 5 years represents a meaningful trend.

The present analysis focused explicitly on accounting metrics based on generally accepted accounting principles. These metrics are designed to promote consistency and comparability in financial statements 16 and represent important benchmarks for corporate performance. However, these metrics do not reflect cash balance or cash flow in any single fiscal year and may not correspond with public conceptions of profitability. 17 Accounting terms have technical definitions that are often not synonymous with colloquial meaning. For example, expense is not synonymous with spending and does not include long-time capital investments in tangible assets (eg, facilities or equipment), capitalized acquisitions of intellectual property, or distributions of earnings through dividends or stock buybacks.

The median net income margins calculated in this report are lower than the weighted mean net income margins reported by the US Government Accountability Office. 5 The report described a weighted mean net income margin of 20.1% for the 25 largest pharmaceutical companies compared with weighted mean net income margins ranging from 21.7% in 2006 to 13.4% in 2015 for the 25 largest software companies and 8.9% in 2006 to 6.7% in 2015 for the largest S&P 500 companies by revenue. 5 These values are substantially lower than those in a National Academies of Sciences, Engineering, and Medicine report, 1 which quoted an estimate of 25.5% “net margin” from an article in Forbes and a mean 28% margin based on work from University of Southern California’s Leonard D. Schaeffer Center for Health Policy and Economics. 8 However, the latter value represents the profit margins of branded products from United States–based activities, not total company profits.

Limitations

This study has several limitations. First, this analysis focused on large, fully integrated pharmaceutical companies that generate revenue and profit primarily from drug sales. It did not consider small or midsized biopharmaceutical companies or biotechnology companies engaged in discovery research or early-stage development, which typically have little revenue and negative profits (losses). 18 As such, the pharmaceutical data set was not representative of the broad biopharmaceutical industry and the results cannot be extrapolated to the industry as a whole.

Second, this analysis did not consider other companies in the layered pharmaceutical distribution system. Thus, these data do not describe the fraction of the sale price ultimately recognized as profit by the health care industry. 8 Such an analysis must take into account not only the profits of pharmaceutical companies, but also those of insurers, pharmacy benefit managers, pharmacies, and wholesalers. 6 , 8

Third, this analysis did not consider whether companies in the pharmaceutical data set had excess profit. In accounting and finance, excess profit is defined as profit over and above a “normal” return on capital invested in the company—a return that is commonly associated with the risk of the investment. Future research can be directed at examining the relationship between investment risk, returns on capital investments, and reported profits.

Fourth, this analysis focused explicitly on pharmaceutical revenue and profit, which are only indirectly related to drug prices in the United States. 6 , 8 Pharmaceutical revenues do not reflect the list price of medicines, but the net received from intermediaries in the pharmaceutical distribution system after rebates or discounts. 6 , 8 , 19 , 20 Moreover, while the US market represents 47% of global pharmaceutical sales (2016-2018), 21 it generates a disproportionately larger fraction of pharmaceutical profits. 8 Thus, while understanding pharmaceutical profits is essential to formulating evidence-based policy regarding drug pricing, considerable caution is required in applying these results to policies aimed at controlling drug prices in the United States.

Conclusions

Supplement..

eAppendix. Definitions of accounting and finance terms

NIH researchers develop AI tool with potential to more precisely match cancer drugs to patients

• Posted: April 18, 2024

240-760-6600

Researchers have used high-resolution gene expression data from individual tumor cells to fine-tune the ability of an AI tool called PERCEPTION to predict drug responses.

In a proof-of-concept study, researchers at the National Institutes of Health (NIH) have developed an artificial intelligence (AI) tool that uses data from individual cells inside tumors to predict whether a person’s cancer will respond to a specific drug. Researchers at the National Cancer Institute (NCI), part of NIH, published their work on April 18, 2024, in Nature Cancer, and suggest that such single-cell RNA sequencing data could one day be used to help doctors more precisely match cancer patients with drugs that will be effective for their cancer.

Current approaches to matching patients to drugs rely on bulk sequencing of tumor DNA and RNA, which takes an average of all the cells in a tumor sample. However, tumors contain more than one type of cell and in fact can have many different types of subpopulations of cells. Individual cells in these subpopulations are known as clones. Researchers believe these subpopulations of cells may respond differently to specific drugs, which could explain why some patients do not respond to certain drugs or develop resistance to them.

In contrast to bulk sequencing, a newer technology known as single-cell RNA sequencing provides much higher resolution data, down to the single-cell level. Using this approach to identify and target individual clones may lead to more lasting drug responses. However, single-cell gene expression data are much more costly to generate than bulk gene expression data and not yet widely available in clinical settings.

In the new study, the researchers investigated whether they could use a machine learning technique called transfer learning to train an AI model to predict drug responses using widely available bulk RNA sequencing data, but then fine-tune that model using single-cell RNA sequencing data. Using this approach on published cell-line data from large-scale drug screens, the researchers built AI models for 44 Food and Drug Administration–approved cancer drugs. The AI models accurately predicted how individual cells would respond to both single drugs and combinations of drugs.

The researchers then tested their approach on published data for 41 patients with multiple myeloma treated with a combination of four drugs and 33 patients with breast cancer treated with a combination of two drugs. The researchers discovered that if just one clone were resistant to a particular drug, the patient would not respond to that drug, even if all the other clones responded. In addition, the AI model successfully predicted the development of resistance in published data from 24 patients treated with targeted therapies for non-small cell lung cancer.

The researchers cautioned that the accuracy of this technique will improve if single-cell RNA sequencing data become more widely available. In the meantime, the researchers have developed a research website and a guide for how to use the AI model, called Personalized Single-Cell Expression-based Planning for Treatments In Oncology (PERCEPTION), with new datasets.

This work was conducted by NCI’s Center for Cancer Research and led by Alejandro Schaffer, Ph.D., and Sanju Sinha, Ph.D., previously at NCI, now at Sanford Burnham Prebys. NCI's Eytan Ruppin, M.D., Ph.D., supervised the work.

Eytan Ruppin, M.D., Ph.D., Center for Cancer Research , National Cancer Institute

“Predicting patient response and resistance to treatment from single-cell transcriptomics of their tumors via the PERCEPTION computational pipeline” appears April 18, 2024, in Nature Cancer.

About the National Cancer Institute (NCI): NCI leads the National Cancer Program and NIH’s efforts to dramatically reduce the prevalence of cancer and improve the lives of people with cancer. NCI supports a wide range of cancer research and training extramurally through grants and contracts. NCI’s intramural research program conducts innovative, transdisciplinary basic, translational, clinical, and epidemiological research on the causes of cancer, avenues for prevention, risk prediction, early detection, and treatment, including research at the NIH Clinical Center—the world’s largest research hospital. Learn more about the intramural research done in NCI’s Center for Cancer Research . For more information about cancer, please visit the NCI website at cancer.gov or call NCI’s contact center at 1-800-4-CANCER (1-800-422-6237).

About the National Institutes of Health (NIH):  NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit  nih.gov .

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Sleep Apnea Reduced in People Who Took Weight-Loss Drug, Eli Lilly Reports

The company reported results of clinical trials involving Zepbound, an obesity drug in the same class as Novo Nordisk’s Wegovy.

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By Gina Kolata

The pharmaceutical manufacturer Eli Lilly announced on Wednesday that its obesity drug tirzepatide, or Zepbound, provided considerable relief to overweight or obese people who had obstructive sleep apnea, or episodes of stopped breathing during sleep.

The results, from a pair of yearlong clinical trials, could offer a new treatment option for some 20 million Americans who have been diagnosed with moderate to severe obstructive sleep apnea. Most people with the condition do not realize they have it, according to the drug manufacturer. People with sleep apnea struggle to get enough sleep, and they face an increased risk for high blood pressure, heart disease, diabetes, strokes and dementia.

The study’s findings have not been published in a peer-reviewed medical journal. Eli Lilly provided only a summary of its results — companies are required to announce such findings that can affect their stock price as soon as they get them. Dr. Daniel M. Skovronsky, Eli Lilly’s chief scientific officer, said the company was still analyzing the data and would provide detailed results at the American Diabetes Association’s 84th Scientific Sessions in June.

But experts not affiliated with Eli Lilly or involved in its studies were encouraged by the summary.

“That’s awesome,” said Dr. Henry Klar Yaggi, director of the Yale Centers for Sleep Medicine in New Haven, Conn.

He added that the most common treatment, a CPAP machine that forces air into the airway, keeping it open during sleep, is effective. About 60 percent of patients who use continuous positive airway pressure continue to use it, he said.

Dr. Eric Landsness, a sleep medicine researcher at Washington University in St. Louis, said the Lilly results were “phenomenal.”

They suggest, he said, that tirzepatide “is a great alternative for people who are obese and can’t use CPAP or are on CPAP and want to improve the effect.”

He added that unlike current treatments that address only the symptoms of sleep apnea, cessation of breathing, tirzepatide goes after the underlying cause, the blockages in the airway that make a person stop breathing.

Tirzepatide, sold under the brand name Zepbound, was approved by the Food and Drug Administration for weight loss in November. The agency previously approved the drug for diabetes under the name Mounjaro. Tirzepatide is part of the class of GLP-1 drugs that includes Ozempic and Wegovy, which are sold by Novo Nordisk.

Patients who participated in these Eli Lilly trials were overweight or obese and had moderate to severe obstructive sleep apnea, with moderate defined as stopped breathing at least 15 times an hour during sleep. The trials did not involve those with central sleep apnea, a type that occurs because the brain stops signaling the muscles that control breathing.

One of the Lilly studies involved about 200 people with obesity who could not or were unwilling to use a CPAP machine. Half were randomly assigned to tirzepatide, a weekly injection. The others got a placebo.

Those who got tirzepatide had an average of 27.4 fewer apnea events per hour compared with an average reduction of 4.8 events per hour for placebo.

The other Lilly trial involved about 200 people with obesity who used a CPAP machine and were encouraged to continue using it except for the assessments of their apnea episodes. Those who took tirzepatide had an average of 30.4 fewer events per hour after a year of the drug, compared with an average reduction of six events per hour for participants who got a placebo.

In both studies, participants who took tirzepatide lost about 20 percent of their weight. Dr. Skovronsky of Eli Lilly attributed the results to the loss of fat deposits in the tongue and airway.

Many people with obesity, Dr. Landsness explained, have fat deposits in the tongue and in the back of the throat. The neck gets larger with fat that narrows the airway, and the tongue gets larger in all directions, “like blowing up a balloon,” he said. During sleep, the tongue obstructs the flow of oxygen, repeatedly waking the person.

Researchers assumed that losing weight would reduce obstructive sleep apnea episodes. But before the new drugs like tirzepatide, significant and permanent weight loss was all but impossible for most people with obesity unless they had bariatric surgery.

Marishka Brown, director of the federally funded National Center on Sleep Disorders Research, said it had been difficult to know how much of an effect weight loss would have on people with sleep apnea.

“Sometimes the sleep apnea goes away, but not always,” Dr. Brown said.

For that reason, she added, when asked if weight loss is an effective treatment, “the research community has been a bit cautious about saying yes or no.”

Now, with the new results, that tentativeness may change, researchers said.

Of course, everyone in the study was eligible for tirzepatide anyway — it is approved for people with obesity, meaning those with a body mass index of at least 30, or for those with a body mass index of at least 27 and with obesity-related medical conditions.

But insurance companies do not always pay for tirzepatide for weight loss. The drug’s list price is about $1,000 a month, but insurers pay much less . Eli Lilly sells the drug to people without insurance for $550 a month.

Dr. Skovronsky said that Eli Lilly planned to submit an application to the F.D.A. and to drug regulatory agencies around the world requesting that tirzepatide be approved for the reduction of sleep apnea in people with obesity or who are overweight.

“The goal is for insurance to cover it,” Dr. Skovronsky said.

Gina Kolata reports on diseases and treatments, how treatments are discovered and tested, and how they affect people. More about Gina Kolata

A Close Look at Weight-Loss Drugs

A Company Remakes Itself: Novo Nordisk’s factories work nonstop turning out Ozempic and Wegovy, its blockbuster weight-loss drugs , but the Danish company has far bigger ambitions.

Transforming a Small Danish Town: In Kalundborg, population under 17,000, Novo Nordisk is making huge investments to increase production  of Ozempic and Wegovy.

Ozempic’s Inescapable Jingle: The diabetes drug has become a phenomenon, and “Oh, oh, oh, Ozempic!” — a takeoff of the Pilot song “Magic”  — has played a big part in its story.

The Era of ‘Brozempic’: Some telehealth start-ups are playing up masculine stereotypes to market GLP-1s  — the revolutionary class of drugs like Ozempic — which have been more widely associated with women.

Taking on Weight Stigma: Oprah Winfrey, a prominent figure in the conversation about dieting and weight bias, tackled the rise of weight loss drugs in a new prime-time special . In December, she shared that she was taking a medication to manage her weight.

Beyond Weight Loss: Wegovy is now approved for a new use: reducing the risk of heart attacks , strokes and cardiovascular-related death in adults who have heart disease and are overweight

Weight-loss Drug Zepbound Eases Sleep Apnea in Company Trials

By Robin Foster HealthDay Reporter

WEDNESDAY, April 17, 2024 (HealthDay News) -- Zepbound, one of the wildly popular weight-loss drugs that millions of Americans now take, eased sleep apnea in obese adults in two company trials, drug maker Eli Lilly announced Wednesday.

First approved to treat obesity by the U.S. Food and Drug Administration last November, Zepbound's power was significant: It reduced sleep apnea severity by nearly two-thirds in patients.

Obstructive sleep apnea (OSA) "impacts 80 million adults in the U.S., with more than 20 million living with moderate-to-severe OSA. However, 85% of OSA cases go undiagnosed and therefore untreated," Dr. Jeff Emmick , senior vice president of product development at Lilly, said in a company news release announcing the results.

"Addressing this unmet need head-on is critical, and while there are pharmaceutical treatments for the excessive sleepiness associated with OSA, tirzepatide [Zepbound] has the potential to be the first pharmaceutical treatment for the underlying disease," he added.

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Importantly, the results have not yet been published in a medical journal.

In the two studies, researchers looked at whether Zepbound worked better than a placebo in reducing how many times per hour, on average, a person partly or fully stopped breathing while sleeping.

In the first study, sleep apnea patients did not use CPAP (continuous positive airway pressure) machines, which blow air into the airway to keep it from collapsing during sleep. Patients in the second study did use the machines.

After 52 weeks, Zepbound prompted an average reduction of 27.4 events per hour in people who were not on PAP machines, compared to a reduction of 4.8 events per hour for people on a placebo.

In people who did use PAP machines, Zepbound led to an average reduction of 30.4 events per hour, compared to an average reduction of 6 events per hour in the placebo group.

Dr. Susan Spratt , an endocrinologist and senior medical director of the Population Health Management Office at Duke Health in North Carolina, said the findings show that obesity “is not a vanity issue.”

“This is about treating a major health problem that reduces significant morbidity [illness] and mortality,” she told NBC News .

She said the findings could also make insurance companies more willing to provide coverage for the weight-loss drug.

Just last month, Medicare said it would cover another popular weight-loss drug, Wegovy, for obese patients who also have heart disease.

Sleep apnea affects about 39 million American adults, according to the National Council on Aging . Obesity, which can narrow a person's airway, can up the chances of a sleep apnea diagnosis.

Left untreated, sleep apnea can lead to heart arrhythmias, heart failure and even death.

Lilly said Wednesday that it plans to share additional findings from the studies at the American Diabetes Association annual meeting in June, and it will also submit the results to the FDA sometime this summer.

More information

Visit the National Institutes of Health for more on sleep apnea .

SOURCE: Eli Lilly Co., news release, April 17, 2024; NBC News

Copyright © 2024 HealthDay . All rights reserved.

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FDA approves bladder cancer treatment by Culver City company

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The Food and Drug Administration on Monday approved a new treatment for a type of bladder cancer.

The treatment, which will be sold under the brand name Anktiva, is intended for some patients suffering from certain types of non-muscle invasive bladder cancer, according to an FDA statement announcing the approval.

News of the FDA action was first reported by Reuters, which said, “The therapy works by activating types of disease fighting white blood cells called natural killer (NK) cells and T-cells to create long-term immunity in the body.”

The drug is now being developed by ImmunityBio of Culver City after its initial development by Altor BioScience of Miramar, Fla.

Dr. Patrick Soon-Shiong, whose family owns the Los Angeles Times, is executive chairman of ImmunityBio.

In a statement, Soon-Shiong heralded the FDA action and called Anktiva “a next-generation immunotherapy.”

The FDA approval was based on the results of a clinical trial led by Dr. Karim Chamie , an associate professor of urology at UCLA’s David Geffen School of Medicine. In a statement released by UCLA Health, Chamie said the treatment offers “a compelling alternative for patients who have exhausted conventional treatment options.”

Anktiva is intended for bladder cancer patients who did not respond to prior treatments, the FDA said. It is delivered via a catheter and prompts the patient’s own immune system “to mount a targeted attack against cancer cells,” Chamie said.

He noted that the treatment could spare some patients from invasive procedures, such as surgery to remove all or part of the bladder.

Most of the new bladder cancer diagnoses are non-muscle invasive — cancer found in the tissue that lines the inner surface of the bladder and hasn’t spread into the bladder wall, according to the UCLA statement. Patients with this type of cancer usually undergo surgery and a bacteria-based immunotherapy, which is placed directly into the bladder.

However, even with this treatment, the cancer can come back, and many patients don’t respond well to further treatment, leaving some patients with limited options.

Last May, according to Reuters , the FDA declined to approve the new therapy “due to deficiencies in the company’s application.” The FDA cited problems in its inspections and offered the firm suggestions for how to resolve the manufacturing issues that were raised, according to the wire service.

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