Over 10,000 Diseases And Only 50 Drugs Approved In 2021. To Improve Pharma R&D Efficiency We Need To Understand It.

The 11th revision of International Classification of Diseases (ICD-11) contains over 17,000 unique codes. In 2020, the year of COVID-19 pandemic, the US Food and Drug Administration (FDA) approved just 53 drugs. Fierce Pharma, the main industry media in biopharma, provided a detailed overview of the approvals in the case that you want to take a deeper dive. In 2021 the FDA approved only 50 drugs, 31 of them were small molecules, about half of them were first-in-class therapeutics (meaning around half are better versions of older drugs or combinations), and only a few of these were for moderately novel targets.

Let’s pause here for a second here and think about this figure for a moment. According to Statista, the global pharmaceutical market in 2020 was valued at about $1.23 Trillion dollars. We can estimate that if we include government research and grants, the total healthcare R&D spending exceeded $150 Billion. Millions of researchers, thousands of biotechnology companies, and hundreds of pharmaceutical companies work for decades just to see around 30 small molecules and only a few novel targets approved annually.

Measuring the efficiency of research and development (R&D) in the pharmaceutical industry has long been a difficult task and still continues to be due to the complex nature of its various processes and activities. There is a plethora of literature that proves that good investment into R&D can have tremendous positive effects for companies.

However, not that many academic groups are doing high quality research into the pharmaceutical R&D activity and doing in-depth studies into how productive the pharmaceutical industry is and how individual companies are performing.

There are three major groups, or as I like to call them, ‘authorities,’ that measure productivity in the pharmaceutical industry: Tufts Center for the Study of Drug Development (CSDD); Boston Consulting Group’s Health Care practice; and a group of experts led by Alexander Schuhmacher and Oliver Gassmann.

CSDD is an independent, academic, non-profit research center at Tufts University. It was founded in 1976 by Dr. Louis Lasagna, with the aim of providing “objective analyses and adding an academic voice to policy debates on biopharmaceutical innovation.” In later years, the Center expanded its focus to include a broad range of economic, political, scientific, and legal issues affecting a diverse group of stakeholders across the global pharmaceutical landscape. Today, CSDD provides scholarly analysis and insight into the drug development process. Three of the highest-cited papers of the centers were authored by Joseph DiMasi. The center did not yet publish any attempts to evaluate the impact of AI on drug discovery.

Boston Consulting Group’s Health Care practice helps biopharma companies deliver medicines and therapies, and take advantage of new technologies such as digital, data, and advanced analytics. The company offers several services like R&D Innovation Strategy, Increased Customer Engagement, Disease Management Platform, Production Network Transformation, and Post-Merger Support. Like CSDD, BCG also provides insights into the pharma industry.

Key opinion leaders at BCG often publish their finding in peer-reviewed journals including the Nature Reviews Drug Discovery. Their recent work titled “AI in Small-Molecule Drug Discovery: A Coming Wave?” published in March 2022, contains valuable industry analysis on the pharma AI productivity.

However, in my opinion, the most productive academic group covering the pharmaceutical industry is the Competence Network for Life Science Innovation at the Institute of Technology Management at University of St. Gallen led by Alexander and Oliver, or as they call it, their R&D ecosystem: Other key members are Markus Hinder, Global Drug Development, Chief Medical Office & Patient Safety, Novartis, or Dominik Hartl, Chief Medical Officer of Quell Therapeutics, as well as senior experts and executives from other universities, biotech/pharma companies or academic institutions. The group, as I call it, understands the importance of R&D in the pharmaceutical industry and their main objective is to scientifically analyze the R&D efficiency of the pharmaceutical industry based on a large-scale quantitative analysis.

There are very few academics in the business world who can compare with Oliver Gassmann by the number of citations or H-index (number of academic papers with the same number of citations). While in the biological sciences it is common to have the H-Index over 45, even mine is higher. However, in the business world, it is very rare. In April 2022, he had over 30,000 citations and the H-index is over 75. In 2012 the Journal of Innovation Management published the list of top 10 scientists in the field globally. Most of them had lower scores than Professor Gassmann, who is now in top 3 globally. In brief, Gassmann and Schuhmacher group is a very big deal.

My most popular article on Forbes.com published in 2020, “Deep Dive Into Big Pharma AI Productivity: One Study Shaking The Pharmaceutical Industry”, provided an overview of their paper titled “The upside of being a digital pharma player”, that evaluated the performance of the top pharmaceutical companies in AI.

In 2021 the group published several very powerful articles that looked at the R&D productivity of the big pharmaceutical companies but also created a framework for how to evaluate the pharma AI startups. One of these papers, “R&D efficiency of leading pharmaceutical companies – A 20-year analysis”, I hope to review in a separate article.

But below I interviewed Alexander and Oliver on what are the key groups focusing on evaluating R&D performance, what are the industry and academic best practices for tracking pharma productivity of pharma R&D, and the approaches the different groups take.

1. Can you tell me a little bit about the academic research circle, including your group and some of the other groups that are working in the field of analyzing R&D in pharmaceutical companies?

Alexander: In my view the topics started with some publications of DiMasi (Tufts University) and was driven by several high impact papers since 2010 – all in front the milestone papers of Paul et al. in 2010 highlighting details to the R&D productivity and of Scannel et al. (2012) on the 60 years decline of the R&D efficiency. We started our work also at that time and published our first paper in this context in 2013. Though our focus was not only on timing, cost or probabilities, but more on the understanding of the context of R&D models, strategies, technologies and R&D efficiency. Hence, our first publication was on open innovation models in pharma R&D and some of its benchmarks.

To our R&D ecosystem: All members are senior people with various backgrounds in industry and academics – a really divers team. Personally, I bring in academic backgrounds from natural sciences, medicine and business administration – 14 years in senior R&D positions in pharma and 10 years in academia – currently working as Professor for Life Science Management at THI Business School. Or Markus has 25 years plus pharma experience in various senior leadership positions in international pharma companies. Or if you take Oliver: He is a thought leader in the field of innovation and new business models, moreover he is the most cited scholar in the field of R&D management. So my understanding is that we differ from other groups because we bring in a systemic understanding (industry, pharma, biotech, academia, consulting) to that field.

Oliver: Absolutely, it’s important to have an interdisciplinary perspective to solve complex problems – which is often missed. We are not fixed in our perspective. We are somehow flexible, including the right people that we need to have on board – pharma industry guys, tech experts, people from biotech, even from consulting. Future research has to overcome the disciplinary boundaries in order to speed up and break boundaries. This is in conflict with academic promotion and career paths, since here disciplines are still more important. The more we address the big problems in the world the more we need to overcome knowledge silos and add different perspectives.

2. In general, I see that there are very few groups in the world who are doing this particular task or are involved in this area of measuring pharmaceutical R&D efficiency. You mentioned Tufts, who are the other players?

Alexander: A group that has done great work over the last years – so far made several high impact publications – is the health care practice of Boston Consulting.

Oliver: I think there’s a lot of research going on, but most of the groups don’t present a holistic perspective by actually building the bridge between different disciplines and R&D efficiency. There’s a lot of research going on, but not with the focus on the pharmaceutical industry.

We are interested in really trying to get access into the companies because I think deep insights on company level is the most critical part. Our team is anchored at our Institute of Technology Management at the University of St. Gallen – we are one of the very few European institutes which gets also financing from the FDA. I think this is the way future research should go, by combining disciplines, building up empirical databases, and diving deeply into company insights. We are lucky as a whole team to have these insights into companies, into large corporates as well as many startups.

3. Is it fair to say that the area that you are spearheading -pharma analytics – is reasonably new? There are some seminal papers on evaluating R&D productivity in Nature Reviews or by groups like AstraZeneca, for example, but they primarily look at their own R&D and explain how they see the different areas. I don’t think that there are many groups that are trying to evaluate pharmaceutical R&D productivity, even though the pharmaceutical industry is centuries old. Is it fair to say that or do you think that there are some ‘fathers’ of this industry?

Alexander: The topic came up at around the 2000s when the first big mergers happened and companies realized that they have an R&D efficiency challenge. It really increased in importance over time. For me personally, the breakeven came with the 2010 paper of Paul. I mean, it’s this really great work that has been cited many times. Since then, other great work has been published. Though I need to say, some papers are related to special settings and, thus, need to be considered more as one hit wonders. Boston Consulting Group, Tufts and maybe our group have published several papers in that field.

Why there are not that many groups? I don’t know. One explanation might be the focused approach academic group usually have – focusing on tech or medicine or management and not considering the holistic perspective needed to give answers to the R&D efficiency challenge. We use special setting and special types of setting combined with our broad knowledge basis, experienced background, and neutral perspective to generalize from science, technology and industry.

Oliver: And the complexity is even increasing. New topics that come up are not rooted in the DNA of pharmaceutical companies, such as digital technologies. For example, if the industry is really building new digital competencies, all in front artificial intelligence, they have the potential to integrate and really actively use (biological and medical) data, leverage from it and change the way of how to go from target identification to candidate selection, translational medicine and clinical research. Actually, there are a lot of areas in pharma R&D where digital competencies can make the difference and increase R&D efficiency. To stress this: We actually have a lot of data which isn’t actually used the right way. And this is the actual huge challenge!

4. It’s actually very important to maintain this neutral perspective, and that brings another question. So it looks like it’s a very new field. And it’s very rewarding field because it feeds for some ideas and directionality into companies like ours, for example. How is this area being funded and how are you planning to grow?

Oliver: We started with a team of two (Alex and Oliver) and have got it made to arrange a group of more than ten senior experts/executives that aim to get answers to the big questions around pharma R&D. This Competence Network is routed at our Institute of Technology Management at the University of St. Gallen and organized flexibly around the specific topic in consideration. There is no contractual arrangement or specific funding but a lot of motivation, fun and dedication for the research questions. So, our Competence Network for Life Science Innovation is a kind of loosely organized public-private-partnership. What brings us together is that we believe that pharma R&D is highly important and very attractive and that we can contribute really significantly to improve the whole industrial field.

5. Oliver, your Google Scholar profile has the H-index of seventy four, and this first paper on open innovation has been cited many, many thousands of times. Is it helping you get additional resources for the field?

Oliver: Absolutely, it’s helping. And we already discussed to go a step further, go for funding and building a more institutionalized form of collaboration. However, pharma efficiency, pharma R&D and AI in the pharmaceutical industry are more transdisciplinary fields, which makes it more difficult to get grants. And, this path would impact our initial setting – being flexible, working in networks, and being driven by the ideas.

6. What you are doing requires very substantial data repositories. For example when you present numbers in your research, they are actually very, very good. How do you manage the data and how do you collect this data on to make this research?

Alexander: Honestly, we are very hands on. We have good ideas and we know how to compile high quality data for the specific question in consideration – most data are open access. We have not yet invested in big data repositories and data management systems. But yes, this is what need to come next. Having prompt access to data and proving ideas immediately would increase our efficiency and effectiveness.

7. One idea could be to create an open dataset that you could open up to the world and that could be openly updated. That could be actually a really nice paper that would be highly cited and that would help grow the entire field, right?

Oliver: I fully agree with you, we want to develop the whole field because this is attractive, underresearched and could change the health care system.

In 2016, together with Markus Hinder, profs Schuhmacher and Gassmann published a book titled “Value Creation in the Pharmaceutical Industry: The Critical Path to Innovation” that is now taught at the university level. We are waiting for the new edition that would include the new findings on the impact of AI and digital technology on R&D productivity.

AmazonValue Creation in the Pharmaceutical Industry: The Critical Path to Innovation

About Profs Alexander Schuhmacher and Oliver Gassmann

Prof. Dr. Alexander Schuhmacher graduated in biology at the University of Konstanz (Germany), in pharmaceutical medicine at the University of Witten/Herdecke (Germany) and made its PhD in molecular biology at the University of Konstanz; he is also a graduate of the Executive MBA program at the University of St. Gallen (Switzerland). Alexander holds a full professorship in life science management at the Technische Hochschule Ingolstadt (Germany). His research focus is on biopharmaceutical innovation management with a specialization on R&D efficiency, artificial intelligence and open innovation. Prior to that, Alexander worked 9 years as professor at Reutlingen University (Germany) and 14 years in various R&D positions in the pharmaceutical industry.

Prof. Dr. Oliver Gassmann is a professor for technology and innovation management at the University of St.Gallen, one of Europe’s leading business schools. He is managing director of the Institute of Technology Management. Until 2002 he worked for Schindler and led its Corporate Research as VP Technology Management. He is co-founder of the BMI-Lab which focusses on business model innovation. His research lead to a revolutionary method of how to design new business models: The Business Model Navigator. Oliver has published over 300 publications and several books on management of innovation. His book ‘The Business Model Navigator’ by Hanser and Financial Times Publishing has been called as a ‘sensation’ by the leading German newspaper F.A.Z. and became rapidly a bestseller. He is one of the most cited innovation researchers, the most published author in R&D Management. In 2014 he has been awarded as a leading researcher by IAMOT in Washington and nominated for the Scholarly Impact Award by the prestigious Journal of Management. Today he serves as a member in several academic, economic and political boards, such as a member of the international advisory board of the Google Research Institute for Internet & Society. He also co-founded the think tank GLORAD Shanghai-St. Gallen on global innovation as well as the Entrepreneurial BMI Clinic in Berlin which incubates start-up companies in Europe’s hottest start-up scene. As a founding partner of the advisory group BGW he coached several of the world’s leading companies such as 3M, Airbus, BASF, BMW, Daimler, IBM, FLSmidth, Nestlé, Siemens and Toshiba.