Plenge Lab
Date posted: July 24, 2016 | Author: | No Comments »

Categories: Drug Discovery Embedded Genomics


Here are my thoughts on the Discussion Paper by Bernard H. Munos and John J. Orloff, “Disruptive Innovation and Transformation of the Drug Discovery and Development Enterprise” (download pdf here). This blog won’t make much sense if read out-of-context. Thus, I recommend reading the Discussion Paper itself, and using this blog as a companion guide at the completion of each section.

[Disclaimer: I am a Merck/MSD employee. The opinions I am expressing are my own and do not necessarily represent the position of my employer.]


In the near-term (10-years), I suspect that the pharma model of late development and commercialization will likely persist, as the cost and complexity of getting a drug approved is difficult by other mechanisms. Over time, however, new ways of performing late-stage trials will likely evolve. Drugs that are today in the early R&D pipeline will drive this evolution. If drugs look like they do today, dominated by small molecules and biologics with high probability of failure in Phase II/III, then the current model will likely continue with incremental improvements in efficiency. However, if new therapeutic modalities emerge (CRISPR, mRNA, microbiome, etc) and/or the probability of success in Phase II/III improves substantially, then the model of late development and commercialization will be forced to evolve, too.

What will evolve quickly in the next 10-years is the discovery, pre-clinical and early development phase of R&D. The optimal model has not been established. Moreover, there are numerous institutions – small, medium and large pharma companies; foundations; government; academics – that are actively experimenting today with different models. As above, I believe the primary driver of change in drug R&D will be scientific advances around selecting new targets and therapeutic modalities that recapitulate causal human biology. I agree with the statement made by Munos and Orloff, “Recent successes have been attributed to a deepening of the science, greater ability to turn scientific insights into new medicines, and the evolution of a new investor base that is better at building successful companies.


What is the origin of insights on new targets? I believe that most fundamental discoveries emerge from academics (e.g., new genetic variants associated with clinical traits), but that most translational discoveries emerge from industry (e.g., how to translate biological insights from genetic associations into therapeutics). Thus, as emphasized by Munos and Orloff, it is the ecosystem that is most critical. Unlike Trump’s “I alone can fix it” statement at the Republican National Convention, I don’t believe any one group can solve the challenges we face in discovering and developing novel therapeutics. The ecosystem needs fundamental research funded by the NIH and translational scientists in all areas to work together – with the right incentives – to turn biological insights into testable therapeutic hypotheses.


A recurring theme from me: new targets and therapeutic modalities that recapitulate human biology will ultimately drive change in clinical development. If the ecosystem continues to advance targets with low probability of success in Phase II/III, then efficiencies in late clinical development will not be the industry’s savior. I really like the idea that “trial design, procedures, site qualification, recruitment, and informed consent…offer significant opportunities for improvement.” However, this alone is insufficient. As the saying goes, if you put lipstick on a pig, it is still a pig. Today, we have too many drugs in clinical development that are, well, pigs, as the drugs are based on targets without much support in humans.


The key here is to remember that it is the ecosystem that delivers drugs. We need public funding for basic research, incentive models to finance translational research (e.g., VC-backed small biotech companies, partnerships between academics-industry), and regulatory agencies such as the FDA that work with industry to advance quickly the most promising therapeutics.

I believe that everyone who participants in the biopharma ecosystem has a moral responsibility of understanding what each component does, and how each is rewarded for the right behavior. In fact, the reason that I blog and tweet is to do my part in bringing the ecosystem together to deliver on a shared vision: turning scientific discoveries into interventions that improve health.


I don’t think the three Vision models described by Munos and Orloff are mutually exclusive. For example, regardless of the origin of new drugs that are tested in late clinical development, I support the concept (Vision #1) that pharmaceutical companies must “lead the integration of clinical research with health care delivery, working with providers to embed continuous learning, including clinical trials, into information technology (IT) systems and electronic medical records”. Similarly, it is hard to imagine a world in which digital health technology does not change medical practice and citizens are not more actively engaged in research (Vision #2).

However, I don’t think that either of the first two Visions alone will be the drivers of change. Again, I evoke the lipstick on a pig argument: if therapeutics with low probability of success are advanced into late stage clinical studies, and if these therapies are unlikely to deliver value in the real world even if approved by regulatory agencies, then I don’t think the first two Visions will change the industry.

Overall, I am most supportive of the third Vision, with a few caveats. If the key is for the ecosystem to deliver drugs that faithfully recapitulate causal human biology, then disruption will come from teams that most effectively accomplish this goal. Right now, I don’t see any obvious model that will win. As described by Munos and Orloff, small VC-backed companies are better at taking risks on new technologies than large pharma companies, but they are often less experienced at navigating the challenges associated with pre-clinical and clinical development. And while large pharma may have more experience in advancing drugs through pre-clinical and clinical development, they often cannot get out of their own way because of excessive bureaucracy and complicated processes that come with scale.

What is exciting to me is that experiments to test different R&D models are underway across the biomedical ecosystem.  Foundations such as the Michael J. Fox Foundation are partnering with companies to advance therapeutic development.  The last five years has seen increased investment in biotech (recent Life Sci VC blog on biotech’s paradox here).  Large pharma companies are moving to environments of emerging science, such as Boston/Cambridge and the Bay Area, to foster partnerships.  The U.S. government is promoting academic-industry partnerships with initiatives such as the Accelerating Medicines Partnership.

One final point before I conclude. I agree with Munos and Orloff that diversity will be the new hallmark of the industry: “If it becomes cheaper to innovate, more players will do it, which will increase the supply of new drugs that can be priced more affordably. Scale, which has historically been an asset, will be less of a success factor. Diversity, rather than scale, will become the new hallmark of the industry.” Here, diversity refers not to personal demographics such as gender or race, but diversity of ideas; diversity of new business and research models; and diversity of partnerships among players in the ecosystem. Those teams that foster a culture of diversity will emerge as winners.


But what will drive the discovery of new targets and increase success in late stage development? Stay tuned…that will be my next blog, with an accompanying perspective piece in Science Translational Medicine.







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