Can open innovation close the pharma productivity gap?
Analysis of research and development (R&D) expenditures compared to the number of new molecular entities approved by the Food and Drug Administration (FDA) each year indicates that there is definitely trouble in Pharmaland.
Put simply, not enough drugs are entering the clinic from internal discovery programs and many of those that do are failing at the worst possible time (late stage clinical trials or in the initial years, post-launch).
What can be done to remedy this? Is the traditional “closed” model of proprietary discovery and development dead? Some commentators have predicted pharma will have no choice but to undergo “reverse M&A” and split into nimble, specialized pharma franchises better able to quickly adapt to market needs and keep development costs down. There certainly doesn’t appear to be much economy of scale using the traditional R&D model so far.
Alternatively, some would say that the multinational pharma model is, to paraphrase Zen master Shunryu Suzuki, “fine just as it is, but could use a little work.”
The “work” in this case means adopting innovative models of rapid drug discovery and development that will deliver increased pipeline breadth, depth, efficiency and quality while avoiding late stage clinical failures. But just how can this be done?
During the event we heard from:
- Aled Edwards (CEO of the Structural Genomics Consortium and an energetic advocate for open innovation)
- Sean Lundie (Director of R&D for Pfizer Canada)
- Michael May (CEO of the newly established Centre for Commercialization of Regenerative Medicine)
- Niall Wallace (CEO of Ontario health care IT start-up InfoNaut)
The ensuing discussion made these important points:
- Traditional pharma R&D has not produced the goods
- Pharma is aggressively scaling back internal R&D programs
- External academic partnerships are currently a high priority model for pharma discovery
- Open innovation models such as the Structural Genomics Consortium (Toronto), which produces target structure data at an incredible pace, and CQDM (Montreal) which harnesses a large pool of academic expertise to solve pharma discovery challenges appear to be the quickest, cheapest and possibly best way for pharma to get the high value leads it requires
- Patenting the targets is a fool’s errand that slows innovation and wastes valuable resources – better to focus on patenting the product
- The barrier for open innovation could be raised as high as Phase II studies via collaborative “test” studies with a prototype compound
The final point – open innovation in the clinic – is a challenging concept at first glance, but on deeper scrutiny it makes abundant sense. Under the traditional model, when a new target of pharmaceutical relevance is discovered, several companies earnestly begin the process of lead identification, selection, preclinical studies and ultimately human trials. However, when any of these companies’ efforts fail, the lessons learned are quietly buried at night. Useful information on safety, metabolism, rare adverse events and so on is lost.
The open innovation clinical model encourages collaboration around a public domain “pioneer” compound. Once the data has been collected, all parties would be free to innovate their own optimized proprietary compounds and hopefully avoid painful and costly missteps. The result? Shorter development times and fewer late stage clinical disasters.
This is good news for pharma, for academia and most importantly, for patients.