I was recently watching BioIDEA’s Biotech vs COVID-19 event. During the event our CEO, Andrew Satz, was asked about the viability of fully computational drug discovery and development. His answer surprised me. He discussed a number of legitimate hurdles that need to be addressed, but what I found most interesting was him pointing to industry resistance likely serving as the largest obstacle.
This is discouraging for us as a company and should be discouraging for anyone interested in drugs reaching patients faster and at more affordable prices. However, while we recognize barriers and continued resistance, we shouldn’t ignore what looks like an almost universal embrace of AI technology from large pharma since the onset of the global coronavirus pandemic.
Johnson & Johnson, the world’s largest pharmaceutical company with over $80 billion in revenue, recently invested heavily in AI. In fact, alongside a cohort of companies such as Bayer, Merck, GSK, and AstraZeneca, the Melloddy project has been initiated to compile data that can develop predictive models for drug discovery without giving up proprietary information. According to the Mathieu Galtier, Project Coordinator, Owkin, “the goal is to harness the collective knowledge of the consortium in a platform containing, amongst others, multi-task predictive machine learning algorithms incorporating an extended privacy management system, to identify the most effective compounds for drug development, while protecting the intellectual property rights of the consortium contributors,” More recently, Roche named computational and systems biologist, Aviv Regev, to lead its Genentech research unit. CEO Severin Schwan said the hire would, “…unlock even more possibilities in data-based drug discovery and development.” [link to source]
The benefits of computational drug development are well known and accepted by many in the pharmaceutical space. However, since the onset of the global pandemic, consensus went from it being an interesting concept that was almost certainly the future, to something we need implemented as soon as possible. This is one of the few silver linings of the coronavirus outbreak. Ronald Dorenbos, PhD, MSc, director and founder of consulting firm BioFrontline and a former head of innovation and scouting at Takeda stated, “A lot of the conservatism that was there in the industry is now kind of disappearing. Even some of these people that were against using [AI and machine learning], they now see the advantages.” [link to source]
One might be concerned over whether this embrace will turn cold or stagnant if/when the coronavirus is under control. I wouldn’t call this concern illegitimate, but we shouldn’t ignore the major profit incentive that comes along with a computational approach. This, if nothing else, should drive continued adoption, especially considering the aforementioned investments.
We can’t expect to revolutionize a system overnight and that’s not what I’m advocating for in this piece. However, I do hope that the next time ground-breaking, industry-shaking technology is readily available, it won’t require a global pandemic to get major players excited. Either way, large pharma is finally embracing AI, and that’s a good thing.