Move Fast But Don’t Break Things (When It Comes to Computational Biology)
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The mindset of “move fast and break things”, while great for code, isn’t exactly great for the human body. So adding computation to biology — especially in the slow-moving pharmaceutical industry, where drug approval can take years — brings with it both opportunities (like drastically faster discovery and assessment) and challenges (the need for hard evidence, not just soft-ware). But there’s more: We don’t want just better outcomes for healthcare. We want better outcomes at a cheaper price. And that’s where machine learning comes in. The benefits of such computation — i.e., software — can provide a powerful, frictionless, and far more cost-effective tool for biopharmaceutical research … but it requires data. So who provides that data? Is it the pharmaceutical companies, or the payers (insurance)? How are organizations incented to overcome intellectual property silos in sharing their data? Especially since it was only relatively recently, Jeff Kindler (the former CEO of the world’s largest pharmaceutical…