Drug discovery isn’t rocket science. It’s harder.

Early in my career, my manager used the phrase in the above headline to highlight the difficulty inherent in drug discovery. Over the ensuing years, I have seen that statement repeatedly confirmed by the brutal attrition in the discovery and development of new drugs. There are so many variables that can kill a drug discovery project — ranging from target validation and hit generation to off-target effects and formulation challenges — and that’s before even entering the clinic, where a whole new set of attrition factors arise. The number of variables to be simultaneously optimized is immense. One is never quite sure if it is even possible to thread the needle and arrive at a global optimum. It is a testament to the grit and persistence of drug discovery scientists that we have found as many lifesaving drugs as we have.

As a multiparameter optimization problem, drug discovery is perhaps the most challenging example we face. But recent advances in computational power and…

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