The questions he asks here are exactly the questions that quantitative systems pharmacology (QSP) seeks to answer (and as a result, it's booming as a field). Ju

The questions he asks here are exactly the questions that quantitative systems pharmacology (QSP) seeks to answer (and as a result, it's booming as a field). Just because you can build a drug to inactivate said protein doesn't mean you should. 85% of clinical trials fail as he states, and one of the main reasons why is because the target ends up being incorrect. Targeting some protein because a lot of it seems to exist when a given disease is occurring might end up targeting the symptom instead of the cause. Understanding how the complex systems interact, their feedbacks and their nonlinearities, is essential to knowing what needs to be targeted. We had already been able to quickly create new drug candidates, and with protein folding predictions we can now do that even faster. Those drugs can be tested in a lab to see if they bind to the proteins they're supposed to, and they keep getting quicker at hitting exactly the function they expected. But without making the billion dollar clinical trial more likely to be solving the actual problem, we're still going to be limited by "okay, so what in this pool of possible drugs should we risk trying next"? We can accurately knock out protein function, but we're still fishing in the dark when it comes to how to actually fix and regulate bodies.