Honest question: how many of the rushed papers for #COVID19 drug predictions have led to experimental testing and subsequent promise? I've heard the "reason" that docking-only and AI-only papers are being pumped out is because we need solutions to the pandemic, and fast. 1/n
It's now been 3-4 months since a lot of that work started being published, and where has it got anyone? Have wet-labs picked up the ongoing stories of 1M, 100M, 600M docked molecules and tested any of them? How about the "AI discovers potential inhibitors of this or that"? 2/n
I'd be happy to be convinced that all this work was put to good use by someone, but somehow I'm doubtful. Certainly not in substantial amounts? Ultimately, in the 3-4 months that have passed, if more complete work was done, we'd have promising results now, no? So why rush? 3/n
Is the appropriate lesson then that nothing replaces good scientific research? The scientific method is described the way it is for a reason? 4/n
Don't get me wrong, serendipity is also an important piece of many scientific advances (and is integral to recent work I assisted), but throwing out computational outputs and hoping for someone else to test them is not collaboration, is not serendipity, and is not productive. 5/n
As far as I know, the approach has yielded little beyond wasting a reader's time. Collaboration is tough to build in a day, and requires fostering and nurturing. Without someone to trust and test your predictions, you may as well use RAND() in Excel and publish that list too. 6/n
If it's actually working, then I'd be glad to sit down and be quiet. Otherwise, maybe we should all spend more of this time at home forging new relationships and starting new collaborations rather than punching numbers into our computers and hoping someone else will care. 8/8
