The scale of this work is quite impressive but the idea of applying neural nets to chemistry dates to the 80's or 90's, possibly earlier. It all comes down to

The scale of this work is quite impressive but the idea of applying neural nets to chemistry dates to the 80's or 90's, possibly earlier. It all comes down to the quality of the data and whether the model(s) are actually predictive rather than retrospective. Medicinal chemistry is a conservative field, but given the series of "totally remakes the field" events that have occurred over the last 30+ years, some of the resistance is understandable. Gasteiger and Zupan have a survey from 1993: Neural Networks in Chemistry (Angew Chem Int Ed Engl 32,503). The big thing will be if it helps prevent compounds dying in the clinic, as such late in the day failures are the most expensive. ADME/Tox prediction would be a huge win, although QSAR/QSPR has been fighting this war basically forever. The companies have the data while the researchers have the methods and bodies - getting these two entities to work together have prevented success in the past. Although the data is not as good as one would hope, particularly after the merger mania in pharma have mixed up all the datasets. Edit: They published a whole book about it in 1999: Neural Networks in Chemistry and Drug Design (Wiley, probably $$). Also thought to add that I have no relationship to his work.