AI in drug discovery is overhyped: examples from AstraZeneca, Harvard, Stanford...

Hallo zusammen,

das Informatik-Forum geht in den Archivmodus, genaue Informationen kann man der entsprechenden Ankündigung entnehmen. Als Dankeschön für die Treue bekommt man von uns einen Gutscheincode (informatikforum30) womit man bei netzliving.de 30% auf das erste Jahr sparen kann. (Genaue Infos sind ebenfalls in der Ankündigung)

Vielen Dank für die Treue und das Verständnis!

    Von dem, was ich bisher gelesen habe, finde ich vor allem diesen Kommentar interessant:

    Zitat

    Imagine you were given raw data from the large hadron collider and you were asked to find interesting things in the data. What would you do ?Any serious scientist would see the folly of trying to run only machine learning algorithms to find the Higgs boson. What you would need (in addition to ML algorithms for processing) is a good theory of what you're looking at. This also means just applying computer science methods to the problem isn't going to work, you need to inject theory from physics.

    For drug discovery this means you need to actually do biology at some point in order to make progress. ML strategies involve tight loop around trying different models, implementing them, and checking to see if it does better than other models. What's needed is then good experiments to test your models and good models to make novel predictions.

    There is no getting away from wet lab experiments in biology if you're going to make any significant advances. The theory just isn't there to do purely computational work.