Robotically driven system could reduce cost of discovering drug and target interactions

A comparison of 51 diverse phenotypes that an active learner identified by the final round of experiments it performed. The phenotypes have been roughly organized in the display by similarity; the learner in several cases identified phenotypes that were created by different drugs that visually were subtly different.  Credit: Armaghan Naik and Robert F. Murphy Researchers from Carnegie Mellon University (CMU) have created the first robotically driven experimentation system to determine the effects of a large number of drugs on many proteins, reducing the number of necessary experiments by 70%. The model, presented in the journal eLife, uses an approach that could lead to accurate predictions of the interactions between novel drugs and their targets, helping reduce the cost of drug discovery. “Biomedical scientists have invested a lot of effort in making…


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