Pushing the boundaries of behavioral analysis could aid psychiatric drug discovery

Drug discovery for psychiatric conditions is stagnating. Behavioral changes could be used as a primary phenotypic screen for new drug candidates, if enough useful data can be generated from behavioral models. Could machine learning be the answer to extracting the data we need?

Automated summary

Drug development for psychiatric conditions is not progressing well. Behavioral changes could be used as the primary screening method for new drug candidates if enough useful data can be generated from behavioral models. Machine learning might be the solution to extract the necessary data.