Low Data Drug Discovery with One-shot Learning

Understand

Recent advances in machine learning have made significant contributions to drug discovery.

• Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds.
• However, the applicability of these techniques has been limited by the requirement for large amounts of training data.
• In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications.