Concepts and Applications of Conformal Prediction in Computational Drug Discovery

Understand

Estimating the reliability of individual predictions is key to increase the adoption of computational models and artificial intelligence in preclinical drug discovery, as well as to foster its application to guide decision making in clinical settings.

• Among the large number of algorithms developed over the last decades to compute prediction errors, Conformal Prediction (CP) has gained increasing attention in the computational drug discovery community.
• A major reason for its recent popularity is the ease of interpretation of the computed prediction errors in both classification and regression tasks.
• For instance, at a confidence level of 90% the true value will be within the predicted confidence intervals in at least 90% of the cases.