Causal inference in drug discovery and development
Tom Michoel, Jitao David Zhang
Abstract
To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and improving decision-making in drug discovery. Although it has been applied across the value chain, the concepts and practice of causal inference remain obscure to many practitioners. This article offers a nontechnical introduction to causal inference, reviews its recent applications, and discusses opportunities and challenges of adopting the causal language in drug discovery and development.
Topics & Concepts
Causal inferenceInferenceCausality (physics)Drug discoveryData scienceComputer scienceArtificial intelligenceCognitive sciencePsychologyBioinformaticsMathematicsEconometricsBiologyQuantum mechanicsPhysicsComputational Drug Discovery MethodsAdvanced Causal Inference TechniquesBioinformatics and Genomic Networks