Causal inference in drug discovery and development
This is an incremental review article aimed at practitioners in drug discovery to clarify concepts and practices of causal inference.
The paper provides a non-technical introduction to causal inference, reviewing its applications and discussing opportunities and challenges in drug discovery and development to reduce cognitive bias and improve decision-making.
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. While it has been applied across the value chain, the concepts and practice of causal inference remain obscure to many practitioners. This article offers a non-technical introduction to causal inference, reviews its recent applications, and discusses opportunities and challenges of adopting the causal language in drug discovery and development.