  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.
