An introduction to causal inference for pharmacometricians

CPT Pharmacometrics Syst Pharmacol. 2023 Jan;12(1):27-40. doi: 10.1002/psp4.12894. Epub 2022 Dec 8.

Abstract

As formal causal inference begins to play a greater role in disciplines that intersect with pharmacometrics, such as biostatistics, epidemiology, and artificial intelligence/machine learning, pharmacometricians may increasingly benefit from a basic fluency in foundational causal inference concepts. This tutorial seeks to orient pharmacometricians to three such fundamental concepts: potential outcomes, g-formula, and directed acyclic graphs (DAGs).

MeSH terms

  • Artificial Intelligence*
  • Biometry*
  • Causality
  • Confounding Factors, Epidemiologic
  • Data Interpretation, Statistical
  • Humans