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Genetically Informed Research Designs in Perinatal Pharmacoepidemiology: A Methodological Overview
Alexis C Carson1,2, Mahmoud Zidan1,2,3, Emilie Willoch Olstad1,2
1PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
Drug Safety
|March 2, 2026
Summary
Genetically informed research designs improve the safety evaluation of medications during pregnancy. These methods address biases in observational studies, strengthening causal inference for child outcomes in perinatal pharmacoepidemiology.
Area of Science:
- Perinatal Pharmacoepidemiology
- Genetic Epidemiology
- Causal Inference
Background:
- Clinical trials for medication safety in pregnancy are ethically and methodologically challenging.
- Observational studies are crucial but susceptible to bias due to lack of randomization.
- Integrating genetic information offers potential to mitigate confounding in perinatal pharmacoepidemiology.
Purpose of the Study:
- To review genetically informed research designs for child outcomes in perinatal pharmacoepidemiology.
- To discuss the strengths, limitations, and current applications of these methods.
- To outline considerations for future implementation in research.
Main Methods:
- Review of genetically informed designs: discordant sibling designs, polygenic scores, and Mendelian randomization.
- Analysis of their application in perinatal pharmacoepidemiology for child outcomes.
- Discussion of challenges including data availability and integration.
Main Results:
- Genetically informed designs can address confounding and strengthen causal inference in observational studies.
- Application of these methods in perinatal pharmacoepidemiology remains limited but promising.
- Successful implementation requires careful consideration of genetic data integration and instrument selection.
Conclusions:
- Genetically informed research designs offer a powerful approach to enhance causal inference in perinatal pharmacoepidemiology.
- Addressing biases through genetic data can improve the assessment of medication safety during pregnancy.
- Future research should focus on overcoming implementation barriers to leverage these advanced methods.
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