A report in the Journal of Medical Internet Research shows developments in the evidence gap in drug safety during pregnancy in its News and Perspectives section. In "How Machine Learning Can Help Close Evidence Gaps for Drug Safety in Pregnant Women", health writer Michelle Falci interviews the principal investigators of two projects which use machine learning to analyze large datasets of medication exposure and outcomes, then identify and evaluate possible links.
Pregnant participants excluded from clinical trials
Medical research has a serious problem with underrepresentation, Falci reports; only 4% of clinical trials over the last decade included pregnant women as participants. This trend dates back to 1977, when the US Food and Drug Administration recommended not to include pregnant women, or women capable of becoming pregnant, in phase 1 and 2 clinical trials, resulting in a gap in evidence on drug safety for pregnant women (and contributing to a broader underrepresentation of female participants in research). Though efforts have been made to determine medication safety for pregnant and breastfeeding women, these have fallen short in practice.
Closing the gap with machine learning
