Encouraging Maternal Sacrifice: How Regulations Governing the Consumption of Pharmaceuticals During Pregnancy...

Pregnant women are routinely faced with the stressful decision of whether to consume needed medications during their pregnancies. Because the risks associated with pharmaceutical drug consumption during pregnancy are largely unknown, pregnant women both inadvertently consume dangerous medications and avoid needed drugs. Both outcomes are harmful to pregnant women and their fetuses. This unparalleled lack of drug safety information is a result of ill-conceived, paternalistic regulations in two areas of the law: regulations governing ethical research in human subjects and regulations that dictate the required labels on drugs. The former categorizes pregnant women as "vulnerable" and thus precludes them from most medical research. The result is that ninety-one percent of drugs lack any reliable safety information for pregnant consumers. The latter currently requires all drug labels to encourage drug avoidance during pregnancy, despite ample evidence that avoiding needed medications can harm pregnant women. On June 30, 2015, new pregnancy labeling regulations took effect. Though these regulations make important improvements, they continue to treat pregnant women unlike any population, including other unique subpopulations, such as children. As a result, the new regulations do not fix the problem of over-warning pregnant women about the risks of drug consumption. This article questions the legitimacy of both regulations and suggests three reforms for how to improve access to vital safety information: (1) amend the regulations governing ethical research in human subjects to reclassify pregnant women as non-vulnerable adults; (2) create incentives to generate safety data in pregnant women by granting a period of market exclusivity for drug companies that invest in this research; and (3) make the FDA pregnancy labeling regulations consistent with the routine FDA practice of requiring the display of balanced, human data on risk.