Equity in health care must begin at birth

Pregnant women, as well as their babies, are often among the most neglected groups in clinical research, a challenge that is magnified by Covid-19. Despite the increased risk the pandemic poses to them and their newborns, vaccines were not systematically evaluated for use in pregnancy before they were widely distributed. This left pregnant patients and their doctors making consistent health decisions in real time with little data to inform their choice of whether or not to vaccinate.

Unfortunately, this is not a new trend: pregnant women are “severely underrepresented” in clinical research worldwide. Due to legal, ethical and logistical challenges in assessing the safety and effectiveness of medical products on them and the babies they carry, pregnant populations are often completely excluded from drug development. This lack of research has designated pregnant and lactating people as “therapeutic orphans” because there are few treatments that have been validated and approved for use in the general population. For people who belong to racial and ethnic minority groups or the LGBTQIA+ community and are pregnant, the disparities are even more profound.

The issue of representation in medical and drug development research is both clinically relevant and a major contributor to health equity disparities. Without reliable evidence of how health interventions affect pregnant patients and their babies, how can we ensure that they receive the same caliber of safe, effective and high-quality treatment as their non-pregnant peers? True health equity requires better-informed pregnancy care—and it must start at birth.

Data limitations make it difficult to conduct studies on how the therapies affect pregnant people and their children.

Ninety percent of women take some medication during pregnancy and postpartum, but of all drugs approved by the US Food and Drug Administration (FDA) between 2000 and 2010, nearly 75 percent reported no data on use in pregnant people.

To make informed decisions, regulators, life science companies, providers and patients must be able to answer fundamental questions about how medical interventions will affect pregnant women: Is this treatment safe and effective for them and their babies? What is the effect of not treating certain conditions during pregnancy? How is this treatment being used to treat pregnant patients in the real world, outside of tightly controlled clinical trials?

To help address some of these uncertainties, the FDA often requires manufacturers to report on the safety and effectiveness of their drugs on pregnant mothers and newborns after the therapies are on the market. Datasets known as pregnancy exposure registries exist to provide detailed real-world health information about individuals’ exposure to drugs, vaccines, and other products during pregnancy, but they have limitations: registries are expensive and can take time years to build with sufficient data to capture parent and child health outcomes over time.

In addition to the logistical challenges of completing a pregnancy registry, the FDA cited “lack of standardization of data collection, inconsistencies in outcome definitions/inclusion/exclusion criteria, and variation in the use of a comparator population” as shortcomings of these data sets. The European Medicines Agency (EMA) acknowledged such limitations, as well as low enrollment rates in pregnancy registries, high rates of patients lost to follow-up, and low statistical power.

Relevant and reliable data combined with advanced analytics can inform better decisions in clinical care during pregnancy and postpartum.

It is critical that the life sciences industry and the health care system enrich drug development with evidence of how medical products affect pregnant women and their children.

Real-world data – when relevant, reliable and appropriate for the purposes of answering a research question – can be used to generate evidence about how health interventions are performed in pregnant people. Where clinical trials may exclude these populations for ethical or safety reasons, properly generated real-world evidence can supplement, or sometimes replace, trials to inform regulatory and drug development decisions.

Equipped with the right data and analysis tools, pharmaceutical manufacturers can be proactive in considering potential risks and adverse events in pregnant populations earlier in development. Real-world data sets that link pregnant women to their babies enable comprehensive tracking of health outcomes over time, which can help overcome the challenges of working with today’s pregnancy registries. These powerful data and analytics capabilities could enable manufacturers to more effectively cater to these underserved groups.

The issue of representation in clinical research remains a threat to health equity, as do the devastating maternal and infant mortality rates in the United States, which disproportionately affect Americans of color and especially black Americans. With the right tools in hand and innovations emerging in the industry every day, the life sciences industry now has the opportunity and ability to ensure that healthcare equity begins at birth. Will we collectively deal with the situation? Only time will tell.

Photo: Natali_Mis, Getty Images

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