Pregnant women and their babies are often one of the most overlooked groups in clinical research, and Covid-19 has exacerbated this challenge.Vaccines despite pandemic putting them and their newborns at greater risk no systematic review Use during pregnancy before widespread distribution. This allows pregnant patients and their doctors to make real-time, corresponding health decisions with little data to inform their vaccination choices.
Unfortunately, this is not a new trend: pregnant women are “Seriously underrepresented“In clinical research around the world. Pregnant women are often completely excluded from drug development due to the legal, ethical and logistical challenges of assessing the safety and efficacy of medical products for them and the infants they carry. This lack of research Pregnant and lactating persons have been designated”Treat orphans,” because few treatments have been validated and approved for use in the population. For those who are part of a minority or LGBTQIA+ community and are pregnant, gap run deeper.
Issues of representation in medical and drug development research are clinically important and a major contributor to health equity disparities. Without solid evidence on how health interventions affect pregnant patients and their babies, how can we ensure they receive the same safe, effective and high-quality treatment as their non-pregnant peers? True health equity requires smarter pregnancy care — and it should start at birth.
Data limitations make it difficult to study how the treatment affects pregnant women and their children.
ninety percent of women take some medications during pregnancy and postpartum, but of all medications approved by the U.S. Food and Drug Administration (FDA) between 2000 and 2010, nearly 75% No data are reported for use in pregnant women.
To make informed decisions, regulators, life sciences companies, providers and patients need to 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 are the effects of not treating certain conditions during pregnancy? How could this treatment be used to treat pregnant patients in the real world, outside of highly controlled clinical studies?
To help resolve some of these uncertainties, the FDA often requires manufacturers to report on the safety and efficacy of their drugs for pregnant mothers and newborns after a therapy is marketed.The dataset is called Pregnancy Exposure Registry Real health information exists to detail an individual’s exposure to drugs, vaccines, and other products during pregnancy, but they have limitations: registration is expensive and can year Build enough data to capture the health of parents and children over time.
In addition to the logistical challenges of completing pregnancy registration, FDA has quote “Lack of standardization of data collection, inconsistent outcome definition/inclusion/exclusion criteria, and differences in the use of comparison populations” are shortcomings of these datasets. European Medicines Agency (EMA) admit Similar limitations, as well as low registration rates in pregnancy registries, high levels of patients lost to follow-up, and low statistical power.
Relevant and reliable data combined with advanced analytics can lead to better decisions for pregnancy and postpartum clinical care.
It is critical that the life sciences industry and healthcare system infuse drug development with evidence of how medical products affect pregnant women and their children.
Real-world data—when relevant, reliable, and appropriate to answer specific research questions—can be used to generate evidence on how health interventions work in pregnant women.clinical trials possible exclude Properly generated real-world evidence in these populations can complement or sometimes replace trials to inform regulatory and drug development decisions for ethical or safety reasons.
Armed with the proper data and analytical tools, drugmakers can think proactively about potential risks and adverse events in pregnant populations early in development. Real-world datasets linking pregnant women with their babies can comprehensively track health outcomes over time, helping to overcome the challenges of working with today’s pregnancy registries. These powerful data and analytics capabilities can enable manufacturers to more effectively care for these underserved populations.
Representation issues in clinical research still pose a threat to health equity, devastating Maternal and Infant Mortality in the U.S.which disproportionately Affects people of color, especially black Americans. With the right tools and the innovations that occur across the industry every day, the life sciences industry now has the opportunity and ability to ensure health equity starts at birth. Will we respond collectively? Only time will tell.
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