Pregnant and breastfeeding women have historically been excluded from medical research, resulting in substantial gaps in evidence on the safety and efficacy of medicines and vaccines.
Analysis led by the Global Observatory on Health Research and Development of all clinical trials in the International Clinical Trials Registry Platform (ICTRP) reveals that just 4% of clinical trials over the past decade allowed the inclusion of pregnant women. As a result, many pregnant and breastfeeding women are left without treatment options or take prescription medicines off-label, without adequate data to inform safe use.
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In response, the World Health Organization (WHO) established a global task force to tackle this, with the aim of achieving timely and ethical inclusion of pregnant and breastfeeding women in clinical research for medical health products by 2030.
This is not just a task for agencies like WHO to take on, however, says Sheila Diamond, director of scientific engagement at Medidata, and is something that all parties involved in clinical trials need to address to improve access.
This interview has been edited for length and clarity.
Abigail Beaney (AB): Why are women so underrepresented in clinical trials?
Shelia Diamond (SD): With my work in Medidata and as a board-certified genetic counsellor, I have seen firsthand how these healthcare disparities widen as medicine becomes more advanced. As we move to an era of precision medicine, it holds such incredible promise, but without including these populations across the board, we can’t necessarily innovate in the way we need to without closing those gaps. This same principle applies to women in clinical trials – we see women and pregnant women are excluded from research, and then we’re not able to eliminate that risk, which further creates that knowledge gap.
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By GlobalDataIn medicine, we see that uncertainty can be just as harmful as exposure. A lot of the challenges boil down to these fundamental biological differences between the male and female bodies, like chromosomal differences and hormonal differences, the way we metabolise drugs, or pharmacokinetics, so promoting this equity in clinical research means designing studies that reflect the real-world populations that we serve. It means moving beyond protecting groups through exclusion and instead protecting them through thoughtful and data-driven inclusion.
A lot of those gaps directly lead into clinical uncertainty and historically, medicine has operated on this assumption that it’s the male physiology that could represent humanity as a whole. That assumption shows up in these clinical trials, from restricting eligibility criteria to underpowering sex-specific differences in these analyses that matter.
It wasn’t until 1993 in the US that women were even allowed to be included or participate in clinical trials. We continue to navigate this systemic bias in health care and when we look at the barriers, structurally and culturally, we see them in specific diseases and therapeutic areas. We know that cardiovascular disease is the leading cause of death for women globally, but despite this, women often receive less preventive counselling, and have delays in diagnosis. There have even been studies that show up to 30% longer wait time for heart attack evaluations for women – a factor that further highlights significant gender biases.
Another disease is Alzheimer’s, where women account for nearly two-thirds of the nearly seven million Americans living with the condition. Another is autoimmune diseases – I think up to 70% of autoimmune diagnoses are in women and the majority of the most common autoimmune diseases, like rheumatoid arthritis and multiple sclerosis, are actually more prevalent in women than men.
When patients experience these delayed diagnoses, it erodes trust and can influence willingness and eligibility to participate in research.
AB: Is there a subpopulation of women who are even less represented in research?
SD: Within the population of women, women who are breastfeeding and women who are pregnant are even further excluded from trials due to these specific barriers. In addition to our differences in biology and hormonal fluctuations, there are logistical burdens, caregiving responsibilities and over-cautious reproductive criteria that are excluding women across the board. Particularly in these populations, we see how that trial design itself can then unintentionally perpetuate that gap.
AB: What kind of dangers can this pose for that population if they’re not aware of the way that a drug might interact with them?
SD: The way women metabolise these drugs is quite different, but adding the layer of pregnancy adds a further layer of complexity. Just because a woman is pregnant, it does not exclude them from developing other diseases and cancers and it’s so important to be able to account for that.
It’s not only a moral and ethical question that’s evolving, but a scientific imperative. The question is, is it more protective to exclude pregnant women, or is it to design more thoughtful stage inclusion strategies that generate some real evidence?
These populations, especially pregnant women, have been historically labelled as a vulnerable population, and that’s led to widespread exclusion from research. While the intention of that was protection, the result has been profound data gaps.
There’s historically been this cautious approach that when we’re involving women in clinical trials, especially those of childbearing age. We see the thalidomide tragedy in pregnant women; it wasn’t known what the effect was on the babies that they were carrying and they then proceeded to give birth to babies with major limb malformations. When this happened in the late ’60s, it caused researchers to be very cautious, as this showed the damage that experimental therapies could have in pregnancies. That very much has stemmed into many of these changes, but there has been movement.
We are seeing more pregnancy exposure registries, more adaptive trial designs and more integration of real-world evidence and with advanced analytics and simulation modelling, we can better evaluate these signals earlier to reduce unnecessary exposure. And this is where responsible use of artificial intelligence (AI) and advanced analytics becomes powerful with the data assets that are available, which helps us design safer inclusion criteria, rather than defaulting to exclusion.
AB: We have seen that call from the WHO to increase the inclusion of pregnant and breastfeeding women in clinical trials. Whose responsibility do you think it is to make sure that sponsors are aware of the best practices to go about this?
SD: I think it’s all stakeholders, WHO, regulators, sponsors, physicians, scientists, trial patients and accessibility to clinical trials for the population to be representative and diverse.
AB: What are some of the best practices that sponsors can implement to try to include more of this patient population in clinical trials?
SD: We are seeing smarter trial designs, with specifically designed inclusion approaches where pregnancy populations may be included after initial safety data is established. Also incorporating more adaptive trial designs – that’s specifically around increasing inclusion of women by using real-time adjustments that can be made to study protocols based on data, modifying eligibility criteria in written populations and even adjusting randomisation to include certain subgroups.
We are also seeing more pregnancy exposure registries, which include studies that collect health information on exposure to certain medicines and therapies during pregnancy, because of the differences in metabolising and the effect it has on the pregnancy.
Then, of course, there are global organisations like the WHO that are encouraging clearer ethical and regulatory guidance; they also encourage multi-stakeholder collaboration. All those things I mentioned require multi-sector collaboration. It’s not just one side of the house; it’s everyone collectively working together, ensuring that their diverse thoughts and input are integrated into this wider remit, and of course, increased investment in funding in women’s health research is key.
