How Modern Data Ecosystems are Transforming Research for Drug Safety in Pregnancy

Nearly all pregnant women take medications during pregnancy, with approximately half of pregnant women in the United States taking at least one prescription medication. Yet, despite this widespread use, pregnancy and lactation data are lacking for more than 90% of FDA-approved drugs, with a similar data gap across Europe.

This evidence gap creates real challenges for pregnant women managing health conditions who may choose or be advised to continue their medication during pregnancy, regardless of whether its safety has been verified. These patients may be asked to participate in research and share intimate details about their health and their babies’ health during an already stressful time.

This requires researchers, drug manufacturers, and clinicians to prioritize the patient’s well-being while also safely, securely and sensitively collecting their data to better understand any maternal or infant health outcomes resulting from medication use. With global research and regulatory momentum, as well as advanced digital and mobile technologies, modern methods for collecting and sharing pregnancy safety data are more comprehensive and less cumbersome.

Their use, over time, will help gather critical safety information on which to base important health decisions during pregnancy.

The evidence gap

The challenges of understanding medication safety during pregnancy stem from various ethical and logistical dilemmas. Clinical trials, for example, test investigational products to assess safety and efficacy.

Exposing pregnant women to unknown risks could potentially impact both the mother’s and the child’s lives. That’s why fewer than 1% of clinical drug trials in the United States and in Europe enroll pregnant participants.

While every stakeholder across the clinical trial lifecycle will always aim to protect both maternal and fetal health and interests, this necessarily protective approach contributes to the evidence gap. Post-approval pregnancy safety studies, which investigate the safety of a drug on the market for pregnant women, are also extremely difficult to execute, primarily due to the challenge of recruiting enough pregnant women willing to share their data.

Because of these challenges, clinicians are left to provide recommendations for medication use despite clinical uncertainty, and patients are likely to receive inconsistent guidance on managing their health conditions while pregnant.

Data collection methodology landscape

While collecting pregnancy medication safety data to create a complete picture of health outcomes is challenging, it’s not impossible. There’s a spectrum of data collection methodologies based on varying evidence needs. The key is understanding what approach to use and when:

• Understanding exposure: Drug utilization studies are focused on understanding who is taking what medication, such as determining how many pregnant women with asthma use corticosteroids. These studies use retrospective data collection methods or existing data to determine the extent and duration of drug exposure.
• Capturing outcomes: These studies—prospective pregnancy registries, single-arm surveillance studies, and the PRegnancy outcomes Intensive Monitoring (PRIM) method—track health outcomes. Prospective registries, for example, collect data about pregnant women and infants (usually up to their first birthday), such as pregnancy complications or low birth weight.
• Leveraging existing data: Database studies focus on data already captured via electronic health records, medical claims, and other secondary sources to understand patterns associated with pregnancy and medication use.

Notably, different study designs have limitations and potential for bias. For rare diseases, the number of affected patients who are also women of childbearing age and taking the medication in question will be too small to be clinically relevant.

In this case, researchers must perform descriptive analytics on collected data (i.e., drawing observations based on available data, with no control group to compare results). Conversely, a condition such as multiple sclerosis affects a larger population within the childbearing age, making a more robust study with control cohorts for direct comparison feasible.

In most cases, complementary approaches will help balance different biases, such as using primary data collection studies that gather information directly from pregnant women alongside secondary database studies that capture data from larger populations but with less detail. Strategic data collection methodologies allow researchers to more efficiently and effectively deliver real-world evidence for this vulnerable group of people.

Building an integrated future

The core challenge researchers, drug manufacturers and clinicians face today is the inability to collect and use the wealth of existing data effectively. Linking disparate sources, with help from modern technologies, can transform that data into quality evidence.

For example, health systems have vast amounts of data on pregnant women and their medications. However, infant health records aren’t linked to maternal records, and when data exists in incompatible formats across siloed systems, valuable data cannot be used.

An integrated data ecosystem combines these data sources to generate larger datasets. A robust ecosystem could also merge registry-based data and patient-mediated data or incorporate regionally specific resources to ensure data for studies remains inclusive and adaptive to diverse populations.

Doing so creates a more comprehensive, longitudinal and accurate picture of outcomes for pregnant women and infants that will, in turn, generate evidence and proven guidance for future pregnancies. Technology can play a crucial role in creating an integrated database while reducing the burden of gathering and sharing information for pregnant women and healthcare providers.

Social media, for example, can be used as a direct-to-patient data strategy to improve recruitment in studies, while electronic questionnaires make participation easier and feel less intrusive. The goal is to minimize the burden of data collection during a stressful time.

When participation in studies feels simple, straightforward and stress-free, data completeness and quality will improve. Global regulatory collaboration is also foundational for pregnancy safety studies.

While regulators serve different populations and regions with distinct health systems and legislative priorities, there is still much-needed collaboration underway to enhance the statistical power of pregnancy safety studies. Initiatives such as IMI ConcePTION, which is working to create an ecosystem of reliable, accessible information about medications used during pregnancy and breastfeeding in Europe, are leading the way.

Taking a global approach allows more robust evidence that can help inform treatment decisions worldwide.

Progress is within reach

Transforming pregnancy drug safety research is possible, and the tools to do so are here. Now, researchers, drug manufacturers, providers and regulators must act by integrating data ecosystems, using technology thoughtfully and collaborating globally.

This is the path forward for closing the evidence gap and ensuring pregnant women, especially those managing existing health conditions, can make more informed decisions about their health and the health of their children.

About the Author

Karin de Haart, MSC Director Safety Evidence for Regulators Real World Solutions, IQVIA, has gained more than 15 years of experience working in drug development and clinical research after receiving her MSc in Health Sciences. Karin joined IQVIA Real World Evidence Solutions in 2009, leading both prospective and retrospective noninterventional studies, including rare disease and pregnancy registries. She has experience in a range of therapeutic areas. In her current role as Product Strategy Lead, she supports marketing global Real World Evidence Solutions study teams with assessing and implementing innovative approaches and study designs to generate safety evidence for regulators.

References

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