Background
Historically, pregnant individuals have been routinely excluded from clinical trials [ 1 ]. This has led to a gap in our understanding of how drugs can be administered safely and effectively during and post‐pregnancy. This absence of data compels clinicians toward two suboptimal treatment choices: using standard adult dosing derived from non‐pregnant individuals, which could lead to suboptimal exposures, or completely withholding therapies due to maternal and fetal safety concerns [ 2 ]. Despite these challenges, medication use during pregnancy is common and often medically necessary, particularly for individuals managing pre‐existing chronic conditions. On average, pregnant individuals are exposed to at least two drugs during the course of their pregnancy [ 3 ], so understanding the altered pharmacology during this time is essential.
The physiological changes during pregnancy such as altered gastrointestinal motility and pH, increases in total body water volume and cardiac output, decreases in blood protein concentrations, and alterations in hepatic enzyme activity have a profound and time‐dependent impact on a drug's absorption, distribution, metabolism, and excretion (ADME) properties, which has the potential to fundamentally change its overall pharmacological effect [ 4 ]. For example, the increase in total body water and concurrent decrease in plasma protein concentration can lead to two counteracting effects: while the increase in total body water can dilute drug concentrations, reduced plasma protein concentrations increase the unbound (free) drug [ 5 ]. Simultaneously, alterations in hepatic enzyme expression significantly influence the way drugs are metabolized and can lead to scenarios of reduced therapeutic exposure (due to increased CYP3A4 activity during pregnancy leading to quicker clearance) or conversely elevated risks of toxicity (due to decreased CYP1A2 activity during pregnancy resulting in slower excretion), ultimately impacting the optimal dose and subsequent efficacy and safety profiles [ 6 ]. Beyond maternal exposure, the fetus may also be exposed to drugs via placental transfer. This exposure is governed by the physicochemical properties of the medication as well as physiological changes in the fetus and placenta at different stages of gestation [ 4 ]. Consequently, clinicians must carefully manage dosing to avoid the risk of sub‐therapeutic treatment or maternal/fetal toxicity.
In an effort to address this knowledge gap, major global organizations, including the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA) in collaboration with the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH), and the World Health Organization (WHO), have issued recommendations or created task forces that support the inclusion of pregnant individuals in clinical trials [ 7 , 8 ]. Each organization emphasizes the need for improving pharmacoequity for this understudied population, highlighting key regulatory expectations and best practices for their inclusion in clinical trials.
The primary benefit of leveraging real‐world data (RWD) in this population is the ability to use post‐marketing safety and outcome data in situations where pregnant individuals are excluded from traditional randomized clinical trials. RWD thus enables researchers to capture the full scope of how drugs are currently being prescribed and used in real clinical practice.
Building upon this methodology, the work presented here demonstrates how RWD, specifically based on a U.S. closed health claims database (IQVIA PharMetrics(R) Plus), can be used to assess DMT and concomitant medication use before, during, and after pregnancy, with the objective of identifying real‐world prescription trends and potential drug–drug interaction (DDI) risks in this population. Two case examples of medication use in pregnant individuals with pre‐existing immune‐mediated diseases, Crohn's Disease (CD) and Multiple Sclerosis (MS), are presented here. These specific conditions were selected because they disproportionately affect women of childbearing age and often require continuous management with complex, highly‐specialized therapies (e.g., biologics), making them highly relevant indications for understanding real‐world medication utilization and potential DDI risks during pregnancy.
Materials and Methods
The IQVIA PharMetrics(R) Plus U.S. health plan claims database was utilized to investigate the use of prescription medications in pregnant individuals [ 9 ]. This database contains longitudinal adjudicated medical and pharmacy claims from de‐identified patients within the United States, dating back to 2006.
Pregnancy Cohort Identification
Pregnancies were identified using the ICD‐10 code (International Classification of Diseases) ‘Z37’ (‘Outcome of Delivery’) in women aged ≥ 18 years. Additional criteria for sex (self‐identified female) were applied, and inclusion was strictly limited to individuals with exactly one delivery during the designated timeframe of January 1, 2022 to December 31, 2023 (i.e., individuals with multiple deliveries within this window were excluded) (Figure 1 ). However, while the ‘Z37’ code encompasses all pre‐term and full‐term deliveries (live births and stillbirths), it does not capture women who experienced a spontaneous abortion, and therefore, those women are not included in this analysis. The ICD‐10 code ‘Z3A’ (‘Weeks of Gestation’) was leveraged to establish a chronological timeline of pre‐pregnancy, pregnancy, and post‐pregnancy periods. The earliest specified ‘Z3A’ record was used to retrospectively estimate the date of conception, classifying all prior medical records as pre‐pregnancy. Any record following the ‘Z37’ record was classified as post‐pregnancy, with any intervening record falling into the pregnancy time period. To analyze longitudinal drug usage across pregnant states, claims data for our pregnancy cohort were extracted from January 1, 2021 to June 30, 2024. This time frame ensures a minimum capture of at least 1 year pre‐pregnancy and 6 months post‐pregnancy.

CD and MS Cohort Identification
Patients diagnosed with CD or MS were identified by utilizing relevant ICD‐10 codes for each disease during 2021–2024. The CD cohort was filtered using the ICD‐10 code ‘K50’, and the MS cohort was filtered using the ICD‐10 code ‘G35’. In both cohorts, individuals needed evidence of at least 2 inpatient or outpatient diagnoses of CD or MS at least 30 days apart to be included.
DMT Analysis
For each patient, drug codes from each doctor's visit were cross‐referenced with the IQVIA PharMetrics(R) Plus database to identify generic drug names. In addition, for each disease cohort, a list of disease‐modifying therapies (DMTs) relevant to disease management/treatment was identified and string‐matched against the IQVIA drug reference tables to systematically extract all corresponding National Drug Codes (NDCs), which were used to identify patients receiving DMTs. For CD, the 13 defined DMTs included: anti‐TNF biologics (adalimumab, certolizumab pegol, and infliximab); non‐anti‐TNF biologics (risankizumab, ustekinumab, and vedolizumab); immunomodulators (azathioprine, mercaptopurine, and methotrexate); corticosteroids (budesonide and prednisone); and aminosalicylates (mesalamine and sulfasalazine). For MS, the 24 defined DMTs included: sphingosine 1‐phosphate (S1P) receptor modulators (fingolimod, ozanimod, siponimod, and ponesimod); interferons (interferon beta‐1a, interferon beta‐1b, and peginterferon beta‐1a); anti‐CD20 monoclonal antibodies (aCD20s) (ocrelizumab, ublituximab, rituximab, and ofatumumab); fumarates (dimethyl fumarate and diroximel fumarate); and other DMTs (alemtuzumab, natalizumab, azathioprine, cladribine, cyclophosphamide, daclizumab, minocycline, mitoxantrone, mycophenolate mofetil, glatiramer acetate, and teriflunomide). As this was an exploratory, observational study designed to characterize real‐world utilization, all analyses were descriptive in nature and no formal statistical hypothesis testing was planned or conducted to evaluate the significance of these trends.
Concomitant Medication Analysis
To assess potential drug–drug interaction (DDI) risks, the top 100 prescribed medications in each disease cohort were identified from the IQVIA PharMetrics(R) Plus database. These medications were cross‐referenced with the Drug Interaction Database (DIDB) to identify clinically relevant CYP3A4 inducers, inhibitors, and substrates, as well as P‐glycoprotein (P‐gp) inhibitors and Breast Cancer Resistance Protein (BCRP) inhibitors [ 10 ]. These specific pathways were selected for review because CYP3A4 is the primary metabolic enzyme for a majority of prescribed drugs, and P‐gp and BCRP are key efflux transporters that play a critical role in placental transfer. It is important to note that other metabolic and transporter pathways that could lead to DDIs exist but were not evaluated in this focused analysis.
Results
Crohn's Disease Cohort: DMT Utilization Patterns During Pregnancy
The initial CD pregnancy cohort consisted of 4414 individuals; filtering for individuals with a history of DMT use between 2021 and 2024 yielded the final analytic cohort of 2522 individuals. Within this cohort, 47% ( n = 1187) of individuals had one or more claims for at least one of the 13 DMTs queried during pregnancy, with utilization patterns showing several key trends across all pregnancy stages (i.e., pre‐pregnancy, pregnancy, and post‐pregnancy) (Figure 2 ). Notably, a shift away from certain therapies was observed, such as prednisone, whose use decreased during pregnancy ( n = 491→ n = 229). Conversely, sustained use of monoclonal antibodies (mAbs) was seen during pregnancy, constituting 67% ( n = 694) of DMT use during pregnancy. While interpreting raw prescription counts from pre‐pregnancy to pregnancy is limited by 33% of the cohort lacking medical records pre‐pregnancy, a comparison of the pre‐ and post‐pregnancy periods demonstrates a robust, sustained use of mAbs. Specifically, the proportion of the total cohort on any mAb therapy (including combination therapies) increased from approximately 21% pre‐pregnancy to 28% post‐pregnancy. Within this class, the specific increase in mAb utilization from pre‐pregnancy to pregnancy was driven by adalimumab (monotherapy) and ustekinumab. The usage of other mAbs or mAb‐derived medicines, including vedolizumab, infliximab, and certolizumab pegol, did not display a notable difference between pregnancy stages. Lastly, consistent prescription of mesalamine throughout all pregnancy stages was also observed.

Analysis of the route of administration for the DMTs used during pregnancy revealed that the majority were administered either orally or subcutaneously (Figure 3 ). Among oral DMTs prescribed, mesalamine, prednisone, and sulfasalazine were the most prevalent; adalimumab (or biosimilar), ustekinumab, and certolizumab pegol were the most prevalent subcutaneous DMTs prescribed.

Multiple Sclerosis Cohort: DMT Utilization Patterns During Pregnancy
The initial MS pregnancy cohort consisted of 2441 individuals; the final analytic cohort decreased to 1130 individuals after filtering for individuals with a history of DMT use between 2021 and 2024. Within this cohort, only 27% ( n = 300) of individuals were prescribed one of the 24 DMTs queried during pregnancy (Figure 4 ), representing a stark difference relative to the CD cohort. The primary DMT used during pregnancy was glatiramer acetate, a well‐studied immunomodulator. Glatiramer acetate use was fairly consistent across pre‐pregnancy ( n = 133), pregnancy ( n = 120), and post‐pregnancy ( n = 122) stages. In contrast, patients on other DMTs pre‐pregnancy often received no prescribed DMTs during pregnancy, highlighting a significant discontinuation of medication. Decreases in use were also observed across DMTs such as dimethyl fumarate ( n = 53→ n = 27), fingolimod hydrochloride ( n = 44→ n = 19), and diroximel fumarate ( n = 24→n = 13).

The predominant routes of administration for DMTs used during pregnancy in MS were subcutaneous or oral (Figure 5 ), with glatiramer acetate, interferon beta‐1A, and ofatumumab being the top subcutaneous DMTs prescribed, and dimethyl fumarate, diroximel fumarate, and fingolimod hydrochloride being the top oral DMTs prescribed.

Concomitant Medication Use
To conduct a comprehensive review of prescribed medications, our analysis of concomitant medications (conmeds) included the full cohort of pregnant individuals diagnosed with CD ( n = 4414) and MS ( n = 2441), including those without documented history of DMT use between 2021 and 2024. Expanding the sample size allowed us to capture a broader picture of prescription trends for each cohort. The top 100 conmeds prescribed during pregnancy for both disease cohorts identified the potential for drug–drug interactions (DDIs) mediated by CYP450s and drug transporters. More specifically, the CD cohort included 6 CYP3A4 inhibitors, 11 CYP3A4 substrates, 2 CYP3A4 inducers, and 3 P‐gp inhibitors in the top 100 conmeds (Table 1 ). The MS cohort showed comparable results, including 5 CYP3A4 inhibitors, 10 CYP3A4 substrates, 2 CYP3A4 inducers, 3 P‐gp inhibitors, and 1 BCRP inhibitor in the top 100 conmeds. Both cohorts showed more frequent usage of sertraline (an antidepressant, 7.1% of the CD cohort and 5.7% of the MS cohort) and azithromycin (an antibiotic, 5.7% of the CD cohort and 6.0% of the MS cohort). A full list of the top 100 conmeds in each cohort can be found in Tables S1 and S2 .
TABLE 1
Concomitant medication use and potential drug–drug interaction risk for the top 100 drugs prescribed during pregnancy in the CD and MS cohorts.
Note: Grayed out boxes indicate use is outside the top 100 drug list. Use in over 5% of individuals is in bold. Prednisone is in the top 100 drug list for MS but not CD; however, it is a DMT for CD.
| Drug | CD ( n = 4414) | MS ( n = 2441) | CYP3A4 inhibitor | CYP3A4 substrate | CYP3A4 inducer | P‐gp inhibitor | BCRP inhibitor |
| Alprazolam | 34 (0.8%) | Weak | Moderate Sensitive | ||||
| Azithromycin | 250 (5.7%) | 146 (6.0%) | Weak | Yes | |||
| Budesonide | 85 (1.9%) | Sensitive | |||||
| Buspirone | 45 (1.0%) | 27 (1.1%) | Sensitive | ||||
| Diazepam | 19 (0.8%) | Moderate Sensitive | |||||
| Fluconazole | 161 (3.6%) | 114 (4.7%) | Moderate | ||||
| Fluoxetine | 88 (2.0%) | 41 (1.7%) | Weak | ||||
| Fluticasone propionate | 101 (2.3%) | 58 (2.4%) | Sensitive | ||||
| Ketoconazole | 37 (0.8%) | 27 (1.1%) | Strong | Moderate Sensitive | Yes | ||
| Methylprednisolone | 62 (1.4%) | 33 (1.4%) | Moderate Sensitive | Weak | |||
| Nifedipine | 79 (1.8%) | 39 (1.6%) | Moderate Sensitive | Yes | |||
| Nirmatrelvir‐ritonavir | 49 (1.1%) | 28 (1.1%) | Strong | ||||
| Omeprazole | 178 (4.0%) | 46 (1.9%) | Moderate Sensitive | ||||
| Oxycodone | 63 (1.4%) | 26 (1.1%) | Moderate Sensitive | ||||
| Pantoprazole | 60 (2.5%) | Yes | |||||
| Prednisone | 254 (5.8%) | 84 (3.4%) | Weak | ||||
| Sertraline | 313 (7.1%) | 140 (5.7%) | Moderate Sensitive | ||||
| Trazodone | 34 (0.8%) | 29 (1.2%) | Moderate Sensitive |
Discussion
We utilized RWD to evaluate drug use patterns in individuals with pre‐existing conditions during different stages of pregnancy. While we initially examined drug use by trimester, the limited variability in DMT usage we observed led us to combine these into a single “pregnancy” stage. Based on the two case examples presented here for CD and MS, our major findings were: (a) 47% and 27% of patients with CD and MS, respectively, sustained DMT use during pregnancy, underscoring a critical clinical necessity of disease management, as untreated conditions can pose a greater risk to maternal and fetal outcomes and (b) both the CD and MS cohorts shared similarities in the frequency of conmed use during pregnancy, with sertraline (a CYP3A4 substrate) and azithromycin (a CYP3A4/P‐gp inhibitor) used in up to 7% of the patients, highlighting a safety consideration for clinical practice. Together these findings highlight the value of RWD as a window into current treatment practices, addressing crucial knowledge gaps in the pregnant population.
Our first case example evaluated the use of DMTs in CD. CD is most commonly diagnosed in early adulthood, with incidences peaking around 30 years of age, which coincides with the median age of our pregnancy cohort [ 11 ]. In our CD cohort ( n = 2522), we found that DMT use was fairly consistent across all pregnancy stages, with 47% ( n = 1187) of individuals taking a DMT during pregnancy. This sustained use of DMTs reflects the clinical necessity of disease management, as moderate to severe disease activity in CD is associated with adverse pregnancy outcomes, such as low birth weight and increased rates of preterm delivery [ 12 , 13 ]. While disease severity may fluctuate during pregnancy, its trajectory is largely dependent on the level of disease activity when conception occurs [ 14 ]. Our pregnancy CD analysis found three notable trends in DMT use that each reflect a high level of concordance with current medical society and global guidelines for the management of inflammatory bowel disease (IBD) during pregnancy [ 15 ]: (1) the decreased use of prednisone during pregnancy, (2) the off‐label use of mesalamine, and (3) the increased use of two mAbs, adalimumab and ustekinumab, during pregnancy.
Prednisone, a corticosteroid used to manage inflammatory conditions, including CD, was used less frequently during pregnancy in our cohort. This observed reduction may be related to a decrease in disease flares during pregnancy, thereby reducing the overall clinical need for the medication [ 16 ]. While some guidelines advise limiting long‐term exposure to minimize potential risks, prednisone is generally considered safe during pregnancy and is recommended when clinically indicated, as the benefits of controlling active disease outweigh the risks [ 17 , 18 , 19 ]. However, the optimal dose and long‐term safety profile of prednisone use during pregnancy remain areas of ongoing study due to a lack of well‐controlled studies in pregnant individuals, which may result in discrepancies in clinical recommendations [ 18 , 20 , 21 ]. Therefore, any treatment involving prednisone during pregnancy requires a highly individualized approach and close monitoring by a multidisciplinary medical team.
The second trend identified was the off‐label use of mesalamine in pregnant CD patients. While its use in CD is off‐label, it remains a commonly prescribed medication in clinical practice. Mesalamine is an anti‐inflammatory medication approved for use in ulcerative colitis, the other primary form of IBD [ 22 ]. While a portion of individuals in our CD cohort prescribed mesalamine were also diagnosed with ulcerative colitis ( n = 183/465), a large proportion were solely diagnosed with the CD form of IBD. Here we show evidence of its use in CD patients throughout all pregnancy stages, with 248 individuals receiving the drug during pregnancy. However, its efficacy for managing Crohn's Disease is inconclusive; research varies, with some articles suggesting benefit only at higher doses (≥ 4.0 g/day), while others conclude it is largely ineffective for management of CD [ 23 , 24 , 25 ]. Despite inconclusive data regarding its efficacy in CD, the continued use of mesalamine here likely reflects adherence to published guidelines that recommend the use of maintenance therapies throughout pregnancy to avoid disease relapse [ 26 ]. In the absence of demonstrably effective alternatives, physicians must carefully weigh the known benefits and theoretical risks of prescribing a medication that is not formally approved for use in this specific disease population, prioritizing disease control while minimizing potential maternal and fetal risk.
Lastly, our analysis revealed the increased use of two mAbs during pregnancy: adalimumab and ustekinumab. Use of these mAbs, which are both commonly used to treat a variety of autoimmune and inflammatory disorders including CD, likely highlights situations where pregnant individuals are experiencing moderate to severe disease activity. The sustained use of these and similar biologics is critical, as untreated severe disease poses a far greater risk for negative pregnancy outcomes than the medication itself [ 12 , 13 ]. While mAbs do have the potential to cross the placental barrier later in gestation via IgG transport, the observed rise in the use of these therapies underscores current clinical consensus and guidelines, which prioritize remission maintenance to ensure the best possible maternal and fetal prognosis [ 27 , 28 ].
Our second case example evaluated DMT use in individuals diagnosed with MS, an immune‐mediated neurodegenerative disorder that is typically diagnosed between the ages of 20 and 40 [ 29 , 30 ]. Within our MS cohort ( n = 1130), only 27% ( n = 300) of individuals were prescribed a DMT during pregnancy. Consistent with recent findings from a poster presentation by Houtchens et al. [ 31 ] and a 2024 review paper summarizing FDA and EMA recommendations [ 32 ], this significant discontinuation of medication during pregnancy and postpartum highlights a potential for under‐treatment. While treatment pauses are sometimes driven by contraindications or fertility planning, this high rate of discontinuation may not fully align with clinical recommendations that encourage continued disease management to prevent severe postpartum relapses. While this discontinuation may partially reflect natural disease fluctuations—as many individuals diagnosed with MS experience similar or fewer disease relapses when the immune system naturally adapts to the developing fetus [ 33 , 34 ]—this temporary remission should not be interpreted as an absence of clinical need. Even if symptoms are milder and more manageable during pregnancy, it is important to note that this period of remission is often followed by a significant rebound in disease activity and relapse risk in the immediate postpartum period [ 35 ].
In our analysis, when DMTs were used during pregnancy, a majority of individuals were prescribed glatiramer acetate ( n = 128), a well‐established immunomodulator approved in 1996. Its consistent use throughout all pregnancy stages is likely due to the large body of reproductive toxicology studies supporting its favorable maternal and fetal safety profile [ 36 , 37 ]. This contrasts with other small‐molecule DMTs, such as dimethyl fumarate, where the lack of data on second and third trimester exposure limits its use to cases where maternal benefit clearly outweighs fetal risk [ 38 ].
Both CD and MS cohorts shared similarities in the frequency of conmeds used during pregnancy. The frequent use of sertraline in both CD (7.1%) and MS (5.7%) cohorts highlights the prevalence of co‐existing mental health conditions, for which sertraline cannot easily be discontinued during pregnancy. Sertraline is a moderately sensitive CYP3A4 substrate, and its exposure can be altered by DMTs for CD or MS that modulate CYP3A4 activity. A similar complexity is observed with the use of the antibiotic azithromycin (CD: 5.7%, MS: 6.0%) which, while used acutely to treat infection, acts as both a weak CYP3A4 inhibitor and a P‐gp inhibitor. The oral administration of both sertraline (used more chronically) and azithromycin (used more acutely) places them at high risk for DDIs. Among our list of DMTs for MS and CD, there were various CYP3A4 substrates (cyclophosphamide, minocycline, azathioprine, budesonide, prednisone) and P‐gp substrates (mycophenolate mofetil, azathioprine, mercaptopurine, methotrexate, budesonide, prednisone). While our analysis did not identify any DMTs that are clinically relevant inhibitors or inducers of these targeted pathways, the presence of various enzyme and transporter modulators among the top 100 concomitant medications highlights a risk for DDIs mediated by these specific pathways. Because claims data cannot confirm concurrent daily consumption, this analysis was not designed to quantify actual DDI events (i.e., simultaneous intake of an inhibitor and substrate); rather, the rationale is to highlight the high baseline prevalence of these modulators to inform real‐world prescribing practices and future drug development programs. While we did not evaluate other potential interaction pathways, this finding necessitates routine evaluation of medication use by healthcare providers to manage individual patient safety in real time. The observed prevalence of polypharmacy during pregnancy not only complicates therapeutic dosing, but also highlights the need for standardized mitigation strategies for effective dosing with DMTs and underscores the need to understand drug disposition in pregnant individuals.
While this real‐world evidence analysis highlights important patterns in DMT use during pregnancy, it is limited by several factors. Notably, the IQVIA PharMetrics(R) Plus database predominantly comprises commercially insured patients, which may limit the generalizability of our findings. Although common in RWD analyses, several factors warrant consideration when interpreting these findings: (1) the potential for classification errors (such as reliance on ICD‐10 billing codes without clinical validation and the resulting temporal misclassification of specific pregnancy stages), (2) the lack of a matched control group for comparison, (3) the lack of granularity on disease severity metrics, (4) missing data, (5) the strictly descriptive nature of the analyses without formal statistical significance testing, and (6) the inability to filter for individuals with consistent coverage over the entire observational period due to small sample size. Furthermore, as our analysis is based on claims data, we lack information regarding the actual administration and concurrent consumption of dispensed drugs (limiting the ability to calculate accurate polypharmacy statistics), the use of over‐the‐counter medications not covered by insurance, and detailed health data that capture patient‐level safety information. Additionally, because our cohort was defined strictly by delivery outcomes, pregnancies ending in spontaneous abortion (miscarriage) were excluded; this introduces a survivorship bias that limits the evaluation of early‐pregnancy safety signals (as potential medication‐induced miscarriages are not captured) and may skew the interpretation of early medication utilization. In future analyses, it would be beneficial to prospectively collect and/or explore additional post‐pregnancy maternal and fetal outcomes (e.g., birth defects, preterm birth rates, and growth parameters) related to drug use to move toward evidence‐based risk assessments.
Drug treatment during pregnancy is a balance of benefits versus risks. On one hand, the possibility of severe disease relapses or rebound effects in individuals with highly active pre‐existing conditions who discontinue DMT use altogether poses serious risks to maternal health and subsequent adverse fetal outcomes. On the other hand, there is an unknown level of risk to fetal health due to the lack of clinical trial data. Although evaluation of adverse fetal outcomes and fetal exposure to DMTs was out of scope for this paper, this fundamental conflict between risks and benefits is the core dilemma that highlights a need for additional research and data for this population. Using RWD can provide a critical window into current treatment practices and use of concomitant medications in a population where clinical trial inclusion is incredibly difficult, but safe and effective drug use is warranted. Ultimately, these real‐world findings help identify specific areas of potential under‐treatment and prevalent DDI risks, providing essential context to guide evidence‐based prescribing practices and support evolving guidelines that optimize maternal and fetal safety.
Author Contributions
J.W., R.S., A.J., K.W.K.C., and B.V. wrote the manuscript and designed the research. J.W. performed the research; J.W., K.W.K.C., and B.V. analyzed the data.
Funding
The authors have nothing to report.
Conflicts of Interest
R.S., A.J., K.W.K.C. and B.V. are employees of Genentech Inc., and hold stocks/shares in F. Hoffmann‐La Roche Ltd. J.W. was an intern at Genentech Inc. when the work was performed.
Supporting information
Table S1: Top 100 Drugs Prescribed During Pregnancy in CD Cohort.
Table S2: Top 100 Drugs Prescribed During Pregnancy in MS Cohort.
Acknowledgments
The authors would like to thank Erwan Muros‐Le Rouzic, Monika Kaul, Maddalena Marchesi, and Wendy Halpern for their scientific guidance and discussions. We also thank Rong Zhang and Annamarie Bustion for RWD technical support and discussions. AI tools were used for assistance in drafting and revising the manuscript.
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