ReviewClinical and translational science2025
Critical Roles for Modeling and Simulation and Real-World Evidence to Inform Challenges in Clinical Trial Diversity Planning.
Review in Clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Diversity in Translation: Equal Is Greater Than.Clinical and translational science · 2026Article
- International Stakeholder Guidance for Improving Informativeness of Randomized Clinical Trials.JAMA network open · 2026Article
- Advancing women's health through equity in quantitative sciences: promoting sex- and gender-based modeling in clinical trials and real-world studies.Frontiers in digital health · 2026Article
- Comparative safety signals of carboplatin and cisplatin in lung cancer: a pharmacovigilance study based on FAERS.Frontiers in medicine · 2026Article
- Closing the loop: human-augmented, mechanistically enhanced AI for proactive management of drug-drug interactions.Frontiers in pharmacology · 2026Article
- Critical Roles for Modeling and Simulation and Real-World Evidence to Inform Challenges in Clinical Trial Diversity Planning.Clinical and translational science · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to the highly controlled settings of clinical trials, enrolled subjects may not be fully representative in age, gender, ethnicity, medical status, or socioeconomic background of the variety of patients who will ultimately receive a medication. This disconnect can lead to post-approval challenges, the most substantial of which could include changes in drug label, dosing, or withdrawal due to severe safety risks that were only observed post-approval. To mitigate these risks and improve the likelihood of approval of safe and effective treatments for patients in the real-world setting from both a medical and socioeconomic perspective, recent regulatory guidance has highlighted a critical role for the inclusion of appropriately diverse populations in clinical trials. To achieve this, there is an increasing need for approaches to facilitate sponsors' ability to generate regulatory-acceptable diversity plans. While epidemiological data may serve as the foundation for diversity planning, researchers are increasingly turning toward modeling and simulation (M&S) approaches to optimize study planning and increase the knowledge gained from study data. Additionally, real-world evidence (RWE) generation is receiving increased attention in the regulatory setting, but prior research has only begun to scratch the surface of the value these approaches can bring to trial diversity planning. Herein, we summarize the strategic value of M&S and RWE-based approaches in the context of trial diversity planning, highlighting unmet needs, prior thought leadership, and recent case examples with the goal of providing readers insight into their diversity planning at different stages of the drug development lifecycle.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.