ReviewClinical and translational science2025
How Clinical Pharmacology Can Support Clinical Trial Diversity and Inclusion.
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 3 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
3 citing papers in PubMed.
- Diversity in Translation: Equal Is Greater Than.Clinical and translational science · 2026Article
- Community Partnerships in Clinical Research: A Framework for Sustainability and Resilience.Clinical pharmacology and therapeutics · 2026Review
- How Clinical Pharmacology Can Support Clinical Trial Diversity and Inclusion.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
Enrolling diverse populations during early clinical trial development and planning for diversity plans could be challenging. In 2024, the Diversity and Inclusion Clinical Pharmacology Leadership Group Working Group (D&I CPLG WG) from The International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) collaborated with the American Society for Clinical Pharmacology and Therapeutics (ASCPT) to develop a pre-conference session with speakers from industry, regulators, and IQ to utilize clinical pharmacology tools and implement the guidance on diversity plans toward improving the participation of under-represented populations in clinical trials. The pre-conference was well attended by industry, academia, as well as regulators and led to robust presentations and panel discussions through speaker sessions and case studies. The three state-of-the-art lectures and five case studies address key issues concerning the inclusion of underrepresented populations, as well as clinical pharmacology strategies to support the assessment of benefits and risks. The sessions offered insights into clinical pharmacology strategies for evaluating the effects of age, ethnic differences, organ impairment, drug metabolism, transporters, and translational pharmacogenetics approaches in clinical trials. They also highlighted the application of model-informed drug development (MIDD)-based extrapolation to bridge Phase III results to targeted subpopulations, thereby enhancing the efficiency of drug development. Additionally, the diverse formats of this pre-conference, including a hands-on workshop, breakout sessions, and panel discussions, provided an opportunity for the audience to discuss the practicalities of incorporating these principles in drug development settings. This conference reinforced that achieving diversity in clinical trials is a multifaceted challenge that requires sustained efforts across the clinical research ecosystem, guided by a commitment to equity and community engagement. As clinical pharmacologists, we are uniquely positioned to lead this transformation, ensuring future therapies are safe, effective, and equitable for all.
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.