ReviewCureus2025
Virtual Patients in Clinical Trials for Drug Development: A Narrative Review.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Model-Based Virtual Clinical Trial Reveals Renal Impairment and Body Size as Key Determinants of Pharmacokinetic Variability and Drug-Drug Interaction Risk in Propranolol Therapy.Pharmaceutics · 2026Article
- A virtual cohort framework with applications to adoptive cell therapy in bladder cancer.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pharmaceutical industry faces significant challenges due to the prolonged development timelines, high failure rates of innovative drugs, and escalating regulatory demands for robust data. A novel solution to address these challenges is the utilization of virtual patient cohorts to simulate drug effects in computer models. This review article provides an overview of the application of virtual patient cohorts in drug development and the diverse methodologies employed, based on a comprehensive literature review. Complementing previous reviews, this work emphasizes the practical applications of virtual patients across various disease conditions, especially rare diseases where patient recruitment is particularly challenging. It also highlights the challenges of conventional trial methodologies, such as limited generalizability, ethical concerns, and recruitment barriers, and discusses virtual patients as a potential solution to these longstanding issues. Since all literature was included according to the judgment of a single reviewer, a potential selection bias must be taken into account when reading this article. Virtual patients can be generated as digital twins through statistical inference or by randomly assigning parameters, followed by plausibility assessments, with the method choice depending upon study objectives and available data. These cohorts find utility across all clinical phases of drug development. The principal advantages of leveraging virtual patient cohorts include potential cost savings through heightened development success and increased innovation. Moreover, they offer improved representation of patient groups often marginalized in drug development efforts. However, it is imperative to acknowledge the computational nature of virtual patients, which can yield erroneous outcomes and necessitate substantial expertise and computational resources. Currently, there is a lack of standardized protocols for generating and utilizing virtual patient cohorts. Nonetheless, virtual patient cohorts hold promise in fundamentally transforming drug development and patient treatment approaches. By creating realistic virtual patients, more efficient and personalized drug development strategies can be pursued. Integrating this technology alongside in vitro and in vivo studies, while considering their respective limitations, might significantly enhance the success rate of drug development across the pipeline, ultimately advancing patient health outcomes.
Indexed as
Identifiers
What Socratic 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 Socratic graph.