ReviewNature reviews. Drug discovery2026
Design, simulate, refine: simulation-guided clinical trials for accelerated drug development.
Review in Nature reviews. Drug discovery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern clinical trials are embracing innovative strategies including adaptive designs, biomarker-guided enrolment, master protocols and real-time decision-making. These approaches may accelerate discovery and improve outcomes, yet they also introduce additional complexity in study conduct and understanding of the design. Simulation-guided design can be a powerful tool for identifying the optimal design to address research questions and for understanding and communicating how the design functions in practice. Simulations can evaluate the operating characteristics of complex trials, including control of type I error and false discovery rate, power for sample size determination, and probabilities of adaptive decisions at interim analyses. Examining individual simulated trials alongside these summaries provides insight into how the design will perform in practice, allowing potential risks to be anticipated and the design refined. Here, we outline how trial simulation can empower clinical development teams, statisticians, data monitoring committees, regulators, sponsors, funders and patient advocates by improving cross-functional communication, enhancing understanding and providing objective justification for design choices. We also provide best-practice recommendations to ensure that simulation studies are valid, transparent, thorough, efficient and comparable - helping to create trial designs that are scientifically rigorous, ethically sound, operationally practical and ultimately capable of bringing safe and effective therapies to patients as efficiently as possible.
Identifiers
42443403What 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.