ReviewClinical pharmacology and therapeutics2026
A Review of Virtual Twins in Physiologically-Based Pharmacokinetic Modeling and Simulation.
Review in Clinical pharmacology and therapeutics, 2026. 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.
- From Prediction to Decision Making: PBPK and QSP as Regulatory-Grade NAMs.Clinical pharmacology and therapeutics · 2026Review
- Editorial: Model-informed approaches: uniting drug development with personalized medicine.Frontiers in pharmacology · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The novel application of Virtual Twins (VT) in PBPK (VT-PBPK) presents the opportunity to advance precision dosing and accelerate the shift from one-size-fits-all to targeted, individualized treatments. This review aims to: (1) critically evaluate existing research on the use of VTs in PBPK, (2) develop a conceptual definition of VT-PBPK, (3) describe and evaluate VT methodological diversity, (4) examine existing regulatory frameworks and guidance governing the integration of VT-PBPK, and (5) identify opportunities and challenges for advancing next-generation VTs. A structured literature search was conducted to identify studies describing VT-PBPK of a whole human body for the purpose of predicting drug concentration and/or effect. Details of the VT-PBPK models and VT design were extracted from each study. A framework assessing and categorizing methods of simulation and virtualization was applied to the extracted data. Twenty-two (22) studies were included which demonstrated the application of VT-PBPK across a range of populations, disease states, and drug classes. All studies applied VT-PBPK to real-world patient-specific covariate data retrospectively for the purpose of PBPK model development and evaluation, or model-informed precision dosing (MIPD). In the VT approaches, three levels of virtualization were identified; low, medium, and high, as determined by the number of covariates integrated into the model. To date there is no specific regulatory guidance on the appropriate use of VT-PBPK. A shift in application of PBPK modeling from population-based to specific, individualized predictions is required to advance VTs toward clinical implementation. Achieving rigorous design and evaluation of VT models will require strong interdisciplinary collaboration.
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.