A Review of Virtual Twins in Physiologically‐Based Pharmacokinetic Modeling and Simulation

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.