Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine
Abstract Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, and Uncertainty Quantification (VVUQ) for digital twins in ensuring safety and efficacy, with...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01447-y |
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| _version_ | 1832594448776691712 |
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| author | Kaan Sel Andrea Hawkins-Daarud Anirban Chaudhuri Deen Osman Ahmad Bahai David Paydarfar Karen Willcox Caroline Chung Roozbeh Jafari |
| author_facet | Kaan Sel Andrea Hawkins-Daarud Anirban Chaudhuri Deen Osman Ahmad Bahai David Paydarfar Karen Willcox Caroline Chung Roozbeh Jafari |
| author_sort | Kaan Sel |
| collection | DOAJ |
| description | Abstract Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, and Uncertainty Quantification (VVUQ) for digital twins in ensuring safety and efficacy, with examples in cardiology and oncology. We highlight challenges and opportunities for developing personalized trial methodologies, validation metrics, and standardizing VVUQ processes. VVUQ frameworks are essential for integrating digital twins into clinical practice. |
| format | Article |
| id | doaj-art-ee5c0fe980e047c0a0fb0c8a67c03892 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-ee5c0fe980e047c0a0fb0c8a67c038922025-01-19T12:39:54ZengNature Portfolionpj Digital Medicine2398-63522025-01-018111210.1038/s41746-025-01447-ySurvey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicineKaan Sel0Andrea Hawkins-Daarud1Anirban Chaudhuri2Deen Osman3Ahmad Bahai4David Paydarfar5Karen Willcox6Caroline Chung7Roozbeh Jafari8Laboratory for Information and Decision Systems, Massachusetts Institute of TechnologyInstitute for Data Science in Oncology, The University of Texas MD Anderson Cancer CenterOden Institute for Computational Engineering and Sciences, The University of Texas at AustinDepartment of Electrical and Computer Engineering, Texas A&M UniversityMicrosystems Technology Laboratories, Massachusetts Institute of TechnologyOden Institute for Computational Engineering and Sciences, The University of Texas at AustinOden Institute for Computational Engineering and Sciences, The University of Texas at AustinInstitute for Data Science in Oncology, The University of Texas MD Anderson Cancer CenterLaboratory for Information and Decision Systems, Massachusetts Institute of TechnologyAbstract Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, and Uncertainty Quantification (VVUQ) for digital twins in ensuring safety and efficacy, with examples in cardiology and oncology. We highlight challenges and opportunities for developing personalized trial methodologies, validation metrics, and standardizing VVUQ processes. VVUQ frameworks are essential for integrating digital twins into clinical practice.https://doi.org/10.1038/s41746-025-01447-y |
| spellingShingle | Kaan Sel Andrea Hawkins-Daarud Anirban Chaudhuri Deen Osman Ahmad Bahai David Paydarfar Karen Willcox Caroline Chung Roozbeh Jafari Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine npj Digital Medicine |
| title | Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine |
| title_full | Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine |
| title_fullStr | Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine |
| title_full_unstemmed | Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine |
| title_short | Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine |
| title_sort | survey and perspective on verification validation and uncertainty quantification of digital twins for precision medicine |
| url | https://doi.org/10.1038/s41746-025-01447-y |
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