npj Systems Biology and Applications, Год журнала: 2024, Номер 10(1)
Опубликована: Окт. 2, 2024
Язык: Английский
npj Digital Medicine, Год журнала: 2025, Номер 8(1)
Опубликована: Янв. 17, 2025
Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, Uncertainty Quantification (VVUQ) for digital ensuring safety efficacy, with examples cardiology oncology. highlight challenges opportunities developing personalized trial methodologies, validation metrics, standardizing VVUQ processes. frameworks are essential integrating into clinical practice.
Язык: Английский
Процитировано
2
ACM Transactions on Multimedia Computing Communications and Applications, Год журнала: 2024, Номер unknown
Опубликована: Июль 10, 2024
Clinical trials are indispensable for medical research and the development of new treatments. However, clinical often involve thousands participants can span several years to complete, with a high probability failure during process. Recently, there has been burgeoning interest in virtual trials, which simulate real-world scenarios hold potential significantly enhance patient safety, expedite development, reduce costs, contribute broader scientific knowledge healthcare. Existing focuses on leveraging electronic health records (EHRs) support trial outcome prediction. Yet, trained limited data, existing approaches frequently struggle perform accurate predictions. Some attempted generate EHRs augment model but fallen short personalizing generation individual profiles. emergence large language models illuminated possibilities, as their embedded comprehensive proven beneficial addressing issues. In this paper, we propose model-based digital twin creation approach, called TWIN-GPT . establish cross-dataset associations information given generating unique personalized twins different patients, thereby preserving characteristics. Comprehensive experiments show that using created by boost prediction, exceeding various previous prediction approaches. Besides, also demonstrate high-fidelity data closely approximates specific aiding more result predictions data-scarce situations. Moreover, our study provides practical evidence application healthcare, highlighting its significance.
Язык: Английский
Процитировано
12
npj Digital Medicine, Год журнала: 2025, Номер 8(1)
Опубликована: Апрель 7, 2025
We developed a practical framework to construct digital twins for predicting and optimizing triple-negative breast cancer (TNBC) response neoadjuvant chemotherapy (NAC). This study employed 105 TNBC patients from the ARTEMIS trial (NCT02276443, registered on 10/21/2014) who received Adriamycin/Cytoxan (A/C)-Taxol (T). Digital were established by calibrating biology-based mathematical model patient-specific MRI data, which accurately predicted pathological complete (pCR) with an AUC of 0.82. then used each patient's twin theoretically optimize outcome identifying their optimal A/C-T schedule 128 options. The patient-specifically optimized treatment yielded significant improvement in pCR rate 20.95-24.76%. Retrospective validation was conducted virtually treating AC-T schedules historical trials obtaining identical observations outcomes: bi-weekly outperforms tri-weekly A/C-T, weekly/bi-weekly T T. proof-of-principle demonstrates that our provides methodology identify schedules.
Язык: Английский
Процитировано
1
npj Systems Biology and Applications, Год журнала: 2024, Номер 10(1)
Опубликована: Фев. 16, 2024
Abstract Medical digital twins are computational models of human biology relevant to a given medical condition, which tailored an individual patient, thereby predicting the course disease and individualized treatments, important goal personalized medicine. The immune system, has central role in many diseases, is highly heterogeneous between individuals, thus poses major challenge for this technology. In February 2023, international group experts convened two days discuss these challenges related twins. consisted clinicians, immunologists, biologists, mathematical modelers, representative interdisciplinary nature twin development. A video recording entire event available. This paper presents synopsis discussions, brief descriptions ongoing projects at different stages progress. It also proposes 5-year action plan further developing main recommendations identify pursue small number promising use cases, develop stimulation-specific assays function clinical setting, database existing models, as well advanced modeling technology infrastructure.
Язык: Английский
Процитировано
8
Knee Surgery Sports Traumatology Arthroscopy, Год журнала: 2025, Номер unknown
Опубликована: Фев. 24, 2025
Язык: Английский
Процитировано
0
The Lancet Oncology, Год журнала: 2025, Номер 26(3), С. e152 - e170
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0
Pervasive Computing Technologies for Healthcare, Год журнала: 2025, Номер unknown, С. 221 - 237
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Journal of Clinical Medicine, Год журнала: 2025, Номер 14(10), С. 3574 - 3574
Опубликована: Май 20, 2025
Background: Digital twin (DT) technology, integrated with artificial intelligence (AI) and machine learning (ML), holds significant potential to transform oncology care. By creating dynamic virtual replicas of patients, DTs allow clinicians simulate disease progression treatment responses, offering a personalized approach cancer treatment. Aim: This narrative review aimed synthesize existing studies on the application digital twins in oncology, focusing their benefits, challenges, ethical considerations. Methods: The reviews (NRR) followed structured selection process using standardized checklist. Searches were conducted PubMed Scopus predefined query oncology. Reviews prioritized based synthesis prior studies, focus Studies evaluated quality parameters (clear rationale, research design, methodology, results, conclusions, conflict disclosure). Only scores above prefixed threshold disclosed conflicts interest included final synthesis; seventeen selected. Results Discussion: offer advantages such as enhanced decision-making, optimized regimens, improved clinical trial design. Moreover, economic forecasts suggest that integration into healthcare systems may significantly reduce costs drive growth precision medicine market. However, challenges include data issues, complexity biological modeling, need for robust computational resources. A comparison cutting-edge contributes this direction confirms also legal considerations, particularly concerning AI, privacy, accountability, remain barriers. Conclusions: great promise, but requires careful attention ethical, legal, operational challenges. Multidisciplinary efforts, supported by evolving regulatory frameworks like those EU, are essential ensuring responsible effective implementation improve patient outcomes.
Язык: Английский
Процитировано
0
npj Systems Biology and Applications, Год журнала: 2025, Номер 11(1)
Опубликована: Май 23, 2025
Язык: Английский
Процитировано
0
Journal of Computational Science, Год журнала: 2024, Номер 82, С. 102400 - 102400
Опубликована: Авг. 2, 2024
Язык: Английский
Процитировано
3