{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T17:39:42Z","timestamp":1793727582893,"version":"4.6.1"},"reference-count":165,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biotechnology Advances"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.biotechadv.2026.109040","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T15:49:07Z","timestamp":1788968947000},"page":"109040","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["A cellular Digital Twin framework for predictive and mechanistic modeling of drug responses in precision medicine"],"prefix":"10.1016","volume":"93","author":[{"family":"Danishuddin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5158-4558","authenticated-orcid":false,"given":"Md Azizul","family":"Haque","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geet","family":"Madhukar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shawez","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahper Nazeer","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jong-Joo","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.biotechadv.2026.109040_bb0005","doi-asserted-by":"crossref","first-page":"321","DOI":"10.3390\/cimb47050321","article-title":"The potential use of digital Twin Technology for Advancing CAR-T cell therapy","volume":"47","author":"Aghamiri","year":"2025","journal-title":"Curr. Iss. Mol. Biol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0010","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s10928-021-09790-9","article-title":"Recent applications of quantitative systems pharmacology and machine learning models across diseases","volume":"49","author":"Aghamiri","year":"2022","journal-title":"J. Pharmacokinet. Pharmacodyn."},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0015","doi-asserted-by":"crossref","DOI":"10.1002\/cnm.3601","article-title":"Toward an artificial intelligence-assisted framework for reconstructing the digital twin of vertebra and predicting its fracture response","volume":"38","author":"Ahmadian","year":"2022","journal-title":"Int. J. Numer. Method Biomed. Eng."},{"issue":"10","key":"10.1016\/j.biotechadv.2026.109040_bb0020","doi-asserted-by":"crossref","first-page":"1392","DOI":"10.1093\/jamia\/ocy106","article-title":"Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype","volume":"25","author":"Albers","year":"2018","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s44446-025-00055-x","article-title":"AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare","volume":"34","author":"Alharthi","year":"2025","journal-title":"Saudi Pharm. J."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0030","doi-asserted-by":"crossref","DOI":"10.3389\/fsysb.2022.928387","article-title":"Drug development digital twins for drug discovery, testing and repurposing: a schema for requirements and development","volume":"2","author":"An","year":"2022","journal-title":"Front. Syst. Biol."},{"issue":"5","key":"10.1016\/j.biotechadv.2026.109040_bb0035","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1093\/bioinformatics\/btw700","article-title":"Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction and a library interface","volume":"33","author":"Andrews","year":"2017","journal-title":"Bioinformatics"},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0040","doi-asserted-by":"crossref","DOI":"10.15252\/msb.20178124","article-title":"Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets","volume":"14","author":"Argelaguet","year":"2018","journal-title":"Mol. Syst. Biol."},{"issue":"4","key":"10.1016\/j.biotechadv.2026.109040_bb0045","doi-asserted-by":"crossref","DOI":"10.1101\/cshperspect.a005934","article-title":"Signaling networks: information flow, computation, and decision making","volume":"7","author":"Azeloglu","year":"2015","journal-title":"Cold Spring Harb. Perspect. Biol."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0050","doi-asserted-by":"crossref","first-page":"e188","DOI":"10.7861\/fhj.2021-0095","article-title":"Artificial intelligence in healthcare: transforming the practice of medicine","volume":"8","author":"Bajwa","year":"2021","journal-title":"Fut. Healthc. J."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0055","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1109\/TPAMI.2018.2798607","article-title":"Multimodal machine learning: a survey and taxonomy","volume":"41","author":"Baltru\u0161aitis","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0060","article-title":"Mechanistic dynamic modelling of biological systems: the road ahead","volume":"42","author":"Banga","year":"2025","journal-title":"Curr. Opin. Syst. Biol."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0065","doi-asserted-by":"crossref","DOI":"10.3389\/fgene.2021.652907","article-title":"Graph representation forecasting of patient's medical conditions: toward a Digital Twin","volume":"12","author":"Barbiero","year":"2021","journal-title":"Front. Genet."},{"issue":"4","key":"10.1016\/j.biotechadv.2026.109040_bb0070","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1109\/JPROC.2006.871775","article-title":"Strategies and tactics in multiscale modeling of cell-to-organ systems","volume":"94","author":"Bassingthwaighte","year":"2006","journal-title":"Proc. IEEE Inst. Electr. Electron. Eng."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0075","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/j.1749-6632.2009.05090.x","article-title":"Multiscale modeling of metabolism, flows, and exchanges in heterogeneous organs","volume":"1188","author":"Bassingthwaighte","year":"2010","journal-title":"Ann. N. Y. Acad. Sci."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0080","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1038\/s41746-020-00324-0","article-title":"The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database","volume":"3","author":"Benjamens","year":"2020","journal-title":"NPJ Dig. Med."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0085","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1038\/nbt.2989","article-title":"Microfluidic organs-on-chips","volume":"32","author":"Bhatia","year":"2014","journal-title":"Nat. Biotechnol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0090","doi-asserted-by":"crossref","DOI":"10.1186\/s13073-019-0701-3","article-title":"Digital twins to personalize medicine","volume":"12","author":"Bjornsson","year":"2019","journal-title":"Genome Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0095","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1080\/17460441.2023.2273839","article-title":"Generative artificial intelligence empowers digital twins in drug discovery and clinical trials","volume":"19","author":"Bordukova","year":"2024","journal-title":"Expert Opin. Drug Discov."},{"issue":"9","key":"10.1016\/j.biotechadv.2026.109040_bb0100","doi-asserted-by":"crossref","first-page":"1757","DOI":"10.1038\/nprot.2016.105","article-title":"Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes","volume":"11","author":"Bray","year":"2016","journal-title":"Nat. Protoc."},{"issue":"25","key":"10.1016\/j.biotechadv.2026.109040_bb0105","doi-asserted-by":"crossref","first-page":"7045","DOI":"10.1016\/j.cell.2024.11.015","article-title":"How to build the virtual cell with artificial intelligence: priorities and opportunities","volume":"187","author":"Bunne","year":"2024","journal-title":"Cell"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0110","first-page":"88","article-title":"Hybridizing mechanistic mathematical modeling with deep learning methods to predict individual cancer patient survival after immune checkpoint inhibitor therapy","volume":"10","author":"Butner","year":"2024","journal-title":"Res. Sq."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0115","doi-asserted-by":"crossref","DOI":"10.1016\/j.cej.2026.177046","article-title":"A digital twin framework for predictive modeling of liver-on-a-chip system dynamics using limited experimental data","volume":"539","author":"Cabral","year":"2026","journal-title":"Chem. Eng. J."},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0120","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1038\/s41592-024-02241-6","article-title":"Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations","volume":"21","author":"Chandrasekaran","year":"2024","journal-title":"Nat. Methods"},{"issue":"11","key":"10.1016\/j.biotechadv.2026.109040_bb0125","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1056\/NEJMp1714229","article-title":"Implementing machine learning in health care - addressing ethical challenges","volume":"378","author":"Char","year":"2018","journal-title":"N. Engl. J. Med."},{"issue":"3","key":"10.1016\/j.biotechadv.2026.109040_bb0130","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1002\/cpt.1987","article-title":"Quantitative systems pharmacology approaches for Immuno-oncology: adding virtual patients to the development paradigm","volume":"109","author":"Chelliah","year":"2021","journal-title":"Clin. Pharmacol. Ther."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0135","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/978-1-0716-2265-0_8","article-title":"Virtual populations for quantitative systems pharmacology models","volume":"2486","author":"Cheng","year":"2022","journal-title":"Methods Mol. Biol."},{"issue":"48","key":"10.1016\/j.biotechadv.2026.109040_bb0140","doi-asserted-by":"crossref","first-page":"4556","DOI":"10.1093\/eurheartj\/ehaa159","article-title":"The 'Digital Twin' to enable the vision of precision cardiology","volume":"41","author":"Corral-Acero","year":"2020","journal-title":"Eur. Heart J."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0145","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1038\/s41592-024-02201-0","article-title":"scGPT: toward building a foundation model for single-cell multi-omics using generative AI","volume":"21","author":"Cui","year":"2024","journal-title":"Nat. Methods"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0150","article-title":"Challenges and opportunities for digital twins in precision medicine from a complex systems perspective","volume":"8","author":"De Domenico","year":"2025","journal-title":"NPJ Dig. Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0155","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1093\/eurpub\/ckae191","article-title":"Could digital twins be the next revolution in healthcare?","volume":"35","author":"de Oliveira El-Warrak","year":"2025","journal-title":"Eur. J. Pub. Health"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0160","doi-asserted-by":"crossref","DOI":"10.2196\/53542","article-title":"Digital representation of patients as medical digital twins: data-centric viewpoint","volume":"13","author":"Demuth","year":"2025","journal-title":"JMIR Med. Inform."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0165","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1016\/j.csbj.2025.11.047","article-title":"Advancing rare disease therapeutics through digital twins: opportunities in drug development and precision dosing","volume":"28","author":"Dette","year":"2025","journal-title":"Comput. Struct. Biotechnol. J."},{"issue":"Pt B","key":"10.1016\/j.biotechadv.2026.109040_bb0170","article-title":"From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities","volume":"198","author":"Doan","year":"2025","journal-title":"Comput. Biol. Med."},{"issue":"4","key":"10.1016\/j.biotechadv.2026.109040_bb0175","doi-asserted-by":"crossref","first-page":"1484","DOI":"10.1038\/s41596-020-0292-x","article-title":"CellPhoneDB: inferring cell-cell communication from combined expression of multi-subunit ligand-receptor complexes","volume":"15","author":"Efremova","year":"2020","journal-title":"Nat. Protoc."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0180","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1186\/s40537-025-01280-w","article-title":"Digital twins in healthcare: a review of AI-powered practical applications across health domains","volume":"12","author":"Elgammal","year":"2025","journal-title":"J. Big Data"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0185","doi-asserted-by":"crossref","DOI":"10.1038\/srep20772","article-title":"Learning (from) the errors of a systems biology model","volume":"6","author":"Engelhardt","year":"2016","journal-title":"Sci. Rep."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0190","article-title":"Bridging mechanism and data: hybrid modeling approaches for cancer and aging research","volume":"44","author":"Eriksson","year":"2026","journal-title":"Curr. Opin. Syst. Biol."},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0195","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1038\/nrg3723","article-title":"Routes for breaching and protecting genetic privacy","volume":"15","author":"Erlich","year":"2014","journal-title":"Nat. Rev. Genet."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0200","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/978-1-59745-525-1_5","article-title":"Rule-based modeling of biochemical systems with BioNetGen","volume":"500","author":"Faeder","year":"2009","journal-title":"Methods Mol. Biol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0205","doi-asserted-by":"crossref","first-page":"4669","DOI":"10.1038\/s41467-023-40380-0","article-title":"A neural-mechanistic hybrid approach improving the predictive power of genome-scale metabolic models","volume":"14","author":"Faure","year":"2023","journal-title":"Nat. Commun."},{"issue":"3","key":"10.1016\/j.biotechadv.2026.109040_bb0210","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1038\/s43588-024-00613-8","article-title":"Digital twins in mechanical and aerospace engineering","volume":"4","author":"Ferrari","year":"2024","journal-title":"Nat. Comput. Sci."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0215","doi-asserted-by":"crossref","first-page":"77","DOI":"10.3389\/fgene.2011.00077","article-title":"Hybrid modeling of cell signaling and transcriptional reprogramming and its application in C. elegans development","volume":"2","author":"Fertig","year":"2011","journal-title":"Front. Genet."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0220","doi-asserted-by":"crossref","DOI":"10.15252\/msb.202210988","article-title":"Mechanistic model of MAPK signaling reveals how allostery and rewiring contribute to drug resistance","volume":"19","author":"Frohlich","year":"2023","journal-title":"Mol. Syst. Biol."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0225","doi-asserted-by":"crossref","DOI":"10.3389\/fcell.2023.1260507","article-title":"Multi-scale models of whole cells: progress and challenges","volume":"11","author":"Georgouli","year":"2023","journal-title":"Front. Cell Dev. Biol."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0230","first-page":"295","article-title":"Ethical and legal challenges of artificial intelligence-driven healthcare","author":"Gerke","year":"2020","journal-title":"Artif. Intell. Healthc."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0235","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005991","article-title":"PhysiCell: an open source physics-based cell simulator for 3-D multicellular systems","volume":"14","author":"Ghaffarizadeh","year":"2018","journal-title":"PLoS Comput. Biol."},{"issue":"4","key":"10.1016\/j.biotechadv.2026.109040_bb0240","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1093\/bib\/bbl043","article-title":"Computational methodologies for modelling, analysis and simulation of signalling networks","volume":"7","author":"Gilbert","year":"2006","journal-title":"Brief. Bioinform."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0245","doi-asserted-by":"crossref","DOI":"10.1080\/19420862.2023.2192251","article-title":"Mechanistic PK\/PD modeling to address early-stage biotherapeutic dosing feasibility questions","volume":"15","author":"Grant","year":"2023","journal-title":"MAbs"},{"issue":"19","key":"10.1016\/j.biotechadv.2026.109040_bb0250","doi-asserted-by":"crossref","first-page":"26941","DOI":"10.1007\/s11042-022-12536-5","article-title":"Application of digital twins in multiple fields","volume":"81","author":"Guo","year":"2022","journal-title":"Multimed. Tools Appl."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0255","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1186\/s13059-024-03436-y","article-title":"scStateDynamics: deciphering the drug-responsive tumor cell state dynamics by modeling single-cell level expression changes","volume":"25","author":"Guo","year":"2024","journal-title":"Genome Biol."},{"issue":"Suppl. 1","key":"10.1016\/j.biotechadv.2026.109040_bb0260","first-page":"8","article-title":"Challenges of reproducible AI in biomedical data science","volume":"18","author":"Han","year":"2025","journal-title":"BMC Med. Genet."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0265","doi-asserted-by":"crossref","DOI":"10.3389\/fcell.2024.1240384","article-title":"From transcriptomics to digital twins of organ function","volume":"12","author":"Hansen","year":"2024","journal-title":"Front. Cell Dev. Biol."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0270","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1038\/s41592-024-02305-7","article-title":"Large-scale foundation model on single-cell transcriptomics","volume":"21","author":"Hao","year":"2024","journal-title":"Nat. Methods"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0275","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1038\/s41591-018-0307-0","article-title":"The practical implementation of artificial intelligence technologies in medicine","volume":"25","author":"He","year":"2019","journal-title":"Nat. Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0280","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1186\/1752-0509-6-96","article-title":"The cell collective: toward an open and collaborative approach to systems biology","volume":"6","author":"Helikar","year":"2012","journal-title":"BMC Syst. Biol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0285","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1111\/j.1541-0420.2009.01245.x","article-title":"Bayesian calibration of a stochastic kinetic computer model using multiple data sources","volume":"66","author":"Henderson","year":"2010","journal-title":"Biometrics"},{"issue":"40","key":"10.1016\/j.biotechadv.2026.109040_bb0290","doi-asserted-by":"crossref","first-page":"46659","DOI":"10.1021\/acsomega.5c03703","article-title":"Digital Twin for the production of hMSC-derived extracellular vesicles for applications in cell and gene therapy toward autonomous operation","volume":"10","author":"Hengelbrock","year":"2025","journal-title":"ACS Omega"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0295","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-019-54849-w","article-title":"Improving the odds of drug development success through human genomics: modelling study","volume":"9","author":"Hingorani","year":"2019","journal-title":"Sci. Rep."},{"issue":"24","key":"10.1016\/j.biotechadv.2026.109040_bb0300","doi-asserted-by":"crossref","first-page":"3067","DOI":"10.1093\/bioinformatics\/btl485","article-title":"COPASI--a COmplex PAthway SImulator","volume":"22","author":"Hoops","year":"2006","journal-title":"Bioinformatics"},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0305","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbad086","article-title":"TEINet: a deep learning framework for prediction of TCR\u2013epitope binding specificity","volume":"24","author":"Jiang","year":"2023","journal-title":"Brief. Bioinform."},{"issue":"11","key":"10.1016\/j.biotechadv.2026.109040_bb0310","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1038\/s41575-024-00992-3","article-title":"Digital twins are integral to personalizing medicine and improving public health","volume":"21","author":"Johnson","year":"2024","journal-title":"Nat. Rev. Gastroenterol. Hepatol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0315","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1038\/s41540-024-00335-7","article-title":"Digital twins elucidate critical role of T(scm) in clinical persistence of TCR-engineered cell therapy","volume":"10","author":"Joslyn","year":"2024","journal-title":"npj Syst. Biol. Appl."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0320","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1002\/cpt.3498","article-title":"Quantitative systems pharmacology-based digital twins approach supplements clinical trial data for enzyme replacement therapies in Pompe disease","volume":"117","author":"Kaddi","year":"2025","journal-title":"Clin. Pharmacol. Ther."},{"issue":"7","key":"10.1016\/j.biotechadv.2026.109040_bb0325","doi-asserted-by":"crossref","first-page":"629","DOI":"10.2217\/pgs-2018-0008","article-title":"Deep learning in pharmacogenomics: from gene regulation to patient stratification","volume":"19","author":"Kalinin","year":"2018","journal-title":"Pharmacogenomics"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0330","series-title":"TumorTwin: A Python Framework for Patient-Specific Digital Twins in Oncology","author":"Kapteyn","year":"2025"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0335","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1038\/s41746-024-01073-0","article-title":"Digital twins for health: a scoping review","volume":"7","author":"Katsoulakis","year":"2024","journal-title":"NPJ Dig. Med."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0340","doi-asserted-by":"crossref","DOI":"10.3389\/fphys.2024.1473125","article-title":"Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine","volume":"15","author":"Kemkar","year":"2024","journal-title":"Front. Physiol."},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0345","doi-asserted-by":"crossref","first-page":"3126","DOI":"10.1137\/070692017","article-title":"Fast Monte Carlo simulation methods for biological reaction-diffusion systems in solution and on surfaces","volume":"30","author":"Kerr","year":"2008","journal-title":"SIAM J. Sci. Comput."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0350","doi-asserted-by":"crossref","DOI":"10.3389\/fdgth.2025.1633539","article-title":"Digital twins in healthcare: a comprehensive review and future directions","volume":"7","author":"Khoshfekr Rudsari","year":"2025","journal-title":"Front. Digital Health"},{"issue":"D1","key":"10.1016\/j.biotechadv.2026.109040_bb0355","doi-asserted-by":"crossref","first-page":"D558","DOI":"10.1093\/nar\/gkx1063","article-title":"Data portal for the library of integrated network-based cellular signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data","volume":"46","author":"Koleti","year":"2018","journal-title":"Nucleic Acids Res."},{"issue":"5795","key":"10.1016\/j.biotechadv.2026.109040_bb0360","doi-asserted-by":"crossref","first-page":"1929","DOI":"10.1126\/science.1132939","article-title":"The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease","volume":"313","author":"Lamb","year":"2006","journal-title":"Science"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0365","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41581-025-01021-5","article-title":"The promise of digital twins as a tool for personalized approaches in nephrology","volume":"22","author":"Laubenbacher","year":"2026","journal-title":"Nat. Rev. Nephrol."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0370","article-title":"Toward mechanistic medical digital twins: some use cases in immunology","volume":"6\u20132024","author":"Laubenbacher","year":"2024","journal-title":"Front. Digital Health"},{"issue":"3","key":"10.1016\/j.biotechadv.2026.109040_bb0375","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1038\/s43588-024-00607-6","article-title":"Digital twins in medicine","volume":"4","author":"Laubenbacher","year":"2024","journal-title":"Nat. Comput. Sci."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0380","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/s13073-022-01048-4","article-title":"A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets","volume":"14","author":"Li","year":"2022","journal-title":"Genome Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0385","article-title":"Applications of deep learning in understanding gene regulation","volume":"3","author":"Li","year":"2023","journal-title":"Cell Rep. Methods"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0390","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s13073-025-01435-7","article-title":"Digital twins as global learning health and disease models for preventive and personalized medicine","volume":"17","author":"Li","year":"2025","journal-title":"Genome Med."},{"issue":"17","key":"10.1016\/j.biotechadv.2026.109040_bb0395","doi-asserted-by":"crossref","first-page":"4488","DOI":"10.1016\/j.cell.2024.07.040","article-title":"Spatiotemporal omics for biology and medicine","volume":"187","author":"Liu","year":"2024","journal-title":"Cell"},{"issue":"11","key":"10.1016\/j.biotechadv.2026.109040_bb0400","doi-asserted-by":"crossref","first-page":"2449","DOI":"10.1038\/s41592-025-02856-3","article-title":"Multitask benchmarking of single-cell multimodal omics integration methods","volume":"22","author":"Liu","year":"2025","journal-title":"Nat. Methods"},{"issue":"2\u20133","key":"10.1016\/j.biotechadv.2026.109040_bb0405","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.pbiomolbio.2004.01.004","article-title":"CellML: its future, present and past","volume":"85","author":"Lloyd","year":"2004","journal-title":"Prog. Biophys. Mol. Biol."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0410","doi-asserted-by":"crossref","first-page":"1538","DOI":"10.1016\/j.drudis.2018.05.010","article-title":"Machine learning in chemoinformatics and drug discovery","volume":"23","author":"Lo","year":"2018","journal-title":"Drug Discov. Today"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0415","doi-asserted-by":"crossref","DOI":"10.1038\/msb.2013.1","article-title":"Programming biological models in Python using PySB","volume":"9","author":"Lopez","year":"2013","journal-title":"Mol. Syst. Biol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0420","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1146\/annurev-bioeng-081623-025834","article-title":"Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data","volume":"26","author":"Lorenzo","year":"2024","journal-title":"Annu. Rev. Biomed. Eng."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0425","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1038\/s41592-019-0494-8","article-title":"scGen predicts single-cell perturbation responses","volume":"16","author":"Lotfollahi","year":"2019","journal-title":"Nat. Methods"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0430","article-title":"Machine learning models for drug-drug interaction prediction from computational discovery to clinical application","volume":"9","author":"Lu","year":"2026","journal-title":"NPJ Dig. Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0435","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/s41746-025-02198-6","article-title":"AI-driven virtual cell models in preclinical research: technical pathways, validation mechanisms, and clinical translation potential","volume":"9","author":"Ma","year":"2025","journal-title":"NPJ Dig. Med."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0440","article-title":"Transformative roles of digital twins from drug discovery to continuous manufacturing: pharmaceutical and biopharmaceutical perspectives","volume":"10","author":"Maharjan","year":"2025","journal-title":"Int. J. Pharm. X"},{"issue":"9","key":"10.1016\/j.biotechadv.2026.109040_bb0445","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1038\/s44320-025-00134-0","article-title":"Longitudinal big biological data in the AI era","volume":"21","author":"Mardinoglu","year":"2025","journal-title":"Mol. Syst. Biol."},{"issue":"10","key":"10.1016\/j.biotechadv.2026.109040_bb0450","doi-asserted-by":"crossref","DOI":"10.3390\/jpm13101522","article-title":"Digital twins in healthcare: methodological challenges and opportunities","volume":"13","author":"Meijer","year":"2023","journal-title":"J. Pers. Med."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0455","doi-asserted-by":"crossref","first-page":"e22214","DOI":"10.2196\/22214","article-title":"The Academic Viewpoint on Patient Data Ownership in the Context of Big Data: Scoping Review","volume":"22","author":"Mirchev","year":"2020","journal-title":"J Med Internet Res."},{"issue":"7","key":"10.1016\/j.biotechadv.2026.109040_bb0460","doi-asserted-by":"crossref","DOI":"10.1016\/j.drudis.2023.103605","article-title":"Virtual patients, digital twins and causal disease models: paving the ground for in silico clinical trials","volume":"28","author":"Moingeon","year":"2023","journal-title":"Drug Discov. Today"},{"issue":"5","key":"10.1016\/j.biotechadv.2026.109040_bb0465","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1049\/iet-syb:20080102","article-title":"Virtual cell modelling and simulation software environment","volume":"2","author":"Moraru","year":"2008","journal-title":"IET Syst. Biol."},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0470","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1016\/j.tem.2024.04.019","article-title":"Digital twins and artificial intelligence in metabolic disease research","volume":"35","author":"Mosquera-Lopez","year":"2024","journal-title":"Trends Endocrinol. Metab."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0475","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1186\/s13046-023-02653-w","article-title":"Newly developed 3D in vitro models to study tumor-immune interaction","volume":"42","author":"Mu","year":"2023","journal-title":"J. Exp. Clin. Cancer Res."},{"issue":"17","key":"10.1016\/j.biotechadv.2026.109040_bb0480","doi-asserted-by":"crossref","first-page":"2997","DOI":"10.3390\/buildings15172997","article-title":"AI-driven digital twins in industrialized offsite construction: a systematic review","volume":"15","author":"Najafzadeh","year":"2025","journal-title":"Buildings"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0485","doi-asserted-by":"crossref","DOI":"10.1016\/j.ceja.2025.100775","article-title":"Hybridised mechanistic and machine learning digital twins for modelling and optimising chemical processes in flow: a comparative analysis of parallel and series-based hybridisation","volume":"23","author":"Nasruddin","year":"2025","journal-title":"Chem. Eng. J. Adv."},{"issue":"7","key":"10.1016\/j.biotechadv.2026.109040_bb0490","doi-asserted-by":"crossref","first-page":"1972","DOI":"10.1016\/j.cell.2018.11.021","article-title":"Organoid modeling of the tumor immune microenvironment","volume":"175","author":"Neal","year":"2018","journal-title":"Cell"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0495","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3109\/15376516.2011.585477","article-title":"Virtual population generator for human cardiomyocytes parameters: in silico drug cardiotoxicity assessment","volume":"22","author":"Polak","year":"2012","journal-title":"Toxicol. Mech. Methods"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0500","first-page":"344","article-title":"Reference information model and interoperable architecture for digital health twins: a position paper","volume":"316","author":"Portilla","year":"2024","journal-title":"Stud. Health Technol. Inform."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0505","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1038\/s41591-018-0272-7","article-title":"Privacy in the age of medical big data","volume":"25","author":"Price","year":"2019","journal-title":"Nat. Med."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0510","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2023.107681","article-title":"Combined mechanistic modeling and machine-learning approaches in systems biology - a systematic literature review","volume":"240","author":"Procopio","year":"2023","journal-title":"Comput. Methods Prog. Biomed."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0515","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2025.108919","article-title":"Pharmacometric and Digital Twin modeling for adaptive scheduling of combination therapy in advanced gastric cancer","volume":"270","author":"Prunella","year":"2025","journal-title":"Comput. Methods Prog. Biomed."},{"issue":"17","key":"10.1016\/j.biotechadv.2026.109040_bb0520","doi-asserted-by":"crossref","DOI":"10.1016\/j.jmb.2025.169181","article-title":"Artificial-intelligence-driven innovations in mechanistic computational modeling and digital twins for biomedical applications","volume":"437","author":"Puniya","year":"2025","journal-title":"J. Mol. Biol."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0525","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s10928-021-09797-2","article-title":"From data to QSP models: a pipeline for using Boolean networks for hypothesis inference and dynamic model building","volume":"49","author":"Putnins","year":"2022","journal-title":"J. Pharmacokinet. Pharmacodyn."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0530","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1016\/j.jcp.2018.10.045","article-title":"Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations","volume":"378","author":"Raissi","year":"2019","journal-title":"J. Comput. Phys."},{"issue":"12","key":"10.1016\/j.biotechadv.2026.109040_bb0535","doi-asserted-by":"crossref","first-page":"866","DOI":"10.7326\/M18-1990","article-title":"Ensuring fairness in machine learning to advance health equity","volume":"169","author":"Rajkomar","year":"2018","journal-title":"Ann. Intern. Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0540","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1038\/s41591-021-01614-0","article-title":"AI in health and medicine","volume":"28","author":"Rajpurkar","year":"2022","journal-title":"Nat. Med."},{"issue":"3","key":"10.1016\/j.biotechadv.2026.109040_bb0545","doi-asserted-by":"crossref","DOI":"10.1016\/j.neurot.2025.e00553","article-title":"Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease","volume":"22","author":"Ren","year":"2025","journal-title":"Neurotherapeutics"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0550","doi-asserted-by":"crossref","DOI":"10.2196\/55015","article-title":"Digital twins for clinical and operational decision-making: scoping review","volume":"27","author":"Riahi","year":"2025","journal-title":"J. Med. Internet Res."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0555","doi-asserted-by":"crossref","DOI":"10.34133\/csbj.0078","article-title":"A hybrid modeling framework for predictive digital twins of CHO cell culture","volume":"35","author":"Richelle","year":"2026","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0560","doi-asserted-by":"crossref","DOI":"10.1016\/j.cej.2025.162018","article-title":"Accelerating bioprocess digital twin development by integrating hybrid modelling with transfer learning","volume":"511","author":"Riezzo","year":"2025","journal-title":"Chem. Eng. J."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0565","doi-asserted-by":"crossref","DOI":"10.2196\/69544","article-title":"Advancing health care with digital twins: Meta-review of applications and implementation challenges","volume":"27","author":"Ringeval","year":"2025","journal-title":"J. Med. Internet Res."},{"issue":"4","key":"10.1016\/j.biotechadv.2026.109040_bb0570","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac229","article-title":"Network approaches for modeling the effect of drugs and diseases","volume":"23","author":"Rintala","year":"2022","journal-title":"Brief. Bioinform."},{"issue":"42","key":"10.1016\/j.biotechadv.2026.109040_bb0575","doi-asserted-by":"crossref","first-page":"10311","DOI":"10.1021\/acs.jpcb.4c02746","article-title":"Single-cell microfluidics: a primer for microbiologists","volume":"128","author":"Ripandelli","year":"2024","journal-title":"J. Phys. Chem. B"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0580","doi-asserted-by":"crossref","first-page":"1796","DOI":"10.1038\/s41467-021-21770-8","article-title":"Identification of disease treatment mechanisms through the multiscale interactome","volume":"12","author":"Ruiz","year":"2021","journal-title":"Nat. Commun."},{"issue":"7","key":"10.1016\/j.biotechadv.2026.109040_bb0585","article-title":"Medical digital twins: enabling precision medicine and medical artificial intelligence","volume":"7","author":"Sadee","year":"2025","journal-title":"Lancet Digit. Health"},{"issue":"9","key":"10.1016\/j.biotechadv.2026.109040_bb0590","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btae525","article-title":"FateNet: an integration of dynamical systems and deep learning for cell fate prediction","volume":"40","author":"Sadria","year":"2024","journal-title":"Bioinformatics"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0595","doi-asserted-by":"crossref","DOI":"10.3389\/fdgth.2025.1583466","article-title":"Digital twin for personalized medicine development","volume":"7","author":"Saratkar","year":"2025","journal-title":"Front. Digital Health"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0600","article-title":"A review and perspective on hybrid modeling methodologies","volume":"10","author":"Schweidtmann","year":"2024","journal-title":"Dig. Chem. Eng."},{"issue":"4","key":"10.1016\/j.biotechadv.2026.109040_bb0605","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1021\/ci200528d","article-title":"Recognizing pitfalls in virtual screening: a critical review","volume":"52","author":"Scior","year":"2012","journal-title":"J. Chem. Inf. Model."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0610","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1038\/s41746-025-01447-y","article-title":"Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine","volume":"8","author":"Sel","year":"2025","journal-title":"NPJ Dig. Med."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0615","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2023.107441","article-title":"Application of uncertainty quantification to artificial intelligence in healthcare: a review of last decade (2013\u22122023)","volume":"165","author":"Seoni","year":"2023","journal-title":"Comput. Biol. Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0620","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s40842-025-00242-8","article-title":"Cardiometabolic risk reduction with digital twinning in patients with type 2 diabetes","volume":"11","author":"Seyedi","year":"2025","journal-title":"Cardiovasc. Diabetol. Endocrinol. Rep."},{"issue":"12","key":"10.1016\/j.biotechadv.2026.109040_bb0625","doi-asserted-by":"crossref","first-page":"1671","DOI":"10.1038\/ejhg.2016.111","article-title":"Who should have access to genomic data and how should they be held accountable? Perspectives of Data Access Committee members and experts","volume":"24","author":"Shabani","year":"2016","journal-title":"Eur. J. Hum. Genet."},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0630","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1038\/s41580-024-00702-6","article-title":"Live-cell imaging powered by computation","volume":"25","author":"Shroff","year":"2024","journal-title":"Nat. Rev. Mol. Cell Biol."},{"issue":"11","key":"10.1016\/j.biotechadv.2026.109040_bb0635","doi-asserted-by":"crossref","DOI":"10.3390\/jpm15110503","article-title":"Digital twins in personalized medicine: bridging innovation and clinical reality","volume":"15","author":"Silva","year":"2025","journal-title":"J. Pers. Med."},{"issue":"1\u20133","key":"10.1016\/j.biotechadv.2026.109040_bb0640","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.pbiomolbio.2007.07.019","article-title":"Multi-scale computational modelling in biology and physiology","volume":"96","author":"Southern","year":"2008","journal-title":"Prog. Biophys. Mol. Biol."},{"issue":"9","key":"10.1016\/j.biotechadv.2026.109040_bb0645","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1093\/bioinformatics\/btt772","article-title":"Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology","volume":"30","author":"Starru\u00df","year":"2014","journal-title":"Bioinformatics"},{"issue":"22","key":"10.1016\/j.biotechadv.2026.109040_bb0650","doi-asserted-by":"crossref","DOI":"10.3390\/cancers16223817","article-title":"Advancing precision oncology with digital and virtual twins: a scoping review","volume":"16","author":"Stefaniga","year":"2024","journal-title":"Cancers"},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0655","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1177\/1087057116635818","article-title":"A perspective on implementing a quantitative systems pharmacology platform for drug discovery and the advancement of personalized medicine","volume":"21","author":"Stern","year":"2016","journal-title":"J. Biomol. Screen."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0660","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1038\/s41592-020-01018-x","article-title":"Cellpose: a generalist algorithm for cellular segmentation","volume":"18","author":"Stringer","year":"2021","journal-title":"Nat. Methods"},{"issue":"5","key":"10.1016\/j.biotechadv.2026.109040_bb0665","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1038\/s41576-019-0093-7","article-title":"Integrative single-cell analysis","volume":"20","author":"Stuart","year":"2019","journal-title":"Nat. Rev. Genet."},{"issue":"7","key":"10.1016\/j.biotechadv.2026.109040_bb0670","doi-asserted-by":"crossref","first-page":"3049","DOI":"10.1016\/j.apsb.2022.02.002","article-title":"Why 90% of clinical drug development fails and how to improve it?","volume":"12","author":"Sun","year":"2022","journal-title":"Acta Pharm. Sin. B"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0675","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/B978-0-12-388403-9.00013-8","article-title":"Multi-scale modeling of tissues using CompuCell3D","volume":"110","author":"Swat","year":"2012","journal-title":"Methods Cell Biol."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0680","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1186\/1752-0509-6-133","article-title":"CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms","volume":"6","author":"Terfve","year":"2012","journal-title":"BMC Syst. Biol."},{"issue":"7965","key":"10.1016\/j.biotechadv.2026.109040_bb0685","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1038\/s41586-023-06139-9","article-title":"Transfer learning enables predictions in network biology","volume":"618","author":"Theodoris","year":"2023","journal-title":"Nature"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0690","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1038\/s41746-025-01910-w","article-title":"A scoping review of human digital twins in healthcare applications and usage patterns","volume":"8","author":"Tudor","year":"2025","journal-title":"NPJ Dig. Med."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0695","first-page":"338","article-title":"Towards real-time control of gene expression: controlling the HOG signaling cascade","author":"Uhlendorf","year":"2011","journal-title":"Pac. Symp. Biocomput."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0700","doi-asserted-by":"crossref","DOI":"10.3389\/fdgth.2023.1253050","article-title":"Digital twin for healthcare systems","volume":"5","author":"Vallee","year":"2023","journal-title":"Front. Digital Health"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0705","doi-asserted-by":"crossref","DOI":"10.2196\/72411","article-title":"Digital twins for personalized medicine require epidemiological data and mathematical modeling: viewpoint","volume":"27","author":"Vallee","year":"2025","journal-title":"J. Med. Internet Res."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0710","doi-asserted-by":"crossref","DOI":"10.3389\/fdgth.2026.1753906","article-title":"Multi-scale digital twins for personalized medicine","volume":"8","author":"Vall\u00e9e","year":"2026","journal-title":"Front. Digital Health"},{"issue":"6","key":"10.1016\/j.biotechadv.2026.109040_bb0715","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1038\/s41573-023-00688-4","article-title":"Applications of single-cell RNA sequencing in drug discovery and development","volume":"22","author":"Van de Sande","year":"2023","journal-title":"Nat. Rev. Drug Discov."},{"issue":"11","key":"10.1016\/j.biotechadv.2026.109040_bb0720","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005177","article-title":"Deep learning automates the quantitative analysis of individual cells in live-cell imaging experiments","volume":"12","author":"Van Valen","year":"2016","journal-title":"PLoS Comput. Biol."},{"issue":"11","key":"10.1016\/j.biotechadv.2026.109040_bb0725","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1002689","article-title":"Machine learning in medicine: addressing ethical challenges","volume":"15","author":"Vayena","year":"2018","journal-title":"PLoS Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0730","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1038\/s41746-022-00694-7","article-title":"Health digital twins as tools for precision medicine: considerations for computation, implementation, and regulation","volume":"5","author":"Venkatesh","year":"2022","journal-title":"NPJ Dig. Med."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0735","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.ymeth.2020.01.011","article-title":"In silico trials: verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products","volume":"185","author":"Viceconti","year":"2021","journal-title":"Methods"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0740","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1038\/clpt.2010.87","article-title":"Multiscale modeling in drug discovery and development: future opportunities and present challenges","volume":"88","author":"Vicini","year":"2010","journal-title":"Clin. Pharmacol. Ther."},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0745","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCEP.124.013660","article-title":"Heart digital twins predict features of invasive reentrant circuits and ablation lesions in scar-dependent ventricular tachycardia","volume":"18","author":"Waight","year":"2025","journal-title":"Circ. Arrhythm. Electrophysiol."},{"issue":"10","key":"10.1016\/j.biotechadv.2026.109040_bb0750","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1109\/TBME.2016.2555481","article-title":"How modeling standards, software, and initiatives support reproducibility in systems biology and systems medicine","volume":"63","author":"Waltemath","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0755","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1038\/s41746-024-01188-4","article-title":"From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling","volume":"7","author":"Wang","year":"2024","journal-title":"npj Dig. Med."},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0760","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1038\/s43588-025-00887-6","article-title":"Predicting drug responses of unseen cell types through transfer learning with foundation models","volume":"6","author":"Wang","year":"2026","journal-title":"Nat. Comput. Sci."},{"issue":"9","key":"10.1016\/j.biotechadv.2026.109040_bb0765","doi-asserted-by":"crossref","first-page":"1386","DOI":"10.1038\/s41551-025-01474-w","article-title":"Towards a multi-organ, multi-omics medical digital twin","volume":"9","author":"Wen","year":"2025","journal-title":"Nat. Biomed. Eng."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0770","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.therap.2025.09.006","article-title":"Digital pharmacological twins: bridging multi-scale modelling and artificial intelligence for precision medicine: the DIGPHAT consortium","volume":"81","author":"Woillard","year":"2025","journal-title":"Therapie"},{"issue":"9","key":"10.1016\/j.biotechadv.2026.109040_bb0775","doi-asserted-by":"crossref","first-page":"2544","DOI":"10.1073\/pnas.1517883113","article-title":"Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM","volume":"113","author":"Wong","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.biotechadv.2026.109040_bb0780","doi-asserted-by":"crossref","first-page":"3481","DOI":"10.1016\/j.csbj.2024.09.030","article-title":"Towards generative digital twins in biomedical research","volume":"23","author":"Wu","year":"2024","journal-title":"Comput. Struct. Biotechnol. J."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0785","doi-asserted-by":"crossref","DOI":"10.1063\/5.0086789","article-title":"Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology","volume":"3","author":"Wu","year":"2022","journal-title":"Biophys. Rev."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0790","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.110013","article-title":"Large-scale synthetic data enable digital twins of human excitable cells","volume":"15","author":"Yang","year":"2026","journal-title":"eLife"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0795","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/s42492-023-00137-4","article-title":"Systematic review of digital twin technology and applications","volume":"6","author":"Yao","year":"2023","journal-title":"Vis. Comput. Ind. Biomed. Art"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0800","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1038\/s41746-024-01396-y","article-title":"Building a modular and multi-cellular virtual twin of the synovial joint in rheumatoid arthritis","volume":"7","author":"Zerrouk","year":"2024","journal-title":"NPJ Dig. Med."},{"issue":"14","key":"10.1016\/j.biotechadv.2026.109040_bb0805","doi-asserted-by":"crossref","first-page":"2395","DOI":"10.1039\/C6LC01554A","article-title":"Organ-on-a-chip devices advance to market","volume":"17","author":"Zhang","year":"2017","journal-title":"Lab Chip"},{"issue":"8","key":"10.1016\/j.biotechadv.2026.109040_bb0810","doi-asserted-by":"crossref","DOI":"10.1016\/j.patter.2024.101028","article-title":"Concepts and applications of digital twins in healthcare and medicine","volume":"5","author":"Zhang","year":"2024","journal-title":"Patterns"},{"issue":"1","key":"10.1016\/j.biotechadv.2026.109040_bb0815","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1038\/s41540-025-00624-9","article-title":"Deciphering cell-fate trajectories using spatiotemporal single-cell transcriptomic data","volume":"12","author":"Zhang","year":"2025","journal-title":"npj Syst. Biol. Appl."},{"key":"10.1016\/j.biotechadv.2026.109040_bb0820","doi-asserted-by":"crossref","DOI":"10.3389\/fsysb.2023.1293076","article-title":"Editorial: virtual patients and digital twins in the systems analysis of drug discovery and development","volume":"3","author":"Zhao","year":"2023","journal-title":"Front. Syst. Biol."},{"issue":"2","key":"10.1016\/j.biotechadv.2026.109040_bb0825","doi-asserted-by":"crossref","DOI":"10.1016\/j.isci.2023.108077","article-title":"A liver digital twin for in silico testing of cellular and inter-cellular mechanisms in regeneration after drug-induced damage","volume":"27","author":"Zhao","year":"2024","journal-title":"iScience"}],"container-title":["Biotechnology Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0734975026002466?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0734975026002466?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T16:15:54Z","timestamp":1790698554000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0734975026002466"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":165,"alternative-id":["S0734975026002466"],"URL":"https:\/\/doi.org\/10.1016\/j.biotechadv.2026.109040","relation":{},"ISSN":["0734-9750"],"issn-type":[{"value":"0734-9750","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A cellular Digital Twin framework for predictive and mechanistic modeling of drug responses in precision medicine","name":"articletitle","label":"Article Title"},{"value":"Biotechnology Advances","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.biotechadv.2026.109040","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109040"}}