{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T05:18:41Z","timestamp":1787894321687,"version":"build-2784847793"},"reference-count":23,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pharmacol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Human immunodeficiency virus (HIV) infection remains a global health challenge, necessitating personalized treatment strategies to optimize patient outcomes. Digital twin technology\u2014synchronized with real-world entities\u2014offers a pathway to precision medicine in HIV care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed 5,436 HIV patients (2016\u20132024) with demographic, immunologic, and antiretroviral therapy (ART) information. Core algorithms comprised gradient boosting and random forest ensembles; deep architectures (LSTM and Transformer networks) were evaluated as comparative benchmarks on longitudinal feature tensors under identical supervision. Models used five-fold cross-validation, regularization, dropout, and early stopping. A probabilistic treatment ranking layer generated diversified regimen suggestions conditioned on model outputs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Ensemble models achieved strong explained variance on the registry-defined CD4 label (test R\n                      <jats:sup>2<\/jats:sup>\n                      up to 0.97; cross-validation stability reported in the Results). Deep models achieved comparable held-out accuracy on the same endpoint; the ranking module produced balanced regimen distributions in an illustrative optimization cohort. Simulated digital twin scenarios demonstrated counterfactual CD4 projections under alternative ART strategies for low, moderate, and higher baseline immunology profiles.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The specific contribution is an explicit patient-state \u2192 prediction \u2192 regimen exploration pipeline suited to integration with telehealth analytics (risk dashboards, adherence supports), while transparently acknowledging endpoint and leakage limitations and the need for prospective outcome validation. A pragmatic HIV treatment optimization strategy is to route model-supported prioritization into clinician-facing dashboards and remote monitoring workflows rather than autonomous prescribing.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fphar.2026.1836330","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T04:33:28Z","timestamp":1787891608000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Digital twin technology for HIV patient virtual modeling: a novel approach to treatment optimization"],"prefix":"10.3389","volume":"17","author":[{"given":"Yuan","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Li","sequence":"additional","affiliation":[{"name":"Drug Clinical Trial Institution Office, Xi\u2019an Chest Hospital","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanhuan","family":"Ba","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajia","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinling","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangxiao","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanqing","family":"Liu","sequence":"additional","affiliation":[{"name":"Information Management Office, Northwestern Polytechnical University","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"3327","DOI":"10.1007\/s10461-022-03610-y","article-title":"Burden and associated factors of virological failure among people living with HIV in Sub-Saharan Africa: a systematic review and meta-analysis","volume":"26","author":"Agegnehu","year":"2022","journal-title":"AIDS Behav."},{"key":"B2","first-page":"820","article-title":"ARTPredict: an interpretable dual-branch LSTM model with attention mechanism for antiretroviral therapy response prediction in HIV treatment","volume-title":"2025 6th International Conference on Data Intelligence and Cognitive Informatics (ICDICI)","author":"Aishitha","year":"2025"},{"key":"B3","doi-asserted-by":"publisher","first-page":"475","DOI":"10.2147\/PPA.S192735","article-title":"Adherence to HIV treatment regimens: systematic literature review and meta-analysis","volume":"13","author":"Altice","year":"2019","journal-title":"Patient Prefer. 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