{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T04:25:51Z","timestamp":1787199951864,"version":"build-2736575974"},"reference-count":32,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:00:00Z","timestamp":1785456000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:00:00Z","timestamp":1785456000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["CPT Pharmacom &amp; Syst Pharma"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Quantitative systems pharmacology (QSP) models require calibration data from literature, yet manual curation is inconsistently documented and large language model (LLM) extraction can hallucinate values and fabricate citations. We present MAPLE (Model\u2010Aware Parameterization from Literature Evidence), which uses structured validation schemas as a collaboration interface between LLMs and modelers. Two schemas span two scales: the SubmodelTarget schema for isolated experiments constraining individual parameters, and the CalibrationTarget schema for clinical and in\u00a0vivo endpoints constraining the full model. Both separate data extraction from modeling decisions, recording every value with full provenance. Targeted validators catch characteristic LLM errors by matching values to source snippets, resolving DOIs, and executing code. For a pancreatic ductal adenocarcinoma QSP model, we used MAPLE to extract and curate 37 SubmodelTargets and 45 CalibrationTargets. Before any human review, the validators triggered 50 automated retries; every value carries a direct quote from its source and a verified citation; and 11 of 19 parameters are supported by more than one independent source. The LLM drafted usable forward models and code from context, while the modeler supplied the context and scientific judgment it cannot infer, revising forward\u2010model choices in 65% of SubmodelTargets, priors in 46%, and source relevance in all files. This evaluation covers one model in one disease area, by a single group, so it characterizes the framework rather than establishing how broadly it generalizes. MAPLE records the modeler's reasoning in a form that can be re\u2010run and independently checked, so it is not lost when the modeling team changes.<\/jats:p>","DOI":"10.1002\/psp4.70306","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T12:39:09Z","timestamp":1785501549000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Structured Schemas for Provenance\u2010Rich,\n                    <scp>LLM<\/scp>\n                    \u2010Assisted\n                    <scp>QSP<\/scp>\n                    Model Calibration"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2227-8727","authenticated-orcid":false,"given":"Joel","family":"Eliason","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6706-9235","authenticated-orcid":false,"given":"Aleksander S.","family":"Popel","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,31]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/psp4.12071"},{"key":"e_1_2_10_3_1","first-page":"261","volume-title":"Handbook of Experimental Pharmacology","author":"Wang H.","year":"2025"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746\u2010024\u201001188\u20104"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pbiomolbio.2018.06.002"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.3389\/fsysb.2023.1174647"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.3389\/fsysb.2024.1380685"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/cpt.3053"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2025.104448"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10928\u2010025\u201009984\u20105"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10928\u2010025\u201009976\u20105"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbaa057"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2412.08255"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010024\u201073338\u20103"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s44387\u2010025\u201000060\u20104"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1101\/2024.09.20.24314108"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/psp4.70127"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamiaopen\/ooaf012"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/cl2.70073"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586\u2010024\u201007421\u20100"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3703155"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2502.14302"},{"key":"e_1_2_10_23_1","unstructured":"S.Colvin E.Jolibois H.Ramezani et\u00a0al. \u201cPydantic Validation \u201d(2025) https:\/\/github.com\/pydantic\/pydantic."},{"key":"e_1_2_10_24_1","unstructured":"H. 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