{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T17:06:59Z","timestamp":1779037619762,"version":"3.51.4"},"reference-count":9,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:00:00Z","timestamp":1778544000000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"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;amp; Syst Pharma"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Population models to identify optimal dosages typically include the evaluation of a drug's pharmacokinetics and the relationships with efficacy and safety. Dose modifications due to intolerable toxicities are frequently required for oncology therapeutics taken chronically and may impact antitumor activity and subsequent occurrences of adverse events. Model\u2010based simulations must account for the impact of dose modifications to provide meaningful predictions that capture the dynamic interplay between pharmacokinetics, safety, and efficacy. While static dose modification schedules may be incorporated into simulations, these pre\u2010determined scenarios are empiric and may not adequately capture the time\u2010dependent and stochastic nature of adverse events that lead to dose modifications. PF\u201006804103 is an anti\u2010HER2 antibody\u2010drug conjugate that demonstrated dose\u2010dependent antitumor activity and safety events. PF\u201006804103 appeared to have a narrow therapeutic window, which made it difficult to identify the optimal starting dosing regimen and dose modification schedule. Thus, quantitative modeling approaches were explored to better understand exposure\u2010response relationships. An adaptive clinical trial simulation framework consisting of pharmacokinetic, tumor dynamic, and repeated time\u2010to\u2010event peripheral neuropathy longitudinal models was developed to guide the dose optimization of PF\u201006804103. This framework provides the advantage of accounting for adverse event\u2010driven dose modifications and their real\u2010time impact of safety on PK and efficacy, and can be adapted to other oncology therapeutics with time\u2010dependent and exposure\u2010related safety and efficacy profiles. The framework could be particularly beneficial to inform dose optimization, by integrating multi\u2010dimensional early clinical data to evaluate different dosage regimens and define the regimen with the best benefit\/risk ratio for further investigation.<\/jats:p>","DOI":"10.1002\/psp4.70261","type":"journal-article","created":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T16:41:55Z","timestamp":1778604115000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Dosing Trial Simulation Framework to Inform Dose Optimization: Case Study Using Longitudinal\n                    <scp>PKPD<\/scp>\n                    Models With\n                    <scp>PF<\/scp>\n                    \u201006804103 Phase 1 Data in Participants With Human Epidermal Growth Factor Receptor 2 (\n                    <scp>HER2<\/scp>\n                    ) Positive and Low Solid Tumors"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8774-826X","authenticated-orcid":false,"given":"Jerry","family":"Li","sequence":"first","affiliation":[{"name":"Clinical Pharmacology, Pfizer Inc.  La Jolla California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9147-9357","authenticated-orcid":false,"given":"Li","family":"Zhou","sequence":"additional","affiliation":[{"name":"Clinical Pharmacology, Pfizer Inc.  La Jolla California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abraham C. F.","family":"Leung","sequence":"additional","affiliation":[{"name":"Early Clinical Development, Pfizer Inc.  San Francisco California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghua","family":"Yin","sequence":"additional","affiliation":[{"name":"Clinical Pharmacology, Pfizer Inc.  La Jolla California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4051-884X","authenticated-orcid":false,"given":"Xiaoying","family":"Chen","sequence":"additional","affiliation":[{"name":"Clinical Pharmacology, Pfizer Inc.  La Jolla California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,5,12]]},"reference":[{"key":"e_1_2_10_2_1","first-page":"S120","article-title":"Evaluation of the Prevalence of Dosage Modifications in Pivotal Trials for Recently\u2010Approved Oncology Drugs","volume":"62","author":"Hudson R. B. Y.","year":"2022","journal-title":"Journal of Clinical Pharmacology"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/psp4.12863"},{"key":"e_1_2_10_4_1","article-title":"A Modeling Framework to Simulate Xeloda Dose Intensity and Survival in Colorectal Cancer","volume":"17","author":"Claret L.","year":"2008","journal-title":"PAGE"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/psp4.13027"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1158\/1535-7163.MCT-23-0101"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/psp4.12442"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/psp4.12192"},{"key":"e_1_2_10_9_1","unstructured":"A. C.HookerandM. O.Karlsson \u201cThe Kaplan\u2010Meier Mean Covariate Plot (KMMC): A New Diagnostic for Covariates in Time\u2010To\u2010Event Models \u201dAbstract 2564. Population Approach Group Europe (PAGE) Meeting 2012."},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10552-012-0115-7"}],"container-title":["CPT: Pharmacometrics &amp; Systems Pharmacology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ascpt.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/psp4.70261","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ascpt.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/psp4.70261","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ascpt.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/psp4.70261","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T16:42:04Z","timestamp":1779036124000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascpt.onlinelibrary.wiley.com\/doi\/10.1002\/psp4.70261"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":9,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["10.1002\/psp4.70261"],"URL":"https:\/\/doi.org\/10.1002\/psp4.70261","archive":["Portico"],"relation":{},"ISSN":["2163-8306","2163-8306"],"issn-type":[{"value":"2163-8306","type":"print"},{"value":"2163-8306","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"2025-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-22","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-05-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70261"}}