{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T09:02:14Z","timestamp":1784538134569,"version":"3.55.0"},"reference-count":25,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T00:00:00Z","timestamp":1780012800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T00:00:00Z","timestamp":1780012800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["accp1.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Clinical Pharma"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Gecacitinib is a novel, broad\u2010spectrum Janus kinase (JAK) inhibitor being developed for the treatment of myelofibrosis, severe alopecia areata, ankylosing spondylitis, and atopic dermatitis. This study aimed to develop population pharmacokinetic (PopPK) models for gecacitinib and its metabolites ZG0244 and ZG0245 to evaluate influential factors. Data from healthy subjects and patients across nine clinical trials were pooled. PopPK models were developed using NONMEM, and covariates of interest were tested. The PopPK structure for gecacitinib was a two\u2010compartment model with first\u2010order absorption and linear elimination. The metabolite ZG0244 was best described by a two\u2010compartment model with Michaelis\u2013Menten formation and linear elimination, while for metabolite ZG0245, it was a one\u2010compartment model with Michaelis\u2013Menten formation and linear elimination. Statistically significant factors affecting pharmacokinetic parameters included sex, age, indication, and co\u2010administration with a strong CYP3A inducer or inhibitor. The effects of sex, age, and strong CYP3A inducer on exposure were limited, requiring no dose adjustment. A strong CYP3A inhibitor increased exposure by approximately 1.3\u2010fold. The median time to reach 95% of steady\u2010state concentration was approximately 3 days for gecacitinib and ZG0244, and approximately 7 days for ZG0245. This study developed population pharmacokinetic models for gecacitinib and its metabolites, and quantified the effects of covariates.<\/jats:p>","DOI":"10.1002\/jcph.70214","type":"journal-article","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T10:24:26Z","timestamp":1780050266000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Population Pharmacokinetics of Oral Gecacitinib in Healthy Subjects and Patients with Autoimmune and Inflammatory Diseases"],"prefix":"10.1002","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5300-2922","authenticated-orcid":false,"given":"Qingheng","family":"Meng","sequence":"first","affiliation":[{"name":"Center for Drug Clinical Research Shanghai University of Traditional Chinese Medicine  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuansheng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Suzhou Zelgen 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