{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T05:03:14Z","timestamp":1784955794457,"version":"3.55.0"},"reference-count":40,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:00:00Z","timestamp":1782950400000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"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":[[2026,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Chimeric antigen receptor (CAR) T\u2010cell therapies exhibit complex cellular kinetics with high variability, frequent observations below the limit of quantification (BLQ), and influential outliers. These features can destabilize parameter estimation under Gaussian assumptions, motivating robust likelihood\u2010based approaches. While Student's t residuals with M3 censoring improve robustness, the lack of a closed\u2010form cumulative distribution function (CDF) complicates implementation across platforms like Monolix. We evaluated the Cauchy distribution as an implementation\u2010friendly, heavy\u2010tailed alternative providing closed\u2010form probability density and CDF expressions. In pharmacokinetic simulations with terminal\u2010phase outliers, Cauchy residuals preserved stable parameter recovery comparable to Student's t while Normal residuals exhibited significant bias. In a real\u2010data integrated CAR\u2010T application using full Bayesian inference, Cauchy and Student's t likelihoods yielded highly concordant posterior inference and subject\u2010level predictions. Furthermore, we extended the semi\u2010mechanistic CAR\u2010T framework by replacing piecewise switching with smooth, S\u2010shaped rate functions and process\u2010specific transition times. Full Bayesian summaries supported asynchronous transitions, revealing earlier memory conversion relative to expansion and delayed decay\u2010related transitions. These results support Cauchy likelihoods for robust cross\u2010platform implementation and demonstrate that smooth, decoupled transition modeling enhances the physiological plausibility of CAR\u2010T kinetics.<\/jats:p>","DOI":"10.1002\/jcph.70232","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T05:15:52Z","timestamp":1783055752000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoupling CAR\u2010T Expansion, Conversion, and Decay Timing: Physiologically Aligned Semi\u2010Mechanistic Modeling With Smooth Gating and a Cauchy Likelihood Residual Model"],"prefix":"10.1002","volume":"66","author":[{"given":"Yiming","family":"Cheng","sequence":"first","affiliation":[{"name":"Clinical Pharmacology and Pharmacometrics Bristol Myers Squibb  Summit NJ 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