Clinical data warehouse analysis of clinical laboratory test results of Korean healthy volunteers: does "not clinically significant" range of healthy volunteers need modification?
Cheol Joong Kim, Tak Don Kim, Ye Chan Park, Jin-Gyu Jung, Jung Sunwoo, Jang Hee Hong
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引用次数: 0
Abstract
This study analyzed clinical laboratory test results of healthy Korean volunteers screened for Phase 1 clinical trials at Chungnam National University Hospital. Data from 53 trials conducted between 2019 and 2023 were extracted from the Clinical Data Warehouse and included tests such as white blood cell count, hemoglobin, aspartate aminotransferase, alanine aminotransferase, and creatinine. The study aimed to evaluate whether current ranges for "not clinically significant (NCS)" values need modification. Results showed that NCS values often varied between studies, with temporary deviations from normal ranges being common among healthy volunteers, especially those engaged in activities such as heavy weight training or recent dietary excess. Comparative pharmacokinetics and bioequivalence studies made up the majority of trials. The analysis highlighted discrepancies in laboratory criteria application, with implications for screening failure rates. The findings suggest that stricter guidelines might exclude otherwise eligible participants unnecessarily. Establishing consistent NCS criteria could optimize screening and reduce variability across clinical sites. This is the first study to provide insights into clinical lab results for healthy Korean volunteers, emphasizing the need for tailored NCS guidelines in Phase 1 trials.
期刊介绍:
Translational and Clinical Pharmacology (Transl Clin Pharmacol, TCP) is the official journal of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT). TCP is an interdisciplinary journal devoted to the dissemination of knowledge relating to all aspects of translational and clinical pharmacology. The categories for publication include pharmacokinetics (PK) and drug disposition, drug metabolism, pharmacodynamics (PD), clinical trials and design issues, pharmacogenomics and pharmacogenetics, pharmacometrics, pharmacoepidemiology, pharmacovigilence, and human pharmacology. Studies involving animal models, pharmacological characterization, and clinical trials are appropriate for consideration.