| Literature DB >> 35854202 |
Carl Petersson1, Xin Zhou2, Joerg Berghausen3, David Cebrian4, Michael Davies5, Kevin DeMent6,7, Peter Eddershaw8, Arian Emami Riedmaier9, Alix F Leblanc10, Nenad Manveski11, Punit Marathe12, Panteleimon D Mavroudis13, Robin McDougall14,15, Neil Parrott11, Andreas Reichel16, Charles Rotter6, David Tess17, Laurie P Volak18, Guangqing Xiao19, Zheng Yang9, James Baker20,21.
Abstract
Accurate prediction of human clearance (CL) and volume of distribution at steady state (Vd,ss) for small molecule drug candidates is an essential component of assessing likely efficacious dose and clinical safety margins. In 2021, the IQ Consortium Human PK Prediction Working Group undertook a survey of IQ member companies to understand the current PK prediction methods being used to estimate these parameters across the pharmaceutical industry. The survey revealed a heterogeneity in approaches being used across the industry (e.g., the use of allometric approaches, differing incorporation of binding terms, and inconsistent use of empirical correction factors for in vitro-in vivo extrapolation, IVIVE), which could lead to different PK predictions with the same input data. Member companies expressed an interest in improving human PK predictions by identifying the most appropriate compound-class specific methods, as determined by physiochemical properties and knowledge of CL pathways. Furthermore, there was consensus that increased understanding of the uncertainty inherent to the compound class-dependent prediction would be invaluable in aiding communication of human PK and dose uncertainty at the time of candidate nomination for development. The human PK Prediction Working Group is utilizing these survey findings to help interrogate clinical IV datasets from across the IQ consortium member companies to understand PK prediction accuracy and uncertainty from preclinical datasets.Entities:
Keywords: Clearance; Human PK prediction; IQ Consortium; Uncertainty; Volume of distribution
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Year: 2022 PMID: 35854202 DOI: 10.1208/s12248-022-00735-9
Source DB: PubMed Journal: AAPS J ISSN: 1550-7416 Impact factor: 3.603