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      Prediction of the intestinal first-pass metabolism of CYP3A and UGT substrates in humans from in vitro data.

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          Abstract

          This study aimed to establish a practical and simplified method of predicting intestinal availability in humans (F(g,human)) at the drug discovery stage using in vitro metabolic clearance values and permeability clearance values. A prediction model for F(g,human) of 19 CYP3A substrates and 5 UGT substrates was constructed based on the concept that the permeability clearance values mean the permeability across the basal membrane with a pH of 7.4 on both sides. Permeability clearance values were obtained by parallel artificial membrane permeability assay (PAMPA) at pH 7.4. PAMPA is widely used in the pharmaceutical industry as the earliest primary screening stage and enables estimation of the kinetics of transport by passive diffusion. For CYP3A substrates, the metabolic clearance was obtained from in vitro intrinsic clearance values in human intestinal or hepatic microsomes (CL(int,HIM) or CL(int,HLM), respectively). Using metabolic clearances corrected by the ratio of CL(int,HIM) to CL(int,HLM), HLM showed equivalent predictability to that of HIM for CYP3A substrates. For UGT substrates, the clearance was obtained from alamethicin-activated HIM using one incubation with both NADPH and UDPGA cofactors. The method proposed in this study could predict F(g,human) for the compounds investigated and represents a simplified method based on a new concept applicable to lower permeability compounds.

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          Author and article information

          Journal
          Drug Metab. Pharmacokinet.
          Drug metabolism and pharmacokinetics
          1880-0920
          1347-4367
          2011
          : 26
          : 6
          Affiliations
          [1 ] Pharmacokinetics Research Laboratory, Dainippon Sumitomo Pharma Co., Ltd., Osaka, Japan. haruka-nishimuta@ds-pharma.co.jp
          Article
          JST.JSTAGE/dmpk/DMPK-11-RG-034
          10.2133/dmpk.DMPK-11-RG-034
          21878741
          04f9ec68-e74e-4cc8-b311-634543673169
          History

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