Shu-Wen Teng , Michael Hafey , Jeanine Ballard , Xinjie Lin , Changhong Yun , Vijay More , Robert Houle , Ravi Katwaru , Ann Thomas , Grace Chan , Kim Michel , Yutai Li , Kara Pearson , Christopher Gibson
{"title":"基于生理学的比格犬胆汁酸盐处置模型(使用和不使用肝转运蛋白抑制剂西莫匹韦)","authors":"Shu-Wen Teng , Michael Hafey , Jeanine Ballard , Xinjie Lin , Changhong Yun , Vijay More , Robert Houle , Ravi Katwaru , Ann Thomas , Grace Chan , Kim Michel , Yutai Li , Kara Pearson , Christopher Gibson","doi":"10.1016/j.comtox.2022.100224","DOIUrl":null,"url":null,"abstract":"<div><p>BSEP inhibition is one risk factor for Drug-Induced Liver Injury (DILI). While in vitro screening of BSEP inhibition may prevent compounds with BSEP liability from progressing into the clinic, these in vitro data alone can result in false-positives and as such a specific in vivo biomarker would further enhance our BSEP inhibition de-risking strategy. Measurement of endogenous bile acids as biomarkers of BSEP inhibition in vivo is complicated by several factors, including drugs that inhibit BSEP can also inhibit other bile acid transporters such as NTCP. Here, we developed a novel translational framework, including an in vivo biomarker with a corresponding mechanistic model, and attempted to decouple the effect of liver sinusoidal uptake inhibition from efflux inhibition on bile acid disposition in the beagle dog. Specifically, we hypothesized that the change of a stable isotope-labeled (SIL) bile acid tracer’s exposure would yield a toxicodynamic signal that can provide insight into BSEP inhibition and ensuing bile salt accumulation. For this purpose we dosed the stable isotope-labeled cholic acid (<sup>13</sup>C-CA) and taurocholic acid (D4-TCA) as biomarker tracers in dogs, with and without the liver transporter inhibitor simeprevir, and determined the plasma and bile exposure of <sup>13</sup>C-CA, <sup>13</sup>C-TCA, D4-CA and D4-TCA in vivo. Key bile acid clearance and transporter inhibition parameters were determined in vitro. We developed a novel Physiologically Based Pharmacokinetic model (PBPK) to integrate the mechanistic physiological understanding, literature knowledge, and in vitro laboratory data to model bile acid disposition. Using modeling and simulation, we provided an increased mechanistic understanding of how to use plasma bile acid tracer data to inform on potential liver transporters inhibition and limitations to in vivo translation. The novel translational framework can enhance the future BSEP inhibition de-risking strategy, particularly if the experimental confounders to studying kinetics in dog hepatocytes in vitro models are solved.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100224"},"PeriodicalIF":3.1000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468111322000123/pdfft?md5=56a90a95a905ed980c1c5a2a975df2c8&pid=1-s2.0-S2468111322000123-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Physiologically-based modeling of cholate disposition in beagle dog with and without treatment of the liver transporter inhibitor simeprevir\",\"authors\":\"Shu-Wen Teng , Michael Hafey , Jeanine Ballard , Xinjie Lin , Changhong Yun , Vijay More , Robert Houle , Ravi Katwaru , Ann Thomas , Grace Chan , Kim Michel , Yutai Li , Kara Pearson , Christopher Gibson\",\"doi\":\"10.1016/j.comtox.2022.100224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>BSEP inhibition is one risk factor for Drug-Induced Liver Injury (DILI). While in vitro screening of BSEP inhibition may prevent compounds with BSEP liability from progressing into the clinic, these in vitro data alone can result in false-positives and as such a specific in vivo biomarker would further enhance our BSEP inhibition de-risking strategy. Measurement of endogenous bile acids as biomarkers of BSEP inhibition in vivo is complicated by several factors, including drugs that inhibit BSEP can also inhibit other bile acid transporters such as NTCP. Here, we developed a novel translational framework, including an in vivo biomarker with a corresponding mechanistic model, and attempted to decouple the effect of liver sinusoidal uptake inhibition from efflux inhibition on bile acid disposition in the beagle dog. Specifically, we hypothesized that the change of a stable isotope-labeled (SIL) bile acid tracer’s exposure would yield a toxicodynamic signal that can provide insight into BSEP inhibition and ensuing bile salt accumulation. For this purpose we dosed the stable isotope-labeled cholic acid (<sup>13</sup>C-CA) and taurocholic acid (D4-TCA) as biomarker tracers in dogs, with and without the liver transporter inhibitor simeprevir, and determined the plasma and bile exposure of <sup>13</sup>C-CA, <sup>13</sup>C-TCA, D4-CA and D4-TCA in vivo. Key bile acid clearance and transporter inhibition parameters were determined in vitro. We developed a novel Physiologically Based Pharmacokinetic model (PBPK) to integrate the mechanistic physiological understanding, literature knowledge, and in vitro laboratory data to model bile acid disposition. Using modeling and simulation, we provided an increased mechanistic understanding of how to use plasma bile acid tracer data to inform on potential liver transporters inhibition and limitations to in vivo translation. 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Physiologically-based modeling of cholate disposition in beagle dog with and without treatment of the liver transporter inhibitor simeprevir
BSEP inhibition is one risk factor for Drug-Induced Liver Injury (DILI). While in vitro screening of BSEP inhibition may prevent compounds with BSEP liability from progressing into the clinic, these in vitro data alone can result in false-positives and as such a specific in vivo biomarker would further enhance our BSEP inhibition de-risking strategy. Measurement of endogenous bile acids as biomarkers of BSEP inhibition in vivo is complicated by several factors, including drugs that inhibit BSEP can also inhibit other bile acid transporters such as NTCP. Here, we developed a novel translational framework, including an in vivo biomarker with a corresponding mechanistic model, and attempted to decouple the effect of liver sinusoidal uptake inhibition from efflux inhibition on bile acid disposition in the beagle dog. Specifically, we hypothesized that the change of a stable isotope-labeled (SIL) bile acid tracer’s exposure would yield a toxicodynamic signal that can provide insight into BSEP inhibition and ensuing bile salt accumulation. For this purpose we dosed the stable isotope-labeled cholic acid (13C-CA) and taurocholic acid (D4-TCA) as biomarker tracers in dogs, with and without the liver transporter inhibitor simeprevir, and determined the plasma and bile exposure of 13C-CA, 13C-TCA, D4-CA and D4-TCA in vivo. Key bile acid clearance and transporter inhibition parameters were determined in vitro. We developed a novel Physiologically Based Pharmacokinetic model (PBPK) to integrate the mechanistic physiological understanding, literature knowledge, and in vitro laboratory data to model bile acid disposition. Using modeling and simulation, we provided an increased mechanistic understanding of how to use plasma bile acid tracer data to inform on potential liver transporters inhibition and limitations to in vivo translation. The novel translational framework can enhance the future BSEP inhibition de-risking strategy, particularly if the experimental confounders to studying kinetics in dog hepatocytes in vitro models are solved.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs