{"title":"药物引起的肝损伤预测:扩展清除模型及其用于前瞻性转运体和酶为基础的肝细胞应激分级","authors":"G. Camenisch","doi":"10.11648/J.IJPC.20190502.11","DOIUrl":null,"url":null,"abstract":"Many enzymes and transporters involved in the hepatic clearance of drugs also play an important role in endogenous compound transport. Inhibition of some of these active mechanisms has frequently been shown to be associated with Drug-Induced Liver Injury (DILI). The Extended Clearance Model (ECM) describes the complex interplay between the different processes driving hepatic clearance, namely sinusoidal uptake and efflux, canalicular secretion and intracellular metabolism. Based on the ECM, we have derived an integral concept (referred as 1/R-value approach) to quantitatively describe the overall inhibition potency of potential drug candidates on active processes involved in the transport and metabolism of endogenous and safety-relevant compounds. For a small training set of in-house compounds with largely complete in vitro inhibition and in vivo exposure data, accurate ECM-based prediction of DILI was realized. Additionally, prediction of several cases of DILI for a comprehensive validation set of external compounds was achieved with no major false-positive results. However, due to general incompleteness of the required input information available in the public space (the most probable reason for the large number of false-negatives in the test set) the overall legitimacy of ECM for large-scale prediction of cell stress mediated DILI still needs to be demonstrated. In order to advance and accelerate science in this exciting but complex field, a more transparent and open sharing of data is therefore urgently needed and should be encouraged.","PeriodicalId":14230,"journal":{"name":"International Journal of Pharmacy and Chemistry","volume":"126 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading\",\"authors\":\"G. Camenisch\",\"doi\":\"10.11648/J.IJPC.20190502.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many enzymes and transporters involved in the hepatic clearance of drugs also play an important role in endogenous compound transport. Inhibition of some of these active mechanisms has frequently been shown to be associated with Drug-Induced Liver Injury (DILI). The Extended Clearance Model (ECM) describes the complex interplay between the different processes driving hepatic clearance, namely sinusoidal uptake and efflux, canalicular secretion and intracellular metabolism. Based on the ECM, we have derived an integral concept (referred as 1/R-value approach) to quantitatively describe the overall inhibition potency of potential drug candidates on active processes involved in the transport and metabolism of endogenous and safety-relevant compounds. For a small training set of in-house compounds with largely complete in vitro inhibition and in vivo exposure data, accurate ECM-based prediction of DILI was realized. Additionally, prediction of several cases of DILI for a comprehensive validation set of external compounds was achieved with no major false-positive results. However, due to general incompleteness of the required input information available in the public space (the most probable reason for the large number of false-negatives in the test set) the overall legitimacy of ECM for large-scale prediction of cell stress mediated DILI still needs to be demonstrated. In order to advance and accelerate science in this exciting but complex field, a more transparent and open sharing of data is therefore urgently needed and should be encouraged.\",\"PeriodicalId\":14230,\"journal\":{\"name\":\"International Journal of Pharmacy and Chemistry\",\"volume\":\"126 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Pharmacy and Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/J.IJPC.20190502.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Pharmacy and Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.IJPC.20190502.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading
Many enzymes and transporters involved in the hepatic clearance of drugs also play an important role in endogenous compound transport. Inhibition of some of these active mechanisms has frequently been shown to be associated with Drug-Induced Liver Injury (DILI). The Extended Clearance Model (ECM) describes the complex interplay between the different processes driving hepatic clearance, namely sinusoidal uptake and efflux, canalicular secretion and intracellular metabolism. Based on the ECM, we have derived an integral concept (referred as 1/R-value approach) to quantitatively describe the overall inhibition potency of potential drug candidates on active processes involved in the transport and metabolism of endogenous and safety-relevant compounds. For a small training set of in-house compounds with largely complete in vitro inhibition and in vivo exposure data, accurate ECM-based prediction of DILI was realized. Additionally, prediction of several cases of DILI for a comprehensive validation set of external compounds was achieved with no major false-positive results. However, due to general incompleteness of the required input information available in the public space (the most probable reason for the large number of false-negatives in the test set) the overall legitimacy of ECM for large-scale prediction of cell stress mediated DILI still needs to be demonstrated. In order to advance and accelerate science in this exciting but complex field, a more transparent and open sharing of data is therefore urgently needed and should be encouraged.