Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading

Gian Camenisch

doi:doi:10.11648/j.ijpc.20190502.11

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Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading

Gian Camenisch

Published in International Journal of Pharmacy and Chemistry (Volume 5, Issue 2)

Received: 24 May 2019 Accepted: 27 June 2019 Published: 9 July 2019

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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.

Published in	International Journal of Pharmacy and Chemistry (Volume 5, Issue 2)
DOI	10.11648/j.ijpc.20190502.11
Page(s)	15-19
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

DILI, ECM, Cell Stress, Enzyme and Transporter Inhibition, BDDCS

References

[1]	S. Russmann, G. Kullak-Ublick, and I. Grattagliano (2009). Current concepts of mechanisms in drug-induced hepatotoxicity. Curr Med Chem 16, 3041-53.
[2]	M. Chen, V. Vijay, Q. Shi, Z. Liu, H. Fang, and W. Tong (2011). FDA-approved drug labeling for the study of drug-induced liver injury. Drug Discov Today 16, 697-703.
[3]	Y. Shitara, H. Sato, and Y. Sugiyama (2005). Evaluation of drug-drug interaction in the hepatobiliary and renal transport of drugs. Annu Rev Pharmacol Toxicol 45, 689-723.
[4]	S. Schadt, S. Simon, S. Kustermann, et al. (2015) Minimizing DILI risk in drug discovery – a screening tool for drug candidates. Toxicology In Vitro 30, 429-437.
[5]	J. Chang, E. Plise, J. Cheong, Q. Ho, and M. Lin (2013). Evaluating the in vitro inhibition of UGT1A1, OATP1B1, OATP1B3, MRP2 and BSEP in predicting drug-induced hyperbilirubinemia. Mol Pharmaceutics 10, 3067-3075.
[6]	O. Fahmi, T. Maurer, M. Kish, E. Cardenas, S. Boldt, and D. Nettleton (2008). A combined model for predicting CYP3A4 clinical net drug-drug interaction based on CYP3A4 inhibition, inactivation, and induction determined in vitro. Drug Metab Dipos 36, 1698-1708.
[7]	G. Camenisch, and K. Umehara (2012). Predicting human hepatic clearance from in vitro drug metabolism and transport data: A scientific and pharmaceutical perspective for assessing drug-drug interactions. Biopharm Drug Dispos 33, 179-194.
[8]	G. Camenisch, J. Riede, A. Kunze, J. Huwyler, B. Poller, and K. Umehara (2015). The extended clearance model and its use for the interpretation of hepatobiliary elimination data. ADMT&DMPK 3, 1-14.
[9]	M. Chen, A. Suzuki, S. Thakkar, K. Yu, C. Hu, and W. Tong (2016). DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans. Drug Discov Today 21, 648-653.
[10]	R. Chan, and L. Benet (2017). Evaluation of DILI predictive hypothesis in early drug development. Chem Res Toxicol 30, 1017-1029.

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APA Style

Gian Camenisch. (2019). Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading. International Journal of Pharmacy and Chemistry, 5(2), 15-19. https://doi.org/10.11648/j.ijpc.20190502.11

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ACS Style

Gian Camenisch. Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading. Int. J. Pharm. Chem. 2019, 5(2), 15-19. doi: 10.11648/j.ijpc.20190502.11

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AMA Style

Gian Camenisch. Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading. Int J Pharm Chem. 2019;5(2):15-19. doi: 10.11648/j.ijpc.20190502.11

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@article{10.11648/j.ijpc.20190502.11,
  author = {Gian Camenisch},
  title = {Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading},
  journal = {International Journal of Pharmacy and Chemistry},
  volume = {5},
  number = {2},
  pages = {15-19},
  doi = {10.11648/j.ijpc.20190502.11},
  url = {https://doi.org/10.11648/j.ijpc.20190502.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijpc.20190502.11},
  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.},
 year = {2019}
}

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TY  - JOUR
T1  - Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading
AU  - Gian Camenisch
Y1  - 2019/07/09
PY  - 2019
N1  - https://doi.org/10.11648/j.ijpc.20190502.11
DO  - 10.11648/j.ijpc.20190502.11
T2  - International Journal of Pharmacy and Chemistry
JF  - International Journal of Pharmacy and Chemistry
JO  - International Journal of Pharmacy and Chemistry
SP  - 15
EP  - 19
PB  - Science Publishing Group
SN  - 2575-5749
UR  - https://doi.org/10.11648/j.ijpc.20190502.11
AB  - 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.
VL  - 5
IS  - 2
ER  -

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Author Information

Gian Camenisch

Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland

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Plain Text BibTeX RIS

APA Style

Gian Camenisch. (2019). Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading. International Journal of Pharmacy and Chemistry, 5(2), 15-19. https://doi.org/10.11648/j.ijpc.20190502.11

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ACS Style

Gian Camenisch. Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading. Int. J. Pharm. Chem. 2019, 5(2), 15-19. doi: 10.11648/j.ijpc.20190502.11

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AMA Style

Gian Camenisch. Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading. Int J Pharm Chem. 2019;5(2):15-19. doi: 10.11648/j.ijpc.20190502.11

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@article{10.11648/j.ijpc.20190502.11,
  author = {Gian Camenisch},
  title = {Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading},
  journal = {International Journal of Pharmacy and Chemistry},
  volume = {5},
  number = {2},
  pages = {15-19},
  doi = {10.11648/j.ijpc.20190502.11},
  url = {https://doi.org/10.11648/j.ijpc.20190502.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijpc.20190502.11},
  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.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Drug-Induced Liver Injury Predictions: Extended Clearance Model and Its Use for Prospective Transporter and Enzyme-Based Hepatic Cell Stress Grading
AU  - Gian Camenisch
Y1  - 2019/07/09
PY  - 2019
N1  - https://doi.org/10.11648/j.ijpc.20190502.11
DO  - 10.11648/j.ijpc.20190502.11
T2  - International Journal of Pharmacy and Chemistry
JF  - International Journal of Pharmacy and Chemistry
JO  - International Journal of Pharmacy and Chemistry
SP  - 15
EP  - 19
PB  - Science Publishing Group
SN  - 2575-5749
UR  - https://doi.org/10.11648/j.ijpc.20190502.11
AB  - 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.
VL  - 5
IS  - 2
ER  -

Copy | Download