Study Purpose
Metabolism is the leading clearance mechanism responsible for about 75% of the marketed drugs [15]. Among the drugs that have undergone metabolism, about 48% and 24% are mediated by cytochrome P450 (CYP) enzymes and non-CYP enzymes, respectively (Figure 1a). The contribution of CYPs to the metabolism of those marketed drugs ranges from 1% to 40%, with CYP3A4 being the most (Figure 1b). The contribution of non-CYP enzymes to the metabolism of those marketed drugs ranges from 2% to 45%, with uridine diphosphate glucuronosyltransferase (UGT) contributing the most (Figure 1c) [16]. Although drugs can be metabolized in several organs, drug metabolism primarily occurs in the liver and intestine. Hepatic metabolism occurs primarily through the CYP family of enzymes but also through non-CYP enzymes (e.g., UGTs). Although CYP enzymes are somewhat similar at all species, the isoform types and expression levels of CYPs vary significantly among different species and even among diverse human populations. The isoform types and expression ratios of CYPs also differ in different tissues, with the highest expression in the liver and intestine. That makes the prediction of human metabolic profiles across populations difficult. It is even more complicated when trying to predict human profiles based on in vivo data. The most valuable and predictive methods begin with human CYPs, either recombinantly expressed or derived from liver microsomes.
Drug interactions (DDI) are primarily examined in vitro by probing well-defined enzymatic reaction bench markers to elucidate the potential mechanism of DDIs and obtain kinetic parameters for further studies. Metabolic enzymes mediated DDIs include determining the main routes of drug elimination and assessing the contribution of relevant metabolic enzymes to drug disposition (enzyme metabolic reaction phenotyping experiments). It also includes investigating the drug's effect on metabolic enzymes (enzyme inhibition or induction experiments). DDI involves the influence of one drug, the “perpetrator,” with the metabolic or pharmacokinetic behavior of a co-administered drug, the “victim.” If the perpetrator inhibits a CYP, this can decrease the metabolic clearance of a victim that CYP primarily metabolizes. Likewise, if the perpetrator activates the CYP, it will expedite the victim’s clearance. Similarly, if the victim is a prodrug converted to the parent or active drug by a CYP, then inhibitive or activating perpetrators will decrease or increase the serum concentrations of the active drug, respectively. Inhibition of cytochrome P450 enzymes causes toxic side effects that may be improved by changes in treatment regimens. Still, drug interactions may lead to severe adverse effects, which lead to some drugs being terminated at an early stage of development and/or even withdrawn from the market.
Figure 1. Metabolic pathways of drugs, data derived from Anitha Saravanakumar et al
Note: Figure 1a . enzymes involved in drug metabolism, Figure 1b . cytochrome P450 enzymes (CYPs) involved in drug metabolism, Figure 1c . non-cytochrome P450 enzymes (CYPs) involved in drug metabolism.ADH: alcohol dehydrogenase, ALDH: aldehyde dehydrogenase, CES: carboxylesterase, FMO: flavin monooxygenase, MAO: monoamine oxidase, UGT: uridine diphosphate glucuronosyltransferases, XO: xanthine oxidase, AO: aldehyde oxidase
Platform Introduction
WuXi AppTec’s DDI platform provides tier-based DDI assays which meet the requirements of different stages in drug discovery and development, namely lead finding (LF), lead optimization (LO), preclinical candidate (PCC), and investigational new drug (IND).
Example of Validation Data
Both CYP3A4 and CYP2C enzymes are induced via activation of the pregnane X receptor (PXR). FDA and NMPA guidance recommend if the investigational drug causes CYP3A4 and the results suggest that a clinical study is warranted, the sponsor should evaluate the potential of the investigational drug to induce CYP2C. WuXi AppTec established a unique CYP2C (CYP2C8, CYP2C9, and CYP2C19) induction test platform through long-term exploration and validation (Figure 2 and Figure 3). The maximum group of induction of known inducers in our test system was significantly greater than those reported in the literature. It provided a more sensitive method for evaluating CYP2C induction and predicting the risk of drug interactions while providing a reference basis for clinical drug interaction study protocols.
CYP Induciton Assay in Human Hepatocytes
Emax Comparison-CYP2C8 and CYP2C9
CYP Induciton Assay in Human Hepatocytes
Induction fold Comparison of CYP2C19
References
1. Frank R, Hargreaves R. 2003. Clinical biomarkers in drug discovery and development. Nature Reviews Drug Discovery. 2(7):566-80
2. Di L, Feng B, Goosen TC, Lai Y, Steyn SJ, Varma MV, Obach RS. 2013. A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development. Drug Metabolism and Disposition. 41(12):1975-93
3. Nomeir, Amin A. 2010. ADME Strategies in Lead Optimization (book chapter) 25-88 in Early Drug Development: Strategies and Routes to First‐in‐Human Trials (book) Editor(s): Mitchell N. Cayen DOI:10.1002/9780470613191
4. Press, B. & Di, G. D. Permeability for intestinal absorption: Caco-2 assay and related issues. Curr. Drug Metab. 9, 893-900 (2008)
5. Giacomini, K.M. et al. Membrane transporters in drug development. Nature reviews drug discovery 9, 215-236 (2010)
6. Lipid-PAMPA with the MultiScreen Filer Plates, Millipore #PC040EN00, June 2004
7. Kansy, M., Senner, F. & Gubernator, K. Physicochemical high throughput screening: parallel artificial membrane permeability assay in the description of passive absorption processes. J. Med. Chem. 41, 1007‒1010 (1998)
8. Food and Drug Administration Center for Drug Evaluation and Research (2020). Clinical Drug Interaction Studies —Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry (FDA Maryland)
9. Suzanne, S. et al. Towards Prediction of in vivo intestinal absorption using a 96-well Caco-2 Assay. J. Pharm. Sci. 99, 32463265 (2010)
10. Smith, D.A. et al. 2010. The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery. Nature Reviews Drug Discovery 9, 929‒939
11. Di L, Breen C, Chambers R, Eckley ST, Fricke R, Ghosh A, Harradine P, Kalvass JC, Ho S, Lee CA, Marathe P, Perkins EJ, Qian M, Tse S, Yan Z, Zamek-Gliszczynski MJ. 2017. Industry Perspective on Contemporary Protein-Binding Methodologies: Considerations for Regulatory Drug-Drug Interaction and Related Guidelines on Highly Bound Drugs, Journal of Pharmaceutical Sciences, 106(12), 3442-3452
12. Obach RS, Lombardo F, Waters NJ. 2008. Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds. Drug Metabolism and Disposition, 36(7):1385-1405
13. Di L. 2014. The role of drug-metabolizing enzymes in clearance. Expert Opinion on Drug Metabolism and Toxicology. 10(3):379-93
14. Poulin P, Haddad S. 2013. Toward a new paradigm for the efficient in vitro-in vivo extrapolation of metabolic clearance in humans from hepatocyte data. Journal of Pharmaceutical Sciences. 102(9):3239-51
15. Di L. 2014. The role of drug-metabolizing enzymes in clearance. Expert Opinion on Drug Metabolism and Toxicology. 10(3):379-93
16. Anitha Saravanakumar et al. 2019. Physicochemical Properties, Biotransformation, and Transport Pathways of Established and Newly Approved Medications: A Systematic Review of the Top 200 Most Prescribed Drugs vs. the FDA-Approved Drugs Between 2005 and 2016
2. Di L, Feng B, Goosen TC, Lai Y, Steyn SJ, Varma MV, Obach RS. 2013. A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development. Drug Metabolism and Disposition. 41(12):1975-93
3. Nomeir, Amin A. 2010. ADME Strategies in Lead Optimization (book chapter) 25-88 in Early Drug Development: Strategies and Routes to First‐in‐Human Trials (book) Editor(s): Mitchell N. Cayen DOI:10.1002/9780470613191
4. Press, B. & Di, G. D. Permeability for intestinal absorption: Caco-2 assay and related issues. Curr. Drug Metab. 9, 893-900 (2008)
5. Giacomini, K.M. et al. Membrane transporters in drug development. Nature reviews drug discovery 9, 215-236 (2010)
6. Lipid-PAMPA with the MultiScreen Filer Plates, Millipore #PC040EN00, June 2004
7. Kansy, M., Senner, F. & Gubernator, K. Physicochemical high throughput screening: parallel artificial membrane permeability assay in the description of passive absorption processes. J. Med. Chem. 41, 1007‒1010 (1998)
8. Food and Drug Administration Center for Drug Evaluation and Research (2020). Clinical Drug Interaction Studies —Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry (FDA Maryland)
9. Suzanne, S. et al. Towards Prediction of in vivo intestinal absorption using a 96-well Caco-2 Assay. J. Pharm. Sci. 99, 32463265 (2010)
10. Smith, D.A. et al. 2010. The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery. Nature Reviews Drug Discovery 9, 929‒939
11. Di L, Breen C, Chambers R, Eckley ST, Fricke R, Ghosh A, Harradine P, Kalvass JC, Ho S, Lee CA, Marathe P, Perkins EJ, Qian M, Tse S, Yan Z, Zamek-Gliszczynski MJ. 2017. Industry Perspective on Contemporary Protein-Binding Methodologies: Considerations for Regulatory Drug-Drug Interaction and Related Guidelines on Highly Bound Drugs, Journal of Pharmaceutical Sciences, 106(12), 3442-3452
12. Obach RS, Lombardo F, Waters NJ. 2008. Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds. Drug Metabolism and Disposition, 36(7):1385-1405
13. Di L. 2014. The role of drug-metabolizing enzymes in clearance. Expert Opinion on Drug Metabolism and Toxicology. 10(3):379-93
14. Poulin P, Haddad S. 2013. Toward a new paradigm for the efficient in vitro-in vivo extrapolation of metabolic clearance in humans from hepatocyte data. Journal of Pharmaceutical Sciences. 102(9):3239-51
15. Di L. 2014. The role of drug-metabolizing enzymes in clearance. Expert Opinion on Drug Metabolism and Toxicology. 10(3):379-93
16. Anitha Saravanakumar et al. 2019. Physicochemical Properties, Biotransformation, and Transport Pathways of Established and Newly Approved Medications: A Systematic Review of the Top 200 Most Prescribed Drugs vs. the FDA-Approved Drugs Between 2005 and 2016
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