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The Use of in Vitro Metabolic Stability for Rapid Selection of Compounds in Early Discovery Based on Their Expected Hepatic Extraction Ratios

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Abstract

Purpose. The in vivo hepatic extraction ratio of cynomolgus monkeys was correlated with the corresponding in vitro extraction ratios that were determined in monkey microsomal incubations.

Method. For compounds that are eliminated mainly through liver phase I metabolism, the extraction ratio calculated from liver microsomal stability studies should correlate with their in vivo hepatic extraction ratios and also with their oral bioavailability in monkey. We used both well-stirred and parallel tube models of intrinsic clearance for the correlation. We also calculated extraction ratios for compounds within a given therapeutic area from fraction absorbed values that were estimated from the Caco-2 absorption model.

Result. The present data show that in vitro extraction ratios in monkey microsomes are predictive of the in vivo hepatic extraction ratios in monkeys. All compounds with high extraction ratio (>70%) in vivo were successfully classified as high-extraction-ratio compounds based on the in vitro monkey microsomal stability data. From the results of this study, it appears that the parallel tube model provided a slightly better classification than the well-stirred model.

Conclusions. The present method appears to be a valuable tool to rapidly screen and prioritize compounds with respect to liver first-pass metabolism in monkeys at an early phase of drug discovery.

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REFERENCES

  1. R. S. Obach, J. G. Baxter, J. G. Listonx, B. M. Silber, B. C. Jones, F. MacIntyre, D. J. Rance, and P. Wastall. The prediction of human pharmacolinetic parameters from preclinical and in vitro metabolism data. J.Pharmacol.Exp.Ther. 283:46-58 (1997).

    PubMed  Google Scholar 

  2. G. Schneider, P. Coassolo, and T. Lave. Combiningin vitro and in vivo pharmacokinetic data for prediction of hepatic drug clearance in humans by artificial neural networks and multivariate statistical techniques. J.Med.Chem. 42:5072-5076 (1999).

    PubMed  Google Scholar 

  3. K. Ito, I. Iwatsubo, S. Kanamitsu, Y. Nakajima, and Y. Sugiyama. Quantitative prediction of in vivo drug clearance and drug interactions from in vitro data on metabolism, together with binding and transport. Annu.Rev.Pharmacol.Toxicol. 38:461-499 (1998).

    PubMed  Google Scholar 

  4. R. S. Obach. Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: an examination of in vitro half-life approach and nonspecific binding to microsomes. Drug Metab.Dispos. 27:1350-1359 (1999).

    PubMed  Google Scholar 

  5. T. Lavé, P. Coassolo, and B. Reigner. Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitro-in vivo correlations. Clin.Pharmacokinet. 36:211-231 (1999).

    PubMed  Google Scholar 

  6. A. Rane, G. R. Wilkinson, and D. G. Shand. Prediction of hepatic extraction ratio from in vitro measurement of intrinsic clearance. J.Pharmacol.Exp.Ther. 200:420-424 (1977).

    PubMed  Google Scholar 

  7. T. Lavé, S. Dupin, C. Schmitt, B. Valles, G. Ubeaud, R. C. Chou, D. Jaeck, and P. Coassolo. The use of human hepatocytes to select compounds based on their expected hepatic extraction ratios in humans. Pharm.Res. 14:152-155 (1997).

    PubMed  Google Scholar 

  8. J. B. Houston and D. J. Carlile. Prediction of hepatic clearance from microsomes, hepatocytes, and liver slices. Drug Metab.Rev. 29:891-922 (1997).

    PubMed  Google Scholar 

  9. J. Zuegge, G. Schneider, P. Coassolo, and T. Lavé. Prediction of hepatic metabolic clearance, a comparison and assessment of prediction models. Clin.Pharmacokinet. 40:553-563 (2001).

    PubMed  Google Scholar 

  10. Y. Naritomi, S. Terashita, S. Kimura, A. Suzuki, A. Kagayama, and Y. Sugiyama. Prediction of human hepatic clearance from in vivo animal experiments and in vitro metabolic studies with liver microsomes from animal and humans. Drug Metab.Dispos. 29:1316-1324 (2001).

    PubMed  Google Scholar 

  11. T. Lavé, S. Dupin, C. Schmitt, R. C. Chou, D. Jaeck, and P. Coassolo. Integration of in vitro data into allometric scaling to predict hepatic metabolic clearance in man: application to 10 extensively metabolized drugs. J.Pharm.Sci. 86:584-590 (1997).

    PubMed  Google Scholar 

  12. G. Krishna, K. Chen, C. Lin, and A. Nomeir. Permeability of lipophilic compounds in drug discovery using in-vitro human absorption model, Caco-2. Int.J.Pharmaceut. 222:77-89 (2001).

    Google Scholar 

  13. W. Rubas, N. Jezyk, and G. M. Grass. Comparison of the permeability characteristics of a human colonic epithelial (Caco-2) cell line to colon of rabbit, monkey, and dog intestine and human drug absorption. Pharm.Res. 10:113-118 (1993).

    PubMed  Google Scholar 

  14. J. B. Houston. Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance. Biochem.Pharmacol. 47:1469-1479 (1994).

    PubMed  Google Scholar 

  15. J. Oravcová, B. Böhs, and W. Lindner. Drug-protein binding studies: new trends in analytical and experimental methodology. J.Chrom.B 677:1-28 (1996).

    Google Scholar 

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Correspondence to Yau Yi Lau.

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Lau, Y.Y., Krishna, G., Yumibe, N.P. et al. The Use of in Vitro Metabolic Stability for Rapid Selection of Compounds in Early Discovery Based on Their Expected Hepatic Extraction Ratios. Pharm Res 19, 1606–1610 (2002). https://doi.org/10.1023/A:1020765025857

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  • DOI: https://doi.org/10.1023/A:1020765025857

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