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Preclinical Drug Metabolism in the Age of High-Throughput Screening: An Industrial Perspective

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Abstract

With the advent of genomics, combinatorial paradigms and high-throughput screen (HTS)-based pharmacological testing, the number of compounds flowing through the discovery pipeline is likely to escalate. At the same time, with increased knowledge of the human drug-metabolizing enzymes and the availability of in vitro absorption-metabolism (AM) models, Preclinical Drug Metabolism is poised to meet the challenges of HTS. In order to be successful, however, a rational HTS strategy (vs. serendipitous HTS) has to be employed. Such a strategy is based on automation, validation and integration of in vitroAM models and database management (AVID). A generalized strategy for rational (AVID-based) HTS in Preclinical Drug Metabolism is described briefly.

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REFERENCES

  1. A. D. Rodrigues. Use of in vitro human metabolism studies in drug development: an industrial perspective. Biochem. Pharmacol. 48:2147–2156 (1994).

    Google Scholar 

  2. A. Parkinson. An overview of current cytochrome P450 technology for assessing the safety and efficacy of new materials. Toxicol. Pathol. 24:45–57 (1996).

    Google Scholar 

  3. L. S. Gan, E. C. Niederer, A. Bridgers, S. Yanni, P. H. Hsyu, F. J. Pritchard, and D. Thakker. Use of Caco-2 cells as an in vitro intestinal absorption and metabolism model. Drug Dev. Industrial Pharmacy 20:615–631 (1994).

    Google Scholar 

  4. L. A. Holland, N. P. Chetwyn, M. D. Perkins, and S. M. Lunte. Capillary electrophoresis in pharmaceutical analysis. Pharm. Res. 14:372–387 (1997).

    Google Scholar 

  5. J. C. Lindon, J. K. Nicholson, U. G. Sidelmann, and I. D. Wilson. Directly coupled HPLC-NMR and its application to drug metabolism. Drug Metab. Revs. 29:705–746 (1997).

    Google Scholar 

  6. J. Berman, K. Halm, K. Adkison, and J. Shaffer. Simultaneous pharmacokinetic screening of a mixture of compounds in dog using API LC/MS/MS analysis for increased throughput. J. Med. Chem. 40:827–829 (1997).

    Google Scholar 

  7. T. V. Olah, D. A. McLoughlin, and J. D. Gilbert. The simultaneous determination of mixtures of drug candidates by liquid chromatography/atmosphere pressure chemical ionization mass spectrometry as an in vivo drug screening procedure. Rapid Commun. Mass Spectrom. 11:17–23 (1997).

    Google Scholar 

  8. J. Singh, J. Soloweij, M. Allen, L. Killar, and M. Ator. Lead development: validation and application of high-throughput screening for determination of pharmacokinetic parameters for enzyme inhibitors. Bioorg. Med. Chem. 4:639–643 (1996).

    Google Scholar 

  9. H. Kubinyi. Strategies and recent technologies in drug discovery. Pharmazie 50:647–662 (1995).

    Google Scholar 

  10. E. M. Gordon, M. A. Gallop, and D. V. Patel. Strategy and tactics in combinatorial organic synthesis. Applications to drug discovery. Acc. Chem. Res. 29:144–154 (1996).

    Google Scholar 

  11. A. Furka. History of combinatorial chemistry. Drug Devel. Res. 36:1–12 (1995).

    Google Scholar 

  12. L. J. Beeley, and D. M. Duckworth. The impact of genomics on drug design. Drug Discov. Today 1:474–480 (1996).

    Google Scholar 

  13. C. N. Selway and N. K. Terett. Parallel-compound synthesis: methodology for accelerating drug discovery. Bioorg. Med. Chem. 4:645–654 (1996).

    Google Scholar 

  14. D. Hook. Ultra high-throughput screening—a journey into nanoland with Gulliver and Alice. Drug Discov. Today 1:267–268 (1996).

    Google Scholar 

  15. M. W. Lutz, J. A. Menius, T. D. Choi, R. G. Laskody, P. L. Domanico, A. S. Goetz, and D. L. Saussy. Experimental design for high-throughput screening. Drug Discov. Today 1:277–286 (1996).

    Google Scholar 

  16. D. D. Bronson, D. M. Daniels, J. T. Dixon, C. C. Redick, and P. D. Haaland. Virtual kinetics: using statistical experimental design for rapid analysis of enzyme inhibitor mechanisms. Biochem. Pharmacol. 50:823–831 (1995).

    Google Scholar 

  17. Q. Zheng and D. J. Kyle. Computational screening of combinatorial libraries via multicopy sampling. Drug Discov. Today 2:229–234 (1997).

    Google Scholar 

  18. W. Rubas, M. E. M. Cromwell, R. J. Mrsny, G. Ingle, and K. A. Elias. An integrated method to determine epithelial transport and bioactivity of oral drug candidates in vitro. Pharm. Res. 13:23–26 (1996).

    Google Scholar 

  19. M. Chee, R. Yang, E. Hubbell, A. Berno, X. C. Huang, D. Stern, J. Winkler, D. J. Lockhart, M. S. Morris, and S. P. A. Fodor. Accessing genetic information with high-density DNA arrays. Science 274:610–614 (1996).

    Google Scholar 

  20. S. P. A. Fodor, J. L. Read, M. C. Pirrung, L. Stryer, A. T. Lu, and D. Solas. Light-directed, spatially addressable, parallel chemical synthesis. Science 251:767–773 (1991).

    Google Scholar 

  21. S. P. A. Fodor, R. Rava, X. C. Huang, A. C. Pease, C. P. Holmes, and C. L. Adams. Multiplexed biochemical assays with biochemical chips. Nature 364:555–556 (1993).

    Google Scholar 

  22. G. W. Bemis and M. A. Murcko. The properties of known drugs. 1: molecular frameworks. J. Med. Chem. 39:2887–2893 (1996).

    Google Scholar 

  23. D. F. V. Lewis. Molecular modelling of mammalian cytochromes P450. C. Ioannides (ed), Cytochromes P450: Metabolic and Toxicological Aspects, CRC Press, New York, 1996, pp 355–398.

    Google Scholar 

  24. D. F. V. Lewis, H. Moereels, B. G. Lake, C. Ioannides, and D. V. Parke. Molecular modelling of enzymes and receptors involved in carcinogenesis: QSARs and COMPACT-3D. Drug Metab. Revs. 26:261–285 (1994).

    Google Scholar 

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

    Google Scholar 

  26. P. Sanwald-Ducray and J. Dow. Prediction of pharmacokinetic parameters of reduced-dolasetron in man using in vitro-in vivo and interspecies allometric scaling. Xenobiotica 27:189–201 (1997).

    Google Scholar 

  27. T. Iwatsubo, N. Hirota, T. Ooie, H. Suzuki, and Y. Sugiyama. Prediction of in vivo drug disposition from in vitro data based on physiological pharmacokinetics. Biopharm. Drug Dispos. 17:273–310 (1996).

    Google Scholar 

  28. M. E. Brier and G. R. Aronoff. Application of artificial neural networks to clinical pharmacology. Int. J. Clin. Pharmacol. Ther. 34:510–514 (1996).

    Google Scholar 

  29. W. A. Ritschel, R. Akileswaran, and A. S. Hussain. Application of neural networks for the prediction of human pharmacokinetic parameters. Meth. Find. Exp. Clin. Pharmacol. 17:629–643 (1995).

    Google Scholar 

  30. R. J. Erb. The backpropagation neural network-a Bayesian classifier. Introduction and applicability to pharmacokinetics. Clin. Pharmacokin. 29:69–79 (1995).

    Google Scholar 

  31. G. S. Sittampalam, P. W. Iverson, I. A. Boadt, S. D. Kahl, S. Bright, J. M. Zock, W. P. Janzen, and M. D. Lister. Design of signal windows in high throughput screening assays for drug discovery. J. Biomol. Screening 2: 159–169 (1997).

    Google Scholar 

  32. M. Banks, A. Binnie, and S. Fogarty. High throughput screening using fully integrated robotic screening. J. Biomol. Screening 2: 133–135 (1997).

    Google Scholar 

  33. J. J. Bouska, R. L. Bell, C. L. Goodfellow, A. O. Stewart, C. D. W. Brooks, and G. W. Carter. Improving the in vivo duration of 5-lipoxygenase inhibitors: application of in vitro glucuronosyltransferase assay. Drug Metab. Dispos. 25: 1032–1038 (1997).

    Google Scholar 

  34. D. A. McLoughlin, T. V. Olah, and J. D. Gilbert. A direct method for the simultaneous determination of 10 drug candidates in plasma by liquid chromatography-atmospheric pressure chemical ionization mass spectrometry interfaced to a Prospekt solid-phase extraction system. J. Pharm. Biomed. Anal. 15: 1893–1901 (1997).

    Google Scholar 

  35. A. L. Ungell. In vitro absorption studies and their relevance to absorption from the GI tract. Drug Devel. Indust. Pharm. 23: 879–892 (1997).

    Google Scholar 

  36. M. Jansson, A. Emmer, J. Roeraade, U. Lindberg, and B. Hok. Micro vials on a silicon wafer for sample introduction in capillary electrophoresis. J. Chrom. 626: 310–314 (1992).

    Google Scholar 

  37. D. J. Harrison, K. Fluri, K. Seiler, Z. Fan, C. S. Effenhauser, and A. Manz. Micromachining a miniaturized capillary electrophoresis-based chemical analysis system on a chip. Science 261: 895–897 (1993).

    Google Scholar 

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Rodrigues, A.D. Preclinical Drug Metabolism in the Age of High-Throughput Screening: An Industrial Perspective. Pharm Res 14, 1504–1510 (1997). https://doi.org/10.1023/A:1012105713585

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