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Feasibility of Developing a Neural Network for Prediction of Human Pharmacokinetic Parameters from Animal Data

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REFERENCES

  1. H. Boxenbaum. Interspecies pharmacokinetic scaling and the evolutionary-comparative paradigm. Drug. Metab. Rev. 15:1071–1121 (1984).

    Google Scholar 

  2. H. Boxenbaum. Interspecies scaling, allometry, physiologic time, and the ground plan for pharmacokinetics. J. Pharmacokin. Biopharm. 10:201–227 (1982).

    Google Scholar 

  3. R. M. J. Ings. Interspecies scaling and comparison in drug development and toxicokinetics. Xenobiotica 20:1201–1231 (1990).

    Google Scholar 

  4. J. Mordenti. Man versus beast: Pharmacokinetic scaling in mammals. J. Pharm. Sci. 75:1028–1039 (1986).

    Google Scholar 

  5. H. Boxenbaum. Time concepts in physics, biology, and pharmacokinetics. J. Pharm. Sci. 75:1053–1062 (1986).

    Google Scholar 

  6. F. E. Yates and P. N. Kugler. Similarity principles and intrinsic geometries: Contrasting approaches to interspecies scaling. J. Pharm. Sci. 75:1019–1027 (1986).

    Google Scholar 

  7. R. L. Dedrick, K. B. Bischoff, and D. Z. Zaharko. Interspecies correlation of plasma concentration history of methotrexate (NSC-740). Cancer Chemother. Rep. Part I 54:95–101 (1970).

    Google Scholar 

  8. M. Bonati, R. Latini, G. Tognoni, J. F. Young, and S. Garattini. Interspecies comparison of in vivo caffeine pharmacokinetics in man, monkey, rabbit, rat, and mouse. Drug Metab. Rev. 15:1355–1383 (1985).

    Google Scholar 

  9. G. S. Duthu. Interspecies correlation of the pharmacokinetics of erythromycin, oleandomycin, and tylosin. J. Pharm. Sci. 74:943–946 (1985).

    Google Scholar 

  10. S. S. Ibrahim and F. D. Boudinot. Pharmacokinetics of 2′,3′-dideoxycytidine in rats: Application to interspecies scale-up. J. Pharm. Pharmacol. 41:829–834 (1989).

    Google Scholar 

  11. S. M. Owens, W. C. Hardwick, and D. Blackall. Phencyclidine pharmacokinetic scaling among species. J. Pharmacol. Exp. Ther. 242:96–101 (1987).

    Google Scholar 

  12. C. Efthymimopoulos, R. Battaglia, and M. Benedetti. Animal pharmacokinetics and interspecies scaling of FCE 22101 a penem antibiotic. J. Antimicrob. Chemother. 27:517–526 (1991).

    Google Scholar 

  13. A. Puigdemont, R. Guitart, F. De Mora, and M. Arboix. Prediction of the disposition of propafenone in humans and dogs from pharmacokinetic parameters in other animal species. J. Pharm. Sci. 80:1106–1109 (1991).

    Google Scholar 

  14. B. A. Patel, F. D. Boudinot, R. F. Schinazi, J. M. Gallo, and C. K. Chu. Comparative pharmacokinetics and interspecies scaling of 3′-azido-3′-deoxythymidine (AZT) in several mammalian species. J. Pharmacobio-Dyn. 13:206–211 (1990).

    Google Scholar 

  15. W. A. Ritschel, N. N. Vachharajani, R. D. Johnson, and A. S. Hussain. Interspecies scaling of coumarin among six different mammalian species. Meth. Find. Clin. Exp. Pharmacol. 13:697–702 (1991).

    Google Scholar 

  16. J. Gasfeiger and J. Zupan: Neural networks: A new method for solving chemical problems or just a passing phase. Anal. Chem. Acta 248:1–30 (1991).

    Google Scholar 

  17. S. Shadmehr and D. Z. D'Argenio. A neural network for nonlinear Bayesian estimation in drug therapy. Neur. Comp. 2:216–225 (1990).

    Google Scholar 

  18. A. S. Hussain, X. Yu, and R. D. Johnson. Application of neural computing in pharmaceutical product development. Pharm. Res. 8:1248–1252 (1991).

    Google Scholar 

  19. H. Matsui, K. Yano, and T. Okuda. Pharmacokinetics of the cephalosporin SM-1652 in mice, rats, rabbits, dogs and rhesus monkeys. Antimicrob. Agents Chemother. 22:213–219 (1982).

    Google Scholar 

  20. M. Komoya, Y. Kikuchi, A. Tachibana, and K. Yano. Pharmacokinetics of a new broad-spectrum cephamycin YM09330, parentally administered to various experimental animals. Antimicrob. Agents Chemother. 20:176–183 (1981).

    Google Scholar 

  21. R. A. Yates, H. K. Adam, R. J. Donnelly, H. L. Houghton, E. A. Charlesworth, and E. A. Laws. Pharmacokinetics and tolerance of single i.v. doses of cefotetan disodium in male caucasian volunteers. J. Antimicrob. Chemother. 11 (Suppl A):185–198 (1982).

    Google Scholar 

  22. L. B. Mellet. Comparative drug metabolism. Prog. Drug. Res. 13:136–169 (1969).

    Google Scholar 

  23. T. Murakama, H. Sakamoto, S. Fukada, S. Nakamoto, T. Hirose, N. Itoh, and M. Nishida. Pharmacokinetics of cefotoxime in animals after parenteral dosing. Antimicrob. Agents Chemother. 17:157–164 (1980).

    Google Scholar 

  24. H. C. Neu. The new β-lactamase stable cephalosporins. Ann. Intern. Med. 97:408–419 (1982).

    Google Scholar 

  25. M. Komuro, W. Hori, M. Hotta, S. Saitoh, R. Ishida, and H. Uchida. Pharmacokinetics of the new antiplatelet agent 2-methyl-3-(1,4,5,6-tetrahydronicotinoyl)pyrazolo[1,5-a]pyridine in laboratory animals. Arzneim. Forsch./Drug Res. 42:55–59 (1992).

    Google Scholar 

  26. M. Komuro, W. Hori, M. Hotta, S. Saitoh, R. Ishida, and H. Uchida. Pharmacokinetics of the new antiplatelet agent 2-methyl-3-(1,4,5,6-tetrahydronicotinoyl)pyrazolo[1,5-a]pyridine in human subjects. Arzneim. Forsch./Drug Res. 42:60–64 (1992).

    Google Scholar 

  27. L. H. Hall and L. B. Kier. The molecular connectivity Chi indexes and Kappa shape indexes in structure property modeling. In K. B. Lipkowitz and D. B. Boyd (eds.), Reviews in Computational Chemistry II, VCH, New York, 1991, pp. 367–422.

    Google Scholar 

  28. A. A. Minai and R. D. Williams. Acceleration of back-propagation through learning rate and momentum adaptation. Int. Joint Conf. Neur. Networks 1:676–679 (1990).

    Google Scholar 

  29. A. S. Hussain and R. D. Johnson. Development of a neural network for QSAR problems. Presented at the 203rd ACS National Meeting (Division of Computers in Chemistry), San Francisco, CA, April 5–10, 1992.

  30. R. S. Markin, W. J. Murray, and H. Boxenbaum. Quantitative structure-activity study on human pharmacokinetic parameters of benzodiazepines using the graph theory approach. Pharm. Res. 5:201–208 (1988).

    Google Scholar 

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Authors and Affiliations

  1. Division of Pharmaceutics and Drug Delivery Systems, College of Pharmacy, University of Cincinnati Medical Center, Cincinnati, Ohio, 45267-004

    Ajaz S. Hussain, Robert D. Johnson, Nimish N. Vachharajani & Wolfgang A. Ritschel

Authors
  1. Ajaz S. Hussain
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  2. Robert D. Johnson
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  3. Nimish N. Vachharajani
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  4. Wolfgang A. Ritschel
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Hussain, A.S., Johnson, R.D., Vachharajani, N.N. et al. Feasibility of Developing a Neural Network for Prediction of Human Pharmacokinetic Parameters from Animal Data. Pharm Res 10, 466–469 (1993). https://doi.org/10.1023/A:1018917128684

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