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Physiologically-Based PK/PD Modelling of Therapeutic Macromolecules

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Abstract

Therapeutic proteins are a diverse class of drugs consisting of naturally occurring or modified proteins, and due to their size and physico-chemical properties, they can pose challenges for the pharmacokinetic and pharmacodynamic studies. Physiologically-based pharmacokinetics (PBPK) modelling has been effective for early in silico prediction of pharmacokinetic properties of new drugs. The aim of the present workshop was to discuss the feasibility of PBPK modelling of macromolecules. The classical PBPK approach was discussed with a presentation of the successful example of PBPK modelling of cyclosporine A. PBPK model was performed with transport of the cyclosporine across cell membranes, affinity to plasma proteins and active membrane transporters included to describe drug transport between physiological compartments. For macromolecules, complex PBPK modelling or permeability-limited and/or target-mediated distribution was discussed. It was generally agreed that PBPK modelling was feasible and desirable. The role of the lymphatic system should be considered when absorption after extravascular administration is modelled. Target-mediated drug disposition was regarded as an important feature for generation of PK models. Complex PK-models may not be necessary when a limited number of organs are affected. More mechanistic PK/PD models will be relevant when adverse events/toxicity are included in the PK/PD modelling.

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References

  1. Baumann A. Early development of therapeutic biologics— Pharmacokinetics. Curent Drug Metabolism. 2006;7:15–21.

    Article  CAS  Google Scholar 

  2. Kamiya H, Akita H, Harashima H. Pharmacokinetic and pharmacodynamic considerations in gene therapy. Drug Discov Today. 2003;8:990–6.

    Article  CAS  PubMed  Google Scholar 

  3. Tang L, Persky AM, Hochhaus G, Meibohm B. Pharmacokinetic aspects of biotechnology products. J Pharm Sci. 2004;93:2184–204.

    Article  CAS  PubMed  Google Scholar 

  4. Rowland M, Balant L, Peck C. Physiologically based pharmacokinetics in drug development and regulatory science: a workshop report (Georgetown University, Washington, DC, May 29–30, 2002). AAPS J. 2004;6:56–67.

    PubMed  Google Scholar 

  5. Edginton AN, Theil FP, Schmitt W, Willmann S. Whole body physiologically-based pharmacokinetic models: their use in clinical drug development. Expert Opin Drug Metab Toxicol. 2008;4:1143–52.

    Article  CAS  PubMed  Google Scholar 

  6. Nestorov I. Whole-body physiologically based pharmacokinetic models. Expert Opin Drug Metab Toxicol. 2007;3:235–49.

    Article  CAS  PubMed  Google Scholar 

  7. Kawai R, Mathew D, Tanaka C, Rowland M. Physiologically based pharmacokinetics of cyclosporine A: extension to tissue distribution kinetics in rats and scale-up to human. J Pharmacol Exp Ther. 1998;287:457–68.

    CAS  PubMed  Google Scholar 

  8. Tanaka C, Kawai R, Rowland M. Physiologically based pharmacokinetics of cyclosporine A: reevaluation of dose-nonlinear kinetics in rats. J Pharmacokinet Biopharm. 1999;27:597–623.

    Article  CAS  PubMed  Google Scholar 

  9. Willmann S, Schmitt W, Keldenich J, Dressman JB. A physiologic model for simulating gastrointestinal flow and drug absorption in rats. Pharm Res. 2003;20:1766–71.

    Article  CAS  PubMed  Google Scholar 

  10. Willmann S, Lippert J, Schmitt W. From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools. Expert Opin Drug Metab Toxicol. 2005;1:159–68.

    Article  CAS  PubMed  Google Scholar 

  11. von Kleist M, Huisinga W. Physiologically based pharmacokinetic modelling: a sub-compartmentalized model of tissue distribution. J Pharmacokinet Pharmacodyn. 2007;34:789.

    Article  Google Scholar 

  12. Kawai R, Lemaire M, Steimer JL, Bruelisauer A, Niederberger W, Rowland M. Physiologically based pharmacokinetic study on a cyclosporin derivative, SDZ IMM 125. J Pharmacokinet Biopharm. 1994;22:327–65.

    Article  CAS  PubMed  Google Scholar 

  13. Garg A, Balthasar JP. Physiologically-based pharmacokinetic (PBPK) model to predict IgG tissue kinetics in wild-type and FcRn-knockout mice. J Pharmacokinet Pharmacodyn. 2007;34:687–709.

    Article  CAS  PubMed  Google Scholar 

  14. Tanaka C, Kawai R, Rowland M. Dose-dependent pharmacokinetics of cyclosporin A in rats: events in tissues. Drug Metab Dispos. 2000;28:582–9.

    CAS  PubMed  Google Scholar 

  15. Schmitt W, Willmann S. Physiology-based pharmacokinetic modelling: ready to be used. Drug Discovery Today: Technologies. 2004;1:449–55.

    Article  CAS  Google Scholar 

  16. Parrott N, Paquereau N, Coassolo P, Lave T. An evaluation of the utility of physiologically based models of pharmacokinetics in early drug discovery. J Pharm Sci. 2005;94:2327–43.

    Article  CAS  PubMed  Google Scholar 

  17. Parrott N, Jones H, Paquereau N, Lave T. Application of full physiological models for pharmaceutical drug candidate selection and extrapolation of pharmacokinetics to man. Basic Clin Pharmacol Toxicol. 2005;96:193–9.

    Article  CAS  PubMed  Google Scholar 

  18. Willmann S, Hohn K, Edginton A, Sevestre M, Solodenko J, Weiss W, et al. Development of a physiology-based whole-body population model for assessing the influence of individual variability on the pharmacokinetics of drugs. J Pharmacokinet Pharmacodyn. 2007;34:401–31.

    Article  PubMed  Google Scholar 

  19. Yu LX, Amidon GLA. Compartmental absorption and transit model for estimating oral drug absorption. Int J Pharm. 1999;186:119–25.

    Article  CAS  PubMed  Google Scholar 

  20. Wang W, Wang EQ, Balthasar JP. Monoclonal antibody pharmakokinetics and pharmacodynamics. Clin Pharmacol Ther 2008;1–11.

  21. Lobo ED, Hansen RJ, Balthasar JP. Antibody pharmacokinetics and pharmacodynamics. J Pharm Sci. 2004;93:2645–68.

    Article  CAS  PubMed  Google Scholar 

  22. Pelkonen O, Kapitulnik J, Gundert-Remy U, Boobis AR, Stockis A. Local kinetics and dynamics of xenobiotics. Crit Rev Toxicol. 2008;38:697–720.

    Article  CAS  PubMed  Google Scholar 

  23. Mahmood I, Green MD. Pharmacokinetic and pharmacodynamic considerations in the development of therapeutic proteins. Clin Pharmacokinet. 2005;44:331–47.

    Article  CAS  PubMed  Google Scholar 

  24. Covell DG, Barbet J, Holton OD, Black CD, Parker RJ, Weinstein JN. Pharmacokinetics of monoclonal immunoglobulin G1, F(ab’)2, and Fab’ in mice. Cancer Res. 1986;46:3969–78.

    CAS  PubMed  Google Scholar 

  25. Baxter LT, Zhu H, Mackensen DG, Jain RK. Physiologically based pharmacokinetic model for specific and nonspecific monoclonal antibodies and fragments in normal tissues and human tumor xenografts in nude mice. Cancer Res. 1994;54:1517–28.

    CAS  PubMed  Google Scholar 

  26. Ferl GZ, Wu AM, DiStefano JJ III. A pedictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn). Annals of Biomedical Engineering. 2005;33:1640–52.

    Article  PubMed  Google Scholar 

  27. Hansen RJ, Balthasar JP. Intravenous immunoglobulin mediates an increase in anti-platelet antibody clearance via the FcRn receptor. Thromb Haemost. 2002;88:898–9.

    CAS  PubMed  Google Scholar 

  28. Boxenbaum H. Interspecies scaling, allometry, physiological time, and the ground plan of pharmacokinetics. J Pharmacokinet Biopharm. 1982;10:201–27.

    Article  CAS  PubMed  Google Scholar 

  29. D’Souza RW, Boxenbaum H. Physiological pharmacokinetic models: some aspects of theory, practice and potential. Toxicol Ind Health. 1988;4:151–71.

    PubMed  Google Scholar 

  30. Mahmood I. Application of fixed exponent 0.75 to the prediction of human drug clearance: an inaccurate and misleading concept. Drug Metabol Drug Interact. 2009;24:57–81.

    CAS  PubMed  Google Scholar 

  31. Grene-Lerouge NA, Bazin-Redureau MI, Debray M, Scherrmann JM. Interspecies scaling of clearance and volume of distribution for digoxin-specific Fab. Toxicol Appl Pharmacol. 1996;138:84–9.

    Article  CAS  PubMed  Google Scholar 

  32. Woo S, Jusko WJ. Interspecies comparisons of pharmacokinetics and pharmacodynamics of recombinant human erythropoietin. Drug Metab Dispos. 2007;35:1672–8.

    Article  CAS  PubMed  Google Scholar 

  33. Vugmeyster Y, Szklut P, Tchistiakova L, Abraham W, Kasaian M, Xu X. Preclinical pharmacokinetics, interspecies scaling, and tissue distribution of humanized monoclonal anti-IL-13 antibodies with different IL-13 neutralization mechanisms. Int Immunopharmacol. 2008;8:477–83.

    Article  CAS  PubMed  Google Scholar 

  34. Krzyzanski W, Jusko WJ, Wacholtz MC, Minton N, Cheung WK. Pharmacokinetic and pharmacodynamic modeling of recombinant human erythropoietin after multiple subcutaneous doses in healthy subjects. Eur J Pharm Sci. 2005;26:295–306.

    Article  CAS  PubMed  Google Scholar 

  35. Ramakrishnan R, Cheung WK, Wacholtz MC, Minton N, Jusko WJ. Pharmacokinetic and pharmacodynamic modeling of recombinant human erythropoietin after single and multiple doses in healthy volunteers. J Clin Pharmacol. 2004;44:991–1002.

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Peter Thygesen.

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Meeting Report from an expert meeting organised by COST Action B25. The workshop entitled “Physiologically-based PK/PD modelling of therapeutic macromolecules” was held in Athens, 11 December 2006. COST is the acronym for European Cooperation in the Field of Scientific and Technical Research. COST Action B25 was launched in 2005 and is entitled “Physiologically based pharmaco-/toxicokinetics and dynamics.” Invited speakers gave presentations on various aspects of physiologically-based PK/PD modelling. Members of the COST Action B25, Working group 1 were Achiel Van Peer (Belgium), Panos Macheras (Greece), Peter Thygesen (Denmark), Constantin Mircioiu (Romania), Melih Babaoglu (Turkey), Jose A. Guimares Morais (Portugal), Jean-Louis Steimer (Switzerland). The invited experts were Stefan Willmann (Bayer Technology Services, Germany), Kim Kristensen (AstraZeneca, Sweden), Ryossei Kawai (Novartis, Japan), Phil Lowe (Novartis, Switzerland), Bill Jusko (University of Buffalo, USA) and Rune Overgaard (Novo Nordisk, Denmark). Lene Alifrangis (Novo Nordisk, Denmark) participated as an observer. The aims of the workshop were i) to discuss the feasibility of physiologically-based PK/PD modelling of therapeutic macromolecules, and ii) to identify important modelling issues with respect to therapeutic macromolecules.

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Thygesen, P., Macheras, P. & Van Peer, A. Physiologically-Based PK/PD Modelling of Therapeutic Macromolecules. Pharm Res 26, 2543–2550 (2009). https://doi.org/10.1007/s11095-009-9990-3

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