Skip to main content
Log in

Physiologically Based Synthetic Models of Hepatic Disposition

  • Published:
Journal of Pharmacokinetics and Pharmacodynamics Aims and scope Submit manuscript

Current physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming. A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together. PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

CV:

central vein

ISL(s):

in silico liver(s)

N1, N2,...:

a set of experiments that explores sinusoidal network arrangement

PBPK:

physiologically based pharmacokinetic

PCs:

properties and characteristics

PK:

pharmacokinetic

PV:

portal vein

S1, S2,...:

a set of experiments that explores spatial relationships within and between sinusoids

S A and S B :

two classes of SS

SD:

standard deviation

SM(s):

similarity measure(s)

SS(s):

sinusoidal segment(s)

References

  1. Rowland M. (1984) Physiologic pharmacokinetic models: relevance, experience, and future trends. Drug Metab. Rev. 15:55–74

    PubMed  CAS  Google Scholar 

  2. Hung D.Y., Chang P., Weiss M., Roberts M.S. (2001) Structure-hepatic disposition relationships for cationic drugs in isolated perfused rat livers: transmembrane exchange and cytoplasmic binding process. J. Pharmacol. Exper. Therap. 297:780–89

    CAS  Google Scholar 

  3. Bassingthwaite J.B. (1970) Blood flow and diffusion through mammalian organs. Science 167:1347–53

    Article  Google Scholar 

  4. M. Rowland, L. Balant, and C. Peck. Physiologically based pharmacokinetics in drug development and regulatory science: a workshop report (Georgetown DC, May 29–30, 2002). AAPS PharmSci. 6: article 6. DOI: 10.1208/ps060106 (2004).

  5. Andersen M.E. (2003) Toxicokinetic modeling and its applications in chemical risk assessment. Toxicol. Lett. 138(1–2):9–27

    Article  PubMed  CAS  Google Scholar 

  6. Leahy D.E. (2003) Progress in simulation modelling for pharmacokinetics. Curr. Top. Med. Chem. 3:1257–68

    Article  PubMed  CAS  Google Scholar 

  7. Corley R.A., Mast T.J., Carney E.W., Rogers J.M., Daston G.P. (2003) Evaluation of physiologically based models of pregnancy and lactation for their application in children’s health risk assessments. Crit. Rev. Toxicol. 34(2):137–211

    Google Scholar 

  8. Roberts M. S., Magnusson B.M., Burczynski F.J., Weiss M. (2002) Enterohepatic circulation: physiological, pharmacokinetic and clinical implications. Clin. Pharmacokinet. 41:751–90

    Article  PubMed  CAS  Google Scholar 

  9. Roberts M.S., Anissimov Y.G. (1999) Modeling of hepatic elimination and organ distribution kinetics with the extended convection-dispersion model. J. Pharmacokin. Biopharm. 27:343–382

    Article  CAS  Google Scholar 

  10. Zeigler B.P., Praehofer H., Kim T.G. (2000) Theory of Modeling and Simulation: Discrete Event and Continuous Complex Dynamic Systems. Academic Press, California, pp. 3–36, 75–85, 99–104, 137–147.

    Google Scholar 

  11. Steels L., Brooks R. (eds). (1995) The Artificial Life Route to Artificial Intelligence. Lawrence Earlbaum Associates Inc., New Jersey, pp. 83–121

    Google Scholar 

  12. Czarnecki K., Eisenecker U. (2000) Generative Programming: Methods, Tools, and Application. Addison-Wesley, New York, pp. 10, 251–254.

    Google Scholar 

  13. G. E. Ropella, C. A. Hunt, and D. A. Nag. Using heuristic models to bridge the gap between analytic and experimental models in biology. 2005 Spring Simulation Multiconference, The Society for Modeling and Simulation International, San Diego, CA, April 2–8, 2005.

  14. G. E. Ropella, C. A. Hunt, and S. Sheikh-Bahaei. Methodological considerations of heuristic modeling of biological systems. The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Orlando, FL, July 10–13, 2005.

  15. Leahy D.E. (2003) Progress in simulation modelling for pharmacokinetics. Curr. Top. Med. Chem. 3(11):1257–1268

    Article  PubMed  CAS  Google Scholar 

  16. Teutsch H.F., Schuerfeld D., Groezinger E. (1999) Three-dimensional reconstruction of parenchymal units in the liver of the rat. Hepatology 29:494–505

    Article  PubMed  CAS  Google Scholar 

  17. Peirce S.M., van Gieson E.J., Skalak T.C. (2004) Multicellular simulation predicts patterning and in silico tissue assembly. FASEB J. 18:731–33

    PubMed  CAS  Google Scholar 

  18. An G. (2004) In-silico experiments of existing and hypothetical cytokine-directed clinical trials using agent based modeling. Crit. Care Med. 32:2050–2060

    Article  PubMed  CAS  Google Scholar 

  19. Gumucio J.J., Miller D.L. (1982) Zonal hepatic function: solute-hepatocyte interactions within the liver acinus. Prog. Liver. Diseases. 7:17–30

    CAS  Google Scholar 

  20. Kato Y., Tanaka J., Koyama K. (2001) Intralobular heterogeneity of oxidative stress and cell death in ischemia-reperfused rat liver. J. Surg. Res. 95:99–106

    Article  PubMed  CAS  Google Scholar 

  21. Scoazec J.Y., Racine L., Couvelard A., Flejou J.F., Geldmann G. (1994) Endothelial cell heterogeneity in the normal human liver acinus: in silico immunohistochemical demonstration. Liver 14:113–23

    PubMed  CAS  Google Scholar 

  22. McCuskey R.S. (2000) Morphological mechanisms for regulating blood flow through hepatic sinusoids. Liver 20:3–7

    Article  PubMed  CAS  Google Scholar 

  23. Koo A., Liang I.Y., Cheng K.K. (1975) The terminal hepatic microcirculation in the rat. Quart. J. Exp. Physiol. Cogn. Med. 60:261–266

    CAS  Google Scholar 

  24. Miller D.L., Zanolli C.S., Gumucio J.J. (1979) Quantitative morphology of the sinusoids of the hepatic acinus. Gastroenterology 76:965–969

    PubMed  CAS  Google Scholar 

  25. Cheung K., Hickman P.E., Potter J.M., Walker N., Jericho M., Haslam R., Roberts M.S. (1996) An optimised model for rat liver perfusion studies. J. Surg. Res. 66:81–89

    Article  PubMed  CAS  Google Scholar 

  26. Liu Y., Hunt C.A. (2005) Studies of intestinal drug transport using an in silico epithelio-mimetic device. Biosystems 82(2):154–167

    Article  PubMed  CAS  Google Scholar 

  27. Liu Y., Hunt C.A. (2006). Mechanistic study of the interplay of intestinal transport and metabolism using the synthetic modeling method. Pharm. Res. 23(3):493–505

    Article  PubMed  CAS  Google Scholar 

  28. S. Sheikh-Bahaei, G. E. P. Ropella, and C. A. Hunt. Agent-based simulation of in vitro hepatic drug metabolism: in silico hepatic intrinsic clearance. 2005 Spring Multiconference, The Society for Modeling and Simulation International, San Diego, CA, April 2–8, 2005.

  29. S. Sheikh-Bahaei, G. E. P. Ropella, and C. A. Hunt. In silico hepatocyte: agent-based modeling of the biliary excretion of drugs. 2006 Spring Simulation Multiconference, The Society for Modeling and Simulation International, Huntsville, AL, April 2–6, 2006.

  30. Santini S., Jain R. (1999) Similarity Measures. IEEE Trans. Pattern Anal. Mach. Intell. 21(9):871–83

    Article  Google Scholar 

  31. D. A. Nag, G. E. P. Ropella, and C. A. Hunt. Similarity measures and validation in automated modeling. Huntsville Simulation Conference, Huntsville, AL, October 25–27, 2005.

  32. Goresky C.A. (1963) A linear method for determining liver sinusoidal and extravascular volumes. Am. J. Physiol. 204:626–40

    PubMed  CAS  Google Scholar 

  33. Pang K.S., Lee W.-F., Cherry W.F., Yuen V., Accaputo J., Fayz S., Schwab A.J., Goresky C.A. (1988) Effects of perfusate flow rate on measured blood volume, Disse space, intracellular water space, and drug extraction in the perfused rat liver preparation: characterization by the multiple indicator dilution technique. J. Pharmacokinet. Biopharm. 16:595–632

    Article  PubMed  CAS  Google Scholar 

  34. Schwab A.J., Pang K.S. (1999) The multiple indicator-dilution method for the study of enzyme heterogeneity in liver: theoretical basis. Drug Metab. Dispos. 27:746–55

    PubMed  CAS  Google Scholar 

  35. Anissimov Y.G., Bracken A.J., Roberts M.S. (2002) Catheter effects in organ perfusion experiments. J. Theor. Biol. 214:263–73

    Article  PubMed  Google Scholar 

  36. Food and Drug Administration. Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products [online], < http://www.fda.gov/oc/initiatives/criticalpath/whitepaper.html > (2004).

  37. Hunt C.A., Ropella G.E.P., Roberts M.S., Yan L. (2005) Biomimetic in silico devices. Lecture Notes in Bioinformatics 3082:35–43

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. Anthony Hunt.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hunt, C.A., Ropella, G.E.P., Yan, L. et al. Physiologically Based Synthetic Models of Hepatic Disposition. J Pharmacokinet Pharmacodyn 33, 737–772 (2006). https://doi.org/10.1007/s10928-006-9031-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10928-006-9031-3

Keywords

Navigation