Skip to main content
SpringerLink
Log in

Modeling and Simulation of Hepatic Drug Disposition Using a Physiologically Based, Multi-agent In Silico Liver

  • Research Paper
  • Published:
Pharmaceutical Research Aims and scope Submit manuscript

Abstract

Purpose

Validate a physiologically based, mechanistic, in silico liver (ISL) for studying the hepatic disposition and metabolism of antipyrine, atenolol, labetalol, diltiazem, and sucrose administered alone or in combination.

Materials and Methods

Autonomous software objects representing hepatic components such as metabolic enzymes, cells, and microarchitectural details were plugged together to form a functioning liver analogue. Microarchitecture features were represented separately from drug metabolizing functions. Each ISL component interacts uniquely with mobile objects. Outflow profiles were recorded and compared to wet-lab data. A single ISL structure was selected, parameterized, and held constant for all compounds. Parameters sensitive to drug-specific physicochemical properties were tuned so that ISL outflow profiles matched in situ outflow profiles.

Results

ISL simulations were validated separately and together against in situ data and prior physiologically based pharmacokinetic (PBPK) predictions. The consequences of ISL parameter changes on outflow profiles were explored. Selected changes altered outflow profiles in ways consistent with knowledge of hepatic anatomy and physiology and drug physicochemical properties.

Conclusions

A synthetic, agent-oriented in silico liver has been developed and successfully validated, enabling us to posit that static and dynamic ISL mechanistic details, although abstract, map realistically to hepatic mechanistic details in PBPK simulations.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

CV:

central vein

ISL(s):

in silico liver(s)

MW:

molecular weight

PB:

physiologically based

PCPs:

physicochemical properties

PK:

pharmacokinetic

PV:

portal vein

S1 and S2 :

two classes of SSs

SD:

standard deviation

SS(s):

sinusoidal segment(s)

References

  1. M. Rowland, L. Balant, and C. Peck. Physiologically based pharmacokinetics in drug development and regulatory science: a workshop report (Georgetown University, Washington, DC, May 29–30, 2002). AAPS PharmSci 6:E6(2004).

    Article  PubMed  Google Scholar 

  2. C. A. Hunt, G. E. Ropella, L. Yan, D. Y. Hung, and M. S. Roberts. Physiologically based synthetic models of hepatic disposition. J. Pharmacokinet. Pharmacodyn 33:737–772 (2006).

    Article  PubMed  Google Scholar 

  3. Y. G. Anissimov, and M. S. Roberts. A compartmental model of hepatic disposition kinetics: 1. Model development and application to linear kinetics. J. Pharmacokinet. Pharmacodyn. 29:131–156 (2002).

    Article  PubMed  CAS  Google Scholar 

  4. D. Y. Hung, P. Chang, K. Cheung, B. McWhinney, P. P. Masci, M. Weiss, and M. S. Roberts. Cationic drug pharmacokinetics in diseased livers determined by fibrosis index, hepatic protein content, microsomal activity, and nature of drug. J. Pharmacol. Exp. Ther 301:1079–1087 (2002).

    Article  PubMed  CAS  Google Scholar 

  5. D. Y. Hung, P. Chang, M. Weiss, and M. S. Roberts. Structure-hepatic disposition relationships for cationic drugs in isolated perfused rat livers: transmembrane exchange and cytoplasmic binding process. J. Pharmacol. Exp. Ther 297:780–789 (2001).

    PubMed  CAS  Google Scholar 

  6. L. Liu, and K. S. Pang. An integrated approach to model hepatic drug clearance. Eur. J. Pharm. Sci 29:215–230 (2006).

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  8. G. A. Siebert, D. Y. Hung, P. Chang, and M. S. Roberts. Ion-trapping, microsomal binding, and unbound drug distribution in the hepatic retention of basic drugs. J. Pharmacol. Exp. Ther 308:228–235 (2004).

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  11. S. Sheikh-Bahaei and C. A. Hunt. Prediction of in vitro hepatic biliary excretion using stochastic agent-based modeling and fuzzy clustering. In L. F. Perrone and et al. (eds.), Proceedings of the 37th conference on Winter simulation, Monterey, CA, 2006, pp. 1617–1624.

  12. H. Steen, R. Oosting, and D. K. Meijer. Mechanisms for the uptake of cationic drugs by the liver: a study with tributylmethylammonium (TBuMA). J. Pharmacol. Exp. Ther 258:537–543 (1991).

    PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  15. D. L. Miller, C. S. Zanolli, and J. J. Gumucio. Quantitative morphology of the sinusoids of the hepatic acinus. Quantimet analysis of rat liver. Gastroenterology 76:965–969 (1979).

    PubMed  CAS  Google Scholar 

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

    PubMed  CAS  Google Scholar 

  17. L. X. Garmire, D. G. Garmire, and C. A. Hunt. An in silico transwell device for the study of drug transport and drug–drug interactions. Pharm Res 24:2171–2186.

  18. S. Sheikh-Bahaei, G. E. P. Ropella, and C. A. Hunt. In silico hepatocyte: agent-based modeling of the biliary excretion of drugs in vitro. In L. Yilmaz et al (eds.), Proceedings of the Agent-Directed Simulation Symposium of the Spring Simulation Multiconference (SMC'06), SCS Press, San Diego, CA, 2006, pp. 157–163.

    Google Scholar 

  19. G. E. Ropella, C. A. Hunt, and D. A. Nag. Using heuristic models to bridge the gap between analytic and experimental models in biology. In L. Yilmaz (ed), Proc 2005 Agent-Direc Simul Symp (ADS'05), Simulation Series, Vol. 37, SCS Press, San Diego, CA, 2005, pp. 182–190.

  20. G. E. Ropella, C. A. Hunt, and S. Sheikh-Bahaei. Methodological Considerations of Heuristic Modeling of Biological Systems, Proc 9th World Multi-Conf Systemics, Cybernetics and Informatics, Orlando, Florida, 2005.

Download references

Acknowledgements

This research was funded in part by grants (to CAH) and Fellowships (to LY and SP) provided by the CDH Research Foundation and the Australian NHMRC (MSR). We thank G. Cosmo Haun for developing the visualizations, Teddy Lam for hepatic clearance and PK discussions, Shahab Sheikh-Bahaei for manuscript review, Pearl Johnson for the support provided to LY, and Laura Veit for manuscript assistance. We also thank the other members of the BioSystems Group for helpful discussion and commentary. The work was abstracted in part from the PhD dissertation presented by LY to the Graduate Division, University of California, Berkeley, CA.

Author information

Authors and Affiliations

  1. The UCSF/UCB Joint Graduate Group in Bioengineering, University of California, Berkeley, California, 94720, USA

    Li Yan & C. Anthony Hunt

  2. Department of Biopharmaceutical Sciences, University of California, 513 Parnassus Ave., S-926, San Francisco, California, 94143-0446, USA

    Glen E. P. Ropella, Sunwoo Park & C. Anthony Hunt

  3. School of Medicine, Princess Alexandra Hospital, University of Queensland, Woolloongabba, Queensland, 4102, Australia

    Michael S. Roberts

Authors
  1. Li Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Glen E. P. Ropella
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sunwoo Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael S. Roberts
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. C. Anthony Hunt
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. Anthony Hunt.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOC 1.51 MB)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yan, L., Ropella, G.E.P., Park, S. et al. Modeling and Simulation of Hepatic Drug Disposition Using a Physiologically Based, Multi-agent In Silico Liver. Pharm Res 25, 1023–1036 (2008). https://doi.org/10.1007/s11095-007-9494-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11095-007-9494-y

Key words

Search

Navigation