Pharmaceutical Research

, Volume 25, Issue 5, pp 1023–1036 | Cite as

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

  • Li Yan
  • Glen E. P. Ropella
  • Sunwoo Park
  • Michael S. Roberts
  • C. Anthony HuntEmail author
Research Paper



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.


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.


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.

Key words

agent-based complex systems discrete event liver mechanistic modeling physiologically based predict simulation 



central vein


in silico liver(s)


molecular weight


physiologically based


physicochemical properties




portal vein

S1 and S2

two classes of SSs


standard deviation


sinusoidal segment(s)



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.

Supplementary material

11095_2007_9494_MOESM1_ESM.doc (1.5 mb)
ESM 1 (DOC 1.51 MB)


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Li Yan
    • 1
  • Glen E. P. Ropella
    • 2
  • Sunwoo Park
    • 2
  • Michael S. Roberts
    • 3
  • C. Anthony Hunt
    • 1
    • 2
    Email author
  1. 1.The UCSF/UCB Joint Graduate Group in BioengineeringUniversity of CaliforniaBerkeleyUSA
  2. 2.Department of Biopharmaceutical SciencesUniversity of CaliforniaSan FranciscoUSA
  3. 3.School of Medicine, Princess Alexandra HospitalUniversity of QueenslandQueenslandAustralia

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