Virtual Experiments Enable Exploring and Challenging Explanatory Mechanisms of Immune-Mediated P450 Down-Regulation

Brenden K Petersen1, Glen E P Ropella2, C Anthony Hunt1,3

  • 1UCSF/UCB Joint Graduate Group in Bioengineering, University of California, Berkeley, California, United States of America.

Plos One
|May 27, 2016
PubMed

Insights

Inflammation reduces drug metabolism by lowering cytochrome P450. Computational models simulating immune responses and P450 regulation offer new insights into drug interactions during disease.

Area of Science:

  • Pharmacology and Toxicology
  • Computational Biology
  • Immunology

Background:

  • Hepatic cytochrome P450 (P450) enzymes are crucial for drug metabolism.
  • Inflammatory disease states often lead to P450 down-regulation, impacting drug efficacy and safety.
  • Current understanding of P450 regulation by the immune system relies on traditional experimental methods.

Purpose of the Study:

  • To develop and validate computational models for simulating immune system influence on hepatic P450 regulation.
  • To investigate the mechanisms by which inflammatory cytokines down-regulate P450 expression and drug metabolism.
  • To create a virtual experimental platform for exploring drug-metabolism interactions in silico.

Main Methods:

  • Development of agent-based computational models of hepatocytes and liver.
  • Instantiation of a model simulating lipopolysaccharide-induced down-regulation of P450 via Kupffer cells and cytokines.
  • Validation of model predictions against in vitro and in vivo experimental data, including dose-response, time-course, and drug clearance studies.

Main Results:

  • The computational model successfully replicated P450 down-regulation in response to inflammatory stimuli.
  • Model predictions aligned with experimental data for cytokine dose-response and P450 time-course changes.
  • Simulated drug clearance for acetaminophen, antipyrine, and chlorzoxazone validated the model's predictive capacity.

Conclusions:

  • Computational modeling provides a powerful tool for understanding complex immune-drug metabolism interactions.
  • Iterative model refinement through validation yields mechanistic insights into P450 regulation.
  • These virtual systems offer actionable insights for anticipating individual drug responses in disease states.