Integrated PK-PD and agent-based modeling in oncology

Zhihui Wang, Joseph D. Butner, Vittorio Cristini, Thomas S. Deisboeck

Research output: Contribution to journalReview article

41 Scopus citations

Abstract

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

Original languageEnglish (US)
Pages (from-to)179-189
Number of pages11
JournalJournal of Pharmacokinetics and Pharmacodynamics
Volume42
Issue number2
DOIs
StatePublished - Mar 11 2015

Keywords

  • Chemotherapy
  • Computer simulation
  • Mathematical modeling
  • Multiscale
  • Translational research
  • Tumor growth and invasion

ASJC Scopus subject areas

  • Pharmacology

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