title: Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity.
abstract: Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients.
authors.affiliation: a Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics , College of Pharmacy, University of Florida , Orlando , FL , USA.
authors.forename: Sihem
authors.initials: S
authors.lastname: Ait-Oudhia
authors.affiliation: b Department of Pharmaceutical Sciences , University at Buffalo, State University of New York , Buffalo , NY , USA.
authors.forename: Meric Ayse
authors.initials: MA
authors.lastname: Ovacik
authors.affiliation: b Department of Pharmaceutical Sciences , University at Buffalo, State University of New York , Buffalo , NY , USA.
authors.forename: Donald E
authors.initials: DE
authors.lastname: Mager
mesh_terms: D000818:Animals; D006801:Humans; D018796:Immunoconjugates / Q000493:pharmacokinetics*; D008962:Models, Theoretical; D049490:Systems Biology / Q000379:methods*
chemical_list: D018796:Immunoconjugates
keywords: Boolean network analysis; In vitro cell-based models; In vivo physiologically-based pharmacokinetic models; mechanistic pharmacodynamic models; target mediated drug disposition; translational systems pharmacology