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Mathematical modeling of receptor occupancy data: A valuable technology for biotherapeutic drug development
Author(s) -
Spilker Mary E.,
Singh Pratap,
Vicini Paolo
Publication year - 2016
Publication title -
cytometry part b: clinical cytometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.646
H-Index - 61
eISSN - 1552-4957
pISSN - 1552-4949
DOI - 10.1002/cyto.b.21318
Subject(s) - drug development , computer science , drug , internalization , computational biology , drug discovery , receptor , pharmacology , bioinformatics , medicine , biology
Background In drug development, in vivo assessment of target engagement provides confidence when testing the drug's mechanism of action and improves the likelihood of clinical success. For biologics, receptor occupancy (RO) determined from circulating cells can provide evidence of target engagement. Integrating this information with mathematical modeling can further enhance the understanding of drug‐target interactions and the biological factors that are critical to the successful modulation of the target and ultimately the disease state. Methods This mini‐review presents two specific types of mathematical models used to describe antibody‐receptor systems and highlights how experimental data can inform the model parameters. Simulations are used to illustrate how various mechanisms influence RO, PK and total cellular receptor profiles. Results The simulations demonstrate the effect antibody‐receptor internalization, affinity and receptor turnover have on commonly acquired data in drug development. Conclusions Integrating RO data with mathematical models such as the two presented here (target‐mediated drug disposition and site‐of‐action models) can provide a more comprehensive view of the biological system, which can be used to test hypotheses, extrapolate preclinical findings to humans and impact clinical study designs and risk assessments for the successful development of biotherapeutics. © 2015 International Clinical Cytometry Society