The presenter of this webinar, Wilhelm Huisinga, Ph.D., received his doctoral degree in mathematics on mathematical concepts of conformation analysis of bio-molecules from the Department of Mathematics and Computer Science at Freie Universität Berlin and has serves as a professor of Mathematical Modelling and Systems Biology at the Institute of Mathematics.
Monoclonal antibodies, which are biotechnologically engineered proteins, have demonstrated their potential in therapies for cancer and other complex diseases. These antibodies have the ability to specifically bind targets, which means they are able to modify specific cellular targets and signaling pathways. Currently, there are various therapeutic proteins on the market that use their binding specificity to inhibit cell surface receptors with critical biologic function. At the same time, many targeted receptor systems also constitute a degradation mechanism for such drugs because binding leads to endocytosis and ultimately degradation of the drug. However, a thorough understanding of the complex interplay between a drug’s pharmacokinetics and its effect is largely missing.
Cell-level kinetic models for therapeutically relevant processes increasingly benefit the early stages of drug development. In later stages of the drug development process, however, such information about the dynamics of the targeted system is typically discarded, when simple compartment models are used to analyze preclinical or clinical in vivo data, e.g., to guide dose finding. This is particularly critical for therapeutic antibodies, where drug effect and pharmacokinetics are inherently interdependent.
The upcoming AAPS webinar, Integrating System Biology Models of Cellular Response into Simple Pharmacokinetic Compartment Models to Predict the F(ab)-mediated Effect of Monoclonal Antibodies In Vivo, will present a systematic approach to integrate cell-level kinetic models into compartment models of drug pharmacokinetics. This approach will be illustrated by analyzing the F(ab)-mediated inhibitory effect of therapeutic monoclonal antibodies targeting the epidermal growth factor receptor (EGFR). The cell-level PK/PD model integrates in vitro determined parameters for the EGFR system into the analysis of pharmacokinetic in vivo data in cynomolgus monkeys. This allows for individualized predictions by incorporating covariates, e.g., on the genetic level discriminating different types of tumor cells. They have investigated in silico the impact of biochemical properties of anti-EGFR antibodies on the F(ab)-mediated inhibitory effect. Model analysis yields that the F(ab)-mediated inhibitory effect saturates with increasing drug-receptor affinity. This suggests that observed differences in the therapeutic effects of high affinity antibodies on the market and in clinical development may result from Fc-mediated indirect mechanisms such as antibody-dependent cell cytotoxicity. This new kind of model allows us to identify in silico opportunities and limitations for the optimization of biophysical properties of future therapeutic antibodies.