Feedback Control Indirect Response Models

Abstract

Most physiological processes are subject to feedback regulation . We hypothesize that PK/PD models that do not appropriately incorporate known autoregulatory mechanisms are incomplete representations of the drug-response relationship, and may lead to an underestimation of a drug’s potency. In this chapter, a new general framework is introduced for modeling pharmacodynamic processes that are subject to autoregulation , in which the canonical IDR models of Jusko are extended to incorporate the time-course of the difference between the pharmacodynamic response and its basal value (the error signal). Following the well-established approach of traditional engineering control theory, the proposed feedback control indirect response (FC IDR) models include linear combinations of terms proportional to the error signal itself, the integral of the error signal, and the derivative of the error signal. Model equations are derived and simulations are conducted to illustrate the characteristic behaviors of FC IDR models. It is demonstrated that ignoring the contributions of feedback control mechanisms in PD studies would lead to the underestimation of drug potency. Four examples were selected from literature to illustrate the broad application of the FC IDR framework. The similarities and differences of this proposed framework and two alternate approaches that also include feedback are further discussed. The FC IDR modeling framework allows the drug’s effects to be quantified independently of the autoregulatory mechanisms that also act on the controlled variables. It addresses the difficulties long-recognized by systems physiologists in understanding the mechanisms of drug action that underlie processes subject to feedback regulation, and may provide a bridge for development of more mechanistic systems pharmacology models.