Integrating experimentation and quantitative modeling to enhance discovery of Beta amyloid lowering therapeutics for Alzheimer's disease.

ABSTRACT

Drug discovery can benefit from a proactive-knowledge-attainment philosophy which strategically integrates experimentation and pharmacokinetic/pharmacodynamic (PK/PD) modeling. Our programs for Alzheimer's disease (AD) illustrate such an approach. Compounds that inhibit the generation of brain beta amyloid (Aß), especially Aß42, are being pursued as potential disease-modifying therapeutics. Complexities in the PK/Aß relationship for these compounds have been observed and the data require an advanced approach for analysis. We established a semimechanistic PK/PD model that can describe the PK/Aß data by accounting for Aß generation and clearance. The modeling characterizes the in vivo PD (i.e., Aß lowering) properties of compounds and generates insights about the salient biological systems. The learning from the modeling enables us to establish a framework for predicting in vivo Aß lowering from in vitro parameters.