Background

A variety of approaches can be taken to incorporate greater mechanistic understanding into PK/PD models, including a variety of bottom-up, middle-out, and top-down approaches. The osteoporosis field is rich with examples of various types, including several bottom-up examples that take advantage of systems biology methods and detailed biological interplay of various signaling pathways which are thought to mediate coupling of bone resorption and formation processes [1, 2]. However, application of these approaches requires assumptions about the quantitative interpretation of biomarkers often identified through qualitative associations in experimental data and additional assumptions regarding the applicability of relationships associated with other classes of anti-osteoporosis agents. Thus, such approaches may be sub-optimal for identifying which mechanism may be key or rate limiting to understanding response for a novel compound or class. For odanacatib (ODN) and the cathepsin K inhibitor class, drug effects on bone formation are unclear, with conflicting data prompting concerns that the traditional formation biomarkers (BSAP and P1NP) may not be quantitatively predictive of the true bone formation rate. For this reason, a top-down, semi-mechanistic approach was taken to model development which combined mechanistic and empirical strategies. Mechanistic model terms were incorporated early to capture well-understood phenomena that are likely to be highly influential. Empirical model terms were subsequently incorporated to capture less-understood aspects by finding functional forms that reproduce patterns seen in the observed data.

American Conference on Pharmacometrics (ACoP), San Diego, California, April 2011

By Julie A. Stone , Stefan Zajic , David Jaworowicz , Albert Leung , Le Thi Duong , Julie Passarell , Jill Fiedler-Kelly, Dosinda Cohn , Nadia Verbruggen , and Aubrey Stoch