Accelerating drug development using biomarkers: a case study with sitagliptin, a novel DPP4 inhibitor for type 2 diabetes

Abstract

The leveraged use of biomarkers presents an opportunity in understanding target engagement and disease impact while accelerating drug development. For effective integration in drug development, it is essential for biomarkers to aid in the elucidation of mechanisms of action and disease progression. The recent years have witnessed significant progress in biomarker selection, validation, and qualification, while enabling surrogate and clinical endpoint qualification and application. Biomarkers play a central role in target validation for novel mechanisms. They also play a central role in the learning/confirming paradigm, particularly when utilized in concert with pharmacokinetic/pharmacodynamic modeling. Clearly, these attributes make biomarker integration attractive for scientific and regulatory applications to new drug development. In this review, applications of proximal, or target engagement, and distal, or disease-related, biomarkers are highlighted using the example of the recent development of sitagliptin for type 2 diabetes, wherein elucidation of target engagement and disease-related biomarkers significantly accelerated sitagliptin drug development. Importantly, use of biomarkers as tools facilitated design of clinical efficacy trials while streamlining dose focus and optimization, the net impact of which reduced overall cycle time to filing as compared to the industry average.

Fig. 1

An idealized model for biomarkers, illustrating proximal or target engagement and distal or disease-related attributes

Fig. 2

Target engagement (DPP4, GLP) and distal (insulin, glucose, glucagon) biomarkers for glucose control via the DPP4 pathway

Fig. 3

Time course of inhibition of plasma DPP4 activity after administration of placebo (open circles) or single oral doses of sitagliptin—1.5 (solid circles), 12.5 (open squares), 50 (solid squares), and 200 (open triangles) mg (A) and 5 (solid circles), 25 (fed [solid squares] and fasted [open squares]), and 100 (open triangles) mg (B) to healthy, young male subjects. [Reprinted with permission from Macmillan Publishers Ltd: Clinical Pharmacology and Therapeutics (78(6), copyright Dec 2005]

Fig. 4

Plasma glucose (a), serum insulin (b), serum C-peptide (c), and plasma glucagon (d) concentrations after administration of single oral doses of sitagliptin 25 (white circles) or 200 mg (black triangles) or placebo (black circles) and an OGTT at 2 h postdose. Plasma glucose concentrations are also displayed for the 2 h after a standardized meal at 6 h postdose and an OGTT at 24 h postdose. Data are expressed as geometric mean ± SE. [Reprinted with permission from The Journal of Clinical Endocrinology & Metabolism Vol. 91, No. 11 4612–4619, Copyright 2006, The Endocrine Society]

Fig. 5

Effect of sitagliptin (25, 50, 100, 200, 400, and 600 mg once daily and 300 mg twice daily) or placebo on geometric mean of weighted average active GLP-1 concentrations through 2 h following standardized meals at 4, 10, and 24 h postdose in healthy male subjects. [Reprinted from Clinical Therapeutics, 28(1), Jan 2006, pages 55–72, copyright (2006), with permission from Excerpta Medica, Inc.]