Evaluation of methods for estimating time to steady state with examples from phase 1 studies.

An overview is provided of the methodologies used in determining the time to steady state for Phase 1 multiple dose studies. These methods include NOSTASOT (no-statistical-significance-of-trend), Helmert contrasts, spline (quadratic) regression, effective half life for accumulation, nonlinear mixed effects modeling, and Bayesian approach using Markov Chain Monte Carlo (MCMC) methods. For each methodology we describe its advantages and disadvantages. The first two methods do not require any distributional assumptions for the pharmacokinetic (PK) parameters and are limited to average assessment of steady state. Also spline regression which provides both average and individual assessment of time to steady state does not require any distributional assumptions for the PK parameters. On the other hand, nonlinear mixed effects modeling and Bayesian hierarchical modeling which allow for the estimation of both population and subject-specific estimates of time to steady state do require distributional assumptions on PK parameters. The current investigation presents eight case studies for which the time to steady state was assessed using the above mentioned methodologies. The time to steady state estimates obtained from nonlinear mixed effects modeling, Bayesian hierarchal approach, effective half life, and spline regression were generally similar.

Effect of sitagliptin, a dipeptidyl peptidase-4 inhibitor, on blood pressure in nondiabetic patients with mild to moderate hypertension.

The effect of sitagliptin, a dipeptidyl peptidase-4 inhibitor, on ambulatory blood pressure was assessed in nondiabetic patients with mild to moderate hypertension in a randomized, double-blind, placebo-controlled, 3-period crossover study. Nineteen patients on stable treatment with antihypertensive agent(s) received sitagliptin 100 mg b.i.d., 50 mg b.i.d., or placebo for 5 days, with at least a 7-day washout interval between periods. Twenty-four-hour ambulatory blood pressure, including systolic blood pressure, diastolic blood pressure, and mean arterial pressure, were monitored on days 1 and 5. Relative to placebo on day 1, the mean difference in 24-hour systolic blood pressure was -0.9 mm Hg (90% confidence interval: -2.9 to 1.1; P = .46) with sitagliptin 50 mg b.i.d. and -2.8 mm Hg (90% confidence interval: -4.9 to -0.8; P < .05) with 100 mg b.i.d. On day 5, the mean difference in 24-hour systolic blood pressure was -2.0 mm Hg (90% confidence interval: -3.5 to -0.4; P < .05) with 50 mg b.i.d. and -2.2 mm Hg (90% confidence interval: -3.7 to -0.6; P < .05) with 100 mg b.i.d. relative to placebo. For 24-hour diastolic blood pressure, there were no between-group differences in mean 24-hour diastolic blood pressure on day 1. On day 5, sitagliptin 50 mg and 100 mg b.i.d significantly (P < .05) lowered mean 24-hour diastolic blood pressure by -1.8 mm Hg (90% confidence interval: -2.8 to -0.8) and -1.6 mm Hg (90% confidence interval: -2.6 to -0.7), respectively, relative to placebo. Sitagliptin produced small but statistically significant reductions of 2 mm Hg to 3 mm Hg in 24-hour ambulatory blood pressure measurements acutely (day 1) and at steady state (day 5), and was generally well tolerated in nondiabetic patients with mild to moderate hypertension.