Development of a Predictive Pharmacokinetic Model for a Novel Cyclooxygenase-2 Inhibitor

Predictive Population Pharmacokinetic/Pharmacodynamic Model for a Novel COX-2 Inhibitor

The objectives of these analyses were to (1) develop a population pharmacokinetic/pharmacodynamic model for a novel COX-2 inhibitor (CS-706) using data from primarily Caucasian subjects, (2) predict responses in subpopulations of interest (including Japanese subjects), and (3) correlate pharmacodynamic parameters to safety outcomes. The model was developed using data from 130 healthy adults following single or multiple doses of CS-706. Serial plasma concentrations of CS-706 and ex vivo whole-blood cyclooxygenase-1 (COX-1) and COX-2 activity were determined up to 72 hours postdose. An E(max) model described relationships between CS-706 plasma concentrations and COX-1 and COX-2 inhibition. CS-706 potency (EC(50)) was 397 ng/mL for COX-1 and 20 ng/mL for COX-2. None of the tested covariates influenced the pharmacodynamics of CS-706. Japanese subjects are expected to show a slightly reduced response to CS-706, consistent with lower exposure following the same dose given to Caucasian subjects. Predictive pharmacokinetic/pharmacodynamic modeling for COX-1 and COX-2 inhibition indicates a 20-fold potency ratio that is expected to be similar in Japanese and Caucasians. There was good correlation between COX-1 inhibition and the incidence of 7-day gastroduodenal mucosal injury. A dose of less than 25 mg bid could be adequate to inhibit COX-2 activity with a low risk of gastrointestinal mucosal injury.

Pain relief model for a COX-2 inhibitor in patients with postoperative dental pain

AIM

To develop a pain relief model for a cyclooxygenase (COX)-2 inhibitor, CS-706, that permits prediction of doses for acute pain relief in Japanese and Western populations.

METHODS

A categorical response model was developed to describe the probability of pain relief (PR) over time for a Phase 2a study. Models were also developed to describe patient's use of rescue medication and onset of pain relief.

RESULTS

The placebo response was described by a first-order increase in PR that achieved a stable response after 4 h. The effect of CS-706 on PR was described using an E(max) model; the plasma concentration of CS-706 producing 50% of the maximum response was estimated to be 87 ng ml(-1), the median peak plasma concentration achieved after a 50-mg oral dose. The probability of rescue medication (REMD) decreased over time and was a function of the last observed PR score. This probability was < 16% for patients with a PR score > or =2. The probability of experiencing meaningful PR was 98% in patients who did not require REMD and 47% in those who required REMD. For patients who did not require REMD, the median onset time of meaningful pain relief (TMPR) decreased with increasing doses. In patients who required REMD, there was a saturable decline in TMPR, with the greatest improvement occurring from placebo to 50-mg doses.

CONCLUSIONS

The set of models developed permitted compilation of multiple dose-response curves for dose selection of CS-706 in Westerners and facilitated scaling of doses to a Japanese population.

A randomized, double-blind, celecoxib- and placebo-controlled study of the effectiveness of CS-706 in acute postoperative dental pain

BACKGROUND

CS-706 is a cyclooxygenase-2 (COX-2)-selective inhibitor with an in vitro selectivity ratio (COX-1:COX-2) similar to that of celecoxib. It has exhibited analgesic, anti-inflammatory, and antitumor properties in animal models.

OBJECTIVES

This study evaluated the tolerability of single doses of CS-706 and compared the analgesic efficacy of CS-706 with that of celecoxib and placebo in the dental pain model.

METHODS

This was a randomized, double-blind, double-dummy, active- and placebo-controlled study. Healthy male and female subjects with moderate to severe pain intensity (PI) after dental surgery were randomized ( approximately 50 per group) to receive a single oral dose of CS-706 10, 50, 100, or 200 mg; celecoxib 400 mg; or placebo. PI and pain relief (PR) were measured on categorical and visual analog scales through 24 hours after the dose. The primary efficacy variable was the time-weighted sum of PR scores at 4 hours after the dose (TOPAR4). The onset of analgesia was assessed by calculating the pain intensity difference (PID). Perceptible and meaningful pain relief were assessed using a 2-stopwatch method.

RESULTS

The majority of subjects were female (62.0%) and white (59.5%). Subjects' mean (SD) age was 22.6 (3.9) years, and their mean body mass index was 25.3 (5.1) kg/m(2). All doses of CS-706 were associated with significant analgesic efficacy compared with placebo based on the primary end point, TOPAR4 (P<0.001), and on all secondary end points (P<0.05, comparisons of all CS-706 doses vs placebo) with the exception of time to 100% PR for CS-706 10 mg. Single 50-, 100-, and 200-mg doses of CS-706 also were significantly more effective than celecoxib for TOPAR4 (P=0.036, P=0.004, and P=0.006, respectively). The onset of analgesia (PID >or= 1) for all CS-706 doses occurred within 1 hour after dosing (P<0.001 vs placebo). The median duration of analgesia, measured as the time to administration of rescue medication, was significantly greater for all doses of CS-706 compared with placebo (5.7 hours for CS-706 10 mg, >24 hours for CS-706 50, 100, and 200 mg, and 1.7 hours for placebo; P<0.001 for CS-706 50, 100, and 200 mg). These data suggest that once-daily administration of CS-706 may be effective in providing relief of acute pain. The incidence of adverse events was similar among all treatment groups. Adverse events occurring in >or= 5 % of subjects in any treatment group were nausea, vomiting, dry socket, dizziness, headache, and paresthesia.

CONCLUSION

Single doses of CS-706 had significant analgesic efficacy compared with celecoxib and placebo in the relief of postoperative dental pain in the healthy subjects enrolled in this study.

A randomized, double-blind, one-week study comparing effects of a novel COX-2 inhibitor and naproxen on the gastric mucosa

CS-706 is a novel cyclooxygenase-2 (COX-2) inhibitor with potent analgesic, anti-inflammatory, and antitumor properties in animal models. This one-week, multicenter study was undertaken to assess the safety and tolerability of CS-706 and to compare the effects of CS-706 versus naproxen on acute gastrointestinal (GI) mucosal injury. Healthy men and women (n=160) without evidence of underlying gastroduodenal lesions were randomized to placebo, 100 mg CS-706 once daily, 200 mg CS-706 once daily, or 500 mg naproxen twice daily, administered for 7 days. On Day 8, subjects underwent a posttreatment upper GI endoscopy to assess development of gastroduodenal petechiae, erosions, and ulcers. Inhibition of COX-1 and COX-2 activity over the 24-hr postdose interval on Day 7 was determined in 48 subjects (12 per treatment group). CS-706 was safe and well tolerated. The extent of upper GI mucosal injury for both CS-706 dose groups was statistically significantly less than that for naproxen (P < 0.001) and was similar to placebo (P=0.615 and P=0.115 for 100 and 200 mg CS-706, respectively). No subject in placebo or either CS-706 treatment group had gastroduodenal ulcers, compared with 11 (28.2%) subjects treated with naproxen (P < 0.001). Both doses of CS-706 inhibited COX-2 activity to a similar extent as naproxen, whereas neither dose of CS-706 showed meaningful inhibition of platelet COX-1. In contrast, naproxen nearly completely inhibited COX-1 over the dosing interval. We conclude that CS-706, dosed up to 200 mg once daily, has an acute, upper GI toxicity profile similar to that of placebo and significantly superior to that of naproxen.

Simulation of Correlated Continuous and Categorical Variables using a Single Multivariate Distribution

Clinical trial simulations make use of input/output models with covariate effects; the virtual patient population generated for the simulation should therefore display physiologically reasonable covariate distributions. Covariate distribution modeling is one method used to create sets of covariate values (vectors) that characterize individual virtual patients, which should be representative of real subjects participating in clinical trials. Covariates can be continuous (e.g., body weight, age) or categorical (e.g., sex, race). A modeling method commonly used for incorporating both continuous and categorical covariates, the Discrete method, requires the patient population to be divided into subgroups for each unique combination of categorical covariates, with separate multivariate functions for the continuous covariates in each subset. However, when there are multiple categorical covariates this approach can result in subgroups with very few representative patients, and thus, insufficient data to build a model that characterizes these patient groups. To resolve this limitation, an application of a statistical methodology (Continuous method) was conceived to enable sampling of complete covariate vectors, including both continuous and categorical covariates, from a single multivariate function. The Discrete and Continuous methods were compared using both simulated and real data with respect to their ability to generate virtual patient distributions that match a target population. The simulated data sets consisted of one categorical and two correlated continuous covariates. The proportion of patients in each subgroup, correlation between the continuous covariates, and ratio of the means of the continuous covariates in the subgroups were varied. During evaluation, both methods accurately generated the summary statistics and proper proportions of the target population. In general, the Continuous method performed as well as the Discrete method, except when the subgroups, defined by categorical value, had markedly different continuous covariate means, for which, in the authors' experience, there are few clinically relevant examples. The Continuous method allows analysis of the full population instead of multiple subgroups, reducing the number of analyses that must be performed, and thereby increasing efficiency. More importantly, analyzing a larger pool of data increases the precision of the covariance estimates of the covariates, thus improving the accuracy of the description of the covariate distribution in the simulated population.