Assessment of Azeliragon QTc Liability Through Integrated, Model-Based Concentration QTc Analysis.

Azeliragon is an inhibitor of the receptor for advanced glycation end products being developed for the treatment of Alzheimer's disease. The objective of the current analysis was to evaluate the relationship between plasma azeliragon concentrations and QT interval. Simultaneous QT values and plasma concentrations were available from 711 subjects (6236 records), pooled from 5 studies in healthy volunteers, 2 studies in patients with mild to moderate Alzheimer's disease, and 1 study in patients with type 2 diabetes and persistent albuminuria. Nonlinear mixed-effects modeling was conducted to describe azeliragon concentration-related changes in QT interval, after correcting for heart rate, using Fridericia's criteria (QTcF) and sex-related differences in baseline QTcF. Azeliragon-related changes in QTcF were predicted using 2 methods: simulation and bias-corrected 90% confidence interval approaches. A small positive relationship between azeliragon plasma concentration and QTcF was noted with a slope of 0.059 ms/ng/mL. Simulations predicted mean (90% prediction interval) changes in QTcF of 0.733 milliseconds (0.32-1.66 milliseconds) with the phase 3 dose (5 mg once daily steady state) and 4.32 milliseconds (1.7-8.74 milliseconds) at supratherapeutic doses (20 mg once daily steady state or 60 mg once daily × 6 days). Bias-corrected upper 90% confidence intervals for therapeutic and supratherapeutic doses were 0.88 and 5.01 milliseconds, respectively. Model-based analysis showed a small, nonclinically meaningful, positive relationship between azeliragon plasma concentration and QTcF with a slope close to zero. Neither the prediction interval nor the upper bound of the 90% confidence interval reached 10 milliseconds, demonstrating no clinically meaningful drug-related effect on QTcF at expected therapeutic and supratherapeutic doses of azeliragon.

Retrospective evaluation of commonly used equations to predict energy expenditure in mechanically ventilated, critically ill patients.

STUDY OBJECTIVE: To determine which of four commonly used equations to estimate energy expenditure is precise and unbiased compared with energy expenditure as measured by indirect calorimetry. DESIGN: Retrospective, observational study. SETTING: Adult medical intensive care unit in a research hospital of the National Institutes of Health Clinical Center. PATIENTS: Seventy-six adult, mechanically ventilated, critically ill patients. INTERVENTION: Indirect calorimetry reports generated by the National Institutes of Health Critical Care Medicine Department's Metabolic Cart Consult Service were reviewed. Bias and precision of resting energy expenditure (REE) estimated by equations were computed using mean prediction error (ME) and root mean squared prediction error (MSE). Equations were considered precise if the 95% confidence interval for MSE was within 15% of the measured energy expenditure (MEE) determined by indirect calorimetry. Equations were considered unbiased if the 95% confidence interval for ME included zero. Paired t tests were used to compare estimated REE values for each predictive equation with MEE values determined by indirect calorimetry. Data were stratified into regions of bias using classification and regression tree analysis, as well as visual inspection of estimated REE-versus-MEE curves for each equation. MEASUREMENTS AND MAIN RESULTS: The Harris-Benedict equation multiplied by an activity factor of 1.2 was unbiased and precise. The Ireton-Jones equation was precise but biased. The American College of Chest Physicians' consensus recommendation was biased and imprecise. The Harris-Benedict equation without an activity factor also demonstrated bias and imprecision. CONCLUSIONS: The Harris-Benedict equation multiplied by an activity factor of 1.2 is suitable for predicting REE and may be used in the absence of indirect calorimetry.