The effect of BI 409306 on heart rate in healthy volunteers: a randomised, double-blind, placebo-controlled, crossover study.

PURPOSE: The potent, selective phosphodiesterase-9A inhibitor BI 409306 may be beneficial for patients with attenuated psychosis syndrome and could prevent relapse in patients with schizophrenia. Transient BI 409306-dependent increases in heart rate (HR) demonstrated previously necessitated cardiac safety characterisation. We evaluated cardiac effects of BI 409306 in healthy volunteers during rest and exercise. METHODS: In this double-blind, three-way crossover study, volunteers received placebo, BI 409306 50 mg or 200 mg in randomised order (same treatment on Days 1 [resting] and 3 [exercise]). Cardiopulmonary exercise testing was performed twice post treatment on Day 3 of each period. BI 409306-mediated effects on placebo-corrected change from baseline in resting HR (ΔΔHR) were evaluated based on exposure-response analysis and a random coefficient model. Adverse events (AEs) were recorded. RESULTS: Overall, 19/20 volunteers completed. Resting ΔΔHR versus BI 409306 concentration yielded a slope of 0.0029 beats/min/nmol/L. At the geometric mean (gMean) maximum plasma concentration (Cmax) for BI 409306 50 and 200 mg, predicted mean (90% CI) ΔΔHRs were 0.80 (- 0.76, 2.36) and 5.46 (2.44, 8.49) beats/min, respectively. Maximum adjusted mean differences from placebo (90% CI) in resting HR for BI 409306 50 and 200 mg were 3.85 (0.73, 6.97) and 4.93 (1.69, 8.16) beats/min. Maximum differences from placebo in resting HR occurred at/near gMean Cmax and returned to baseline after approximately 4 h. The proportion of volunteers with AEs increased with BI 409306 dose. CONCLUSION: Observed hemodynamic effects following BI 409306 administration were of low amplitude, transient, and followed the pharmacokinetic profile of BI 409306.

A phase I, randomized, proof-of-clinical-mechanism study assessing the pharmacokinetics and pharmacodynamics of the oral PDE9A inhibitor BI 409306 in healthy male volunteers.

OBJECTIVE: Cyclic guanosine monophosphate (cGMP)-specific phosphodiesterase (PDE) inhibitors are hypothesized to improve cognition in schizophrenia and Alzheimer disease by increasing cGMP levels in certain brain regions. This phase I, randomized, parallel-group, double-blind, placebo-controlled study provides proof-of-mechanism evidence for BI 409306, a novel, oral PDE9A inhibitor. METHODS: In healthy males, exposure of BI 409306 (25-, 50-, 100-, and 200-mg single dose) and placebo was assessed in plasma and cerebrospinal fluid (CSF). Effect of BI 409306 on CSF cGMP levels was evaluated, and adverse events (AEs) were monitored. RESULTS: In all enrolled subjects (N = 20), plasma BI 409306 concentration increased rapidly (median tmax : 0.75-1.25 hr) followed by rapid increases in CSF (median tmax : 1.5-2.0 hr). Maximum CSF cGMP concentrations were achieved within 2 to 5 hr, declining to baseline levels 10 to 14 hr after dosing. Dose-dependent increases in plasma and CSF exposure and CSF cGMP were shown. BI 409306 was safe and well tolerated. Most AEs were mild to moderate in intensity and study procedure-related. CONCLUSIONS: BI 409306 increased rapidly in plasma and was subsequently detected in CSF, resulting in dose-dependent increases in cGMP levels in CSF. Results indicate BI 409306 efficiently crosses the blood-CSF barrier, with an acceptable level of AEs.

A semi-physiological model of amyloid-ß biosynthesis and clearance in human cerebrospinal fluid: a tool for alzheimer's disease research and drug development.

Stable isotope labeling kinetics (SILK) was successfully applied to quantify endogenous amyloid-ß (Aß) metabolism in human cerebrospinal fluid (CSF). A semi-physiological model describing Aß biosynthesis and degradation in human CSF and the impact of the γ-secretase inhibitor semagacestat should be developed and validated based on digitized data from three published SILK studies. Aß biosynthesis was adequately characterized by six transit compartments. At each transition step, a first-order degradation process was implemented. A two-compartment model best described semagacestat CSF concentration-time profiles. Semagacestat concentrations were linked to the Aß production by an inhibitory Emax model. For model validation, three individual Aß profiles from literature were successfully predicted. Model application demonstrated a 35% decreased Aß elimination rate constant in Alzheimer's disease (AD) patients. Study design optimization revealed that SILK studies could be conducted with significant less sampling points compared to the standard protocol without losing information about the Aß metabolism, if analyzed by the presented model. In conclusion, the analysis outlined the advantages and opportunities of integrating all available data and knowledge into a semi-physiological model. The model can serve as valuable tool for researchers and clinicians interested in the pathology of AD as well as in the development of new therapeutics for AD.

Approaches to handling pharmacodynamic baseline responses.

A few approaches for handling baseline responses are available for use in pharmacokinetic (PK)-pharmacodynamic (PD) analysis. They include: (method 1-B1) estimation of the typical value and interindividual variability (IIV) of baseline in the population, (B2) inclusion of the observed baseline response as a covariate acknowledging the residual variability, (B3) a more general version of B2 as it also takes the IIV of the baseline in the population into account, and (B4) normalization of all observations by the baseline value. The aim of this study was to investigate the relative performance of B1-B4. PD responses over a single dosing interval were simulated from an indirect response model in which a drug acts through stimulation or inhibition of the response according to an Emax model. The performance of B1-B4 was investigated under 22 designs, each containing 100 datasets. NONMEM VI beta was used to estimate model parameters with the FO and the FOCE method. The mean error (ME, %) and root mean squared error (RMSE, %) of the population parameter estimates were computed and used as an indicator of bias and imprecision. Absolute ME (|ME|) and RMSE from all methods were ranked within the same design, the lower the rank value the better method performance. Average rank of each method from all designs was reported. The results showed that with B1 and FOCE, the average of |ME| and RMSE across all typical individual parameters and all conditions was 5.9 and 31.8%. The average rank of |ME| for B1, B2, B3, and B4 was 3.7, 3.8, 3.3, and 5.2 for the FOCE method, and 4.6, 4.3, 4.7, and 6.4 for the FO method. The smallest imprecision was noted with the use of B1 (rank of 3.1 for FO, and 2.9 for FOCE) and increased, in order, with B3 (3.9-FO and 3.6-FOCE), B2 (4.8-FO; 4.7-FOCE), and B4 (6.4-FO; 6.5-FOCE). We conclude that when considering both bias and imprecision B1 was slightly better than B3 which in turn was better than B2. Differences between these methods were small. B4 was clearly inferior. The FOCE method led to a smaller bias, but no marked reduction in imprecision of parameter estimates compared to the FO method.

A Bayesian approach for population pharmacokinetic modelling of sirolimus.

AIMS: To explore a Bayesian approach for the pharmacokinetic analysis of sirolimus concentration data arising from therapeutic drug monitoring (poorly informative concentration-time point design), and to explore possible covariate relationships for sirolimus pharmacokinetics. METHODS: Sirolimus concentration-time data were available as part of routine clinical care from 25 kidney transplant recipients. Most samples were taken at or near the trough time point at steady state. The data were analyzed using a fully conditional Bayesian approach with PKBUGS (v 1.1)/WinBUGS (v 1.3). Features of the data included noncompliance and missing concentration measurements below the limit of sensitivity of the assay. Informative priors were used. RESULTS: A two-compartment model with proportional residual error provided the best fit to the data (consisting of 315 sirolimus concentration-time points). The typical value for the apparent clearance (CL/F ) was 12.5 l h(-1) at the median age of 44 years. Apparent CL was found to be inversely related to age with a posterior probability of a clinically significant effect of 0.734. CONCLUSIONS: A population pharmacokinetic model was developed for sirolimus using a novel approach. Bayesian modelling with informative priors allowed interpretation of a significant covariate relationship, even using poorly informative data.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients.

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).