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.

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).

A semi-physiological model of amyloid-β 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-β (Aβ) metabolism in human cerebrospinal fluid (CSF). A semi-physiological model describing Aβ 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. Aβ biosynthesis was adequately characterized by six transit compartments.

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.

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.

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.

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.