A Randomized, Double-Blind, Placebo- and Positive-Controlled, Three-Way Crossover Study in Healthy Participants to Investigate the Effect of Savolitinib on the QTc Interval.

Savolitinib (AZD6094, HMPL-504, volitinib) is an oral, bioavailable, selective MET-tyrosine kinase inhibitor. This randomized, double-blind, 3-way, crossover phase 1 study of savolitinib versus moxifloxacin (positive control) and placebo-evaluated effects on the QT interval after a single savolitinib dose. Healthy non-Japanese men were randomized to 1 of 6 treatment sequences, receiving single doses of savolitinib 600 mg, moxifloxacin 400 mg, and placebo. The primary end point was time-matched, placebo-adjusted change from baseline in the QT interval corrected for the time between corresponding points on 2 consecutive R waves on electrocardiogram (RR) by the Fridericia formula (ΔΔQTcF). Secondary end points included 12-lead electrocardiogram (ECG) variables, pharmacokinetics, and safety. All 3 treatment periods were completed by 44 of 45 participants (98%). Baseline demographics were balanced across treatment groups. After a single savolitinib 600-mg dose, the highest least-squares mean ΔΔQTcF of 12 milliseconds was observed 5 hours postdose. Upper limits of the 2-sided 90% confidence interval for ΔΔQTcF exceeded 10 milliseconds (the prespecified International Council for Harmonisation limit) 3-6 hours postsavolitinib but otherwise remained less than the threshold. Savolitinib showed no additional effect on PR, QRS, QT, or RR intervals. A positive ΔΔQTcF signal from the moxifloxacin group confirmed study validity. Savolitinib was well tolerated, with a low incidence of adverse events. In this thorough QT/QTc study, QTcF prolongation was observed with a single savolitinib 600-mg dose. ECG monitoring will be implemented in ongoing and future studies of savolitinib to assess the clinical relevance of the observed QT changes from this study.

Repeatability of dose painting by numbers treatment planning in prostate cancer radiotherapy based on multiparametric magnetic resonance imaging.

Dose painting by numbers (DPBN) refers to a voxel-wise prescription of radiation dose modelled from functional image characteristics, in contrast to dose painting by contours which requires delineations to define the target for dose escalation. The direct relation between functional imaging characteristics and DPBN implies that random variations in images may propagate into the dose distribution. The stability of MR-only prostate cancer treatment planning based on DPBN with respect to these variations is as yet unknown. We conducted a test-retest study to investigate the stability of DPBN for prostate cancer in a semi-automated MR-only treatment planning workflow. Twelve patients received a multiparametric MRI on two separate days prior to prostatectomy. The tumor probability (TP) within the prostate was derived from image features with a logistic regression model. Dose mapping functions were applied to acquire a DPBN prescription map that served to generate an intensity modulated radiation therapy (IMRT) treatment plan. Dose calculations were done on a pseudo-CT derived from the MRI. The TP and DPBN map and the IMRT dose distribution were compared between both MRI sessions, using the intraclass correlation coefficient (ICC) to quantify repeatability of the planning pipeline. The quality of each treatment plan was measured with a quality factor (QF). Median ICC values for the TP and DPBN map and the IMRT dose distribution were 0.82, 0.82 and 0.88, respectively, for linear dose mapping and 0.82, 0.84 and 0.94 for square root dose mapping. A median QF of 3.4% was found among all treatment plans. We demonstrated the stability of DPBN radiotherapy treatment planning in prostate cancer, with excellent overall repeatability and acceptable treatment plan quality. Using validated tumor probability modelling and simple dose mapping techniques it was shown that despite day-to-day variations in imaging data still consistent treatment plans were obtained.

Evaluation of the Effect of Selumetinib on Cardiac Repolarization: A Randomized, Placebo- and Positive-controlled Crossover QT/QTc Study in Healthy Subjects.

PURPOSE: Selumetinib (AZD6244, ARRY-142886) is an oral, potent, and selective allosteric mitogen-activated protein kinase 1/2 inhibitor with a short t1/2. The purpose of this study was to characterize the effect of selumetinib on cardiac repolarization and a potential exposure-QT effect relationship. METHODS: A double-blind (selumetinib), randomized, 3-period crossover study was conducted to assess the effects of a single oral dose of selumetinib (75 mg) on the QTc interval compared with placebo, using moxifloxacin as an open-label positive control, in healthy male subjects aged 18 to 45 years. QT intervals were evaluated by using the Fridericia formula (QTcF) and the Bazett formula. Further analysis was conducted by using nonlinear mixed effects modeling to characterize any relationship between selumetinib exposure and QTc and was used to predict the effect if selumetinib 150 mg was administered. All adverse events were characterized and recorded. FINDINGS: A total of 54 healthy male subjects were enrolled, and 48 completed all treatments. Mean age was 27 years; four subjects were of Hispanic or Latino ethnicity, and 53.7% were White and 46.3% were Black. The BMI of subjects ranged from 19.4 to 29.6 kg/m2. After a single oral dose of selumetinib 75 mg, the highest upper bound of the 2-sided 90% CI for placebo-corrected, baseline-adjusted QTcF (ΔΔQTcF) over the 24-hour postdose measurement interval was 2.5 milliseconds, which was well below the 10-millisecond upper bound for concluding no effect. The relationship between ΔΔQTcF and selumetinib concentrations was adequately described by using a nonlinear mixed effect model. The mean estimated ∆∆QTcF interval prolongation based on the geometric mean Cmax of 75 mg selumetinib was 2.38 milliseconds (90% CI, 1.25 to 3.52), which was in good agreement with the statistical analysis results. The model also predicted mean ∆∆QTcF interval prolongations of 4.70 milliseconds (90% CI, 2.46 to 6.95) after a single supratherapeutic dose of selumetinib 150 mg, indicating the upper bound of 2-sided 90% CIs for ΔΔQTcF are predicted to be <10 milliseconds. Selumetinib, administered as a single 75 mg oral dose, was generally safe and well tolerated. IMPLICATIONS: Selumetinib 75 mg did not cause any QT/QTc interval prolongation in these healthy subjects, and selumetinib is not expected to have a clinically relevant effect on cardiac repolarization in patients at the anticipated therapeutic dose of 75 mg. The model also demonstrated the low potential for any QTc effects of selumetinib at doses higher than the standard therapeutic dose.

Prediction and modeling of effects on the QTc interval for clinical safety margin assessment, based on single-ascending-dose study data with AZD3839.

Corrected QT interval (QTc) prolongation in humans is usually predictable based on results from preclinical findings. This study confirms the signal from preclinical cardiac repolarization models (human ether-a-go-go-related gene, guinea pig monophasic action potential, and dog telemetry) on the clinical effects on the QTc interval. A thorough QT/QTc study is generally required for bioavailable pharmaceutical compounds to determine whether or not a drug shows a QTc effect above a threshold of regulatory interest. However, as demonstrated in this AZD3839 [(S)-1-(2-(difluoromethyl)pyridin-4-yl)-4-fluoro-1-(3-(pyrimidin-5-yl)phenyl)-1H-isoindol-3-amine hemifumarate] single-ascending-dose (SAD) study, high-resolution digital electrocardiogram data, in combination with adequate efficacy biomarker and pharmacokinetic data and nonlinear mixed effects modeling, can provide the basis to safely explore the margins to allow for robust modeling of clinical effect versus the electrophysiological risk marker. We also conclude that a carefully conducted SAD study may provide reliable data for effective early strategic decision making ahead of the thorough QT/QTc study.

Early clinical development: evaluation of drug-induced torsades de pointes risk.

Drug-induced arrhythmias or QT interval prolongation is one of the two most common reasons for drugs to be denied regulatory approval or to have warnings imposed on their clinical labelling. The assessment of torsades de pointes (TdP) risk during clinical development of a new pharmaceutical compound has been an issue of debate since the original description of drug-induced proarrhythmia. TdP risk assessment is complicated by the very low incidence (e.g., <1/100,000 patient years of exposure) of clinical events for non-antiarrhythmic agents and thus the improbable likelihood of observing even one event during clinical development. Thus surrogate methods of determining risk are necessary. A clinical approach to the issue of TdP risk assessment during drug development has been developed and implemented internationally. These efforts have markedly reduced the likelihood that drugs with unknown TdP risks will be commercialized, have resulted in fostering extensive productive pre-clinical and clinical research, and subsequent improved understanding of drug-induced proarrhythmia. Current research efforts are directed to increasing the efficiency of clinical QT assessment and the impact of pre-clinical assessment on clinical development. This article describes the clinical evaluation of TdP risk during drug development and how pre-clinical assessment can impact the early clinical development TdP risk assessment.

Robust pose estimation and recognition using non-gaussian modeling of appearance subspaces.

We present an original appearance model that generalizes the usual Gaussian visual subspace model to non-Gaussian and nonparametric distributions. It can be useful for the modeling and recognition of images under difficult conditions such as large occlusions and cluttered backgrounds. Inference under the model is efficiently solved using the mean shift algorithm.

On the modeling, construction, and evaluation of a probabilistic atlas of brain perfusion.

To detect subtle, abnormal perfusion patterns in brain single photon emission computer tomography (SPECT) images, it is necessary to develop quantitative methods in which computer-aided statistical analysis takes advantage of information present in databases of normal subjects. The purpose of this study was to evaluate and examine aspects of the creation and the modeling power of three statistical models for representing brain perfusion as observed in ECD-SPECT. The first model is a local model of voxel-by-voxel mean and variance. The second model is a PCA-based global model that accounts for covariance patterns in the images. The third model is an original model that is a non-linear extension to the second model. This model is based on robust statistics for modeling abnormalities. To evaluate the models, a leave-one-out procedure combined with simulations of abnormal perfusion patterns was adopted. Abnormal perfusion patterns were simulated at different locations in the brain, with different intensities and different sizes. The procedure yields receiver operator characteristics (ROC) that present a combined measure of model-fit and model-sensitivity at detecting abnormalities. The scheme can further be used to compare models as well as the influence of different preprocessing steps. In particular, the influence of different registration approaches is studied and analyzed. The results show that the original non-linear model always performed better than the other models. Finally, location-dependent detection performance was found. Most notably, a higher variation of perfusion was observed in the right frontal cortex than in the other locations studied.