Hitesh Mistry

A new classifier-based strategy for in-silico ion-channel cardiac drug safety assessment.

There is currently a strong interest in using high-throughput in-vitro ion-channel screening data to make predictions regarding the cardiac toxicity potential of a new compound in both animal and human studies. A recent FDA think tank encourages the use of biophysical mathematical models of cardiac myocytes for this prediction task. However, it remains unclear whether this approach is the most appropriate. Here we examine five literature data-sets that have been used to support the use of four different biophysical models and one statistical model for predicting cardiac toxicity in numerous species using various endpoints. We propose a simple model that represents the balance between repolarisation and depolarisation forces and compare the predictive power of the model against the original results (leave-one-out cross-validation). Our model showed equivalent performance when compared to the four biophysical models and one statistical model. We therefore conclude that this approach should be further investigated in the context of early cardiac safety screening when in-vitro potency data is generated.

Synthesis and structure–activity relationships study of dithiolethiones as inducers of glutathione in the SH-SY5Y neuroblastoma cell line

Parkinsons disease is a neurodegenerative disorder that involves the degeneration of nigrostriatal dopaminergic neurons. Elevated levels of reactive oxygen species have been shown to deplete cellular levels of the ubiquitous antioxidant glutathione, leading to oxidative stress and eventual neuronal cell death. Dithiolethiones, a class of sulfur-containing heterocyclic molecules, have been shown to induce cellular production of glutathione in a variety of tissues, but have not been extensively evaluated in neurons. Herein, we report the synthesis and preliminary structure-activity relationships study of several substituted dithiolethiones. Three molecules were identified (D3T, CPDT, and 2d) that potently induced cellular glutathione in the SH-SY5Y neuroblastoma cell line. Furthermore, these compounds were found to provide neuroprotection in the 6-hydroxydopamine model of neurotoxicity. This study suggests that dithiolethione-mediated neuroprotection may have potential as a disease-modifying antiparkinsonian therapy.

Predicting survival of pancreatic cancer patients treated with gemcitabine using longitudinal tumour size data

PurposeMeasures derived from longitudinal tumour size data have been increasingly utilised to predict survival of patients with solid tumours. The aim of this study was to examine the prognostic value of such measures for patients with metastatic pancreatic cancer undergoing gemcitabine therapy.MethodsThe control data from two Phase III studies were retrospectively used to develop (271 patients) and validate (398 patients) survival models. Firstly, 31 baseline variables were screened from the training set using penalised Cox regression. Secondly, tumour shrinkage metrics were interpolated for each patient by hierarchical modelling of the tumour size time-series. Subsequently, survival models were built by applying two approaches: the first aimed at incorporating model-derived tumour size metrics in a parametric model, and the second simply aimed at identifying empirical factors using Cox regression. Finally, the performance of the models in predicting patient survival was evaluated on the validation set.ResultsDepending on the modelling approach applied, albumin, body surface area, neutrophil, baseline tumour size and tumour shrinkage measures were identified as potential prognostic factors. The distributional assumption on survival times appeared to affect the identification of risk factors but not the ability to describe the training data. The two survival modelling approaches performed similarly in predicting the validation data.ConclusionsA parametric model that incorporates model-derived tumour shrinkage metrics in addition to other baseline variables could predict reasonably well survival of patients with metastatic pancreatic cancer. However, the predictive performance was not significantly better than a simple Cox model that incorporates only baseline characteristics.

Complex versus simple models: ion-channel cardiac toxicity prediction

There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model Bnet was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the Bnet model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

Further structure–activity relationships study of substituted dithiolethiones as glutathione-inducing neuroprotective agents

BackgroundParkinson’s disease is a neurodegenerative disorder associated with oxidative stress and glutathione depletion. The induction of cellular glutathione levels by exogenous molecules is a promising neuroprotective approach to limit the oxidative damage that characterizes Parkinson’s disease pathophysiology. Dithiolethiones, a class of sulfur-containing heterocyclic molecules, are known to increase cellular levels of glutathione; however, limited information is available regarding the influence of dithiolethione structure on activity. Herein, we report the design, synthesis, and pharmacological evaluation of a further series of dithiolethiones in the SH-SY5Y neuroblastoma cell line.ResultsOur structure–activity relationships data show that dithiolethione electronic properties, given as Hammett σp constants, influence glutathione induction activity and compound toxicity. The most active glutathione inducer identified, 6a, dose-dependently protected cells from 6-hydroxydopamine toxicity. Furthermore, the protective effects of 6a were abrogated by the inhibitor of glutathione synthesis, buthionine sulfoximine, confirming the importance of glutathione in the protective activities of 6a.ConclusionsThe results of this study further delineate the relationship between dithiolethione chemical structure and glutathione induction. The neuroprotective properties of analog 6a suggest a role for dithiolethiones as potential antiparkinsonian agents.

Formulation of Biocides Increases Antimicrobial Potency and Mitigates the Enrichment of Non-Susceptible Bacteria in Multi-Species Biofilms

ABSTRACT The current investigation aimed to generate data to inform the development of risk assessments of biocide usage. Stabilized domestic drain biofilm microcosms were exposed daily over 6 months to increasing concentrations (0.01% to 1%) of the biocide benzalkonium chloride (BAC) in a simple aqueous solution (BAC-s) or in a complex formulation (BAC-f) representative of a domestic cleaning agent. Biofilms were analyzed by culture, differentiating by bacterial functional group and by BAC or antibiotic susceptibility. Bacterial isolates were identified by 16S rRNA sequencing, and changes in biofilm composition were assessed by high-throughput sequencing. Exposure to BAC-f resulted in significantly larger reductions in levels of viable bacteria than exposure to BAC-s, while bacterial diversity greatly decreased during exposure to both BAC-s and BAC-f, as evidenced by sequencing and viable counts. Increases in the abundance of bacteria exhibiting reduced antibiotic or BAC susceptibility following exposure to BAC at 0.1% were significantly greater for BAC-s than BAC-f. Bacteria with reduced BAC and antibiotic susceptibility were generally suppressed by higher BAC concentrations, and formulation significantly enhanced this effect. Significant decreases in the antimicrobial susceptibility of bacteria isolated from the systems before and after long-term BAC exposure were not detected. In summary, dose-dependent suppression of bacterial viability by BAC was enhanced by formulation. Biocide exposure decreased bacterial diversity and transiently enriched populations of organisms with lower antimicrobial susceptibility, and the effects were subsequently suppressed by exposure to 1% BAC-f, the concentration most closely reflecting deployment in formulated products. IMPORTANCE Assessment of the risks of biocide use has been based mainly on the exposure of axenic cultures of bacteria to biocides in simple aqueous solutions. The current investigation aimed to assess the effects of formulation on the outcome of biocide exposure in multispecies biofilms. Formulation of the cationic biocide BAC significantly increased antimicrobial potency. Bacteria with lower antimicrobial susceptibility whose populations were enriched after low-level biocide exposure were more effectively suppressed by the biocide at in-use concentrations (1% [wt/vol]) in a formulation than in a simple aqueous solution. These observations underline the importance of simulating normal deployment conditions in considering the risks and benefits of biocide use.

Complexity vs. Simplicity: The Winner Is?

To the Editor: In the recent article by Lancaster and Sobie, the authors present an approach which combines simulation of large biophysical models with machinelearning methods to classify the torsadegeneic risk of a drug. The approach taken by the authors can be viewed as quite complex. They first simulate compounds through three large biophysical models that consist of 10 of differential equations and 100 of parameters. Next, from those simulations 331 metrics were derived for each compound creating a large simulated dataset. The dimensionality of this dataset is then reduced using principal components analysis. Finally, the leading principal components are then used within a classifier to predict a risk category. Computationally, this can be considered as very demanding and clearly requires expert knowledge. Their approach showed quite impressive performance against the drugs used with a ROC AUC (receiver operating characteristic curve area under curve) value of 0.963. Indeed, this was better than simply using the ratio of hERG IC50 to drug concentration, which gave a ROC AUC value of 0.815. However, what we have shown is that the predictive performance seen by such complex approaches can be mirrored by simple models. In fact, when we apply a rather simple model:

The Effect Of Labetalol And Nifedipine MR On Blood Pressure In Women With Chronic Hypertension In Pregnancy

AIM To compare the blood pressure (BP) lowering effects of labetalol and nifedipine modified release (MR) in hypertensive pregnant women. We also investigated the effect on the heart rate (HR) and determined the proportion of time spent in target. METHODS This was an exploratory study. Women with chronic hypertension taking either labetalol or nifedipine were offered 24-h ambulatory blood pressure monitoring (ABPM). Sleep, wake and drug ingestion times were self-reported. An indirect response model was used to analyse the systolic BP (SBP), diastolic BP (DBP) and HR time-series; the effect of gestation and type of drug was evaluated. RESULTS Forty-eight women were recruited: 24 in each group. There was no difference in clinical characteristics. In women taking nifedipine there was a positive association between the dose of nifedipine and pre-dose BP p = .002, this was not present in the labetalol group. There was a difference between the drug effects on both the SBP and DBP time-series (p = .014). In comparison to labetalol, there was less variation in day time BP in those women prescribed nifedipine. Women on labetalol spent a larger proportion of time with their DBP below target (<80 mmHg). The HR dynamics were qualitatively different, a stimulatory effect was found with nifedipine compared to an inhibitory effect with labetalol. CONCLUSION There are significant and important differences between the BP lowering effects of nifedipine and labetalol. A large randomised control trial is required to investigate the relationship between BP variability and time in target on pregnancy outcomes.

Systems Pharmacology Modeling of Prostate-Specific Antigen in Patients With Prostate Cancer Treated With an Androgen Receptor Antagonist and Down-Regulator

First‐in‐human (FIH) studies with AZD3514, a selective androgen receptor (AR) down‐regulator, showed decreases of >30% in the prostate‐specific antigen (PSA) in some patients. A modeling approach was adopted to understand these observations and define the optimum clinical use hypothesis for AZD3514 for clinical testing. Initial empirical modeling showed that only baseline PSA correlated significantly with this biological response, whereas drug concentration did not. To identify the mechanistic cause of this observation, a mechanism‐based model was first developed, which described the effects of AZD3514 on AR protein and PSA mRNA levels in LNCaP cells with and without dihydrotestosterone (DHT). Second, the mechanism‐based model was linked to a population pharmacokinetic (PK) model; PSA effects of clinical doses were subsequently simulated under different clinical conditions. This model was used to adjust the design of the ongoing clinical FIH study and direct the backup program.

Severity and threshold of peanut reactivity during hospital-based open oral food challenges: An international multicenter survey

Peanut allergy is classically managed by food avoidance. Immunotherapy programs are available at some academic centers for selected patients reacting to small amounts of peanut during food challenge. We aimed to determine and compare reaction thresholds and prevalence of anaphylaxis during peanut oral challenges at multiple specialist allergy centers.