Background-The current proarrhythmia safety testing paradigm, although highly efficient in preventing new torsadogenic drugs from entering the market, has important limitations that can restrict the development and use of valuable new therapeutics. The CiPA (Comprehensive in vitro Proarrhythmia Assay) proposes to overcome these limitations by evaluating drug effects on multiple cardiac ion channels in vitro and using these data in a predictive in silico model of the adult human ventricular myocyte. A set of drugs with known clinical torsade de pointes risk was selected to develop and calibrate the in silico model. Methods and Results-Manual patch-clamp data assessing drug effects on expressed cardiac ion channels were integrated into the O'Hara-Rudy myocyte model modified to include dynamic drug-hERG channel (human Ether-à-go-go-Related Gene) interactions. Together with multichannel pharmacology data, this model predicts that compounds with high torsadogenic risk are more likely to be trapped within the hERG channel and show stronger reverse use dependency of action potential prolongation. Furthermore, drug-induced changes in the amount of electronic charge carried by the late sodium and L-type calcium currents was evaluated as a potential metric for assigning torsadogenic risk. Conclusions-Modeling dynamic drug-hERG channel interactions and multi-ion channel pharmacology improves the prediction of torsadogenic risk. With further development, these methods have the potential to improve the regulatory assessment of drug safety models under the CiPA paradigm. (Circ Arrhythm Electrophysiol. 2017;10:e004628.

The International Council on Harmonization (ICH) S7B and E14 regulatory guidelines are sensitive but not specific for predicting which drugs are pro-arrhythmic. In response, the Comprehensive In Vitro Proarrhythmia Assay (CiPA) was proposed that integrates multi-ion channel pharmacology data in vitro into a human cardiomyocyte model in silico for proarrhythmia risk assessment. Previously, we reported the model optimization and proarrhythmia metric selection based on CiPA training drugs. In this study, we report the application of the prespecified model and metric to independent CiPA validation drugs. Over two validation datasets, the CiPA model performance meets all pre-specified measures for ranking and classifying validation drugs, and outperforms alternatives, despite some in vitro data differences between the two datasets due to different experimental conditions and quality control procedures. This suggests that the current CiPA model/metric may be fit for regulatory use, and standardization of experimental protocols and quality control criteria could increase the model prediction accuracy even further.

Drug-induced Torsade-de-Pointes (TdP) has been responsible for the withdrawal of many drugs from the market and is therefore of major concern to global regulatory agencies and the pharmaceutical industry. The Comprehensive in vitro Proarrhythmia Assay (CiPA) was proposed to improve prediction of TdP risk, using in silico models and in vitro multi-channel pharmacology data as integral parts of this initiative. Previously, we reported that combining dynamic interactions between drugs and the rapid delayed rectifier potassium current (IKr) with multi-channel pharmacology is important for TdP risk classification, and we modified the original O'Hara Rudy ventricular cell mathematical model to include a Markov model of IKr to represent dynamic drug-IKr interactions (IKr-dynamic ORd model). We also developed a novel metric that could separate drugs with different TdP liabilities at high concentrations based on total electronic charge carried by the major inward ionic currents during the action potential. In this study, we further optimized the IKr-dynamic ORd model by refining model parameters using published human cardiomyocyte experimental data under control and drug block conditions. Using this optimized model and manual patch clamp data, we developed an updated version of the metric that quantifies the net electronic charge carried by major inward and outward ionic currents during the steady state action potential, which could classify the level of drug-induced TdP risk across a wide range of concentrations and pacing rates. We also established a framework to quantitatively evaluate a system's robustness against the induction of early afterdepolarizations (EADs), and demonstrated that the new metric is correlated with the cell's robustness to the pro-EAD perturbation of IKr conductance reduction. In summary, in this work we present an optimized model that is more consistent with experimental data, an improved metric that can classify drugs at concentrations both near and higher than clinical exposure, and a physiological framework to check the relationship between a metric and EAD. These findings provide a solid foundation for using in silico models for the regulatory assessment of TdP risk under the CiPA paradigm.

The dorsal hippocampus is crucial for learning the hidden-platform location in the hippocampus-dependent, spatial watermaze task. We have previously demonstrated that the postburst afterhyperpolarization (AHP) of hippocampal pyramidal neurons is reduced after acquisition of the hippocampus-dependent, temporal trace eyeblink conditioning task. We report here that the AHP and one or more of its associated currents (IAHP and/or sIAHP) are reduced in dorsal hippocampal CA1 pyramidal neurons from rats that learned the watermaze task as compared with neurons from control rats. This reduction was a learning-induced phenomenon as the AHP of CA1 neurons from rats that failed to learn the hidden-platform location was similar to that of neurons from control rats. We propose that reduction of the AHP in pyramidal neurons in regions crucial for learning is a cellular mechanism of learning that is conserved across species and tasks.

Aging is associated with learning deficits and a decrease in neuronal excitability, reflected by an enhanced post-burst afterhyperpolarization (AHP), in CA1 hippocampal pyramidal neurons. To identify the current(s) underlying the AHP altered in aging neurons, whole-cell voltage-clamp recording experiments were performed in hippocampal slices from young and aging rabbits. Similar to previous reports, aging neurons were found to rest at more hyperpolarized potentials and have larger AHPs than young neurons. Given that compounds that reduce the slow outward calcium-activated potassium current (sI(AHP)), a major constituent of the AHP, also facilitate learning in aging animals, the sI(AHP) was pharmacologically isolated and characterized. Aging neurons were found to have an enhanced sI(AHP,) the amplitude of which was significantly correlated to the amplitude of the AHP (r = 0.63; p < 0.001). Thus, an enhanced sI(AHP) contributes to the enhanced AHP in aging. No differences were found in the membrane resistance, capacitance, or kinetic and voltage-dependent properties of the sI(AHP). Because enhanced AHP in aging neurons has been hypothesized to be secondary to an enhanced Ca2+ influx via the voltage-gated L-type Ca2+ channels, we further examined the sI(AHP) in the presence of an L-type Ca2+ channel blocker, nimodipine (10 microm). Nimodipine caused quantitatively greater reductions in the sI(AHP) in aging neurons than in young neurons; however, the residual sI(AHP) was still significantly larger in aging neurons than in young neurons. Our data, in conjunction with previous studies showing a correlation between the AHP and learning, suggest that the enhancement of the sI(AHP) in aging is a mechanism that contributes to age-related learning deficits.

The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP) is assessed using an in silico model of the human ventricular action potential (AP) that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ) must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet), which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax). However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an accurate determination of drug IC50-values in vitro. Thus, we demonstrate that UQ provides valuable information about in silico modeling predictions that can inform future proarrhythmic risk evaluation of drugs under the CiPA paradigm.

Common beans contain non-digestible fermentable components (SCFA precursors) and phenolic compounds (phenolic acids, flavonoids and anthocyanins) with demonstrated antioxidant and anti-inflammatory potential. The objective of the present study was to assess the in vivo effect of cooked whole-bean flours, with differing phenolic compound levels and profiles, in a mouse model of acute colitis. C57BL/6 mice were fed a 20 % navy bean or black bean flour-containing diet or an isoenergetic basal diet (BD) for 2 weeks before the induction of experimental colitis via 7 d dextran sodium sulphate (DSS, 2 % (w/v) in the drinking-water) exposure. Compared with the BD, both bean diets increased caecal SCFA and faecal phenolic compound concentrations (P,0·05), which coincided with both beneficial and adverse effects on colonic and systemic inflammation. On the one hand, bean diets reduced mRNA expression of colonic inflammatory cytokines (IL-6, IL-9, IFN-g and IL-17A) and increased anti-inflammatory IL-10 (P,0·05), while systemically reduced circulating cytokines (IL-1b, TNFa, IFNg, and IL-17A, P, 0·05) and DSS-induced oxidative stress. On the other hand, bean diets enhanced DSS-induced colonic damage as indicated by an increased histological injury score and apoptosis (cleaved caspase-3 and FasL mRNA expression) (P,0·05). In conclusion, bean-containing diets exerted both beneficial and adverse effects during experimental colitis by reducing inflammatory biomarkers both locally and systemically while aggravating colonic mucosal damage. Further research is required to understand the mechanisms through which beans exert their effects on colonic inflammation and the impact on colitis severity in human subjects.

A Cardiac Safety Research Consortium / Health and Environmental Sciences Institute / FDA-sponsored Think Tank Meeting was convened in Washington, DC, on May 21, 2018, to bring together scientists, clinicians, and regulators from multiple geographic regions to evaluate progress to date in the Comprehensive In Vitro Proarrhythmia Assay (CiPA) Initiative, a new paradigm to evaluate proarrhythmic risk. Study reports from the 4 different components of the CiPA paradigm (ionic current studies, in silico modeling to generate a Torsade Metric Score, human induced pluripotent stem cell-derived ventricular cardiomyocytes, and clinical ECG assessments including J-Tpeakc) were presented and discussed. This paper provides a high-level summary of the CiPA data presented at the meeting.