Supporting an integrated QTc risk assessment using the hERG margin distributions for three positive control agents derived from multiple laboratories and on multiple occasions.

BACKGROUND: Determination of a drug's potency in blocking the hERG channel is an established safety pharmacology study. Best practice guidelines have been published for reliable assessment of hERG potency. In addition, a set of plasma concentration and plasma protein binding fraction data were provided as denominators for margin calculations. The aims of the current analysis were five-fold: provide data allowing creation of consistent denominators for the hERG margin distributions of the key reference agents, explore the variation in hERG margins within and across laboratories, provide a hERG margin to 10 ms QTc prolongation based on several newer studies, provide information to use these analyses for reference purposes, and provide recommended hERG margin 'cut-off' values. METHODS: The analyses used 12 hERG IC50 'best practice' data sets (for the 3 reference agents). A group of 5 data sets came from a single laboratory. The other 7 data sets were collected by 6 different laboratories. RESULTS: The denominator exposure distributions were consistent with the ICH E14/S7B Training Materials. The inter-occasion and inter-laboratory variability in hERG IC50 values were comparable. Inter-drug differences were most important in determining the pooled margin variability. The combined data provided a robust hERG margin reference based on best practice guidelines and consistent exposure denominators. The sensitivity of hERG margin thresholds were consistent with the sensitivity described over the course of the last two decades. CONCLUSION: The current data provide further insight into the sensitivity of the 30-fold hERG margin 'cut-off' used for two decades. Using similar hERG assessments and these analyses, a future researcher can use a hERG margin threshold to support a negative QTc integrated risk assessment.

Enhancing hERG Risk Assessment with Interpretable Classificatory and Regression Models.

The human Ether-à-go-go-Related Gene (hERG) is a transmembrane protein that regulates cardiac action potential, and its inhibition can induce a potentially deadly cardiac syndrome. In vitro tests help identify hERG blockers at early stages; however, the high cost motivates searching for alternative, cost-effective methods. The primary goal of this study was to enhance the Pred-hERG tool for predicting hERG blockage. To achieve this, we developed new QSAR models that incorporated additional data, updated existing classificatory and multiclassificatory models, and introduced new regression models. Notably, we integrated SHAP (SHapley Additive exPlanations) values to offer a visual interpretation of these models. Utilizing the latest data from ChEMBL v30, encompassing over 14,364 compounds with hERG data, our binary and multiclassification models outperformed both the previous iteration of Pred-hERG and all publicly available models. Notably, the new version of our tool introduces a regression model for predicting hERG activity (pIC50). The optimal model demonstrated an R2 of 0.61 and an RMSE of 0.48, surpassing the only available regression model in the literature. Pred-hERG 5.0 now offers users a swift, reliable, and user-friendly platform for the early assessment of chemically induced cardiotoxicity through hERG blockage. The tool provides versatile outcomes, including (i) classificatory predictions of hERG blockage with prediction reliability, (ii) multiclassificatory predictions of hERG blockage with reliability, (iii) regression predictions with estimated pIC50 values, and (iv) probability maps illustrating the contribution of chemical fragments for each prediction. Furthermore, we implemented explainable AI analysis (XAI) to visualize SHAP values, providing insights into the contribution of each feature to binary classification predictions. A consensus prediction calculated based on the predictions of the three developed models is also present to assist the user's decision-making process. Pred-hERG 5.0 has been designed to be user-friendly, making it accessible to users without computational or programming expertise. The tool is freely available at http://predherg.labmol.com.br.

Nonclinical Cardiovascular Assessment of the Soluble Guanylate Cyclase Stimulator Vericiguat.

Vericiguat and its metabolite M-1 were assessed for proarrhythmic risk in nonclinical in vitro and in vivo studies. In vitro manual voltage-clamp recordings at room temperature determined the effect of vericiguat on human Ether-a-go-go Related Gene (hERG) K+ channels. Effects of vericiguat and M-1 on hERG K+, Nav1.5, hCav1.2, hKvLQT1/1minK, and hKv4.3 channels were investigated via automated voltage-clamp recordings at ambient temperature. Effects of vericiguat and M-1 on hERG K+ and Nav1.5 channels at pathophysiological conditions were explored via manual voltage-clamp recordings at physiologic temperature. Single oral doses of vericiguat (0.6, 2.0, and 6.0 mg/kg) were assessed for in vivo proarrhythmic risk via administration to conscious telemetered dogs; electrocardiogram (ECG) and hemodynamic parameters were monitored. ECG recordings were included in 4- and 39-week dog toxicity studies. In manual voltage-clamp recordings, vericiguat inhibited hERG K+-mediated tail currents in a concentration-dependent manner (20% threshold inhibitory concentration ∼1.9 µM). In automated voltage-clamp recordings, neither vericiguat nor M-1 were associated with biologically relevant inhibition (>20%) of hNav1.5, hCav1.2, hKvLQT1, and hKv4.3. No clinically relevant observations were made for hNav1.5 and hKvLQT1 under simulated pathophysiological conditions. Vericiguat was associated with expected mode-of-action-related dose-dependent changes in systolic arterial blood pressure (up to -20%) and heart rate (up to +53%). At maximum vericiguat dose, corrected QT (QTc) interval changes from baseline varied slightly (-6 to +1%) depending on correction formula. Toxicity studies confirmed absence of significant QTc interval changes. There was no evidence of an increased proarrhythmic risk from nonclinical studies with vericiguat or M-1. SIGNIFICANCE STATEMENT: There was no evidence of an increased proarrhythmic risk from in vitro and in vivo nonclinical studies with vericiguat or M-1. The integrated risk assessment of these nonclinical data combined with existing clinical data demonstrate administration of vericiguat 10 mg once daily in patients with heart failure with reduced ejection fraction is not associated with a proarrhythmic risk.

Toward Quantitative Models in Safety Assessment: A Case Study to Show Impact of Dose-Response Inference on hERG Inhibition Models.

Due to challenges with historical data and the diversity of assay formats, in silico models for safety-related endpoints are often based on discretized data instead of the data on a natural continuous scale. Models for discretized endpoints have limitations in usage and interpretation that can impact compound design. Here, we present a consistent data inference approach, exemplified on two data sets of Ether-à-go-go-Related Gene (hERG) K+ inhibition data, for dose-response and screening experiments that are generally applicable for in vitro assays. hERG inhibition has been associated with severe cardiac effects and is one of the more prominent safety targets assessed in drug development, using a wide array of in vitro and in silico screening methods. In this study, the IC50 for hERG inhibition is estimated from diverse historical proprietary data. The IC50 derived from a two-point proprietary screening data set demonstrated high correlation (R = 0.98, MAE = 0.08) with IC50s derived from six-point dose-response curves. Similar IC50 estimation accuracy was obtained on a public thallium flux assay data set (R = 0.90, MAE = 0.2). The IC50 data were used to develop a robust quantitative model. The model's MAE (0.47) and R2 (0.46) were on par with literature statistics and approached assay reproducibility. Using a continuous model has high value for pharmaceutical projects, as it enables rank ordering of compounds and evaluation of compounds against project-specific inhibition thresholds. This data inference approach can be widely applicable to assays with quantitative readouts and has the potential to impact experimental design and improve model performance, interpretation, and acceptance across many standard safety endpoints.

Electrocardiogram-based index for the assessment of drug-induced hERG potassium channel block.

INTRODUCTION: Drug-induced block of the hERG potassium channel could predispose to torsade de pointes, depending on occurrence of concomitant blocks of the calcium and/or sodium channels. Since the hERG potassium channel block affects cardiac repolarization, the aim of this study was to propose a new reliable index for non-invasive assessment of drug-induced hERG potassium channel block based on electrocardiographic T-wave features. METHODS: ERD30% (early repolarization duration) and TS/A (down-going T-wave slope to T-wave amplitude ratio) features were measured in 22 healthy subjects who received, in different days, doses of dofetilide, ranolazine, verapamil and quinidine (all being hERG potassium channel blockers and the latter three being also blockers of calcium and/or sodium channels) while undergoing continuous electrocardiographic acquisition from which ERD30% and TS/A were evaluated in fifteen time points during the 24 h following drug administration ("ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects" database by Physionet). A total of 1320 pairs of ERD30% and TS/A measurements, divided in training (50%) and testing (50%) datasets, were obtained. Drug-induced hERG potassium channel block was modelled by the regression equation BECG(%) = a·ERD30% + b·TS/A+ c·ERD30%·TS/A + d; BECG(%) values were compared to plasma-based measurements, BREF(%). RESULTS: Regression coefficients values, obtained on the training dataset, were: a = -561.0 s-1, b = -9.7 s, c = 77.2 and d = 138.9. In the testing dataset, correlation coefficient between BECG(%) and BREF(%) was 0.67 (p < 10-81); estimation error was -11.5 ± 16.7%. CONCLUSION: BECG(%) is a reliable non-invasive index for the assessment of drug-induced hERG potassium channel block, independently from concomitant blocks of other ions.

Use of automated patch clamp in cardiac safety assessment: Past, present & future perspectives.

There is no doubt that automated patch clamp (APC) technology has revolutionized research in biomedical science. High throughput ion channel screening is now an integral part of the development and safety profiling of the majority of new chemical entities currently developed to address unmet medical needs. The increased throughput it provides has significantly improved the ability to overcome the time-consuming, low throughput bottlenecks resulting from the more conventional manual patch clamp method, considered the 'gold standard', for studying ion channel function and pharmacology. While systems offering the luxury of automation have only been commercially available for two decades, the road leading to this new technology is long and rich in seminal, hands-on, studies dating back as far as the 18th century. So where does this technology currently stand, and what will it look like in the future? In the current article, we review the scientific history leading to the development of APC systems, examine key drivers in the rapid development of this technology (such as failed ion channel programmes and the issue of drug-induced hERG inhibition and QT interval prolongation), highlight key capabilities and finally provide some perspective on the current and future impact of the technology on cardiac safety assessment and biomedical science.

Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the "Big Data" Era.

The rise of novel artificial intelligence (AI) methods necessitates their benchmarking against classical machine learning for a typical drug-discovery project. Inhibition of the potassium ion channel, whose alpha subunit is encoded by the human ether-à-go-go-related gene (hERG), leads to a prolonged QT interval of the cardiac action potential and is a significant safety pharmacology target for the development of new medicines. Several computational approaches have been employed to develop prediction models for the assessment of hERG liabilities of small molecules including recent work using deep learning methods. Here, we perform a comprehensive comparison of hERG effect prediction models based on classical approaches (random forests and gradient boosting) and modern AI methods [deep neural networks (DNNs) and recurrent neural networks (RNNs)]. The training set (∼9000 compounds) was compiled by integrating the hERG bioactivity data from the ChEMBL database with experimental data generated from an in-house, high-throughput thallium flux assay. We utilized different molecular descriptors including the latent descriptors, which are real-value continuous vectors derived from chemical autoencoders trained on a large chemical space (>1.5 million compounds). The models were prospectively validated on ∼840 in-house compounds screened in the same thallium flux assay. The best results were obtained with the XGBoost method and RDKit descriptors. The comparison of models based only on latent descriptors revealed that the DNNs performed significantly better than the classical methods. The RNNs that operate on SMILES provided the highest model sensitivity. The best models were merged into a consensus model that offered superior performance compared to reference models from academic and commercial domains. Furthermore, we shed light on the potential of AI methods to exploit the big data in chemistry and generate novel chemical representations useful in predictive modeling and tailoring a new chemical space.

A rapid solubility assay of protein domain misfolding for pathogenicity assessment of rare DNA sequence variants.

PURPOSE: DNA sequencing technology has unmasked a vast number of uncharacterized single-nucleotide variants in disease-associated genes, and efficient methods are needed to determine pathogenicity and enable clinical care. METHODS: We report an E. coli-based solubility assay for assessing the effects of variants on protein domain stability for three disease-associated proteins. RESULTS: First, we examined variants in the Kv11.1 channel PAS domain (PASD) associated with inherited long QT syndrome type 2 and found that protein solubility correlated well with reported in vitro protein stabilities. A comprehensive solubility analysis of 56 Kv11.1 PASD variants revealed that disruption of membrane trafficking, the dominant loss-of-function disease mechanism, is largely determined by domain stability. We further validated this assay by using it to identify second-site suppressor PASD variants that improve domain stability and Kv11.1 protein trafficking. Finally, we applied this assay to several cancer-linked P53 tumor suppressor DNA-binding domain and myopathy-linked Lamin A/C Ig-like domain variants, which also correlated well with reported protein stabilities and functional analyses. CONCLUSION: This simple solubility assay can aid in determining the likelihood of pathogenicity for sequence variants due to protein misfolding in structured domains of disease-associated genes as well as provide insights into the structural basis of disease.

hERG toxicity assessment: Useful guidelines for drug design.

All along the drug development process, one of the most frequent adverse side effects, leading to the failure of drugs, is the cardiac arrhythmias. Such failure is mostly related to the capacity of the drug to inhibit the human ether-à-go-go-related gene (hERG) cardiac potassium channel. The early identification of hERG inhibition properties of biological active compounds has focused most of attention over the years. In order to prevent the cardiac side effects, a great number of in silico, in vitro and in vivo assays have been performed. The main goal of these studies is to understand the reasons of these effects, and then to give information or instructions to scientists involved in drug development to avoid the cardiac side effects. To evaluate anticipated cardiovascular effects, early evaluation of hERG toxicity has been strongly recommended for instance by the regulatory agencies such as U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA). Thus, following an initial screening of a collection of compounds to find hits, a great number of pharmacomodulation studies on the novel identified chemical series need to be performed including activity evaluation towards hERG. We provide in this concise review clear guidelines, based on described examples, illustrating successful optimization process to avoid hERG interactions as cases studies and to spur scientists to develop safe drugs.

Preclinical Safety Assessment of a Highly Selective and Potent Dual Small-Molecule Inhibitor of CBP/P300 in Rats and Dogs.

Cyclic adenosine monophosphate-response element (CREB)-binding protein (CBP) and EP300E1A-binding protein (p300) are members of the bromodomain and extraterminal motif (BET) family. These highly homologous proteins have a key role in modulating transcription, including altering the status of chromatin or through interactions with or posttranslational modifications of transcription factors. As CBP and p300 have known roles for stimulating c-Myc oncogenic activity, a small-molecule inhibitor, GNE-781, was developed to selectively and potently inhibit the CBP/p300 bromodomains (BRDs). Genetic models have been challenging to develop due to embryonic lethality arising from germline homozygous mutations in either CBP or P300. Hence, the purpose of this study was to characterize the role of dual inhibition of these proteins in adult rats and dogs. Repeat dose toxicity studies were conducted, and toxicologic and pathologic end points were assessed. GNE-781 was generally tolerated; however, marked effects on thrombopoiesis occurred in both species. Evidence of inhibition of erythroid, granulocytic, and lymphoid cell differentiation was also present, as well as deleterious changes in gastrointestinal and reproductive tissues. These findings are consistent with many preclinical (and clinical) effects reported with BET inhibitors targeting BRD proteins; thus, the current study findings indicate a likely important role for CBP/p300 in stem cell differentiation.

Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology.

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.

Early drug development: assessment of proarrhythmic risk and cardiovascular safety.

INTRODUCTION: hERG assays and thorough ECG trials have been mandated since 2005 to evaluate the QT interval and potential proarrhythmic risk of new chemical entities. The high cost of these studies and the shortcomings inherent in these binary and limited approaches to drug evaluation have prompted regulators to search for more cost effective and mechanistic paradigms to assess drug liability as exemplified by the CiPA initiative and the exposure response ICH E14(R3) guidance document. Areas covered: This review profiles the changing regulatory landscape as it pertains to early drug development and outlines the analyses that can be performed to characterize preclinical and early clinical cardiovascular risk. Expert commentary: It is further acknowledged that the narrow focus on the QT interval needs to be expanded to include a more comprehensive evaluation of cardiovascular risk since unanticipated off target effects have led to the withdrawal of multiple drugs after they had been approved and marketed.

Assessment of drug-induced proarrhythmia: The importance of study design in the rabbit left ventricular wedge model.

In the present study, we investigated an impact of the stimulation rate on the detection of the proarrhythmic potential of 10 reference compounds with effects on different cardiac ion channels in the isolated arterially-perfused rabbit left ventricular wedge preparation. The compounds were tested in the wedge model using two distinct protocols; including baseline stimulation at 1-Hz followed by a brief period at 0.5-Hz, either without an additional brief period of 2-Hz stimulation (i.e. Protocol 1) or with 2-Hz stimulation (i.e. Protocol 2). As expected, QT-prolonging drugs (ibutilide and quinidine) prolonged the QT interval, similarly increased the Torsades de Pointes (TdP) score, and elicited early afterdepolarizations (EADs) in both protocols. HMR1556 and JNJ-303 (IKs blockers) also prolonged the QT interval up to 1µM similarly in both protocols. Nifedipine (Ca(2+) antagonist) shortened the QT interval, and reduced force of contraction similarly in both protocols. However, Na(+) channel blockers (Ia, Ib, Ic) widened the QRS duration more in Protocol 2 than in Protocol 1. Furthermore, it was only possible to detect non-TdP-like ventricular tachycardia/fibrillation (VT/VF) induced by Na(+) blockers and by QT-shortening drugs (levcromakalim and mallotoxin) using the 2-Hz stimulation (Protocol 2). Our data suggest that the inclusion of a brief period of fast stimulation at 2Hz is critical for detecting drug-induced slowing of conduction (QRS widening), QT shortening and associated (non-TdP-like) VT/VF, which are distinct from the QT prolongation/TdP proarrhythmia in isolated, arterially-perfused rabbit left ventricular wedges.

A temperature-dependent in silico model of the human ether-à-go-go-related (hERG) gene channel.

INTRODUCTION: Current regulatory guidelines for assessing the risk of QT prolongation include in vitro assays assessing drug effects on the human ether-à-go-go-related (hERG; also known as Kv11.1) channel expressed in cell lines. These assays are typically conducted at room temperature to promote the ease and stability of recording hERG currents. However, the new Comprehensive in vitro Proarrhythmia Assay (CiPA) paradigm proposes to use an in silico model of the human ventricular myocyte to assess risk, requiring as input hERG channel pharmacology data obtained at physiological temperatures. To accommodate current industry safety pharmacology practices for measuring hERG channel activity, an in silico model of hERG channel that allows for the extrapolation of hERG assay data across different temperatures is desired. Because temperature may have an effect on both channel gating and drug binding rate, such models may need to have two components: a base model dealing with temperature-dependent gating changes without drug, and a pharmacodynamic component simulating temperature-dependent drug binding kinetics. As a first step, a base mode that can capture temperature effects on hERG channel gating without drug is needed. METHODS AND RESULTS: To meet this need for a temperature-dependent base model, a Markov model of the hERG channel with state transition rates explicitly dependent on temperature was developed and calibrated using data from a variety of published experiments conducted over a range of temperatures. The model was able to reproduce observed temperature-dependent changes in key channel gating properties and also to predict the results obtained in independent sets of new experiments. DISCUSSION: This new temperature-sensitive model of hERG gating represents an attempt to improve the predictivity of safety pharmacology testing by enabling the translation of room temperature hERG assay data to more physiological conditions. With further development, this model can be incorporated into the CiPA paradigm and also be used as a tool for developing insights into the thermodynamics of hERG channel gating mechanisms and the temperature-dependence of hERG channel block by drugs.

QT interval correction for drug-induced changes in body temperature during integrated cardiovascular safety assessment in regulatory toxicology studies in dogs: A case study.

INTRODUCTION: Cardiovascular safety assessment requires accurate evaluation of QT interval, which depends on the length of the cardiac cycle and also on core body temperature (BT). Increases in QT interval duration have been shown to be associated with decreases in BT in dogs. METHODS: An example of altered QT interval duration associated with changes in body temperature observed during a 4-week regulatory toxicology study in dogs is presented. Four groups of Beagle dogs received the vehicle or test item once on Day 1, followed by a 4-week observation period. Electrocardiogram (ECG) parameters were continuously recorded on Days 1 and 26 by jacketed external telemetry (JET). Core body temperature (BT) was measured with a conventional rectal thermometer at appropriate time-points during the Day 1 recording period. RESULTS: Decreased BT was observed approximately 2h after treatment on Day 1, along with increased QT interval duration corrected according to the Van de Water formula (QTcV), but the effect was no longer observed after correction for changes in BT [QTcVcT=QTcV-14(37.5-BT)] according to the Van der Linde formula. No significant changes in QTcV were reported at the end of the observation period, on Day 26. DISCUSSION: The present study demonstrates that core body (rectal) temperature can easily be monitored at appropriate time-points during JET recording in regulatory toxicology studies in dogs, in order to correct QT interval duration values for treatment-related changes in BT. The successful application of the Van der Linde formula to correct QTc prolongation for changes in BT was demonstrated.

Implications of Dynamic Occupancy, Binding Kinetics, and Channel Gating Kinetics for hERG Blocker Safety Assessment and Mitigation.

Blockade of the hERG potassium channel prolongs the ventricular action potential (AP) and QT interval, and triggers early after depolarizations (EADs) and torsade de pointes (TdP) arrhythmia. Opinions differ as to the causal relationship between hERG blockade and TdP, the relative weighting of other contributing factors, definitive metrics of preclinical proarrhythmicity, and the true safety margin in humans. Here, we have used in silico techniques to characterize the effects of channel gating and binding kinetics on hERG occupancy, and of blockade on the human ventricular AP. Gating effects differ for compounds that are sterically compatible with closed channels (becoming trapped in deactivated channels) versus those that are incompatible with the closed/closing state, and expelled during deactivation. Occupancies of trappable blockers build to equilibrium levels, whereas those of non-trappable blockers build and decay during each AP cycle. Occupancies of ~83% (non-trappable) versus ~63% (trappable) of open/inactive channels caused EADs in our AP simulations. Overall, we conclude that hERG occupancy at therapeutic exposure levels may be tolerated for nontrappable, but not trappable blockers capable of building to the proarrhythmic occupancy level. Furthermore, the widely used Redfern safety index may be biased toward trappable blockers, overestimating the exposure-IC50 separation in nontrappable cases.

Kv3.1 uses a timely resurgent K(+) current to secure action potential repolarization.

High-frequency action potential (AP) transmission is essential for rapid information processing in the central nervous system. Voltage-dependent Kv3 channels play an important role in this process thanks to their high activation threshold and fast closure kinetics, which reduce the neuron's refractory period. However, premature Kv3 channel closure leads to incomplete membrane repolarization, preventing sustainable AP propagation. Here, we demonstrate that Kv3.1b channels solve this problem by producing resurgent K(+) currents during repolarization, thus ensuring enough repolarizing power to terminate each AP. Unlike previously described resurgent Na(+) and K(+) currents, Kv3.1b's resurgent current does not originate from recovery of channel block or inactivation but results from a unique combination of steep voltage-dependent gating kinetics and ultra-fast voltage-sensor relaxation. These distinct properties are readily transferrable onto an orthologue Kv channel by transplanting the voltage-sensor's S3-S4 loop, providing molecular insights into the mechanism by which Kv3 channels contribute to high-frequency AP transmission.

Integrated nonclinical and clinical risk assessment of the investigational proteasome inhibitor ixazomib on the QTc interval in cancer patients.

BACKGROUND: Ixazomib is the first oral, proteasome inhibitor to reach phase III trials. Here, we present an integrated nonclinical and clinical assessment of ixazomib's effect on QTc intervals. METHODS: Nonclinical studies assessed (1) the in vitro binding of ixazomib to the hERG channel and (2) its effect on QT/QTc in dogs (N = 4) via telemetry. Pharmacokinetic-matched triplicate electrocardiograms were collected in four clinical phase I studies of intravenous (0.125-3.11 mg/m(2), N = 125, solid tumors/lymphoma) or oral (0.24-3.95 mg/m(2), N = 120, multiple myeloma) ixazomib. The relationship between ixazomib plasma concentration and heart rate (HR)-corrected QT using Fridericia (QTcF) or population (QTcP) methods was analyzed using linear mixed-effects models with fixed effects for day and time. RESULTS: In vitro binding potency for ixazomib to the hERG channel was weak (K i 24.9 µM; IC50 59.6 µM), and nonclinical telemetry studies showed no QT/QTc prolongation at doses up to 4.2 mg/m(2). In cancer patients, ixazomib, when evaluated at doses yielding various plasma concentrations (with 26 % of data greater than mean C max for the 4 mg phase 3 dose), had no meaningful effect on QTc based on model-predicted mean change in QTcF/QTcP from baseline. There was no relationship between ixazomib concentration and RR, suggesting no effect on HR. CONCLUSIONS: Ixazomib has no clinically meaningful effects on QTc or HR. Integrating preclinical data and concentration-QTc modeling of phase 1 data may obviate the need for a dedicated QTc study in oncology. A framework for QT assessment in oncology drug development is proposed.

Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

BACKGROUND: Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. METHODS: The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. RESULTS: The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico tools. CONCLUSIONS: The combination of in silico tools with the best performance is gene-dependent. The in silico tools reported here may have some value in assessing variants in the KCNQ1 and KCNH2 genes, but caution should be taken when the analysis is applied to SCN5A gene variants.

Comprehensive T wave morphology assessment in a randomized clinical study of dofetilide, quinidine, ranolazine, and verapamil.

BACKGROUND: Congenital long QT syndrome type 2 (abnormal hERG potassium channel) patients can develop flat, asymmetric, and notched T waves. Similar observations have been made with a limited number of hERG-blocking drugs. However, it is not known how additional calcium or late sodium block, that can decrease torsade risk, affects T wave morphology. METHODS AND RESULTS: Twenty-two healthy subjects received a single dose of a pure hERG blocker (dofetilide) and 3 drugs that also block calcium or sodium (quinidine, ranolazine, and verapamil) as part of a 5-period, placebo-controlled cross-over trial. At pre-dose and 15 time-points post-dose, ECGs and plasma drug concentration were assessed. Patch clamp experiments were performed to assess block of hERG, calcium (L-type) and late sodium currents for each drug. Pure hERG block (dofetilide) and strong hERG block with lesser calcium and late sodium block (quinidine) caused substantial T wave morphology changes (P<0.001). Strong late sodium current and hERG block (ranolazine) still caused T wave morphology changes (P<0.01). Strong calcium and hERG block (verapamil) did not cause T wave morphology changes. At equivalent QTc prolongation, multichannel blockers (quinidine and ranolazine) caused equal or greater T wave morphology changes compared with pure hERG block (dofetilide). CONCLUSIONS: T wave morphology changes are directly related to amount of hERG block; however, with quinidine and ranolazine, multichannel block did not prevent T wave morphology changes. A combined approach of assessing multiple ion channels, along with ECG intervals and T wave morphology may provide the greatest insight into drug-ion channel interactions and torsade de pointes risk. CLINICAL TRIAL REGISTRATION: URL: http://clinicaltrials.gov/ Unique identifier: NCT01873950.