Assessment of corrected JT-peak (JTpc) and Tpeak-to-Tend (TpTec) as proarrhythmia biomarkers in non-human primates: Outcome from a HESI consortium.

INTRODUCTION: Corrected QT interval (QTc)is an established biomarker for drug-induced Torsade de Pointe (TdP), but with concerns for a false positive signal. Clinically, JTpc and TpTec have emerged as ECG sub-intervals to differentiate predominant hERG vs. mixed ion channel blocking drugs that prolong QTc. METHODS: In a multicentric, prospective, controlled study, different proarrhythmic drug effects on QTc, JTpc and TpTec were characterized with cynomolgus monkeys using telemetry in a Lead II configuration for internal and external telemetry.Drugs and vehicle were administered orally (PO) to group size of 4 to 8 animals, in 4 laboratories. RESULTS: In monkeys, dofetilide (0.03-0.3 mg/kg) was associated with exposure dependent QTc and JTpc increase, but no significant TpTec effect. Similarly, quinidine (2-50 mg/kg) increased QTc and JTpc but did not change TpTec. Mexiletine (1-15 mg/kg) and verapamil (50 mg/kg) did not induce any significant effect on QTc, JTpc or TpTec. DISCUSSION: Clinically, predominant hERG blockers (dofetilide and quinidine) prolong QTc, JTpc and TpTec and are associated with increased risk for TdP. Results from this study demonstrate that ECG changes after dofetilide and quinidine administration to telemetered monkeys differ from the clinical response, lacking the expected effects on TpTec. Potential explanations for the lack of translation include physio-pharmacology species differences or ECG recording and analysis methodology variations. Mixed ion channel blockers verapamil and mexiletine administered to monkeys showed no significant QTc, JTpc or TpTec prolongation as expected based on the similar clinical response for these agents.

A simple accurate method for concentration-QTc analysis in preclinical animal models.

INTRODUCTION: In preclinical cardiovascular safety pharmacology studies, statistical analysis of the rate corrected QT interval (QTc) is the focus for predicting QTc interval changes in the clinic. Modeling of a concentration/QTc relationship, common clinically, is limited due to minimal pharmacokinetic (PK) data in nonclinical testing. It is possible, however, to relate the average drug plasma concentration from sparse PK samples over specific times to the mean corrected QTc. We hypothesize that averaging drug plasma concentration and the QTc-rate relationship over time provides a simple, accurate concentration-QTc relationship bridging statistical and concentration/QTc modeling. METHODS: Cardiovascular telemetry studies were conducted in non-human primates (NHP; n = 48) and canines (n = 8). Pharmacokinetic samples were collected on separate study days in both species. Average plasma concentrations for specific intervals (CAverage0-X) were calculated for moxifloxacin in canines and NHP using times corresponding to super-intervals for the QTc data statistical analysis. The QTc effect was calculated for each super-interval using a linear regression correction incorporating QT and HR data from the whole super-interval. The concentration QTc effects were then modeled. RESULTS: In NHP, a 10.9 ± 0.06 ms (mean ± 95% CI) change in QTc was detected at approximately 1.5× the moxifloxacin plasma concentration that causes a 10 ms QTc change in humans, based on a 0-24 h super-interval. When simulating a drug without QT effects, mock, no effect on QTc was detected at up to 3× the clinical concentration. Similarly, in canines, a 16.6 ± 0.1 ms change was detected at 1.7× critical clinical moxifloxacin concentration, and a 0.04 ± 0.1 ms change was seen for mock. CONCLUSIONS: While simultaneous PK and QTc data points are preferred, practical constraints and the need for QTc averaging did not prevent concentration-QTc analyses. Utilizing a 0-24 h super-interval method illustrates a simple and effective method to address cardiovascular questions when preclinical drug exposures exceed clinical concentrations.

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.

A comparison of the performance of contemporary, historical, and cross-lab controls in QTc assessment in conscious nonhuman primates.

Cardiovascular safety pharmacology and toxicology studies include vehicle control animals in most studies. Electrocardiogram data on common vehicles is accumulated relatively quickly. In the interests of the 3Rs principles it may be useful to use this historical information to reduce the use of animals or to refine the sensitivity of studies. We used implanted telemetry data from a large nonhuman primate (NHP) cardiovascular study (n = 48) evaluating the effect of moxifloxacin. We extracted 24 animals to conduct a n = 3/sex/group analysis. The remaining 24 animals were used to generate 1000 unique combinations of 3 male and 3 female NHP to act as control groups for the three treated groups in the n = 3/sex/group analysis. The distribution of treatment effects, median minimum detectable difference (MDD) values were gathered from the 1000 studies. These represent contemporary controls. Data were available from 42 NHP from 3 other studies in the same laboratory using the same technology. These were used to generate 1000 unique combinations of 6, 12, 18, 24 and 36 NHP to act as historical control animals for the 18 animals in the treated groups of the moxifloxacin study. Data from an additional laboratory were also available for 20 NHP. The QT, RR and QT-RR data from the three sources were comparable. However, differences in the time course of QTc effect in the vehicle data from the two laboratories meant that it was not possible to use cross-lab controls. In the case of historical controls from the same laboratory, these could be used in place of the contemporary controls in determining a treatment's effect. There appeared to be an advantage in using larger (≥18) group sizes for historical controls. These data support the opportunity of using historical controls to reduce the number of animals used in new cardiovascular studies.

The Efficacy, Effectiveness, and Efficiency of Integrated QTc Assessment: Rationalizing Approaches to New Drug Modalities.

After nearly 3 decades of regulatory activity concerning new drugs' potential for delayed cardiac repolarization an integrated risk assessment paradigm for small molecule drugs has been established. Regulatory guidance also suggests that for large, targeted proteins and monoclonal antibodies no quantitative clinical QTc assessment is necessary. The expansion of new drug modalities prompts the question: "Should these new modalities be treated like small molecule drugs or like monoclonal antibodies?"

The "One-Step" approach for QT analysis increases the sensitivity of nonclinical QTc analysis.

Whether a compound prolongs cardiac repolarization independent of changes in beat rate is a critical question in drug research and development. Current practice is to resolve this in two steps. First, the QT interval is corrected for the influence of rate and then statistical significance is tested. There is renewed interest in improving the sensitivity of nonclinical corrected QT interval (QTc) assessment with modern studies having greater data density than previously utilized. The current analyses examine the effects of moxifloxacin or vehicle on the QT interval in nonhuman primates (NHPs) using a previously described one-step method. The primary end point is the statistical sensitivity of the assessment. Publications suggest that for a four animal crossover (4 × 4) in NHPs the minimal detectable difference (MDD) is greater than or equal to 10 ms, whereas in an eight animal crossover the MDD is ~6.5 ms. Using the one-step method, the MDD for the four animal NHP assessments was 3 ms. In addition, the one-step model accounted for day-to-day differences in the heart rate and QT-rate slope as well as drug-induced changes in these parameters. This method provides an increase in the sensitivity and reduces the number of animals necessary for detecting potential QT change and represents "best practice" in nonclinical QTc assessment in safety pharmacology studies.

The New S7B/E14 Q&A Document Provides Additional Opportunities to Replace the Thorough QT Study.

Since 2015, concentration-QTc (C-QTc) analysis has been used to exclude the possibility that a drug has a concerning effect on the QTc interval. This has enabled the replacement of the designated thorough QT (TQT) study with serial electrocardiograms (ECGs) in routine clinical pharmacology studies, such as the first-in-human (FIH) study. The E14 revision has led to an increased proportion of FIH studies with the added objective of QT evaluation, with the intention of replacing the TQT study. With the more recent revision of the S7B/E14 Q&A document in February 2022, nonclinical assays/studies can be brought into the process of regulatory decisions at the time of marketing application. If the hERG (human ether-a-go-go-related gene) and the non-rodent in vivo study are conducted according to the described best practices and are negative, the previous requirement that a QTc effect of >10 milliseconds must be excluded in healthy subjects at plasma concentrations 2-fold above what can be seen in patients can be reduced to covering the concentrations seen in patients. For drugs that cannot be safely given in high doses to healthy subjects, ECG evaluation is often performed at the therapeutic dose in patients. If a QTc effect of >10 milliseconds can be excluded, an argument can be made that the drug should be considered as having a low likelihood of proarrhythmic effects due to delayedrepolarization, if supported by negative best practices hERG and in vivo studies. In this article, we describe what clinicians involved in early clinical development need to understand in terms of the hERG and in vivo studies to determine whether these meet best practices and therefore can be used in an integrated clinical/nonclinical QT/QTc risk assessment.

Comparing the sensitivity of cross-over and parallel study designs for QTc assessment: An analysis based on a single large study of moxifloxacin in 48 nonhuman primates.

The cardiovascular safety pharmacology (SP) study conducted to satisfy ICH S7A and S7B has commonly used a cross-over study design where each animal receives all treatments. In an increasing number of cases, cross-over designs are not possible and parallel studies have to be used. These can seldom be as large as 8 animals/treatment to match an n = 8 cross-over. Animals in parallel designs receive only one treatment. Parallel studies will have a different sensitivity to detect changes. This sensitivity is a critical question in using nonclinical QTc evaluations to support an integrated proarrhythmic risk assessment under the newly released ICH E14/S7B Q&As. The current analysis used a study large enough (n = 48) to be analyzed both as a parallel and as a cross-over design to directly compare the performance of the two experimental designs coupled to different statistical models, while all other study conduct aspects were the same. A total of 48 nonhuman primates (NHP) received 2 different treatments twice: vehicle, moxifloxacin (80 mg/kg), vehicle, moxifloxacin (80 mg/kg). Post-dose QTc interval data were recorded for 48 h for each treatment. Data were analyzed using 12 animals randomly selected for each treatment in a parallel design or as an n = 48 animal cross-over study. Different statistical models were used. The primary endpoint was the residual deviation (sigma) from the models applied to hourly time intervals. The sigma was used to determine the minimal detectable difference (MDD) for the study design-statistical model combination. Two statistical models were applicable to either study design. They gave similar sigma and resulting MDD values. In cross-over designs, the individual animal identification (ID) can be used in the statistical model. This enabled the smallest MDD value. Simple statistical models for analysis were identified: Treatment + Baseline for parallel designs and Treatment + ID for cross-over designs. The statistical sensitivity of NHP parallel study designs is reasonable (MDD for n = 6 of 12.7 ms), and in combination with testing exposures higher than likely to be necessary in man could be used in an integrated risk assessment. Where sensitivity of the NHP in vivo QTc assessment is critical, the cross-over design enabled a higher sensitivity (MDD 12.2 ms for n = 4; 8 ms for n = 8).

Best practice considerations for nonclinical in vivo cardiovascular telemetry studies in non-rodent species: Delivering high quality QTc data to support ICH E14/S7B Q&As.

The ICH E14/S7B Questions and Answers (Q&As) guideline introduces the concept of a "double negative" nonclinical scenario (negative hERG assay and negative in vivo QTc study) to demonstrate that a drug does not produce a clinically relevant QT prolongation (i.e., no QT liability). This nonclinical "double negative" data package, along with negative Phase 1 clinical QTc data, may be sufficient to substitute for a clinical Thorough QT (TQT) study in some specific cases. While standalone GLP in vivo cardiovascular studies in non-rodent species are standard practice during nonclinical drug development for small molecule programs, a variety of approaches to the design, conduct, analysis and interpretation are utilized across pharmaceutical companies and contract research organizations (CROs) that may, in some cases, negatively impact the stringent sensitivity needed to fulfill the new Q&As. Subject matter experts from both Pharma and CROs have collaborated to recommend best practices for more robust nonclinical cardiovascular telemetry studies in non-rodent species, with input from clinical and regulatory experts. The aim was to increase consistency and harmonization across the industry and to ensure delivery of high quality nonclinical QTc data to meet the proposed sensitivities defined within the revised ICH E14/S7B Q&As guideline (Q&As 5.1 and 6.1). The detailed best practice recommendations presented here cover the design and execution of the safety pharmacology cardiovascular study, including optimal methods for acquiring, analyzing, reporting, and interpreting the resulting QTc and pharmacokinetic data to allow for direct comparison to clinical exposures and assessment of safety margin for QTc prolongation.

Improving the in Vivo QTc assay: The value of implementing best practices to support an integrated nonclinical-clinical QTc risk assessment and TQT substitute.

Recent updates and modifications to the clinical ICH E14 and nonclinical ICH S7B guidelines, which both relate to the evaluation of drug-induced delayed repolarization risk, provide an opportunity for nonclinical in vivo electrocardiographic (ECG) data to directly influence clinical strategies, interpretation, regulatory decision-making and product labeling. This opportunity can be leveraged with more robust nonclinical in vivo QTc datasets based upon consensus standardized protocols and experimental best practices that reduce variability and optimize QTc signal detection, i.e., demonstrate assay sensitivity. The immediate opportunity for such nonclinical studies is when adequate clinical exposures (e.g., supratherapeutic) cannot be safely achieved, or other factors limit the robustness of the clinical QTc evaluation, e.g., the ICH E14 Q5.1 and Q6.1 scenarios. This position paper discusses the regulatory historical evolution and processes leading to this opportunity and details the expectations of future nonclinical in vivo QTc studies of new drug candidates. The conduct of in vivo QTc assays that are consistently designed, executed and analyzed will lead to confident interpretation, and increase their value for clinical QTc risk assessment. Lastly, this paper provides the rationale and basis for our companion article which describes technical details on in vivo QTc best practices and recommendations to achieve the goals of the new ICH E14/S7B Q&As, see Rossman et al., 2023 (this journal).

Comparison of validity of standard nonclinical group size selection versus standard clinical group sizes for nonhuman primate QTc prolongation evaluation.

The number of animals used in a nonhuman primate (NHP) in vivo QTc assessment conducted as part of the safety pharmacology (SP) studies on a potential new drug is relatively small (4-8 subjects). The number is much smaller than the number of healthy volunteers in a conventional thorough QT (TQT) study (40-60 volunteers). How is it possible that such small studies could offer an equivalent sensitivity in an integrated nonclinical and clinical cardiac repolarization risk assessment? This study provided the opportunity to empirically demonstrate in a large number of NHPs the performance of a nonclinical evaluation at a similar size to a TQT study. By contrasting an analysis mimicking the sampling and aggregation of QTc interval data in a manner which is TQT-like with a more conventional SP-like analysis it was demonstrated that the SP-like analysis was more sensitive. In prospective power calculations 80% power at p = 0.05 can be achieved for a 5 ms QTc change with only n = 8 NHPs using the SP-like analysis and in a group of only 4 NHPs 80% power to detect 10 ms could be achieved. By contrast groups of 24 NHPs would be required to achieve 80% power to detect 5 ms using the TQT-like sampling and aggregation approach. Overall, this study has demonstrated that smaller safety pharmacology in vivo QTc assessments using all the available data in larger data aggregates can achieve sensitivity comparable to a human TQT study.

2000-2023 over two decades of ICH S7A: has the time come for a revamp?

The ICH S7A guideline on safety pharmacology studies released over 20 years ago largely achieved its objective "to help protect clinical trial participants and patients receiving marketed products from potential adverse effects of pharmaceuticals". Although, Phase I clinical trials are generally very safe, the incidence and severity of adverse events, the safety related attrition and product withdrawal remain elevated during late-stage clinical development and post approval, a proportion of which can be attributed at least in part to safety pharmacology related issues. Considering the latest scientific and technological advancements in drug safety science, the paradigm shift of the drug discovery and development process and the continuously evolving regulatory landscape, we recommend revisiting, adapting and evolving the ICH S7A guideline. This might offer opportunities i) to select and progress optimized drugs with increased confidence in success, ii) to refine and adapt the clinical monitoring at all stages of clinical development resulting in an optimized benefit/risk assessment, iii) to increase likelihood of regulatory acceptance in a way compatible with an expedited and streamlined drug discovery and development process to benefit patients and iv) to avoid the unnecessary use of animals in 'tick-the-box' studies and encourage alternative approaches. As presented in the article, several options could be envisioned to revisit and adapt the ICH S7A taking into consideration several key features.

QT Ratio: A simple solution to individual QT correction.

Preclinical risk assessment of drug-induced arrhythmias is critical for drug development and relies on heart rate corrected QT interval (QT) prolongation as a biomarker for arrhythmia risk. However, the methods used to correct QT vary in complexity and don't account for all changes in the QT-rate relationship. Thus, we developed the novel Ratio QT correction method which characterizes that relationship at each timepoint using the ratio between QT, adjusted for a species-specific constant, and rate (RR interval). This ratio represents the slope between the intercept and the datapoint being corrected, which is then used in a linear equation like individual methods. A unique correction coefficient for each datapoint avoids assuming static relationships. We hypothesize that the simple and dynamic nature of the Ratio method will provide more consistent rate correction and error reduction compared to Bazett's and individual regression methods. Comparisons were made using ECG data from non-human primates (NHPs) treated with dofetilide or moxifloxacin, separated into small groups (n = 4). The methods were compared based on corrected QT vs RR slopes, standard error, and minimal detectable difference (MDD) for each method. The Ratio method resulted in smaller corrected QT-rate relationship slopes than Bazett's, more closely matching those of individual methods. It produced similar or lower MDDs compared to individual and Bazett's correction, respectively, with more consistent reduction in standard error. This simple and effective method has the potential for easy translatability across species.

A novel cardiovascular systems model to quantify drugs effects on the inter-relationship between contractility and other hemodynamic variables.

The use of systems-based pharmacological modeling approaches to characterize mode-of-action and concentration-effect relationships for drugs on specific hemodynamic variables has been demonstrated. Here, we (i) expand a previously developed hemodynamic system model through integration of cardiac output (CO) with contractility (CTR) using pressure-volume loop theory, and (ii) evaluate the contribution of CO data for identification of system-specific parameters, using atenolol as proof-of-concept drug. Previously collected experimental data was used to develop the systems model, and included measurements for heart rate (HR), CO, mean arterial pressure (MAP), and CTR after administration of atenolol (0.3-30 mg/kg) from three in vivo telemetry studies in conscious Beagle dogs. The developed cardiovascular (CVS)-contractility systems model adequately described the effect of atenolol on HR, CO, dP/dtmax, and MAP dynamics and allowed identification of both system- and drug-specific parameters with good precision. Model parameters were structurally identifiable, and the true mode of action can be identified properly. Omission of CO data did not lead to a significant change in parameter estimates compared to a model that included CO data. The newly developed CVS-contractility systems model characterizes short-term drug effects on CTR, CO, and other hemodynamic variables in an integrated and quantitative manner. When the baseline value of total peripheral resistance is predefined, CO data was not required to identify drug- and system-specific parameters. Confirmation of the consistency of system-specific parameters via inclusion of data for additional drugs and species is warranted. Ultimately, the developed model has the potential to be of relevance to support translational CVS safety studies.

Pharmacokinetics and Pharmacodynamics of Human Regular U-500 Insulin Administered via Continuous Subcutaneous Insulin Infusion Versus Subcutaneous Injection in Adults With Type 2 Diabetes and High-Dose Insulin Requirements.

INTRODUCTION: Human regular U-500 insulin (U-500R) is approved for subcutaneous (SC) injection in patients with diabetes requiring >200 units/day of insulin. Here, pharmacokinetic and pharmacodynamic (PK/PD) profiles following U-500R administered by continuous subcutaneous insulin infusion (CSII) and SC injection in adults with type 2 diabetes (T2D) on high-dose insulin were studied. METHODS: In this randomized, crossover, euglycemic clamp study, patients received a 100-unit bolus of U-500R via SC injection or CSII with basal infusion using a U-500R specific pump. PK parameters were estimated using non-compartmental methods. PD estimates were derived from the glucose infusion rate during the euglycemic clamp procedure. RESULTS: When corrected for the basal infusion, the PK profiles for the 100-unit bolus of U-500R were similar for CSII and SC injection. Without correction for basal infusion, PK and PD profiles showed a greater insulin concentration and effect when U-500R was administered via CSII compared to SC injection, primarily due to basal insulin infusion for CSII. The ratio of geometric least squares AUC0-tlast means SC:CSII (90% CI) is 0.857 (0.729, 1.01) with correction (mean AUC0-tlast: 5230 pmol*L/h [SC injection] and 6070 pmol*L/h [CSII, with correction]) and 0.424 (0.361, 0.499) without correction (mean AUC0-tlast: 12300 pmol*L/h [CSII, without correction]). Median time-to-peak insulin concentration was six hours (range 0.5-8 hours) via SC injection and five hours (0.5-12 hours) via CSII. CONCLUSIONS: In adults with T2D on high-dose insulin, U-500R PK/PD parameters were similar for a 100-unit bolus when given by SC injection or CSII via a U-500R pump.

Improving corrected QT; Why individual correction is not enough.

The use of QT-prolongation as a biomarker for arrhythmia risk requires that researchers correct the QT-interval (QT) to control for the influence of heart rate (HR). QT correction methods can vary but most used are the universal correction methods, such as Bazett's or Van de Water's, which use a single correction formula to correct QT-intervals in all the subjects of a study. Such methods fail to account for differences in the QT/HR relationship between subjects or over time, instead relying on the assumption that this relationship is consistent. To address these changes in rate relationships, we test the effectiveness of linear and non-linear individual correction methods. We hypothesize that individual correction methods that account for additional influences on the rate relationship will result in more effective and consistent correction. To increase the scope of this study we use bootstrap sampling on ECG recordings from non-human primates and beagle canines dosed with vehicle control. We then compare linear and non-linear individual correction methods through their ability to reduce HR correlation and standard deviation of corrected QT values. From these results, we conclude that individual correction methods based on post-treatment data are most effective with the linear methods being the best option for most cases in both primates and canines. We also conclude that the non-linear methods are more effective in canines than primates and that accounting for light status can improve correction while examining the data from the light periods separately. Individual correction requires careful consideration of inter-subject and intra-subject variabilities.

Characterization of a high throughput human stem cell cardiomyocyte assay to predict drug-induced changes in clinical electrocardiogram parameters.

Human induced pluripotent stem cell derived cardiomyocytes (hIPSC-CM's) play an increasingly important role in the safety profiling of candidate drugs. For such models to have utility a clear understanding of clinical translation is required. In the present study we examined the ability of our hIPSC-CM model to predict the clinically observed effects of a diverse set of compounds on several electrocardiogram endpoints, including changes in QT and QRS intervals. To achieve this, compounds were profiled in a novel high throughput voltage-sensitive dye platform. Measurements were taken acutely (30 min) and chronically (24 h) to ensure that responses from compounds with slow onset kinetics or that affected surface ion channel expression would be captured. In addition, to avoid issues associated with changes in free drug levels due to protein binding, assays were run in serum free conditions. Changes in hIPSC-CM threshold APD90 values correlated with compound plasma exposures that produced a +10 ms change in clinical QTc (Pearson r2 = 0.80). In addition, randomForest modeling showed high predictivity in defining TdP risk (AUROC value = 0.938). Risk associated with QRS prolongation correlated with an increase in action potential rise-time (AUROC value = 0.982). The in-depth understanding of the clinical translatability of our hIPSC-CM model positions this assay to play a key role in defining cardiac risk early in drug development. Moreover, the ability to perform longer term studies enables the detection of compounds that may not be highlighted by more acute assay formats, such as inhibitors of hERG trafficking.

Applying the CiPA approach to evaluate cardiac proarrhythmia risk of some antimalarials used off-label in the first wave of COVID-19.

We applied a set of in silico and in vitro assays, compliant with the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm, to assess the risk of chloroquine (CLQ) or hydroxychloroquine (OH-CLQ)-mediated QT prolongation and Torsades de Pointes (TdP), alone and combined with erythromycin (ERT) and azithromycin (AZI), drugs repurposed during the first wave of coronavirus disease 2019 (COVID-19). Each drug or drug combination was tested in patch clamp assays on seven cardiac ion channels, in in silico models of human ventricular electrophysiology (Virtual Assay) using control (healthy) or high-risk cell populations, and in human-induced pluripotent stem cell (hiPSC)-derived cardiomyocytes. In each assay, concentration-response curves encompassing and exceeding therapeutic free plasma levels were generated. Both CLQ and OH-CLQ showed blocking activity against some potassium, sodium, and calcium currents. CLQ and OH-CLQ inhibited IKr (half-maximal inhibitory concentration [IC50 ]: 1 µM and 3-7 µM, respectively) and IK1 currents (IC50 : 5 and 44 µM, respectively). When combining OH-CLQ with AZI, no synergistic effects were observed. The two macrolides had no or very weak effects on the ion currents (IC50  > 300-1000 µM). Using Virtual Assay, both antimalarials affected several TdP indicators, CLQ being more potent than OH-CLQ. Effects were more pronounced in the high-risk cell population. In hiPSC-derived cardiomyocytes, all drugs showed early after-depolarizations, except AZI. Combining CLQ or OH-CLQ with a macrolide did not aggravate their effects. In conclusion, our integrated nonclinical CiPA dataset confirmed that, at therapeutic plasma concentrations relevant for malaria or off-label use in COVID-19, CLQ and OH-CLQ use is associated with a proarrhythmia risk, which is higher in populations carrying predisposing factors but not worsened with macrolide combination.