The recently approved ICH E14/S7B Q&As allow sponsors to forgo a dedicated clinical QT study together with submission of high-quality in vitro hERG (human Ether-à-go-go-Related Gene) and in vivo QTc (corrected QT interval) data that support a nonclinical double-negative, when paired with satisfactory clinical QTc data. This has heightened the interest of drug developers and regulators in utilizing nonclinical data from in vivo QT studies to complement clinical ECG data for an integrated assessment of proarrhythmia risk. In this scenario, it's crucial to demonstrate no QTc prolongation in a nonclinical study with sufficient power to detect an effect of a similar magnitude as a dedicated clinical QT study to mitigate against a potential false negative result, particularly for E14 Q6.1. While some nonclinical in vivo QTc study designs may have limited ability to achieve this level of sensitivity/power based on statistical methods, the utilization of concentration-QTc (C-QT) analysis of nonclinical data may enhance sensitivity to enable exclusion of a QTc effect of regulatory concern. Moreover, in instances where in vivo QTc prolongation is observed, C-QT will facilitate translation to clinical assessment and estimation of a clinical safety margin. To improve consistency and harmonization across the industry for the conduct of nonclinical C-QT analysis, subject matter experts from Pharma and CROs (Contract Research Organizations) are collaborating to review current methodologies and pros/cons/limitations to establish best practices for this analysis. These will be presented along with responses from a survey to spotlight the current state-of-the-science to position use of nonclinical double-negative data together with Phase 1 ECG data for substitution of the dedicated clinical QT study per ICH E14/S7B Q&As. Most safety pharmacology groups have some experience with C-QT modeling within their companies for internal decision making. The Linear Mixed Effect Model (LME) is most commonly used with ΔQTc (change from predose) as the dependent variable extracted to match 5–7 PK sample timepoints collected from the same animals in a separate dosing/PK phase. These or similar methods have been utilized to perform C-QT analysis across species with positive (e.g. moxifloxacin) and negative (e.g. levocetirizine) QTc-prolonging drugs.

The recently published ICH E14/S7B Q&As incorporated an additional thorough QT (TQT) substitution path for compounds that are double negative in nonclinical studies (hERG and in vivo QT). To increase regulatory confidence in such an approach, general requirements for nonclinical telemetry studies were detailed in the Q&As that focus on model sensitivity, data analysis techniques, and clinical translation. Briefly, criteria for the integrated risk assessment include prescriptive in vitro hERG requirements, and an in vivo evaluation at sufficient multiples over the highest clinical exposure with demonstrated adequate sensitivity to detect an effect of a similar magnitude as a dedicated clinical QT study. Harmonization of best practices for a Latin square crossover study design were recently published by industry subject matter experts (SMEs) to ensure high quality QTc data to support an ICH E14/S7B Q&A 5.1 scenario that meets regulatory expectations. However, there is no industry consensus on best practices for alternate study designs (ascending dose, parallel groups, etc.) routinely utilized for oncology small molecule, large molecule, oligonucleotide, and peptide modalities. To increase industry consistency and ensure data quality, SMEs are collaborating to review current methodologies for alternative study designs where continuous data collection is required in implanted and jacketed telemetry studies. A survey was generated by members of the working group to gather information on alternative study designs employed, data analysis processes, QT interval correction and statistical methods, individual study and test facility sensitivity, and use of pharmacokinetic sampling. The most common current alternative designs included escalating dose (vehicle plus 3 doses levels, N = 4) and parallel (2–3 treatment groups plus concurrent vehicle, N = 4–8/group) which have been submitted to satisfy the ICH S7B, S6, S9, and to a limited extent, the S7B 5.1/6.1 Q&As. Escalating dose designs were typically applied to small molecules, whereas parallel designs were used to test oligonucleotides, large and small molecules. Data from this survey will be used as a starting point for the working group to recommend best practices for alternate study designs in the context of supporting the ICH E14/S7B Q&A 5.1 and 6.1 scenarios and build regulatory confidence in nonclinical QTc data.

Elevated arterial blood pressure (BP) is highly correlated with adverse cardiovascular (CV) outcomes in patients. The effects of a drug on arterial pressure are routinely evaluated during preclinical safety assessment as outlined in the ICH S7A guidance document. A Health and Environmental Sciences Institute (HESI) Consortium initiated a multi-site study with the objective to assess the ability of the standard conscious telemetered CV beagle dog model to detect drug-induced changes in BP and evaluate translation to human data. Animals will be chronically instrumented with a BP catheter and ECG electrodes for telemetric collection of hemodynamic endpoints. Study endpoints include systolic, diastolic, and mean BP, heart rate, electrocardiogram (ECG), body temperature, and locomotor activity. Drugs evaluated include midodrine (alpha-1 agonist), nifedipine (calcium channel blocker), hydralazine (direct-acting smooth muscle relaxant), prazosin (alpha-1 blocker) and milrinone (phosphodiesterase-3 inhibitor) were selected based on known mechanisms of action as well as availability of clinical exposure data. Drugs will be evaluated in beagle dogs using a single (4 × 4) or double (8 × 4) Latin square design. Drugs will be administered orally at 3 doses selected to match clinical exposure data and a vehicle control. A full pharmacokinetic profile for each drug will be conducted at the doses selected at a single site (Abbvie). Blood samples at participating sites will be drawn to confirm drug exposures predicted from independent pharmacokinetic studies. The goal of these studies is to determine whether the assessment of BP, when measured across different laboratories using the same protocol, can consistently detect drug-induced changes in hemodynamics using drugs known to clinically increase and decrease BP.

Nonclinical QTc studies can augment clinical QTc assessments in regulatory submissions provided they are of sufficient quality and sensitivity. Both the statistical performance and species translation play a role in determining the sensitivity of the model. The current analyses examine the effects of dofetilide or vehicle on the QT interval in nonhuman primate (NHP; n = 16) using a one-step estimated marginal means method where both treatment and animal ID are used in regression models to avoid a separate rate correction step, in comparison to other commonly utilized methods. The doses of dofetilide were chosen to span a threshold dose with exposure only just exceeding the concentration associated with 10 ms QTc prolongation in man, to a dose where exposures exceed the Emax for QTc prolongation. The primary objective was an evaluation of which doses and exposures can be detected as eliciting a statistically significant change in QTc. A group size of 8 for cross-over analysis was insufficient to detect, as statistically significant, the effects of the threshold dose of 0.01 mg/kg dofetilide using common correction and statistical analysis methods and hourly time intervals. Higher doses were all detected as causing a statistically significant effect using the same techniques. The 'One-Step' method was able to detect as statistically significant effects at all doses of dofetilide across a wide range of time and exposure. There were also temporal differences between the mean effects observed using the common and 'One-Step' methods. Preliminary concentration-QTc assessment suggests a higher maximum prolongation in concentration QTc with the 'One-Step' method. Furthermore, this analysis suggests that at exposures associated with a 10 ms QTc prolongation in man a 10 ms prolongation is also observed in NHP. The observed ED50 concentration (0.85 ng/ml unbound) is close to that described in man (0.98 ng/ml). These analyses demonstrate the statistical sensitivity of the 'One-Step' method of QTc assessment in NHP. The pharmacological sensitivity was also demonstrated and a detection threshold of 10 ms was consistent in terms of exposure between NHP and man. Overall, QTc assessment using the 'One-Step' method in NHP is a robust and sensitive model to supplement clinical QTc assessment.

Abstract 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 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.

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.

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).

Introduction: Characterization of the incidence of spontaneous arrhythmias to identify possible drug-related ef-fects is often an important part of the analysis in safety pharmacology studies using telemetry.Methods: A retrospective analysis in non-clinical species with and without telemetry transmitters was conducted. Electrocardiograms (24 h) from male and female beagle dogs (n = 131), Go center dot ttingen minipigs (n = 108) and cynomolgus non-human primates (NHP; n = 78) were analyzed.Results: Ventricular tachycardia (VT) was observed in 3% of the dogs but was absent in minipigs and NHPs. Ventricular fibrillation (VF) was not observed in the 3 species. Ventricular premature beats (VPBs) were more frequent during daytime and atrioventricular blocks (AVBs) were more frequent at night in all species. A limited number of animals exhibited a high arrhythmia frequency and there was no correlation between animals with higher frequency of an arrhythmia type and the frequency of other arrythmias in the same animals. Clinical chemistry or hematology parameters were not different with or without telemetry devices. NHP with a trans-mural left ventricular pressure (LVP) catheter exhibited a greater incidence of VPBs and PJCs compared to telemetry animals without LVP. Discussion: All species were similar with regards to the frequency of ventricular ectopic beats (26-46%) while the dog seemed to have more frequent junctional complexes and AVB compared to NHP and minipigs. Arrhythmia screening may be considered during pre-study evaluations, to exclude animals with abnormally high arrhythmia incidence.

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).