QT Study Research Articles

Concentration-QTc analysis of soticlestat in healthy adults: An alternative to a thorough QT study.

This study aimed to examine the cardiac and overall safety and pharmacokinetic (PK) profiles of soticlestat (TAK-935), an oral, first-in-class selective cholesterol 24-hydroxylase inhibitor. Data came from a randomised, phase 1 study of soticlestat in 33 healthy Japanese adults (NCT04461483); 24 adults in Part 1 (single-dose soticlestat 200-1200 mg or placebo) and 9 in Part 2 (soticlestat 100-300 mg twice daily or placebo for 21 days). PK sample collection was paired with 12-lead electrocardiogram data from continuous Holter recordings. The concentration-QTc relationship was analysed using a linear mixed-effects model. QTc prolongation safety margins were determined for two scenarios of calculated high clinical exposures: scenario 1 (NCT05064449) involved coadministration of single-dose soticlestat 300 mg with itraconazole or mefenamic acid and scenario 2 (NCT05098054) involved single-dose soticlestat 300 mg administration in participants with mild/moderate hepatic impairment (implementing a 3-fold dose reduction for moderate severity). Based on concentration-QTc analysis, placebo-corrected change-from-baseline QT values (90% confidence intervals), corrected for heart rate (Fridericia's method), were 0.94 ms (-2.35, 4.23) for soticlestat and 0.63 ms (-3.15, 4.41) for its N-oxide metabolite plasma concentrations at therapeutic doses (soticlestat 300 mg twice daily); safety margins were >2-fold for scenarios of calculated high clinical exposures. No (Part 1) and five (83.3%; Part 2) participants experienced treatment-emergent adverse events (all mild). There was no evidence for QT prolongation with soticlestat at therapeutic doses or in two scenarios of high clinical exposures, which resulted in regulatory agencies waiving requirements of a thorough QT study. Safety/PK findings aligned with previous soticlestat clinical studies.

Cagrilintide is not associated with clinically relevant QTc prolongation: A thorough QT study in healthy participants.

The combination of cagrilintide and semaglutide (CagriSema) is being developed for the treatment of obesity and type 2 diabetes. The objective of this thorough QT study was to confirm that cagrilintide does not result in a clinically relevant prolongation in cardiac repolarization compared with placebo. This was a double-blind study (NCT05804162) in which healthy participants were randomized to cagrilintide, administered as a once-weekly subcutaneous injection dose escalated to 4.5 mg, or a placebo. The primary end point was the time-matched change from baseline in Fridericia heart rate-corrected QT interval (QTcF) at 12-, 24-, 48- and 72 h after the last cagrilintide 4.5-mg dose. To conclude that cagrilintide does not induce a clinically relevant prolongation, the upper limit of the two-sided 90% confidence interval (CI) for the treatment difference at each of the four time points must fall below 10 ms. To establish QT assay sensitivity, participants in the placebo arms received a single 400-mg oral moxifloxacin dose as a positive control and moxifloxacin placebo in a nested cross-over fashion. A total of 105 participants received cagrilintide (n = 53) or placebo (n = 52). No clinically relevant QTcF prolongation occurred after the last cagrilintide 4.5-mg dose; the upper limits of the two-sided 90% CIs of the placebo-adjusted QTcF changes from baseline were below 10 ms at all time points. QT assay sensitivity was demonstrated with moxifloxacin as a positive control. Cagrilintide did not result in clinically relevant QTcF prolongation, indicating no increased risk of ventricular tachyarrhythmias.

Meta-analysis application to hERG safety evaluation in clinical trials

ABSTRACT One objective of meta-analysis, which synthesizes evidence across multiple studies, is to assess the consistency and investigate the heterogeneity across studies. In this project, we performed a meta-analysis on moxifloxacin (positive control in QT assessment studies) data to characterize the exposure–response relationship and determine the safety margin associated with 10-msec QTc effects for moxifloxacin based on 26 thorough QT studies submitted to the FDA. Multiple meta-analysis methods were used (including two novel methods) to evaluate the exposure–response relationship and estimate the critical concentration and the corresponding confidence interval of moxifloxacin associated with a 10-msec QTc effect based on the concentration-QTc models. These meta-analysis methods (aggregate data vs. individual participant data; fixed effect vs. random effect) were compared in terms of their precision and robustness. With the selected meta-analysis method, we demonstrated the homogeneity and heterogeneity of the moxifloxacin concentration-QTc relationship in studies. We also estimated the critical concentration of moxifloxacin that can be used to calculate the hERG safety margin of this drug.

Abstract Mo043: Advanced waveform analysis of the electrocardiogram signals using complementary signal processing techniques to investigate the response to a QTc prolonging drug vs control including food effect.

Background: Thorough QT studies using Electrocardiogram data, are a well-established method for testing the pro-arrhythmic propensity of drugs performed during drug development. ECG analysis is currently reduced to simplified biomarkers, such as rate, intervals and amplitudes. However, ECG waveforms are complex and generally sampled with high fidelity 125-1000 Hz. Our novel mathematical method, Symmetric Projection Attractor Reconstruction analyses the morphology and variability of such waveforms, using every data point to generate a new, faithful 2D waveform representation termed an attractor. Moxifloxacin know QT prolonging medicine and has been shown to cause a mean increase of the QTc interval of 10–14 mS after a single dose of 400 mg. Separately, studies have shown that meals can alter QT interval as well as altering the pharmacokinetic profile of moxifloxacin itself with gender and ethnicity impacting individual responses. In-depth knowledge of these physiological factors could support safer medicines development and clinical use. Purpose: This project investigated the feasibility of SPAR analysis of ECG signals to detect drug induced changes which a higher degree of sensitivity, to support safety evaluation during medicines development Methods: High resolution triplicate 12 lead ECG time-series data from a Phase one study of healthy human volunteers cross over of placebo, moxifloxacin or moxifloxacin + food was retrospectively analysed using SPAR at 0,1 and 6 hours. MATLAB bespoke software tool was used to perform SPAR analyses to transform ECG time-series into corresponding attractors. Corresponding single point measurements were previously obtained as part of the original Phase one study. Results: Initial evaluation of attractors revealed high inter-individual variation, consistent with previous SPAR ECG analysis. Nevertheless, we identified changes in subjects receiving Moxifloxacin +/- food vs placebo control. These changes were not as evident in previously obtained QT intervals. Conclusion: This pilot study illustrates that SPAR is highlighting changes on the ECG in fasted and fed states that are less obvious from QT data alone. Further evaluation of the whole dataset to identify generalisable SPAR features, and their comparison with existing markers is now necessary. The individualised nature of ECGs and corresponding attractors indicates the method may have highest utility in personalised medicine.

Weaning off Thorough QT Studies.

Weaning off Thorough QT Studies.

Should You Run a Dedicated TQT Study? Sponsor and Regulatory Considerations on Substitution Pathways to Assess QT Liability.

Cardiac safety regulatory guidance for drug development has undergone several monumental shifts over the past decade as technological advancements, analysis models and study best practices have transformed this landscape. Once, clinical proarrhythmic risk assessment of a new chemical entity (NCE) was nearly exclusively evaluated in a dedicated thorough QT (TQT) study. However, since the introduction of the International Council for Harmonisation (ICH) E14/S7B Q&A 5.1 and 6.1 TQT substitutions, drug developers are offered an alternative pathway to evaluate proarrhythmic risk during an ascending dose study in healthy volunteers or during a powered patient study, respectively. In addition, the findings as well as the manner in which nonclinical studies are conducted (i.e., utilizing best practices) can dictate the need for a positive control in the clinical study and/or affect the labeling outcome. Drug sponsors are now faced with the option of pursuing a dedicated TQT study or requesting a TQT substitution. Potential factors influencing the choice of pathway include the NCE mechanism of action, pharmacokinetic properties, and safety profile, as well as business considerations. This tutorial will highlight the regulatory framework for integrated arrhythmia risk prediction models to outline drug safety, delineate potential reasons why a TQT substitution request may be rejected and discuss when a standalone TQT is recommended.

A Human-Centered AI Framework for Efficient Labelling of ECGs From Drug Safety Trials.

Drug safety trials require substantial ECG labelling like, in thorough QT studies, measurements of the QT interval, whose prolongation is a biomarker of proarrhythmic risk. The traditional method of manually measuring the QT interval is time-consuming and error-prone. Studies have demonstrated the potential of deep learning (DL)-based methods to automate this task but expert validation of these computerized measurements remains of paramount importance, particularly for abnormal ECG recordings. In this paper, we propose a highly automated framework that combines such a DL-based QT estimator with human expertise. The framework consists of 3 key components: (1) automated QT measurement with uncertainty quantification (2) expert review of a few DL-based measurements, mostly those with high model uncertainty and (3) recalibration of the unreviewed measurements based on the expert-validated data. We assess its effectiveness on 3 drug safety trials and show that it can significantly reduce effort required for ECG labelling-in our experiments only 10% of the data were reviewed per trial-while maintaining high levels of QT accuracy. Our study thus demonstrates the possibility of productive human-machine collaboration in ECG analysis without any compromise on the reliability of subsequent clinical interpretations.

Concentration-QTcF Modeling of Icenticaftor from a Randomized, Placebo- and Positive-Controlled Thorough QT Study in Healthy Participants.

Icenticaftor (QBW251) is a potentiator of the cystic fibrosis transmembrane receptor. Based on its mechanism of action, icenticaftor is expected to provide benefits in patients with chronic obstructive pulmonary disease by restoring mucociliary clearance, which would eventually lead to a reduction of bacterial colonization and related inflammatory cascade. A placebo- and positive-controlled, 4-way crossover thorough QT study was conducted in 46 healthy participants with the objective to assess the effect of therapeutic (300mg twice daily for 6 days) and supratherapeutic (750mg twice daily for 6 days) oral doses of icenticaftor on electrocardiogram parameters, including concentration-corrected QT (QTc) analysis. Moxifloxacin (400mg, oral) was used as a positive control. In the concentration-QTc analysis performed on pooled data from Day 1 and Day 6 (steady state), the estimated population slope was shallow and slightly negative: -0.0012ms/ng/mL. The effect on the Fridericia corrected QT (QTcF) interval (∆ΔQTcF) was predicted to be -1.3milliseconds at the icenticaftor 300-mg twice-daily peak concentration (geometric mean was 1094ng/mL) and -5.5milliseconds at the 750-mg twice-daily peak concentration (geometric mean Cmax was 4529ng/mL) indicated a mild shortening effect of icenticaftor on QTcF interval length. The results of the by-time-point analysis indicated least squares placebo corrected mean ∆∆QTcF across time points ranged from -7.9 to 0.1milliseconds at 1 and 24hours after dosing both on Day 6 in the 750-mg dose group compared with -3.7 to 1.6milliseconds at 1.5 and 24 hours after dosing on Day1 in the 300-mg dose group. Assay sensitivity was demonstrated with moxifloxacin. The large accumulation of exposures, especially the 4.3-fold increase in peak plasma concentration observed at the icenticaftor 750-mg twice-daily dosage compared with Icenticaftor 300mg twice daily (2.3-fold) on Day 6 provided a large concentration range (up to 9540ng/mL) to evaluate the effect of icenticaftor on ΔΔQTcF. Based on the concentration-QTc analysis, an effect on ΔΔQTcF exceeding 10milliseconds can be excluded within the full observed ranges of plasma concentrations on icenticaftor, up to approximately 9540ng/mL. Icenticaftor at the studied doses demonstrated a mild shortening in QTcF, which is unlikely to be of clinical relevance in a therapeutic setting.

Abstract 13543: Novel Genes That Regulate QT Interval in Taiwanese Cohort

Introduction: QT interval denoted repolarization of the ventricule. QT intervals prolongation or shortening would lead patients prone to sudden cardiac death, i.e. Long QT or Short QT syndrome. There are many genes that have been reported to be related to QT interval changes. In this study, we used Genome wide association study(GWAS) to search for genes that regulate QT interval in a large Taiwanese cohort. Methods: We collected 13020 samples and did GWAS study. We collect ECG and analyze QTc interval by standard method. We search for genes and SNP have correlation with QT interval and used Taiwan Biobank as control. The QTc was measured as continuous variables. A P<10 -8 was considered significant variants. Results: In this study, we found many variants that regulate QT interval. (Figure 1). The variants included rs36092684 encoding C1orf132 which was long none coding RNA (never reported before), rs846111 that influences QT interval, 1:162021296:A:ATTG (a novel variants non reported yet), rs12143965, encoding NME7 ( ATP1B1 was a strong functional candidate, although NME7 could not be excluded without functional validation), rs10490255 encoding SLC8A1 Na + -Ca ++ exchanger that wound prolonged QT, rs16862199, encoded SLC19A2 genes that was associated with Thiamine-responsive megaloblastic anemia (TRMA), in such patients, their QT prolonged, rs2277923, encoding NKS2-5 that would cause dilated cardiomyopathy, conduction disorder, long QT, tetralogy of Fallot, rs144500919 (a novel SNP), rs12665409 encoding SLC35F1 that affects QT interval, and rs3778873(KCNH2), rs2074239 (KCNQ1). Conclusion: In this large Taiwanese QT study, we identified variants that would regulate QT interval. Some were reported before, such in QTGEN or QTSCD studies, and others were novel. The novel variants warrant further functional studies.

Unbiased and efficient estimation of causal treatment effects in crossover trials.

We introduce causal inference reasoning to crossover trials, with a focus on thorough QT (TQT) studies. For such trials, we propose different sets of assumptions and consider their impact on the modeling strategy and estimation procedure. We show that unbiased estimates of a causal treatment effect are obtained by a g-computation approach in combination with weighted least squares predictions from a working regression model. Only a few natural requirements on the working regression and weighting matrix are needed for the result to hold. It follows that a large class of Gaussian linear mixed working models lead to unbiased estimates of a causal treatment effect, even if they do not capture the true data-generating mechanism. We compare a range of working regression models in a simulation study where data are simulated from a complex data-generating mechanism with input parameters estimated on a real TQT data set. In this setting, we find that for all practical purposes working models adjusting for baseline QTc measurements have comparable performance. Specifically, this is observed for working models that are by default too simplistic to capture the true data-generating mechanism. Crossover trials and particularly TQT studies can be analyzed efficiently using simple working regression models without biasing the estimates for the causal parameters ofinterest.

The new S7B/E14 Q&A document provides additional opportunities to replace the thorough QT study.

Since 2015, concentration-QTc analysis can be used to exclude that a drug has a concerning effect on the QTc interval. This has enabled replacing the designated TQT study by implementation of serial ECGs into routine clinical pharmacology studies, such as the First-in-Human (FIH) study. This has led to an increased proportion of FIH studies with this added objective of QT evaluation with the intention of replacing the TQT study. With the more recent, February 2022 revision of the S7B/E14 Q&A document, nonclinical assays/studies can be brought into the process of regulatory decisions at the time of marketing application. If the hERG and the non-rodent in vivo study are conducted according to described best practices, the previous requirement that a QTc effect > 10 ms must be excluded in healthy subjects at plasma concentrations 2-fold above what can be seen in patients can be reduced to covering 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 > 10 ms can be excluded, an argument can be made that the drug should be considered as having a low likelihood of proarrhythmic effects due to delayed repolarization. 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. This article is protected by copyright. All rights reserved.

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.

Abstract #1403093: Absence of QT Prolongation Associated with Relacorilant, a Selective Glucocorticoid Receptor Modulator in Development for the Treatment of Cushing Syndrome

QT prolongation is a significant concern for patients with Cushing syndrome (CS). Approximately 26% of men with CS present with QT prolongation, and the risk of cardiac arrhythmic events correlates with the extent of QT prolongation. All currently approved CS medications are associated with QT prolongation, posing a significant risk for the management of CS. Here, we evaluate the impact relacorilant, an investigational selective glucocorticoid receptor modulator, on QT prolongation in healthy volunteers and patients with CS. In a 3-part, single-center, first-in-human study (NCT03508635, “phase 1 study”), 103 healthy volunteers received single or multiple ascending doses of relacorilant (up to 500 mg QD) for up to 14 days; 24 received placebo. In a randomized, partial double-blind, crossover thorough QT study (NCT04795479, “TQT study”), the effect of multiple therapeutic (400 mg QD, n=25) and supra-therapeutic (800 mg QD, n=28) doses of relacorilant on cardiac repolarization was studied in healthy volunteers. A single dose of moxifloxacin (400 mg, n=28) was used as a positive control; 29 participants received placebo. In a single-arm, open-label phase 2 study (NCT02804750, “CS study”), 17 patients with CS received low-dose relacorilant (100–200 mg QD) for 12 weeks and 18 patients received high-dose relacorilant (250–400 mg QD) for 16 weeks. In all studies, ECG data were collected, and the heart rate-corrected QT interval using Fridericia’s formula (QTcF) was assessed. In the phase 1 study, relacorilant up to 500 mg daily did not adversely affect ECG parameters. An effect on placebo-corrected change from baseline QTcF (ΔΔQTcF) above 10 msec was excluded. In the TQT study, moxifloxacin control showed the expected QT prolongation, confirming assay sensitivity. Relacorilant had no adverse effects on ECG parameters and showed effects similar to placebo. Based on concentration-QTc analysis, an effect on ΔΔQTcF exceeding 10 msec was excluded within the full observed range of relacorilant plasma concentrations. These results constitute a negative TQT study. The CS study confirmed that these favorable findings also apply to patients with CS: Throughout the CS study, no significant changes in median QTcF were observed in either dose group. There is an unmet need for medications to treat CS that do not cause QT prolongation and possibly fatal arrhythmias. Based on the TQT study and supported by additional data in healthy volunteers and patients with CS, relacorilant did not show an association with QT prolongation.

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.

Characterisation of the Cardiovascular Effects of a Meal: QTcF Assessment and Further Insights into the Physiological Effects

The electrical activity of the heart, characterised by the QT interval on an electrocardiogram (ECG), serves as a crucial parameter for evaluating cardiac health. Variations in the QT interval, particularly when corrected for heart rate using Fridericia's formula (QTcF), have long been of interest in cardiology and play a pivotal role in assessing cardiac safety in clinical trials. Understanding the influence of meals given at different times on QTcF intervals is essential for the accurate execution of Thorough QT (TQT) studies. Moreover, it has been proposed that this meal-related QT interval shortening could serve as a valuable indicator of assay sensitivity in TQT studies or even as a potential integration of TQT investigations into in Phase I/II studies. This study explores the impact of meals on QTcF intervals, specifically in the context of pharmacodynamic studies and TQT investigations. The primary goal is to gain insights into how different meals and baseline calculations affect QTcF changes and their potential implications for cardiac health and the risk of arrhythmias. Recent research has begun shedding light on the intricate relationship between meal composition, timing, and QTcF alterations. Several studies have investigated the effects of various nutrients, such as carbohydrates, fats, and proteins, on QTcF duration, as well as the implications of postprandial changes. These investigations have unveiled the complex interplay between dietary components and the cardiovascular system, raising essential questions about how our dietary choices may influence cardiac electrophysiology. In this comprehensive meta-analysis, we analyse data from nine studies, all conducted in accordance with Good Clinical Practice and ethical standards. These studies were approved by Ethics Committees and Regulatory authorities. Our analysis focuses on ECG assessments, involving the use of 12-lead ECGs recorded electronically and evaluated by certified cardiologists. We apply the Fridericia formula for QT correction (QTcF), as it has been shown to provide more accurate results across different heart rates compared to other correction methods. Our findings confirm existing literature into the impact of meals on QTcF intervals. We observe a consistent shortening of QTcF following breakfast, exceeding 5 milliseconds, which aligns with the positive control requirement defined by ICH E14, thus demonstrating the validity of our approach. In contrast, the effect of lunch is consistently less than 5 milliseconds across various timepoints and studies, indicating differences in the meal-related QTcF changes. Furthermore, our analysis incorporates gender-based assessments, showing that women exhibit a smaller effect than men, which is significant for breakfast and the fasted condition. These results suggest that the observed QTcF effect post-breakfast is a combination of the meal itself and factors unique to the initial day of a study. This insight holds potential for improving the design and interpretation of cardiac safety studies, particularly in Phase I investigations, and may offer the opportunity to explore the removal of positive control agents like Moxifloxacin, thereby reducing exposure to harmful challenge agents and contributing to the global effort to combat antimicrobial resistance (AMR). In conclusion, this meta-analysis advances our understanding of meal-induced QTcF changes and their significance in cardiac safety assessment, offering the prospect of more efficient and patient-focused drug development practices. This not only contributes to enhanced safety but also supports the reduction of antibiotic consumption, a key element in the global fight against AMR.

Validation of Risk-Stratification Method for the Chronic Atrioventricular Block Cynomolgus Monkey Model and Its Mechanistic Interpretation Using 6 Drugs With Pharmacologically Distinct Profile.

Validation of risk-stratification method for the chronic atrioventricular block cynomolgus monkey model and its mechanistic interpretation was performed using 6 pharmacologically distinct drugs. The following drugs were orally administered in conscious state, astemizole: 1, 5, and 10 mg/kg (n = 6); haloperidol: 1, 10, and 30 mg/kg (n = 5); amiodarone: 30 mg/kg (n = 4); famotidine: 10 mg/kg (n = 4); levofloxacin: 100 mg/kg (n = 4); and tolterodine: 0.2, 1, and 4.5 mg/kg (n = 4). Astemizole of 5 and 10 mg/kg significantly prolonged ΔΔQTcF, whereas no significant change was observed by the others. Torsade de pointes (TdP) was induced by astemizole of 5 and 10 mg/kg in 3/6 and 6/6, and by haloperidol of 10 and 30 mg/kg in 1/5 and 1/5, respectively, which was not observed in the others. Torsadogenic risk of the drugs was quantified using the criteria for the monkey model specified in our previous study. Namely, high-risk drugs induced TdP at ≤ 3 times of their maximum clinical daily dose. Intermediate-risk drugs did not induce TdP at this dose range, but induced it at higher doses. Low/no-risk drugs never induced TdP at any dose tested. The magnitude of risk was intermediate for astemizole and haloperidol, and low/no risk for the others. The prespecified, risk-stratification method for the monkey model may solve the issue existing between nonclinical models and patients with labile repolarization, which can reinforce the regulatory decision-making and labeling at time of marketing application of nondouble-negative drug candidate (hERG assay positive and/or in vivo QT study positive).

A Randomized Thorough QT Study of Apomorphine Sublingual Film in Patients With Parkinson's Disease.

A randomized thorough QT study was conducted to assess the effects of apomorphine sublingual film (SL‐APO) on corrected QT interval (QTc) and other cardiac conduction parameters in patients with Parkinson's disease (PD) and “OFF” episodes. Patients were titrated to an SL‐APO dose that resulted in FULL “ON,” followed by up to two additional doses (maximum 60 mg), then randomized at the highest tolerated dose to a treatment sequence of SL‐APO, placebo, and moxifloxacin (400 mg, positive control) in a three‐way crossover design. Changes from baseline in time‐matched, placebo‐adjusted Fridericia‐corrected QTc interval (ΔΔQTcF) and Bazett‐corrected QTc interval (ΔΔQTcB) were analyzed from postdose electrocardiograms. Forty patients were randomized and received single doses of study treatments. Upper limits of 90% confidence intervals (CIs) for ΔΔQTcF of SL‐APO were below the 10‐millisecond regulatory threshold at all prespecified timepoints, demonstrating no clinically significant effect on QTcF. Lower limits of 90% CIs for ΔΔQTcF of moxifloxacin exceeded the 5‐millisecond regulatory threshold at all timepoints up to 3 hours, confirming assay sensitivity. SL‐APO had no clinically meaningful effects on QTcB, PR/QRS intervals, heart rate, or electrocardiogram‐derived morphology (EudraCT identifier: 2016‐001762‐29; ClinicalTrials.gov identifier: NCT03187301).

ECG Evaluation as Part of the Clinical Pharmacology Strategy in the Development of New Drugs: A Review of Current Practices and Opportunities Based on Five Case Studies.

The International Conference on Harmonization (ICH) E14 document was revised in 2015 to allow concentration-corrected QT interval (C-QTc) analysis to be applied to data from early clinical pharmacology studies to exclude a small drug-induced effect on QTc. Provided sufficiently high concentrations of the drug are obtained in the first-in-human (FIH) study, this approach can be used to obviate the need for a designated thorough QT (TQT) study. The E14 revision has resulted in a steady reduction in the number of TQT studies and an increased use of FIH studies to evaluate electrocardiogram (ECG) effects of drugs in development. In this review, five examples from different sponsors are shared in which C-QTc analysis was performed on data from FIH studies. Case1 illustrates a clearly negative C-QTc evaluation, despite observations of QTc prolongation at high concentrations in nonclinical studies. In case2 C-QTc analysis of FIH data was performed prior to full pharmacokinetic characterization in patients, and the role of nonclinical assays in an integrated risk assessment is discussed. Case3 illustrates a positive clinical C-QTc relationship, despite negative nonclinical assays. Case4 demonstrates a strategy for characterizing the C-QTc relationship for a nonracemic therapy and formulation optimization, and case5 highlights an approach to perform a preliminary C-QTc analysis early in development and postpone the definitive analysis until proof of efficacy is demonstrated. The strategy of collecting and storing ECG data from FIH studies to enable an informed decision on whether and when to apply C-QTc analysis to obviate the need for a TQT study is described.

How to Successfully Generate an Alternative Approach to a Thorough QT Study: GLPG1972 as an Example.

During development of a drug, the requirement of evaluating the proarrhythmic risk and delayed repolarization needs to be fulfilled. Would it be possible to create an alternative to a thorough QT (TQT) study or is there a need to perform a dedicated TQT study? How is an alternative approach generated, what information is available, and which instructions are considered missing today to generate such an approach? This tutorial describes the considerations and path followed to create an early and feasible alternative to a TQT study using experience-based insights from a successful application to the US Food and Drug Administration for GLPG1972, an ADAMTS-5 inhibitor, and discusses the approach used in light of the current guidelines and literature.

Postmarketing pharmacovigilance: Remdesivir and cardiovascular events.

Postmarketing pharmacovigilance: Remdesivir and cardiovascular events.