Pharmacokinetic-pharmacodynamic modeling in the data analysis and interpretation of drug-induced QT/QTc prolongation

QT Interval, Antipsychotics and Correlates Among Patients with Schizophrenia: Cross-Sectional Data from the Multicentric Real-World FACE-SZ

BACKGROUND

The life expectancy of patients with schizophrenia is reduced, partly due to cardiovascular diseases. Antipsychotics are associated with QT interval prolongation, which is a risk factor for arrhythmia and cardiac arrest. The differences between antipsychotic with regard to QT interval prolongation are not well understood.

OBJECTIVE

The aim was to compare the QT values associated with different antipsychotics within a real-world population of subjects with clinically stable forms of schizophrenia.

METHODS

The FACE-SZ cohort comprises subjects with psychotic disorders, referred to schizophrenia expert cents. QT interval was measured, as well as all treatments (psychotropic and others). The following maintenance treatment for schizophrenia was analysed cross-sectionally: aripiprazole, clozapine, haloperidol, amisulpride, olanzapine, quetiapine, risperidone. Age, sex, smoking status, body mass index, blood potassium levels, and the co-prescription of another QT-prolonging treatment were used as adjustment factors in multivariable linear regression analyses.

RESULTS

Among 792 patients, the mean corrected QT (QTc) interval in the sample of patients under monotherapy was 407 ms. The mean age was 31.7 years, and the majority were male (73.3 %). In comparison to the rest of the sample, clozapine was associated with a longer QTc interval (β = 0.012, 95% CI [0.006-0.018]), while aripiprazole was significantly associated with a shorter QTc interval (β = - 0.010, 95% CI [- 0.016 to - 0.005]). Other antipsychotics were not associated with significant variations of the QTc.

CONCLUSIONS

The prescription of antipsychotics should always be accompanied by close monitoring of the QTc interval to prevent the risk of severe cardiac arrhythmia, particularly concerning clozapine.

Concentration-QTcF analysis of quizartinib in patients with newly diagnosed FLT3-internal-tandem-duplication-positive acute myeloid leukemia

Quizartinib prolongs QT interval through inhibition of the slow delayed rectifier potassium current (IKs). We used non-linear mixed-effects modeling to explore the relationship between quizartinib and its pharmacologically active metabolite AC886 and the Fridericia-corrected QT interval (QTcF) in newly diagnosed acute myeloid leukemia (AML) patients. We evaluated linear and non-linear drug effect models, using triplicate QTcF measurements with available time-matched pharmacokinetic samples from the Phase 3 QuANTUM-First trial. The effect of intrinsic and extrinsic factors on model parameters was tested using stepwise covariate model building. Simulations were conducted to predict the change from baseline in QTcF (ΔQTcF) at the maximum concentration at steady-state (Cmax,ss) for quizartinib maintenance daily doses of 30 and 60 mg. The concentration-QTcF (C-QTcF) relationship was best described by a sigmoidal maximum effect model. After accounting for the effect of quizartinib, including AC886 concentrations did not further explain changes in QTcF. Circadian variations in QTcF were described using an empirical change from baseline based on clock times. Age and hypokalaemia were identified as statistically significant covariates on baseline QTcF; no covariates were found to impact the C-QTcF relationship. The median model-predicted ΔQTcF at Cmax,ss was 18.4 ms (90% confidence interval (CI): 16.3-20.5) at 30 mg and 24.1 ms (90% CI: 21.4-26.6) at 60 mg. In conclusion, in newly diagnosed AML patients, ΔQTcF increased non-linearly with increasing quizartinib concentrations. The predicted ΔQTcF increase at Cmax,ss supports the proposed dose adaptation based on observed QTcF and the dose reduction in case of strong cytochrome P450 3A (CYP3A) inhibitors coadministration.

Identification of urine biomarkers predictive of prolonged QTc interval in multidrug-resistant tuberculosis patients treated with bedaquiline

The most frequent adverse event associated with bedaquiline (BDQ) is the QTc interval prolongation; however, there was no biomarkers that could be used to predict the occurrence of QTc prolongation in BDQ-treated patients. In this study, we employed the ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS) to generate metabolic profiling for the discovery of potential predictive urine biomarkers of QTc prolongation in these patients. Untargeted metabolomic technique was used to concentrate the differential metabolic pathway, and targeted metabolomic technique was subsequently performed to identify predictive biomarkers for QTc prolongation. A total of 45 rifampicin-resistant TB (RR-TB) and multidrug-resistant TB (MDR-TB) patients were enrolled in our study, including 15 RR/MDR-TB patients with QTc interval prolongation (QIP) and 30 RR/MDR-TB patients with QTc interval un-prolongations (QIU). Untargeted technique revealed that the lipid metabolism was the most differential metabolic pathway between two groups. Further targeted technique identified four differential metabolites, including betaine, LPE (18:2), LPE (20:3), and LPE (20:4). The combined analysis of metabolisms revealed that the combined use of LPE (20:3) and LPE (20:4) had the best performance for predicting the occurrence of QTc prolongation in TB patients, yielding a sensitivity of 87.4% and a specificity of 78.5%. In addition, with the progression of BDQ treatment, the LPEs exhibited persistent difference in the BDQ-treated TB patients experiencing QTc interval prolongation. In conclusion, our data demonstrate that the combined use of LPE (20:3) and LPE (20:4) yields promising performance for predicting the occurrence of QTc interval prolongation in BDQ-treated patients.

Serial electrocardiogram recordings revealed a high prevalence of QT interval prolongation in patients with tuberculosis receiving fluoroquinolones

BACKGROUND

Fluoroquinolones, crucial components of treatment regimens for drug-resistant tuberculosis (TB), are associated with QT interval prolongation and risks of fatal cardiac arrhythmias. However, few studies have explored dynamic changes in the QT interval in patients receiving QT-prolonging agents.

METHODS

This prospective cohort study recruited hospitalized patients with TB who received fluoroquinolones. The study investigated the variability of the QT interval by using serial electrocardiograms (ECGs) recorded four times daily. This study analyzed the accuracy of intermittent and single-lead ECG monitoring in detecting QT interval prolongation.

RESULTS

This study included 32 patients. The mean age was 68.6 ± 13.2 years. The results revealed mild-to-moderate and severe QT interval prolongation in 13 (41%) and 5 (16%) patients, respectively. The incremental yields in sensitivity of one to four daily ECG recordings were 61.0%, 26.1%, 5.6%, and 7.3% in detecting mild-to-moderate QT interval prolongation, and 66.7%, 20.0%, 6.7%, and 6.7% in detecting severe QT interval prolongation. The sensitivity levels of lead II and V5 ECGs in detecting mild-to-moderate and severe QT interval prolongation exceeded 80%, and their specificity levels exceeded 95%.

CONCLUSION

This study revealed a high prevalence of QT interval prolongation in older patients with TB who receive fluoroquinolones, particularly those with multiple cardiovascular risk factors. Sparsely intermittent ECG monitoring, the prevailing strategy in active drug safety monitoring programs, is inadequate owing to multifactorial and circadian QT interval variability. Additional studies performing serial ECG monitoring are warranted to enhance the understanding of dynamic QT interval changes in patients receiving QT-prolonging anti-TB agents.

Characterizing Associations of QTc Interval with Nocturnal Glycemic Control in Children with Type 1 Diabetes

An association between QT prolongation (Bazett's corrected QT interval, QTcB) of 7 milliseconds and nocturnal hypoglycemia, compared with euglycemia, has been observed in children with type 1 diabetes (T1D). The objective of this pharmacometric analysis was to understand this association and other sources of QTc variability quantitatively. Data originate from a prospective observational study (25 cardiac healthy children with T1D, aged 8.1-17.6 years) with continuous subcutaneous glucose and electrocardiogram measurements for 5 consecutive nights. Mixed-effect modeling was used to compare QTcB with individual heart-rate correction (QTcI). Covariate models accounting for circadian variation, age, and sex were evaluated, followed by an investigation of glucose-QTc relationships (with univariable and combined adjusted analysis). Factors potentially modifying sensitivity to QTc lengthening were explored. Random inter-individual variability was reduced in the QTcI versus QTcB model (±12.6 vs 14.1 milliseconds), and was further reduced in the adjusted covariate model (±9.7 milliseconds), accounting for the significantly (P < .01) shortened QTc in adolescent boys (-14.6 milliseconds), circadian variation (amplitude, 19.2 milliseconds; shift, 2.9 hours), and linear glucose-QTc relationship (delay rate, 0.56-h ; slope, 0.76 milliseconds [95%CI 0.67- 0.85 milliseconds] per 1 mmol/L decrease in glucose). Differing sensitivity was suggested to depend upon hemoglobin A1c (HbA1c), T1D duration, and time spent in nocturnal hypoglycemia. In conclusion, a clinically mild association of QTc prolongation with nocturnal hypoglycemia was confirmed and quantified in this pharmacometric analysis, and the longest QTc interval was around 03:00 a.m. The characterized delayed association with glucose highlights the relevance of both the extent and the duration of hypoglycemia. Further clinical studies are warranted to investigate whether these factors contribute to increased risk of hypoglycemia-associated cardiac arrhythmia in children with T1D.

Modeling time-delayed concentration-QT effects with ACT-1014-6470, a novel oral complement factor 5a receptor 1 (C5a1 receptor) antagonist

The novel oral complement factor 5a receptor 1 antagonist ACT-1014-6470 was well tolerated in single- and multiple-ascending dose studies, including 24 h Holter electrocardiogram (ECG) recordings evaluating its cardiodynamics based on data from single doses of 30-200 mg and twice-daily (b.i.d.) dosing of 30-120 mg for 4.5 days. By-time point, categorical, and morphological analyses as well as concentration-QT modeling and simulations were performed. No relevant effect of ACT-1014-6470 on ECG parameters was observed in the categorical and morphological analyses. After single-dose administration, the by-time point analysis indicated a delayed dose-dependent increase in placebo-corrected change from baseline in QT interval corrected with Fridericia's formula (ΔΔQTcF) at >6 h postdose. After b.i.d. dosing, ΔΔQTcF remained elevated during the 24-h recording period, suggesting that the effect was not directly related to ACT-1014-6470 plasma concentration. The concentration-QT model described change from baseline in QTcF (ΔQTcF)-time profiles best with a 1-oscillator model of 24 h for circadian rhythm, an effect compartment, and a sigmoidal maximum effect model. Model-predicted ΔΔQTcF was derived for lower doses and less-frequent dosing than assessed clinically. Median and 90% prediction intervals of ΔΔQTcF for once-daily doses of 30 mg and b.i.d. doses of 10 mg did not exceed the regulatory threshold of 10 ms but would achieve ACT-1014-6470 plasma concentrations enabling adequate target engagement. Results from cardiodynamic assessments identified dose levels and dosing regimens that could be considered for future clinical trials, attempting to reduce QT liability.

Pharmacometric and Electrocardiographic Evaluation of Chloroquine and Azithromycin in Healthy Volunteers

Chloroquine and azithromycin were developed in combination for the preventive treatment of malaria in pregnancy, and more recently were proposed as coronavirus disease 2019 (COVID‐19) treatment options. Billions of doses of chloroquine have been administered worldwide over the past 70 years but concerns regarding cardiotoxicity, notably the risk of torsades de pointes (TdP), remain. This investigation aimed to characterize the pharmacokinetics and electrocardiographic effects of chloroquine and azithromycin observed in a large previously conducted healthy volunteer study. Healthy adult volunteers (n = 119) were randomized into 5 arms: placebo, chloroquine alone (600 mg base), or chloroquine with either 500 mg, 1,000 mg, or 1,500 mg of azithromycin all given daily for 3 days. Chloroquine and azithromycin levels, measured using liquid‐chromatography tandem mass spectrometry, and electrocardiograph intervals were recorded at frequent intervals. Time‐matched changes in the PR, QRS, and heart rate‐corrected JT, and QT intervals were calculated and the relationship with plasma concentrations was evaluated using linear and nonlinear mixed‐effects modeling. Chloroquine and azithromycin pharmacokinetics were described satisfactorily by two‐ and three‐compartment distribution models, respectively. No drug–drug interaction between chloroquine and azithromycin was observed. Chloroquine resulted in concentration‐dependent prolongation of the PR, QRS, JTc and QTc intervals with a minimal additional effect of azithromycin. QRS widening contributed ~ 28% of the observed QT prolongation. Chloroquine causes significant concentration‐dependent delays in both ventricular depolarization and repolarization. Co‐administration of azithromycin did not significantly increase these effects. The arrhythmogenic risk of TdP associated with chloroquine may have been substantially overestimated in studies which did not separate electrocardiograph QRS and JT prolongation.

Exposure-safety analysis of QTc interval and transaminase levels following bedaquiline administration in patients with drug-resistant tuberculosis

Bedaquiline (BDQ) has shown great value in the treatment of multidrug‐resistant tuberculosis (MDR‐TB) in recent years. However, exposure–safety relationships must be explored to extend the use of BDQ. Two reported safety findings for BDQ are prolongation of the QTc interval and elevation of transaminase levels. In this study, we investigated the potential relationships between BDQ and/or its main metabolite (M2) pharmacokinetic (PK) metrics and QTcF interval or transaminase levels in patients with MDR‐TB using the approved dose regimen. Data from 429 patients with MDR‐TB from two phase IIb studies were analyzed via nonlinear mixed‐effects modeling. Individual model‐predicted concentrations and summary PK metrics were evaluated, respectively, in the QTcF interval and transaminase level exposure–response models. Investigation of further covariate effects was performed in both models. M2 concentrations were found to be responsible for the drug‐related QTcF increase in a model accounting for circadian rhythm patterns, time on study, effect of concomitant medication with QT liability, and patient demographics. Simulations with the final model suggested that doses higher than the approved dose (leading to increased M2 concentrations) are not expected to lead to a critical QTcF interval increase. No exposure–safety relationship could be described with transaminase levels despite previous reports of higher levels in patients treated with BDQ. The developed longitudinal models characterized the role of M2 concentrations in QTc interval prolongation and found no concentration dependency for transaminase level elevation, together suggesting that BDQ exposure at the high end of the observed range may not be associated with a higher risk of safety events.

Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity

Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).

Effect of Clofazimine Concentration on QT Prolongation in Patients Treated for Tuberculosis

Clofazimine is classified as a WHO group B drug for the treatment of rifampin-resistant tuberculosis. QT prolongation, which is associated with fatal cardiac arrhythmias, is caused by several antitubercular drugs, including clofazimine, but there are no data quantifying the effect of clofazimine concentration on QT prolongation. Our objective was to describe the effect of clofazimine exposure on QT prolongation. Fifteen adults drug-susceptible tuberculosis patients received clofazimine monotherapy as 300 mg daily for 3 days, followed by 100 mg daily in one arm of a 2-week, multiarm early bactericidal activity trial in South Africa. Pretreatment Fridericia-corrected QT (QTcF) (105 patients, 524 electrocardiograms [ECGs]) and QTcFs from the clofazimine monotherapy arm matched with clofazimine plasma concentrations (199 ECGs) were interpreted with a nonlinear mixed-effects model. Clofazimine was associated with significant QT prolongation described by a maximum effect (E_max) function. We predicted clofazimine exposures using 100-mg daily doses and 2 weeks of loading with 200 and 300 mg daily, respectively. The expected proportions of patients with QTcF change from baseline above 30 ms (ΔQTcF > 30) were 2.52%, 11.6%, and 23.0% for 100-, 200-, and 300-mg daily doses, respectively. At steady state, the expected proportion with ΔQTcF of >30 ms was 23.7% and with absolute QTcF of >450 ms was 3.42% for all simulated regimens. The use of loading doses of 200 and 300 mg is not predicted to expose patients to an increased risk of QT prolongation, compared with the current standard treatment, and is, therefore, an alternative option for more quickly achieving therapeutic concentrations.

Population pharmacokinetic/pharmacodynamic modeling of delayed effect of escitalopram-induced QT prolongation

BACKGROUND

A thorough QT study identified that escitalopram-induced QT prolongation was delayed. This study thus aimed to develop a population pharmacokinetic (PK)/pharmacodynamic (PD) model to characterize the relationship between escitalopram concentrations and the delayed effect on QT prolongation.

METHODS

The data of completed subjects who had placebo (n=36) and a single dose of 20 mg escitalopram (n=33) from a previous thorough QT study were used. Population PK/PD analysis was performed by nonlinear mixed-effects modeling. A escitalopram concentration-drug effect model was developed with estimated individual PK and baseline QT parameters. To explain the relationship between escitalopram concentrations and QT prolongation delay, an effect compartment model was utilized.

RESULTS

A two-compartment model with first-order absorption and lag time and first-order elimination adequately described the PK of escitalopram. The circadian rhythm of baseline QT interval was best explained by two harmonic cosine functions. A linear model properly characterized escitalopram-induced QT prolongation. The average estimated maximal QT prolongation was 5.4 ms (range: 1.9-7.6 ms). The equilibrium half-life of delayed QT prolongation was 1.9 h. The drug effect of QTc change compared with that at baseline remained relatively constant from 1.3 to 3.5 ms over 24 h, and the maximum QTc change occurred with a 3-h delay after the time to the maximum plasma concentration.

LIMITATIONS

We did not include genetic polymorphisms, such as CYP2C19, as potential covariates owing to limited information.

CONCLUSIONS

These results may provide useful information on when to monitor electrocardiogram in patients who require intensive care after drug administration.

Concentration-QTc analysis of quizartinib in patients with relapsed/refractory acute myeloid leukemia

PURPOSE

This analysis evaluated the relationship between concentrations of quizartinib and its active metabolite AC886 and QT interval corrected using Fridericia's formula (QTcF) in patients with relapsed/refractory acute myeloid leukemia (AML) treated in the phase 3 QuANTUM-R study (NCT02039726).

METHODS

The analysis dataset included 226 patients with AML. Quizartinib dihydrochloride was administered as daily doses of 20, 30, and 60 mg. Nonlinear mixed-effects modeling was performed using observed quizartinib and AC886 concentrations and time-matched mean electrocardiogram measurements.

RESULTS

Observed QTcF increased with quizartinib and AC886 concentrations; the relationship was best described by a nonlinear maximum effect (Emax) model. The predicted mean increase in QTcF at the maximum concentration of quizartinib and AC886 associated with 60 mg/day was 21.1 ms (90% CI, 18.3-23.6 ms). Age, body weight, sex, race, baseline QTcF, QT-prolonging drug use, hypomagnesemia, and hypocalcemia were not significant predictors of QTcF. Hypokalemia (serum potassium < 3.5 mmol/L) was a statistically significant covariate affecting baseline QTcF, but no differences in ∆QTcF (change in QTcF from baseline) were predicted between patients with versus without hypokalemia at the same quizartinib concentration. The use of concomitant QT-prolonging drugs did not increase QTcF further.

CONCLUSION

QTcF increase was dependent on quizartinib and AC886 concentrations, but patient factors, including sex and age, did not affect the concentration-QTcF relationship. Because concomitant strong cytochrome P450 3A (CYP3A) inhibitor use significantly increases quizartinib concentration, these results support the clinical recommendation of quizartinib dose reduction in patients concurrently receiving a strong CYP3A inhibitor.

CLINICAL TRIAL REGISTRATION

NCT02039726 (registered January 20, 2014).

Concentration-QTc analysis for single arm studies

Concentration-QTc (C-QTc) modeling is being increasingly used in phase 1 studies. For studies without a placebo arm (single arm studies), the scientific whitepaper by Garnett et al. ( https://doi.org/10.1007/s10928-017-9558-5 ) states that time-matched baseline adjustments may minimize the effect of diurnal variation in QTc intervals, and categorical time effects are not needed in the model. However, how diurnal variations can be accounted for when only pre-dose baselines are available is unclear. This research investigates whether including categorical time effects in the model can adjust diurnal variation in single arm studies with pre-dose baselines, where QTc prolongation is evaluated at a concentration of interest based on ΔQTc at 24 h and ΔΔQTc (a model-derived difference in ΔQTc from concentration zero). To understand the operating characteristics for the models with and without categorical time effects, simulations were conducted under various scenarios considering oncology early phase studies. When the C-QTc relationship is linear, models without categorical time effects provided biased estimates for model parameters and inflated or decreased false negative rates (FNRs) depending on the pattern of diurnal variations in QTc intervals, whereas models with categorical time effects caused no biases and controlled the FNRs. For non-linear C-QTc relationships, ΔΔQTc estimations made using the model with categorical time effects were not robust. Thus, for single arm studies where only pre-dose baselines are available, we recommend collecting QTc measurements at 24 h and estimating ΔQTc at a concentration of interest at 24 h using the C-QTc model with categorical time effects.

PK/PD modeling of a clazosentan thorough QT study with hysteresis in concentration-QT and RR-QT

Clazosentan's potential QT liability was investigated in a thorough QT study in which clazosentan was administered intravenously as a continuous infusion of 20 mg/h immediately followed by 60 mg/h. Clazosentan prolonged the placebo-corrected change-from-baseline QT interval corrected for RR with Fridericia's formula (ΔΔQTcF) with the maximum QT effect occurring 4 h after the maximum drug concentration, apparently associated with vomiting. The delayed effect precluded the standard linear modeling approach. This analysis aimed at characterizing the concentration-QT relationship in consideration of RR-QT hysteresis, concentration-ΔΔQTcF hysteresis, and the influence of vomiting. Nonlinear mixed-effects modeling was applied to characterize pharmacokinetics and pharmacodynamics, i.e., ΔΔQTcF. Simulations were used to predict ΔΔQTcF for expected therapeutic dose used in Phase 3 clinical development. Correction for RR-QT hysteresis did not influence ΔΔQTcF to a relevant extent. Pharmacokinetics of clazosentan were best described by a linear two-compartment model. The delayed QT prolongation was characterized by an indirect-response model with loglinear drug effect. Vomiting had no statistically significant influence on QT prolongation despite apparent differences between subjects vomiting and not vomiting, probably since vomiting occurred mostly after the main QT prolongation. Following a simulated 3-h infusion of 15 mg/h of clazosentan, the upper bound of the predicted 90% CI for mean ΔΔQTcF was expected to exceed the 10-ms regulatory threshold of concern with maximum effect 3.5 h after end of infusion. TRN: NCT03657446, 05 Sep 2018.

Pooled Multicenter Analysis of Cardiovascular Safety and Population Pharmacokinetic Properties of Piperaquine in African Patients with Uncomplicated Falciparum Malaria

Dihydroartemisinin-piperaquine has shown excellent efficacy and tolerability in malaria treatment. However, concerns have been raised of potentially harmful cardiotoxic effects associated with piperaquine. The population pharmacokinetics and cardiac effects of piperaquine were evaluated in 1,000 patients, mostly children enrolled in a multicenter trial from 10 sites in Africa. A linear relationship described the QTc-prolonging effect of piperaquine, estimating a 5.90-ms mean QTc prolongation per 100-ng/ml increase in piperaquine concentration. The effect of piperaquine on absolute QTc interval estimated a mean maximum QTc interval of 456 ms (50% effective concentration of 209 ng/ml). Simulations from the pharmacokinetic-pharmacodynamic models predicted 1.98 to 2.46% risk of having QTc prolongation of >60 ms in all treatment settings. Although piperaquine administration resulted in QTc prolongation, no cardiovascular adverse events were found in these patients. Thus, the use of dihydroartemisinin-piperaquine should not be limited by this concern. (This study has been registered at ClinicalTrials.gov under identifier NCT02199951.).

Evaluation of QT Liability for PF-05251749 in the Presence of Potential Circadian Rhythm Modification

PF-05251749 is a dual inhibitor of casein kinase 1 δ/ε, key regulators of circadian rhythm. As a result of its mechanism of action, PF-05251749 may also change the heart rate corrected QT (QTc) circadian rhythm, which may confound detection of drug-induced QTc prolongation. In this analysis, a nonlinear mixed effect model including a multioscillator function was developed in addition to fitting the prespecified linear mixed effect concentration-QTc model, to identify QTc liability of PF-05251749 in the presence of potential circadian rhythm change. The modeling results suggested lack of clinically meaningful QTc prolongation (upper bound of 90% confidence interval for ∆∆QTc < 10 milliseconds) and that the drug-induced QTc circadian rhythm change was not present. However, simulation results indicated that inference of drug-induced QTc prolongation could be misleading if the drug effect on QTc circadian rhythm is not properly addressed. The modeling and simulation results suggest that prespecification of the concentration-QTc model should be reconsidered for drugs with circadian rhythm modulation potential.

Concentration-response modeling of ECG data from early-phase clinical studies to assess QT prolongation risk of contezolid (MRX-I), an oxazolidinone antibacterial agent

The effects of contezolid (MRX-I, an oxazolidinone antibacterial agent) on cardiac repolarization were evaluated retrospectively using a population modeling approach in a Phase I study incorporating single ascending dose, multiple ascending dose, and food effect assessments. Linear mixed effect models were used to assess the relationships between MRX-I plasma concentrations and QT/QTc/∆QTc (baseline-adjusted), in which different correction methods for heart rate have been included. The upper bound of the one-sided 95% confidence interval (CI) for predicted ∆∆QTc was < 10 ms (ms) at therapeutic doses of MRX-I. Model performance/suitability was determined using diagnostic evaluations, which indicated rationality of one-stage concentration-QT model, as well as C-QT model suggested by Garnett et al. The finding demonstrated that MRX-I may have no clinical effects on the QT interval. Concentration-QT model may be an alternative to conventional thorough QT studies.

Assessment of the effect of erdafitinib on cardiac safety: analysis of ECGs and exposure-QTc in patients with advanced or refractory solid tumors

PURPOSE

To characterize the effect of erdafitinib on electrocardiogram (ECG) parameters and the relationship between erdafitinib plasma concentrations and QTc interval changes in patients with advanced or refractory solid tumors.

METHODS

Triplicate ECGs and continuous 12-lead Holter data were collected in the dose escalation part (Part 1) of the first-in-human study, with doses ranging from 0.5 to 12 mg. Triplicate ECG monitoring continued in Parts 2-4 where 2 dose regimens selected from Part 1 were expanded in prespecified tumor types. Analyses of ECG data included central tendency analyses, identification of categorical outliers and morphological assessment. A concentration-QTc analysis was conducted using a linear mixed-effect model based on extracted time matching Holter data.

RESULTS

Central tendency, categorical outlier, and ECG morphologic analyses from 187 patients revealed no clinically significant effect of erdafitinib on heart rate, atrioventricular conduction or cardiac depolarization (PR and QRS), and no effect on cardiac repolarization (QTc). Concentration-QTc analysis from 62 patients indicated that the slopes of relationship between total and free erdafitinib plasma concentrations and QTcI (mean exponent of 0.395) were estimated as - 0.00269 ms/(ng/mL) and - 1.138 ms/(ng/mL), respectively. The predicted change in QTcI at the observed geometric mean of total and free concentration at the highest therapeutic erdafitinib dose (9 mg daily) was < 10 ms at the upper bound of the two-sided 90% confidence interval.

CONCLUSIONS

ECG data and the concentration-QTc relationships demonstrate that erdafitinib does not prolong QTc interval and has no effects on cardiac repolarization or other ECG parameters. Clinical trial registration numbers NCT01703481, EudraCT: 2012-000697-34.

Models of Variability and Circadian Rhythm in Heart Rate, Blood Pressure, and QT Interval for Healthy Subjects Who Received Placebo in Phase I Trials

This work characterized the time‐course, circadian rhythm, and inherent variability in key cardiovascular variables (heart rate, corrected QT interval, and systolic and diastolic blood pressure) that are routinely collected as part of safety monitoring in phase I trials. Longitudinal data from 1,035 healthy volunteers who received placebo in 65 single‐dose and multiple‐dose phase I trials conducted by AbbVie were compiled and analyzed using nonlinear mixed‐effects modeling. An independent nonlinear mixed‐effects model was developed for each variable, and combinations of cosine functions were used to capture circadian oscillations. Gender, race, age, and body weight were significant covariates for variability in baseline measures, and the contributions of these covariates were quantitatively characterized. Based on the extensive data set analyzed, the developed models represent valuable tools to help contextualize and differentiate inherent variability that can be expected in a typical phase I setting from true drug‐related cardiovascular safety signals. In addition, these placebo models can be used to support exposure–response analyses that estimate treatment‐related effects on the evaluated cardiovascular measures.

Research on the mechanism of drug-drug interaction between salvianolate injection and aspirin based on the metabolic enzyme and PK-PD model: study protocol for a PK-PD trial

Background

Coronary heart disease (CHD) is a common cardiovascular disease accounting for 10–20% mortality by heart disease worldwide. The gold standard treatment to manage CHD is aspirin, which may prevent myocardial infarction and sudden death; however, long-term use of aspirin may increase its side effects. Currently, more and more clinicians are exploring different approaches to use the right combination of medicine to enhance the efficacy and reduce side effects. Salvianolate can significantly inhibit the aggregation and activation of platelets in patients with CHD; however, its optimum combination with western medicine is not established or supported by clinical trial results.

Methods/design

This trial is a prospectively planned, open-labeled, parallel-grouped, single-centered clinical trial with aggregated pharmacodynamics-pharmacokinetics (PK-PD) data. All treatment courses will last for 10 days and blood sample will be acquired before administration on days 8, 9, and 10, and after administration at 5 min, 15 min, 30 min, 45 min, 1 h, 2 h, 4 h, 8 h, 12 h, and 24 h on day 10. This trial uses PK-PD modeling to provide a description of the concentration–effect relationship and an estimate of pharmacological potency of the medicine. The primary outcome will be changes in aspirin esterase and catechol-o-methyltransferase (COMT) activity at different blood concentrations to determine the PK-PD characteristics of the combination of salvianolate and aspirin, followed by analysis of the correlation between exposure level and pharmacodynamic index of the medicines.

Discussion

This trial will aim to evaluate the relationship between changes in the pharmacokinetics and therapeutic effect index in the combined use of salvianolate and aspirin. It also discusses the possible mechanism of medicine combination in the treatment for CHD and provides an experimental basis for a clinically rational medicine combination.

Trial registration

ClinicalTrials.gov, NCT03306550. Registered on 9 October 2017. ClinicalTrials.gov https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S0007D8H&selectaction=Edit&uid=U0003QY8&ts=2&cx=oiuc9g

Electronic supplementary material

The online version of this article (10.1186/s13063-018-2861-7) contains supplementary material, which is available to authorized users.

Evaluation of dependent variable, time effect, covariates, and covariation structure in concentration-QTc modeling: A simulation study

The revised ICH E14 Question and Answer (R3) document issued in December 2015 enables pharmaceutical companies to use concentration-QTc (C-QTc) modeling as the primary analysis for assessing QTc prolongation risk of new drugs. A new approach by including the time effect into the current C-QTc model is introduced. Through a simulation study, we evaluated performances of different C-QTc modeling with different dependent variables, covariates, and covariance structures. This simulation study shows that C-QTc models with ΔQTc being dependent variable without time effect inflate false negative rate and that fitting C-QTc models with different dependent variables, covariates, and covariance structures impacts the control of false negative and false positive rates. Appropriate C-QTc modeling strategies with good control of false negative rate and false positive rate are recommended.

A tutorial on model informed approaches to cardiovascular safety with focus on cardiac repolarisation

Drugs can affect the cardiovascular (CV) system either as an intended treatment or as an unwanted side effect. In both cases, drug-induced cardiotoxicities such as arrhythmia and unfavourable hemodynamic effects can occur, and be described using mathematical models; such a model informed approach can provide valuable information during drug development and can aid decision-making. However, in order to develop informative models, it is vital to understand CV physiology. The aims of this tutorial are to present (1) key background biological and medical aspects of the CV system, (2) CV electrophysiology, (3) CV safety concepts, (4) practical aspects of development of CV models and (5) regulatory expectations with a focus on using model informed and quantitative approaches to support nonclinical and clinical drug development. In addition, we share several case studies to provide practical information on project strategy (planning, key questions, assumptions setting, and experimental design) and mathematical models development that support decision-making during drug discovery and development.

Evaluating cardiac risk: exposure response analysis in early clinical drug development

The assessment of a drug's cardiac liability has undergone considerable metamorphosis by regulators since International Council for Harmonization of Technical Requirement for Pharmaceuticals for Human Use E14 guideline was introduced in 2005. Drug developers now have a choice in how proarrhythmia risk can be evaluated; the options include a dedicated thorough QT (TQT) study or exposure response (ER) modeling of intensive electrocardiogram (ECG) captured in early clinical development. The alternative approach of ER modeling was incorporated into a guidance document in 2015 as a primary analysis tool which could be utilized in early phase dose escalation studies as an option to perform a dedicated TQT trial. This review will describe the current state of ER modeling of intensive ECG data collected during early clinical drug development; the requirements with regard to the use of a positive control; and address the challenges and opportunities of this alternative approach to assessing QT liability.

Assessing QT/QTc interval prolongation with concentration-QT modeling for Phase I studies: impact of computational platforms, model structures and confidence interval calculation methods

Modeling the relationship between drug concentrations and heart rate corrected QT interval (QTc) change from baseline (C-∆QTc), based on Phase I single ascending dose (SAD) or multiple ascending dose (MAD) studies, has been proposed as an alternative to thorough QT studies (TQT), in assessing drug-induced QT prolongation risk. The present analysis used clinical SAD, MAD and TQT study data of an experimental compound, AZD5672, to evaluate the performance of: (i) three computational platforms (linear mixed-effects modeling implemented via PROC MIXED in SAS, as well as in R using LME4 package and linear quantile mixed models (LQMM) implemented via LQMM package; (ii) different model structures with and without treatment- or time-specific intercepts; and (iii) three methods for calculating the confidence interval (CI) of QTc prolongation (analytical and bootstrap methods with fixed or varied geometric mean concentrations). We show that treatment- and time-specific intercepts may need to be included into C-∆QTc modeling through PROC MIXED or LME4, regardless of their statistical significance. With the intersection union test (IUT) in the TQT study as a reference for comparison, inclusion of these intercepts increased the feasibility for C-∆QTc modelling of SAD or MAD to reach the same conclusion as the IUT analysis based on TQT study. Compared to PROC MIXED or LME4, the LQMM method is less dependent on inclusion of treatment- or time-specific intercepts, and the bootstrap CI calculation methods provided higher likelihood for C-∆QTc modeling of SAD and MAD studies to reach the same conclusion as the IUT based on the TQT study.

Population pharmacokinetics and electrocardiographic effects of dihydroartemisinin-piperaquine in healthy volunteers

Aims

The aims of the present study were to evaluate the pharmacokinetic properties of dihydroartemisinin (DHA) and piperaquine, potential drug–drug interactions with concomitant primaquine treatment, and piperaquine effects on the electrocardiogram in healthy volunteers.

Methods

The population pharmacokinetic properties of DHA and piperaquine were assessed in 16 healthy Thai adults using an open‐label, randomized, crossover study. Drug concentration–time data and electrocardiographic measurements were evaluated with nonlinear mixed‐effects modelling.

Results

The developed models described DHA and piperaquine population pharmacokinetics accurately. Concomitant treatment with primaquine did not affect the pharmacokinetic properties of DHA or piperaquine. A linear pharmacokinetic–pharmacodynamic model described satisfactorily the relationship between the individually corrected QT intervals and piperaquine concentrations; the population mean QT interval increased by 4.17 ms per 100 ng ml^–1 increase in piperaquine plasma concentration. Simulations from the final model showed that monthly and bimonthly mass drug administration in healthy subjects would result in median maximum QT interval prolongations of 18.9 ms and 16.8 ms, respectively, and would be very unlikely to result in prolongation of more than 50 ms. A single low dose of primaquine can be added safely to the existing DHA–piperaquine treatment in areas of multiresistant Plasmodium falciparum malaria.

Conclusions

Pharmacokinetic–pharmacodynamic modelling and simulation in healthy adult volunteers suggested that therapeutic doses of DHA–piperaquine in the prevention or treatment of P. falciparum malaria are unlikely to be associated with dangerous QT prolongation.

Influence of Meals and Glycemic Changes on QT Interval Dynamics

Thorough QT/QTc studies have become an integral part of early drug development programs, with major clinical and regulatory implications. This analysis expands on existing pharmacodynamic models of QT interval analysis by incorporating the influence of glycemic changes on the QT interval in a semimechanistic manner. A total of 21 healthy subjects enrolled in an open-label phase 1 pilot study and provided continuous electrocardiogram monitoring and plasma glucose and insulin concentrations associated with a 24-hour baseline assessment. The data revealed a transient decrease in QTc, with peak suppression occurring approximately 3 hours after the meal. A semimechanistic modeling approach was applied to evaluate temporal delays between meals and subsequent changes that might influence QT measurements. The food effect was incorporated into a model of heart rate dynamics, and additional delayed effects of the meal on QT were incorporated using a glucose-dependent hypothetical transit compartment. The final model helps to provide a foundation for the future design and analysis of QT studies that may be confounded by meals. This study has significant implications for QT study assessment following a meal or when a cohort is receiving a medication that influences postprandial glucose concentrations.

Integrated TK-TD modeling for drug-induced concurrent tachycardia and QT changes in beagle dogs

Drug-induced cardiotoxicity, including tachycardia and QT prolongation, remains a major safety concern that needs to be identified and its risk mitigated in early stages of drug development. In the present study, an integrated toxicokinetic-toxicodynamic (TK-TD) modeling approach within a nonlinear mixed-effect modeling framework is applied to investigate concurrent abnormal heart rate and QT changes in three beagle dogs, using a Novartis internal compound (NVS001) as the case example. By accounting for saturable drug absorption, circadian rhythms, drug-effect tolerance, and nonlinear rate-dependency of QT interval, the dynamic TK-TD model captures the experimentally observed drug effects on heart rate and QT interval across a wide dosing range of NVS001 in beagle dogs. Further analyses reveal that the NVS001-induced QT prolongation observed in the low-dose groups is potentially caused by direct drug inhibition on the hERG channel, while the apparent QT shortening in the high-dose groups may be due to strong rate-dependency of QT at high heart rates. This study also suggests that the TK-TD model can be used to identify direct drug effects on the non-rate-dependent QT component by dissociating QT changes from tachycardia and deriving a new QT correction method. The integrated TK-TD model presented here may serve as a novel quantitative framework for evaluating drug-induced concurrent changes in heart rate and QT to potentially facilitate preclinical and clinical safety studies.

Model-Based Evaluation of Exenatide Effects on the QT Interval in Healthy Subjects Following Continuous IV Infusion

Investigation of the cardiovascular proarrhythmic potential of a new chemical entity is now an integral part of drug development. Studies suggest that meals and glycemic changes can influence QT intervals, and a semimechanistic model has been developed that incorporates the effects of changes in glucose concentrations on heart rate (HR) and QT intervals. This analysis aimed to adapt the glucose-HR-QT model to incorporate the effects of exenatide, a drug that reduces postprandial increases in glucose concentrations. The final model includes stimulatory drug effects on glucose elimination and HR perturbations. The targeted and constant exenatide plasma concentrations (>200 pg/mL), via intravenous infusions at multiple dose levels, resulted in significant inhibition of glucose concentrations. The exenatide concentration associated with 50% of the stimulation of HR production was 584 pg/mL. After accounting for exenatide effects on glucose and HR, no additional drug effects were required to explain observed changes in the QT interval. Resulting glucose, HR, and QT profiles at all exenatide concentrations were adequately described. For therapeutic agents that alter glycemic conditions, particularly those that alter postprandial glucose, the QT interval cannot be directly compared to that with placebo without first accounting for confounding factors (eg, glucose) either through mathematical modeling or careful consideration of mealtime placement in the study design.

Systems Chronotherapeutics

Chronotherapeutics aim at treating illnesses according to the endogenous biologic rhythms, which moderate xenobiotic metabolism and cellular drug response. The molecular clocks present in individual cells involve approximately fifteen clock genes interconnected in regulatory feedback loops. They are coordinated by the suprachiasmatic nuclei, a hypothalamic pacemaker, which also adjusts the circadian rhythms to environmental cycles. As a result, many mechanisms of diseases and drug effects are controlled by the circadian timing system. Thus, the tolerability of nearly 500 medications varies by up to fivefold according to circadian scheduling, both in experimental models and/or patients. Moreover, treatment itself disrupted, maintained, or improved the circadian timing system as a function of drug timing. Improved patient outcomes on circadian-based treatments (chronotherapy) have been demonstrated in randomized clinical trials, especially for cancer and inflammatory diseases. However, recent technological advances have highlighted large interpatient differences in circadian functions resulting in significant variability in chronotherapy response. Such findings advocate for the advancement of personalized chronotherapeutics through interdisciplinary systems approaches. Thus, the combination of mathematical, statistical, technological, experimental, and clinical expertise is now shaping the development of dedicated devices and diagnostic and delivery algorithms enabling treatment individualization. In particular, multiscale systems chronopharmacology approaches currently combine mathematical modeling based on cellular and whole-body physiology to preclinical and clinical investigations toward the design of patient-tailored chronotherapies. We review recent systems research works aiming to the individualization of disease treatment, with emphasis on both cancer management and circadian timing system-resetting strategies for improving chronic disease control and patient outcomes.

Psychotropic drugs and ventricular repolarisation: The effects on QT interval, T-peak to T-end interval and QT dispersion

OBJECTIVE

We aimed to investigate in a clinical setting, the effects of different classes of psychotropic drugs on cardiac electrophysiological measures linked with an increased risk of sudden cardiac death.

METHODS

We conducted a cross-sectional study in a population of 1059 psychiatric inpatients studying the effects of various psychotropic drugs on the T-peak to T-end (TpTe) interval, QT dispersion and QT interval.

RESULTS

Methadone use showed a strong association with TpTe prolongation (odds ratio (OR)=12.66 (95% confidence interval (CI), 3.9-41.1), p<0.001), an effect independent from action on QT interval. Mood stabilisers showed significant effects on ventricular repolarisation: lithium was associated with a TpTe prolongation (OR=2.12 (95% CI, 1.12-4), p=0.02), while valproic acid with a TpTe reduction (OR=0.6 (95% CI, 0.37-0.98), p=0.04). Among antipsychotics, clozapine increased TpTe (OR=9.5 (95% CI, 2.24-40.39), p=0.002) and piperazine phenothiazines increased QT dispersion (OR=2.73 (95% CI, 1.06-7.02), p=0.037).

CONCLUSIONS

Treatment with psychotropic drugs influences TpTe and QT dispersion. These parameters might be considered to better estimate the sudden cardiac death risk related to specific medications. Beyond antipsychotics and antidepressants, mood stabilisers determine significant effects on ventricular repolarisation.

Translating QT interval prolongation from conscious dogs to humans

AIM

In spite of screening procedures in early drug development, uncertainty remains about the propensity of new chemical entities (NCEs) to prolong the QT/QTc interval. The evaluation of proarrhythmic activity using a comprehensive in vitro proarrhythmia assay does not fully account for pharmacokinetic-pharmacodynamic (PKPD) differences in vivo. In the present study, we evaluated the correlation between drug-specific parameters describing QT interval prolongation in dogs and in humans.

METHODS

Using estimates of the drug-specific parameter, data on the slopes of the PKPD relationships of nine compounds with varying QT-prolonging effects (cisapride, sotalol, moxifloxacin, carabersat, GSK945237, SB237376 and GSK618334, and two anonymized NCEs) were analysed. Mean slope estimates varied between -0.98 ms μM-1 and 6.1 ms μM-1 in dogs and -10 ms μM-1 and 90 ms μM-1 in humans, indicating a wide range of effects on the QT interval. Linear regression techniques were then applied to characterize the correlation between the parameter estimates across species.

RESULTS

For compounds without a mixed ion channel block, a correlation was observed between the drug-specific parameter in dogs and humans (y = -1.709 + 11.6x; R2  = 0.989). These results show that per unit concentration, the drug effect on the QT interval in humans is 11.6-fold larger than in dogs.

CONCLUSIONS

Together with information about the expected therapeutic exposure, the evidence of a correlation between the compound-specific parameter in dogs and in humans represents an opportunity for translating preclinical safety data before progression into the clinic. Whereas further investigation is required to establish the generalizability of our findings, this approach can be used with clinical trial simulations to predict the probability of QT prolongation in humans.

Olaparib does not cause clinically relevant QT/QTc interval prolongation in patients with advanced solid tumours: results from two phase I studies

BACKGROUND

Some therapeutic agents in oncology can be causally associated with specific cardiovascular events including QT/QTc interval prolongation. We investigated the effect of multiple dosing of the oral poly (ADP-ribose)-polymerase (PARP) inhibitor, olaparib (tablet formulation) on QT/QTc interval.

METHODS

Two phase I, open-label, three-part studies (NCT01921140 [study 4] and NCT01900028 [study 7]) were conducted in adults with refractory/resistant advanced solid tumours. In both studies, parts A and B assessed the QT/QTc interval effects of single-dose oral olaparib 100 (study 4) or 300 (study 7) mg and multiple-dose olaparib 300 mg bid for 5 days, respectively, while part C evaluated continued access to olaparib for additional safety analyses. An ANCOVA model tested the primary objective of multiple-dose effects of olaparib on QT interval corrected using Fridericia's formula (QTcF).

RESULTS

Data from 119 and 109 patients were pooled from parts A and B, respectively, for QT/QTc analysis. At pre-dose and up to 12 h post-dose, the upper limits of the 90 % confidence intervals (CIs) for the difference in QTcF least squares means after olaparib multiple dosing versus control (day -1) were <10 ms, suggesting a lack of clinically relevant effect on cardiac repolarization. A slight shortening of QTcF was observed at most time points versus control. QTcF results for the individual studies and single-dose olaparib paralleled the primary multiple-dose pooled analysis, with upper limits of the 90 % CIs < 10 ms.

CONCLUSION

Olaparib tablets administered as multiple or single doses had no clinically significant effect on QT/QTc interval.

Cardiovascular Safety Assessment in Early-Phase Clinical Studies: A Meta-Analytical Comparison of Exposure-Response Models

Exposure‐response analysis of QT interval in clinical studies has been proposed as a thorough QT study alternative. Many exposure‐response model structures have been proposed for cardiovascular (CV) safety markers, but few studies have compared models across multiple drugs. To recommend preferred drug‐effect exposure‐response models on vital signs and electrocardiogram (ECG) intervals, an individual‐level model‐based meta‐analysis (39 studies and 1,291 subjects) compared 90 model structures. Models were selected to describe the data and cross‐validate studies on the same drug. The most commonly selected baseline model was an unstructured model (estimation of a value at each study nominal time) for all measures but blood pressure. The unstructured model estimated a better cross‐validated drug‐effect when considering all markers. A linear model was the most commonly selected to characterize drug‐effect on all markers. We propose these models as a starting point assisting with CV safety exposure‐response assessment in nondedicated small studies with healthy subjects.

PK/PD Modelling of the QT Interval: a Step Towards Defining the Translational Relationship Between In Vitro, Awake Beagle Dogs, and Humans

Inhibiting the human ether-a-go-go-related gene (hERG)-encoded potassium ion channel is positively correlated with QT-interval prolongation in vivo, which is considered a risk factor for the occurrence of Torsades de Pointes (TdP). A pharmacokinetic/pharmacodynamic model was developed for four compounds that reached the clinic, to relate drug-induced QT-interval change in awake dogs and humans and to derive a translational scaling factor a 1. Overall, dogs were more sensitive than humans to QT-interval change, an a 1 of 1.5 was found, and a 10% current inhibition in vitro produced a higher percent QT-interval change in dogs as compared to humans. The QT-interval changes in dogs were predictive for humans. In vitro and in vivo information could reliably describe the effects in humans. Robust translational knowledge is likely to reduce the need for expensive thorough QT studies; therefore, expanding this work to more compounds is recommended.

Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment

Purpose

Adverse effects related to anti-cancer drug treatment influence patient’s quality of life, have an impact on the realized dosing regimen, and can hamper response to treatment. Quantitative models that relate drug exposure to the dynamics of adverse effects have been developed and proven to be very instrumental to optimize dosing schedules. The aims of this review were (i) to provide a perspective of how adverse effects of anti-cancer drugs are modeled and (ii) to report several model structures of adverse effect models that describe relationships between drug concentrations and toxicities.

Methods

Various quantitative pharmacodynamic models that model adverse effects of anti-cancer drug treatment were reviewed.

Results

Quantitative models describing relationships between drug exposure and myelosuppression, cardiotoxicity, and graded adverse effects like fatigue, hand-foot syndrome (HFS), rash, and diarrhea have been presented for different anti-cancer agents, including their clinical applicability.

Conclusions

Mathematical modeling of adverse effects proved to be a helpful tool to improve clinical management and support decision-making (especially in establishment of the optimal dosing regimen) in drug development. The reported models can be used as templates for modeling a variety of anti-cancer-induced adverse effects to further optimize therapy.

PKPD modelling of PR and QRS intervals in conscious dogs using standard safety pharmacology data

INTRODUCTION

Pharmacokinetic-pharmacodynamic (PKPD) modelling can improve safety assessment, but few PKPD models describing drug-induced QRS and PR prolongations have been published. This investigation aims to develop and evaluate PKPD models for describing QRS and PR effects in routine safety studies.

METHODS

Exposure and telemetry data from safety pharmacology studies in conscious beagle dogs were acquired. Mixed effects baseline and PK-QRS/PR models were developed for the anti-arrhythmic compounds AZD1305, flecainide, quinidine and verapamil and the anti-muscarinic compounds AZD8683 and AZD9164. RR interval correction and circadian rhythms were investigated for predicting baseline variability. Individual PK predictions were used to drive the pharmacological effects evaluating linear and non-linear direct and effect compartment models.

RESULTS

Conduction slowing induced by the tested anti-arrhythmics was direct and proportional at low exposures, whilst time delays and non-linear effects were evident for the tested anti-muscarinics. AZD1305, flecainide and quinidine induced QRS widening with 4.2, 10 and 5.6% μM(-1) unbound drug. AZD1305 and flecainide also prolonged PR with 13.5 and 11.5% μM(-1). PR prolongations induced by the anti-muscarinics and verapamil were best described by Emax models with maximal effects ranging from 55 to 95%. RR interval correction and circadian rhythm improved PR but not QRS modelling. However, circadian rhythm had minor impact on estimated drug effects.

DISCUSSION

Baseline and drug-induced effects on QRS and PR intervals can be effectively described with PKPD models using routine data, providing quantitative safety information to support drug discovery and development.

Model-based evaluation of drug-induced QTc prolongation for compounds in early development

AIMS

Significant differences between dogs and humans have been observed in the concentration-QTc effect relationship of compounds with known pro-arrhythmic properties. These findings suggest that interspecies differences must be considered when evaluating drug effects. The aim of this study was to evaluate the performance of a model-based approach to assess the risk of QTc prolongation for three investigational compounds (NCE01, NCE02 and NCE03).

METHODS

Pharmacokinetic and pharmacodynamic data from experiments in conscious dogs and healthy subjects were included in this analysis. Pharmacokinetic modelling and deconvolution methods were applied to derive drug concentrations at the time of each QT measurement. An integrated pharmacokinetic-pharmacodynamic (PKPD) model was then used to describe QT prolongation. A threshold of ≥10 ms was used to characterize the probability of QTc prolongation.

RESULTS

The PKPD relationships of all three compounds were successfully described in both species. A strong effect was observed after administration of NCE01 to dogs and humans, with a slope of 0.0061 and 0.0662 ms nm(-1), respectively, and maximal probability of QTc prolongation ≥10 ms at peak concentration. For NCE02 and NCE03, QTc-shortening and borderline QT effects were observed both in dogs and humans, as described by negative or very shallow slopes (NCE02, -0.00098 and -0.01 ms nm(-1); NCE03, 0.00064 and -0.0002 ms nm(-1)).

CONCLUSIONS

Whilst NEC01 shows clear pro-arrhythmic effects, the liability for QT/QTc prolongation for NCE02 and NCE03 can be deemed low at the expected therapeutic exposure. Moreover, our results show the advantages of an integrated PKPD approach as the basis for translating pro-arrhythmic effects from dogs to humans.

The role of concentration-effect relationships in the assessment of QTc interval prolongation

Population pharmacokinetic and pharmacokinetic-pharmacodynamic (PKPD) modelling has been widely used in clinical research. Yet, its application in the evaluation of cardiovascular safety remains limited, particularly in the evaluation of pro-arrhythmic effects. Here we discuss the advantages of disadvantages of population PKPD modelling and simulation, a paradigm built around the knowledge of the concentration-effect relationship as the basis for decision making in drug development and its utility as a guide to drug safety. A wide-ranging review of the literature was performed on the experimental protocols currently used to characterize the potential for QT interval prolongation, both pre-clinically and clinically. Focus was given to the role of modelling and simulation for design optimization and subsequent analysis and interpretation of the data, discriminating drug from system specific properties. Cardiovascular safety remains one of the major sources of attrition in drug development with stringent regulatory requirements. However, despite the myriad of tests, data are not integrated systematically to ensure accurate translation of the observed drug effects in clinically relevant conditions. The thorough QT study addresses a critical regulatory question but does not necessarily reflect knowledge of the underlying pharmacology and has limitations in its ability to address fundamental clinical questions. It is also prone to issues of multiplicity. Population approaches offer a paradigm for the evaluation of drug safety built around the knowledge of the concentration-effect relationship. It enables quantitative assessment of the probability of QTc interval prolongation in patients, providing better guidance to regulatory labelling and understanding of benefit/risk in specific populations.

Assessment of Interspecies Differences in Drug-Induced QTc Interval Prolongation in Cynomolgus Monkeys, Dogs and Humans

Background and Purpose

The selection of the most suitable animal species and subsequent translation of the concentration-effect relationship to humans are critical steps for accurate assessment of the pro-arrhythmic risk of candidate molecules. The objective of this investigation was to assess quantitatively the differences in the QTc prolonging effects of moxifloxacin between cynomolgus monkeys, dogs and humans. The impact of interspecies differences is also illustrated for a new candidate molecule.

Experimental Approach

Pharmacokinetic data and ECG recordings from pre-clinical protocols in monkeys and dogs and from a phase I trial in healthy subjects were identified for the purpose of this analysis. A previously established Bayesian model describing the combined effect of heart rate, circadian variation and drug effect on the QT interval was used to describe the pharmacokinetic-pharmacodynamic relationships. The probability of a ≥10 ms increase in QT was derived as measure of the pro-arrhythmic effect.

Key Results

For moxifloxacin, the concentrations associated with a 50% probability of QT prolongation ≥10 ms (Cp₅₀) varied from 20.3 to 6.4 and 2.6 μM in dogs, monkeys and humans, respectively. For NCE05, these values were 0.4 μM vs 2.0 μM for monkeys and humans, respectively.

Conclusions and Implications

Our findings reveal significant interspecies differences in the QT-prolonging effect of moxifloxacin. In addition to the dissimilarity in pharmacokinetics across species, it is likely that differences in pharmacodynamics also play an important role. It appears that, regardless of the animal model used, a translation function is needed to predict concentration-effect relationships in humans.

Single Doses up to 800 mg of E-52862 Do Not Prolong the QTc Interval--A Retrospective Validation by Pharmacokinetic-Pharmacodynamic Modelling of Electrocardiography Data Utilising the Effects of a Meal on QTc to Demonstrate ECG Assay Sensitivity

Background

E-52862 is a Sigma-1 receptor antagonist (S1RA) currently under investigation as a potential analgesic medicine. We successfully applied a concentration-effect model retrospectively to a four-way crossover Phase I single ascending dose study and utilized the QTc shortening effects of a meal to demonstrate assay sensitivity by establishing the time course effects from baseline in all four periods, independently from any potential drug effects.

Methods

Thirty two healthy male and female subjects were included in four treatment periods to receive single ascending doses of 500 mg, 600 mg or 800 mg of E-52862 or placebo. PK was linear over the dose range investigated and doses up to 600 mg were well tolerated. The baseline electrocardiography (ECG) measurements on Day-1 were time-matched with ECG and pharmacokinetic (PK) samples on Day 1 (dosing day).

Results

In this conventional mean change to time-matched placebo analysis, the largest time-matched difference to placebo QTcI was 1.44 ms (90% CI: -4.04, 6.93 ms) for 500 mg; -0.39 ms (90% CI: -3.91, 3.13 ms) for 600 mg and 1.32 ms (90% CI: -1.89, 4.53 ms) for 800 mg of E-52862, thereby showing the absence of any QTc prolonging effect at the doses tested. In addition concentration-effect models, one based on the placebo corrected change from baseline and one for the change of QTcI from average baseline with time as fixed effect were fitted to the data confirming the results of the time course analysis.

Conclusion

The sensitivity of this study to detect small changes in the QTc interval was confirmed by demonstrating a shortening of QTcF of -8.1 (90% CI: -10.4, -5.9) one hour and -7.2 (90% CI: -9.4, -5.0) three hours after a standardised meal.

Trial Registration

EU Clinical Trials Register EudraCT 2010 020343 13

Modeling and Simulation Approaches for Cardiovascular Function and Their Role in Safety Assessment

Systems pharmacology modeling and pharmacokinetic-pharmacodynamic (PK/PD) analysis of drug-induced effects on cardiovascular (CV) function plays a crucial role in understanding the safety risk of new drugs. The aim of this review is to outline the current modeling and simulation (M&S) approaches to describe and translate drug-induced CV effects, with an emphasis on how this impacts drug safety assessment. Current limitations are highlighted and recommendations are made for future effort in this vital area of drug research.