Translational PK/PD modeling for cardiovascular safety assessment of drug candidates: Methods and examples in drug development

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

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

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.

Evaluation of levocetirizine in beagle dog and cynomolgus monkey telemetry assays: Defining the no QTc effect profile by timepoint and concentration-QTc analysis

In prior clinical studies, levocetirizine (LEVO) has demonstrated no effect on ventricular repolarization (QTc intervals), therefore it is a relevant negative control to assess in nonclinical assays to define low proarrhythmic risk. LEVO was tested in beagle dog and cynomolgus monkey (nonhuman primate [NHP]) telemetry models to understand the nonclinical-clinical translation of this negative control. One oral dose of vehicle, LEVO (10 mg/kg/species) or moxifloxacin (MOXI; 30 mg/kg/dog; 80 mg/kg/NHP) was administered to instrumented animals (N = 8/species) using a cross-over dosing design; MOXI was the in-study positive control. Corrected QT interval values (QTcI) were calculated using an individual animal correction factor. Blood samples were taken for drug exposure during telemetry and for pharmacokinetic (PK) analysis (same animals; different day) for exposure-response (C-QTc) modeling. Statistical analysis of QTc-by-timepoint data showed that LEVO treatment was consistent with vehicle, thus no effect on ventricular repolarization was observed over 24 h in both species. PK analysis indicated that LEVO-maximum concentration levels in dogs (range: 12,300-20,100 ng/ml) and NHPs (range: 4090-12,700 ng/ml) were ≥4-fold higher than supratherapeutic drug levels in clinical QTc studies. Slope analysis values in dogs (0.00019 ms/ng/ml) and NHPs (0.00016 ms/ng/ml) were similar to the human C-QTc relationship and indicated no relationship between QTc intervals and plasma levels of LEVO. MOXI treatment caused QTc interval prolongation (dog: 18 ms; NHP: 29 ms). The characterization of LEVO in these non-rodent telemetry studies further demonstrates the value and impact of the in vivo QTc assay to define a "no QTc effect" profile and support clinical safety assessment.

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

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

"Digital biomarkers" in preclinical heart failure models - a further step towards improved translational research

Innovations in the development of novel heart failure therapies are essential to further increase the predictive value of early research findings. Animal models are still playing a pivotal role in 'translational research'. In recent years, the transferability from animal studies has been more and more critically discussed due to persistent high attrition rates in clinical trials. However, there is an increasing trend to implement mobile health devices in preclinical studies. These devices can increase the predictive value of animal models by providing more accurate and translatable data and protect from confounding factors. This review outlines the current prevalence and opportunities of these techniques in preclinical heart failure research studies to accelerate the integration of these important tools. A literature screening for preclinical heart failure studies in large animals implementing telemetry devices over the last decade was performed. Twelve out of 43 publications were included. A variety of different hemodynamic and cardiac parameters can be recorded in conscious state by means of telemetry devices in both, the animal model and the patient. The measurement quality is consistently rated as valid and robust. Mobile health technologies functioning as digital biomarkers represent a more predictive approach compared to the traditionally used invasive measurement techniques, due to the possibility of continuous data collection in the conscious animal. Furthermore, they help to implement the 3R concept (reduction, refinement, replacement) in animal research. Despite this, the use of these techniques in preclinical research has been restrained to date.

Utilization of Pharmacokinetic/Pharmacodynamic Modeling in Pharmacoepidemiological Studies: A Systematic Review on Antiarrhythmic and Glucose-Lowering Medicines

Introduction: In human pharmacology, there are two important scientific branches: clinical pharmacology and pharmacoepidemiology. Pharmacokinetic/pharmacodynamic (PK/PD) modeling is important in preclinical studies and randomized control trials. However, it is rarely used in pharmacoepidemiological studies on the effectiveness and medication safety where the target population is heterogeneous and followed for longer periods. The objective of this literature review was to investigate how far PK/PD modeling is utilized in observational studies on glucose-lowering and antiarrhythmic drugs.

Method: A systematic literature search of MEDLINE, Embase, and Web of Science was conducted from January 2010 to 21 February 2020. To calculate the utilization of PK/PD modeling in observational studies, we followed two search strategies. In the first strategy, we screened a 1% random set from 95,672 studies on glucose-lowering and antiarrhythmic drugs on inclusion criteria. In the second strategy, we evaluated the percentage of studies in which PK/PD modeling techniques were utilized. Subsequently, we divided the total number of included studies in the second search strategy by the total number of eligible studies in the first search strategy.

Results: The comprehensive search of databases and the manual search of included references yielded a total of 29 studies included in the qualitative synthesis of our systematic review. Nearly all 29 studies had utilized a PK model, whereas only two studies developed a PD model to evaluate the effectiveness of medications. In total, 16 out of 29 studies (55.1%) used a PK/PD model in the observational setting to study effect modification. The utilization of PK/PD modeling in observational studies was calculated as 0.42%.

Conclusion: PK/PD modeling techniques were substantially underutilized in observational studies of antiarrhythmic and glucose-lowering drugs during the past decade.

Automated blood sampling in canine telemetry studies: Enabling enhanced assessments of cardiovascular liabilities and safety margins

INTRODUCTION

A successful integration of automated blood sampling (ABS) into the telemetry instrumented canine cardiovascular model is presented in this study. This combined model provides an efficient means to quickly gain understanding of potential effects on key cardiovascular parameters in dog while providing a complete Pharmacokinetic/Pharmacodynamic (PK/PD) profile for discovery compounds without handling artifacts, reducing the need for a separate pharmacokinetic study.

METHODS

Male beagle dogs were chronically implanted with telemetry devices (PhysioTel™ model D70-PCTP) and vascular access ports (SPMID-GRIDAC-5NC). BASi Culex-L automated blood sampling (Bioanalytical Systems, Inc) system was used to collect blood samples at multiple time points. A series of four use cases utilizing four different test compounds and analytical endpoints are described to illustrate some of the potential applications of the technique.

RESULTS

In the four presented use cases, automated blood sampling in telemetry instrumented dogs provides simultaneous cardiovascular (heart rate, arterial blood pressure, and left ventricular pressure), electrophysiological assessment (QTc, PR, and QRS intervals), body temperature, and animal activity, while collecting multiple blood samples for drug analysis.

CONCLUSION

The combination of automated blood sampling with cardiovascular telemetry monitoring is a novel capability designed to support safety pharmacology cardiovascular assessment of discovery molecules. By combining telemetry and high-fidelity ABS, the model provides an enhanced PK/PD understanding of drug-induced hemodynamic and electrocardiographic effects of discovery compounds in conscious beagles in the same experimental session. Importantly, the model can reduce the need for a separate pharmacokinetic study (positive reduction 3R impact), reduces compound syntheses requirements, and shorten development timelines. Furthermore, implementation of this approach has also improved animal welfare by reducing the animal handling during a study, thereby reducing stress and associated data artifacts (positive refinement 3R impact).

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).

Evaluation of moxifloxacin in canine and non-human primate telemetry assays: Comparison of QTc interval prolongation by timepoint and concentration-QTc analysis

The in vivo correct QT (QTc) assay is used by the pharmaceutical industry to characterize the potential for delayed ventricular repolarization and is a core safety assay mentioned in International Conference on Harmonization (ICH) S7B guideline. The typical telemetry study involves a dose‐response analysis of QTc intervals over time using a crossover (CO) design. This method has proven utility but does not include direct integration of pharmacokinetic (PK) data. An alternative approach has been validated and is used routinely in the clinical setting that pairs pharmacodynamic (PD) responses with PK exposure (e.g., concentration‐QTc (C‐QTc) analysis. The goal of our paper was to compare the QTc sensitivity of two experimental approaches in the conscious dog and non‐human primate (NHP) QTc assays. For timepoint analysis, a conventional design using eight animals (8 × 4 CO) to detect moxifloxacin‐induced QTc prolongation was compared to a PK/PD design in a subset (N = 4) of the same animals. The findings demonstrate that both approaches are equally sensitive in detecting threshold QTc prolongation on the order of 10 ms. Both QTc models demonstrated linearity in the QTc prolongation response to moxifloxacin dose escalation (6 to 46 ms). Further, comparison with human QTc findings with moxifloxacin showed agreement and consistent translation across the three species: C‐QTc slope values were 0.7‐ (dog) and 1.2‐ (NHP) fold of the composite human value. In conclusion, our data show that dog and NHP QTc telemetry with an integrated PK arm (C‐QTc) has the potential to supplement clinical evaluation and improve integrated QTc risk assessment.

The in vivo QTc core assay: An evaluation of QTc variability, detection sensitivity and implications for the improvement of conscious dog and non-human primate telemetry studies

The ICH S7B guideline describes the requirement to conduct an in vitro I_Kr (hERG) and in vivo QTc assay for human risk assessment of new drug products, but the guidance is devoid of recommendations on study execution or quality. In the absence of standard practice, multiple study designs and experimental approaches have been utilized, especially with the nonclinical QTc assay. Since 2009, our approach to the in vivo QTc assay has been consistent for small molecules and yields reproducible and sensitive levels for QTc signal detection. Our database and experience indicate that nonrodent telemetry studies can achieve high sensitivity and a calculated metric of study power can be used to indicate study quality. Using a retrospective statistical power analysis of multiple studies (n = 14 dog; n = 6 NHP), the detection sensitivity for a specific study design (N = 8; double Latin square cross-over) was determined. The output of the power analysis is the minimal detectable effect at 80% power and a 95% probability level. The design provided an average sensitivity to detect a 4.7 (2.0%) and 6.5 (1.9%) msec QTcI change in dog and NHP, respectively. These findings suggest that this experimental approach has a consistent and reproducible sensitivity to enable a robust QTcI risk evaluation and can be used confidently to support an integrated nonclinical-clinical pro-arrhythmia risk assessment. The inclusion of power analysis (i.e., QTc sensitivity) data in a regulatory submission provides key information to critical stakeholders about the quality of the in vivo QTc assessment and its value for human safety testing.

Confirmation of the cardiac safety of nolasiban in a randomised cohort of healthy female volunteers

Nolasiban is an orally active oxytocin receptor antagonist being developed to increase the efficiency of assisted reproductive technologies. This study evaluated the pharmacokinetics, pharmacodynamics, and cardiac safety of nolasiban in 45 healthy women of child-bearing age. Nolasiban was administered in a fasted state with a standardised lunch served 4.5 h post-dose. Concentration-effect modelling was used to assess the effect of two dosages of nolasiban (900 mg and 1800 mg) on QTc following single-dose administration. We found no significant change in QTc at all tested dosages. Two-sided 90% confidence intervals of geometric mean C_max for estimated QTc effects of nolasiban were below the threshold of regulatory concern. The sensitivity of the assay to detect small changes in QTc was confirmed by a significant shortening of QTc between 2 and 4 h after consumption of a meal, which served to validate the model. Independent of the nolasiban assessment, this study also explored the effects of sex hormones on ECG parameters, especially QT subintervals. We found a significant relationship between JTpc and oestradiol. Heart rate was negatively correlated with progesterone. This study confirms the cardiovascular safety of nolasiban and describes relationships of sex hormones and ECG parameters.

Phase 1 Clinical Trials of Small Molecules: Evolution and State of the Art

BACKGROUND

Phase 1 studies comprise the first exposure of a promising new chemical entity in healthy volunteers or, when appropriate, in patients. To assure a solid foundation for subsequent drug development, this first step must carefully assess the safety and tolerance of a new compound and often provide some indication of potential effect, so that a safe dose or dose range can be confidently selected for the initial Phase 2 efficacy study in the target patient population.

METHODS

This review was based on a literature search using both Google Scholar and PubMed, dated back to 1970, using search terms including "healthy volunteers", "Phase 1", and "normal volunteers", and also based on the authors' own experience conducting Phase 1 clinical trials. This paper reviews the history of Phase 1 studies of small molecules and their rapid evolution, focusing on the critical single and multiple dose studies, their designs, methodology, use of pharmacokinetic and pharmacodynamic modeling, application of potentially helpful biomarkers, study stopping criteria, and novel study designs.

RESULTS

We advocate for determining the safe dose range of a new compound by conducting careful dose escalation in a well-staffed inpatient setting, defining the maximally tolerated dose (MTD) by reaching the minimally intolerated dose (MID). The dose immediately below the MID is then defined as the MTD. This is best accomplished by using appropriately screened patients for the target indication, as patients in many CNS indications often tolerate doses differently than healthy non-patients. Biomarkers for safety and pharmacodynamic measures can also assist in further defining a safe and potentially effective dose range for subsequent clinical trial phases.

CONCLUSION

Phase 1 studies can yield critical insights into the pharmacology of a new compound in man and offer perhaps the only development period in which the dose range can be safely and thoroughly explored. Phase 1 studies often contain multiple endpoint objectives, the reconciliation of which can present a dilemma for drug developers and study investigators alike, but which can crucially determine whether a compound can survive to the next step in the drug development process.

A minimal model to describe short-term haemodynamic changes of the cardiovascular system

AIMS

Current pharmacokinetic-pharmacodynamic models describing the haemodynamic changes often do not include necessary feedback mechanisms. These models provide adequate description of current data but may fail to adequately extrapolate to additional scenarios. This study aims to develop a minimal model to describe the short-term changes of haemodynamics that can be used as the basis for model development by future researchers.

METHODS

A minimal haemodynamic model was developed to describe the influence of drugs on blood pressure components. The model structure was defined based on known mechanisms and previously published models. The model was evaluated under 2 different simulation settings. The model parameters were calibrated to describe (without estimation) the haemodynamics of 2 antihypertensive drugs with data extracted from the literature. Structural identifiability analysis was done using various combinations of the observed variable.

RESULTS

The proposed model structure includes mean arterial pressure, heart rate and stroke volume and is composed of 4 states described by differential equations. Model evaluation showed flexibility in describing the haemodynamics at different target perturbations. Overlay plots of model predictions and literature data showed a good description without data fitting. The structural identifiability analysis revealed all model parameters and initial conditions were identifiable only when heart rate, mean arterial pressure and cardiac output were measured together.

CONCLUSIONS

A minimal model of the haemodynamic system was developed and evaluated. The model accounted for short-term haemodynamic feedback processes. We propose that this model can be used as the basis for future pharmacometric analyses of drugs acting on the haemodynamic system.

Statistical Approach to Identify Threshold and Point of Departure in Dose-Response Data

The study presents an integrated, rigorous statistical approach to define the likelihood of a threshold and point of departure (POD) based on dose-response data using nested family of bent-hyperbola models. The family includes four models: the full bent-hyperbola model, which allows for transition between two linear regiments with various levels of smoothness; a bent-hyperbola model reduced to a spline model, where the transition is fixed to a knot; a bent-hyperbola model with a restricted negative asymptote slope of zero, named hockey-stick with arc (HS-Arc); and spline model reduced further to a hockey-stick type model (HS), where the first linear segment has a slope of zero. A likelihood-ratio test is used to discriminate between the models and determine if the more flexible versions of the model provide better or significantly better fit than a hockey-stick type model. The full bent-hyperbola model can accommodate both threshold and nonthreshold behavior, can take on concave up and concave down shapes with various levels of curvature, can approximate the biochemically relevant Michaelis-Menten model, and even be reduced to a straight line. Therefore, with the use of this model, the presence or absence of a threshold may even become irrelevant and the best fit of the full bent-hyperbola model be used to characterize the dose-response behavior and risk levels, with no need for mode of action (MOA) information. Point of departure (POD), characterized by exposure level at which some predetermined response is reached, can be defined using the full model or one of the better fitting reduced models.

Quantifying the relationship between inhibition of VEGF receptor 2, drug-induced blood pressure elevation and hypertension

BACKGROUND AND PURPOSE

Several anti-angiogenic cancer drugs that inhibit VEGF receptor (VEGFR) signalling for efficacy are associated with a 15-60% incidence of hypertension. Tyrosine kinase inhibitors (TKIs) that have off-target activity at VEGFR-2 may also cause blood pressure elevation as an undesirable side effect. Therefore, the ability to translate VEGFR-2 off-target potency into blood pressure elevation would be useful in development of novel TKIs. Here, we have sought to quantify the relationship between VEGFR-2 inhibition and blood pressure elevation for a range of kinase inhibitors.

EXPERIMENTAL APPROACH

Porcine aortic endothelial cells overexpressing VEGFR-2 (PAE) were used to determine IC₅₀ for VEGFR-2 phosphorylation. These IC₅₀ values were compared with published reports of exposure attained during clinical use and the corresponding incidence of all-grade hypertension. Unbound average plasma concentration (C_av,u ) was selected to be the most appropriate pharmacokinetic parameter. The pharmacokinetic-pharmacodynamic (PKPD) relationship for blood pressure elevation was investigated for selected kinase inhibitors, using data derived either from clinical papers or from rat telemetry experiments.

KEY RESULTS

All-grade hypertension was predominantly observed when the C_av,u was >0.1-fold of the VEGFR-2 (PAE) IC₅₀ . Furthermore, based on the PKPD analysis, an exposure-dependent blood pressure elevation >1 mmHg was observed only when the C_av,u was >0.1-fold of the VEGFR-2 (PAE) IC₅₀ .

CONCLUSIONS AND IMPLICATIONS

Taken together, these data show that the risk of blood pressure elevation is proportional to the amount of VEGFR-2 inhibition, and a margin of >10-fold between VEGFR-2 IC₅₀ and C_av,u appears to confer a minimal risk of hypertension.

Unveiling changes in the landscape of patient populations in cancer early drug development

The introduction of new Molecularly Targeted Agents (MTA) has changed the landscape in Early Drug Development (EDD) over the last two decades, leading to an improvement in clinical trial design. Previous Phase 1 (Ph1) studies with cytotoxics focused on safety objectives, only recruiting heavily pre-treated cancer patients, have been left behind. In this review, we will illustrate the slow although unstoppable change that has increasingly been observed in those populations candidate to participate in EDD trials with the advent of MTA. As more evidence regarding oncogene addiction becomes available, molecular-biomarker driven selection has been implemented among Molecularly-Selected Population (MSP) studies. New Window-Of-Opportunity (WOO) and Phase 0 (Ph0) studies have been developed in order to assess whether a MTA produces the hypothetical proposed biological effect. The rising need of getting early pharmacokinetics and pharmacodynamics data has led to the conduction of Healthy Volunteer (HV) studies, in part favoured for the particular and different toxicity profile of these MTA. However, several challenges will need to be addressed in order to boost the implementation of these new clinical trial designs in the forthcoming years. Among the problems to overcome, we would highlight a better coordination effort between centers for ensuring adequate patient accrual among small patient populations and a deepening into the ethics implied in enrolling patients in studies with no therapeutic intent. However, these tribulations will be certainly compensated by the possibility of opening a new horizon of treatment for diseases with dismal prognosis.

Translational PK/PD modeling to increase probability of success in drug discovery and early development

In this review we present ways in which translational PK/PD modeling can address opportunities to enhance probability of success in drug discovery and early development. This is achieved by impacting efficacy and safety-driven attrition rates, through increased focus on the quantitative understanding and modeling of translational PK/PD. Application of the proposed principles early in the discovery and development phases is anticipated to bolster confidence of successfully evaluating proof of mechanism in humans and ultimately improve Phase II success. The present review is centered on the application of predictive modeling and simulation approaches during drug discovery and early development, and more specifically of mechanism-based PK/PD modeling. Case studies are presented, focused on the relevance of M&S contributions to real-world questions and the impact on decision making.

Recent developments in using mechanistic cardiac modelling for drug safety evaluation

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Modelling and simulation can streamline decision making in drug safety testing.

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Computational cardiac electrophysiology is a mature technology with a long heritage.

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There are many challenges and opportunities in using in silico techniques in future.

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We discuss how models can be used at different stages of drug discovery.

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CiPA will combine screening platforms, human cell assays and in silico predictions.

On the tenth anniversary of two key International Conference on Harmonisation (ICH) guidelines relating to cardiac proarrhythmic safety, an initiative aims to consider the implementation of a new paradigm that combines in vitro and in silico technologies to improve risk assessment. The Comprehensive In Vitro Proarrhythmia Assay (CiPA) initiative (co-sponsored by the Cardiac Safety Research Consortium, Health and Environmental Sciences Institute, Safety Pharmacology Society and FDA) is a bold and welcome step in using computational tools for regulatory decision making. This review compares and contrasts the state-of-the-art tools from empirical to mechanistic models of cardiac electrophysiology, and how they can and should be used in combination with experimental tests for compound decision making.

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.

Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is

Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way.

Inter-study variability of preclinical in vivo safety studies and translational exposure-QTc relationships--a PKPD meta-analysis

BACKGROUND AND PURPOSE

Preclinical cardiovascular safety studies (CVS) have been compared between facilities with respect to their sensitivity to detect drug-induced QTc prolongation (ΔQTc). Little is known about the consistency of quantitative ΔQTc predictions that are relevant for translation to humans.

EXPERIMENTAL APPROACH

We derived typical ΔQTc predictions at therapeutic exposure (ΔQTcTHER ) with 95% confidence intervals (95%CI) for 3 Kv 11.1 (hERG) channel blockers (moxifloxacin, dofetilide and sotalol) from a total of 14 CVS with variable designs in the conscious dog. Population pharmacokinetic-pharmacodynamic (PKPD) analysis of each study was followed by a meta-analysis (pooling 2-6 studies including 10-32 dogs per compound) to derive meta-predictions of typical ΔQTcTHER . Meta-predictions were used as a reference to evaluate the consistency of study predictions and to relate results to those found in the clinical literature.

KEY RESULTS

The 95%CIs of study-predicted ΔQTcTHER comprised in 13 out of 14 cases the meta-prediction. Overall inter-study variability (mean deviation from meta-prediction at upper level of therapeutic exposure) was 30% (range: 1-69%). Meta-ΔQTcTHER predictions for moxifloxacin, dofetilide and sotalol overlapped with reported clinical QTc prolongation when expressed as %-prolongation from baseline.

CONCLUSIONS AND IMPLICATIONS

Consistent exposure-ΔQTc predictions were obtained from single preclinical dog studies of highly variable designs by systematic PKPD analysis, which is suitable for translational purposes. The good preclinical-clinical pharmacodynamic correlations obtained suggest that such an analysis should be more routinely applied to increase the informative and predictive value of results obtained from animal experiments.

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.