A pharmacokinetic–pharmacodynamic model for cardiovascular safety assessment of R1551

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).

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.

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.

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.

Identifying the translational gap in the evaluation of drug-induced QTc interval prolongation

AIMS

Given the similarities in QTc response between dogs and humans, dogs are used in pre-clinical cardiovascular safety studies. The objective of our investigation was to characterize the PKPD relationships and identify translational gaps across species following the administration of three compounds known to cause QTc interval prolongation, namely cisapride, d, l-sotalol and moxifloxacin.

METHODS

Pharmacokinetic and pharmacodynamic data from experiments in conscious dogs and clinical trials were included in this analysis. First, pharmacokinetic modelling and deconvolution methods were applied to derive drug concentrations at the time of each QT measurement. A Bayesian PKPD model was then used to describe QT prolongation, allowing discrimination of drug-specific effects from other physiological factors known to alter QT interval duration. A threshold of ≥10 ms was used to explore the probability of prolongation after drug administration.

RESULTS

A linear relationship was found to best describe the pro-arrhythmic effects of cisapride, d,l-sotalol and moxifloxacin both in dogs and in humans. The drug-specific parameter (slope) in dogs was statistically significantly different from humans. Despite such differences, our results show that the probability of QTc prolongation ≥10 ms in dogs nears 100% for all three compounds at the therapeutic exposure range in humans.

CONCLUSIONS

Our findings indicate that the slope of PKPD relationship in conscious dogs may be used as the basis for the prediction of drug-induced QTc prolongation in humans. Furthermore, the risk of QTc prolongation can be expressed in terms of the probability associated with an increase ≥10 ms, allowing direct inferences about the clinical relevance of the pro-arrhythmic potential of a molecule.

Establishing in vitro to clinical correlations in the evaluation of cardiovascular safety pharmacology

Preclinical studies are vital in establishing the efficacy and safety of a new chemical entity (NCE) in humans. To deliver meaningful information, experiments have to be well defined and provide outcome that is relevant and translatable to humans. This review briefly surveys the various preclinical experiments that are frequently conducted to assess drug effects on cardiac conductivity in early drug development. We examine the different approaches used to establish correlations between non-clinical and clinical settings and discuss their value in the evaluation of cardiovascular risk.