Is the era of “hERGphobia” finally coming to an end? Drug-induced cardiovascular adverse events are one of the leading causes of drug withdrawals from the market and of drug label restrictions. そのため、心拍のリズムが異常を示す不整脈を引き起こす可能性の高い新薬候補を、研究開発の早期段階において同定することは、製薬企業にとって重要な関心事項です。
The hERG channel plays a key role in cardiac repolarization. Inhibition of this channel is correlated with potentially lethal ventricular arrhythmias. This has led to widespread “hERGphobia” which tends to overlook the effects of drugs on other important cardiac ion channels. Consequently, a number of potentially safe drug programs have been terminated over false-positive hERG signals. In this blog post, I’ll discuss a technology that integrates physiologically-based pharmacokinetic (PBPK) modeling and simulation with a heart muscle cell model to predict a drug’s cardiac effects.
The regulatory requirement to assess drug candidates’ cardiotoxicity risk
ICH E14 guidance, which was introduced in 2005, required biopharmaceutical companies to conduct a Thorough QT/QTc study (TQT) to assess the likelihood of a new drug candidate producing lethal ventricular arrhythmias. A TQT study requires a new drug candidate to be given to healthy volunteers in escalating doses, often up to the maximally-tolerated dose. The participant’s response to the drug is then monitored using high quality electrocardiograms (ECGs) to gain more understanding about its potential cardiotoxicity. しかし、QT/QTc評価試験は多額の費用を必要とするため、医薬品候補化合物の臨床プロファイルが全て明らかになる前に開発が早期に中止される可能性を懸念する科学者もいます。Organizations such as the FDA, the Cardiac Safety Research Consortium , and HESI’s CIPA (Comprehensive In Vitro Proarrhythmia Assay) initiative are currently evaluating alternatives to the TQT study, including model based drug development approaches.
The Cardiac Safety Simulator: a tool for the cardiotoxicity evaluation process
I believe that the Cardiac Safety Simulator (CSS) will play a central role in the cardiotoxicity evaluation process by enabling early assessment of a drug’s pro-arrhythmic risk using in vitro data. By enabling early cardiotoxicity risk to be measured more precisely, CSS will allow biopharmaceutical companies to make more informed go/no-go decisions regarding their new drug candidates.
CSS integrates mechanistic PBPK modeling and simulation with a heart muscle cell model to predict a drug’s cardiac effects; it uses available in vitro data to simulate in vivo effects. It has the potential to replace TQT studies using ECG and PK data collected during Phase I ascending dose studies.
CSS can also be used in the early stages of drug development as a screening tool, even in situations where in vitro data are not available. CSS uses drug-triggered cardiac ion-current disruption data, together with predicted in vivo exposure information to evaluate the factors influencing potential cardiac risk. It determines the drug candidate’s pro-arrhythmic potency by assessing its inhibition of several cardiac ion channels (multiple potassium, sodium and calcium). It also factors in population variability, examining the likely impact of demographic, physiological and genetic influences, including age, gender and ethnicity. In addition, it assesses the influence of multiple drugs on ventricular ion current and simulated ECGs to account for participants who may be receiving treatment for more than one condition.
CSS v2.0 offers many new features including the following:
- Provides enhanced QSAR models for predicting drug-triggered IKr, IKs, INa and ICaL current inhibition based on automatically-calculated phys-chem data (when in vitro data are not available)
- Predicts population variability and drug-triggered physiology modifications
- Permits assessment of the potential impact of disease and genotypes; allows for genotype-related ionic current modification at the multiple channels level
- Contains an additional human left ventricular muscle cell model
- Evaluates up to seven chemical species (drugs, metabolites and other substances) simultaneously that are interacting at the ion channel(s) level
- Provides a new flexible, Excel-based tool to enhance visualization and analysis of simulation results
Predicting how a DDI caused QT prolongation using purely in vitro data
Clearly, we are standing on the brink of a new era of comprehensive cardiac risk assessment for drug candidates. To learn more about how model based drug development can be leveraged as a cardiac safety assessment tool, please read the CPT: Pharmacometrics & Systems Pharmacology article “Interaction Between Domperidone and Ketoconazole: Toward Prediction of Consequent QTc Prolongation Using Purely In Vitro Information” by my colleagues, Drs. Sebastian Polak and Amin Rostami. There is also an interesting commentary on this paper.