Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment.

The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP) is assessed using an in silico model of the human ventricular action potential (AP) that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ) must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet), which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax). However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an accurate determination of drug IC50-values in vitro. Thus, we demonstrate that UQ provides valuable information about in silico modeling predictions that can inform future proarrhythmic risk evaluation of drugs under the CiPA paradigm.

Corrigendum: Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment.

[This corrects the article on p. 616 in vol. 8, PMID: 28878692.].

Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment.

Drug-induced Torsade-de-Pointes (TdP) has been responsible for the withdrawal of many drugs from the market and is therefore of major concern to global regulatory agencies and the pharmaceutical industry. The Comprehensive in vitro Proarrhythmia Assay (CiPA) was proposed to improve prediction of TdP risk, using in silico models and in vitro multi-channel pharmacology data as integral parts of this initiative. Previously, we reported that combining dynamic interactions between drugs and the rapid delayed rectifier potassium current (IKr) with multi-channel pharmacology is important for TdP risk classification, and we modified the original O'Hara Rudy ventricular cell mathematical model to include a Markov model of IKr to represent dynamic drug-IKr interactions (IKr-dynamic ORd model). We also developed a novel metric that could separate drugs with different TdP liabilities at high concentrations based on total electronic charge carried by the major inward ionic currents during the action potential. In this study, we further optimized the IKr-dynamic ORd model by refining model parameters using published human cardiomyocyte experimental data under control and drug block conditions. Using this optimized model and manual patch clamp data, we developed an updated version of the metric that quantifies the net electronic charge carried by major inward and outward ionic currents during the steady state action potential, which could classify the level of drug-induced TdP risk across a wide range of concentrations and pacing rates. We also established a framework to quantitatively evaluate a system's robustness against the induction of early afterdepolarizations (EADs), and demonstrated that the new metric is correlated with the cell's robustness to the pro-EAD perturbation of IKr conductance reduction. In summary, in this work we present an optimized model that is more consistent with experimental data, an improved metric that can classify drugs at concentrations both near and higher than clinical exposure, and a physiological framework to check the relationship between a metric and EAD. These findings provide a solid foundation for using in silico models for the regulatory assessment of TdP risk under the CiPA paradigm.

Characterization of loperamide-mediated block of hERG channels at physiological temperature and its proarrhythmia propensity.

BACKGROUND: Loperamide (Immodium®) is indicated for symptomatic control of diarrhea. It is a µ-opioid receptor agonist, and recently has been associated with misuse and abuse. At therapeutic doses loperamide has not been associated with cardiotoxicity. However, loperamide overdose is associated with proarrhythmia and death - two effects that are likely attributable to its block of cardiac ion channels that are critical for generating action potentials. In this study, we defined loperamide-hERG channel interaction characteristics, and used a ventricular myocyte action potential model to compare loperamide's proarrhythmia propensity to twelve drugs with defined levels of clinical risk. METHODS AND RESULTS: Whole-cell voltage-clamp recordings were performed at 37°C on a HEK293 cell line stably expressing the hERG channel proteins, and loperamide was bath-applied to assess its effects on hERG current. Loperamide suppressed hERG current in a use- and voltage-dependent but frequency-independent manner, with a half-maximal inhibitory concentration <90nM. The onset of current suppression was concentration-dependent and appeared to follow a first-order reaction. Loperamide also altered the voltage-dependence of steady state hERG current properties. Electrophysiological data were integrated into a myocyte model that simulated dynamic drug-hERG channel interaction to estimate Torsade de Pointes risk through comparisons with reference drugs with defined clinical risk. In the context of overdose that would result in loperamide levels far exceeding those produced by therapeutic doses, loperamide is placed in the high risk category, alongside quinidine, bepridil, dofetilide, and sotalol. CONCLUSIONS: The combined in vitro and in silico approach provides mechanistic insight regarding the potential for loperamide to generate cardiotoxicity in overdose situations. This strategy holds promise for improving cardiac safety assessment.

Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology.

BACKGROUND: The current proarrhythmia safety testing paradigm, although highly efficient in preventing new torsadogenic drugs from entering the market, has important limitations that can restrict the development and use of valuable new therapeutics. The CiPA (Comprehensive in vitro Proarrhythmia Assay) proposes to overcome these limitations by evaluating drug effects on multiple cardiac ion channels in vitro and using these data in a predictive in silico model of the adult human ventricular myocyte. A set of drugs with known clinical torsade de pointes risk was selected to develop and calibrate the in silico model. METHODS AND RESULTS: Manual patch-clamp data assessing drug effects on expressed cardiac ion channels were integrated into the O'Hara-Rudy myocyte model modified to include dynamic drug-hERG channel (human Ether-à-go-go-Related Gene) interactions. Together with multichannel pharmacology data, this model predicts that compounds with high torsadogenic risk are more likely to be trapped within the hERG channel and show stronger reverse use dependency of action potential prolongation. Furthermore, drug-induced changes in the amount of electronic charge carried by the late sodium and L-type calcium currents was evaluated as a potential metric for assigning torsadogenic risk. CONCLUSIONS: Modeling dynamic drug-hERG channel interactions and multi-ion channel pharmacology improves the prediction of torsadogenic risk. With further development, these methods have the potential to improve the regulatory assessment of drug safety models under the CiPA paradigm.

Characterization of the methemoglobin forming metabolites of benzocaine and lidocaine.

1. Topical anesthesia with benzocaine or lidocaine occasionally causes methemoglobinemia, an uncommon but potentially fatal disorder where the blood has a reduced ability to transport oxygen. Previous in vitro studies using human whole blood have shown that benzocaine causes more methemoglobin (MetHb) formation than lidocaine, and that both compounds require metabolic transformation to form the MetHb producing species. In the current investigation, the active species of benzocaine forming the MetHb was investigated. 2. HPLC analysis of benzocaine samples incubated with human hepatic S9 showed the formation of a peak with the same UV spectrum and retention time as benzocaine hydroxylamine (BenzNOH). To confirm the activity of BenzNOH, MetHb production following exposure to the compound was determined in whole human blood using an Avoximeter 4000 CO-oximeter. 3. BenzNOH produced MetHb in a concentration dependent manner without the need for metabolic activation. Benzocaine in the presence of metabolic activation required a concentration of 500 µM to produce a similar degree of MetHb formation as 20 µM BenzNOH without activation. Previous work suggested that two metabolites of lidocaine may also form MetHb; N-hydroxyxylidine and 4-hydroxyxylidine. Of these two metabolites 4-hydroxyxylidine produced the most MetHb in whole blood in vitro in the absence of metabolic activation, however BenzNOH produced up to 14.2 times more MetHb than 4-hydroxyxylidine at a similar concentration. 4. These results suggest that the ability of benzocaine to form MetHb is likely to be mediated through its hydroxylamine metabolite and that this metabolite is inherently more active than the potentially MetHb-forming metabolites of lidocaine.

The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative - Update on progress.

The implementation of the ICH S7B and E14 guidelines has been successful in preventing the introduction of potentially torsadogenic drugs to the market, but it has also unduly constrained drug development by focusing on hERG block and QT prolongation as essential determinants of proarrhythmia risk. The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative was established to develop a new paradigm for assessing proarrhythmic risk, building on the emergence of new technologies and an expanded understanding of torsadogenic mechanisms beyond hERG block. An international multi-disciplinary team of regulatory, industry and academic scientists are working together to develop and validate a set of predominantly nonclinical assays and methods that eliminate the need for the thorough-QT study and enable a more precise prediction of clinical proarrhythmia risk. The CiPA effort is led by a Steering Team that provides guidance, expertise and oversight to the various working groups and includes partners from US FDA, HESI, CSRC, SPS, EMA, Health Canada, Japan NIHS, and PMDA. The working groups address the three pillars of CiPA that evaluate drug effects on: 1) human ventricular ionic channel currents in heterologous expression systems, 2) in silico integration of cellular electrophysiologic effects based on ionic current effects, the ion channel effects, and 3) fully integrated biological systems (stem-cell-derived cardiac myocytes and the human ECG). This article provides an update on the progress of the initiative towards its target date of December 2017 for completing validation.

A temperature-dependent in silico model of the human ether-à-go-go-related (hERG) gene channel.

INTRODUCTION: Current regulatory guidelines for assessing the risk of QT prolongation include in vitro assays assessing drug effects on the human ether-à-go-go-related (hERG; also known as Kv11.1) channel expressed in cell lines. These assays are typically conducted at room temperature to promote the ease and stability of recording hERG currents. However, the new Comprehensive in vitro Proarrhythmia Assay (CiPA) paradigm proposes to use an in silico model of the human ventricular myocyte to assess risk, requiring as input hERG channel pharmacology data obtained at physiological temperatures. To accommodate current industry safety pharmacology practices for measuring hERG channel activity, an in silico model of hERG channel that allows for the extrapolation of hERG assay data across different temperatures is desired. Because temperature may have an effect on both channel gating and drug binding rate, such models may need to have two components: a base model dealing with temperature-dependent gating changes without drug, and a pharmacodynamic component simulating temperature-dependent drug binding kinetics. As a first step, a base mode that can capture temperature effects on hERG channel gating without drug is needed. METHODS AND RESULTS: To meet this need for a temperature-dependent base model, a Markov model of the hERG channel with state transition rates explicitly dependent on temperature was developed and calibrated using data from a variety of published experiments conducted over a range of temperatures. The model was able to reproduce observed temperature-dependent changes in key channel gating properties and also to predict the results obtained in independent sets of new experiments. DISCUSSION: This new temperature-sensitive model of hERG gating represents an attempt to improve the predictivity of safety pharmacology testing by enabling the translation of room temperature hERG assay data to more physiological conditions. With further development, this model can be incorporated into the CiPA paradigm and also be used as a tool for developing insights into the thermodynamics of hERG channel gating mechanisms and the temperature-dependence of hERG channel block by drugs.

A New Perspective in the Field of Cardiac Safety Testing through the Comprehensive In Vitro Proarrhythmia Assay Paradigm.

For the past decade, cardiac safety screening to evaluate the propensity of drugs to produce QT interval prolongation and Torsades de Pointes (TdP) arrhythmia has been conducted according to ICH S7B and ICH E14 guidelines. Central to the existing approach are hERG channel assays and in vivo QT measurements. Although effective, the present paradigm carries a risk of unnecessary compound attrition and high cost, especially when considering costly thorough QT (TQT) studies conducted later in drug development. The C: omprehensive I: n Vitro P: roarrhythmia A: ssay (CiPA) initiative is a public-private collaboration with the aim of updating the existing cardiac safety testing paradigm to better evaluate arrhythmia risk and remove the need for TQT studies. It is hoped that CiPA will produce a standardized ion channel assay approach, incorporating defined tests against major cardiac ion channels, the results of which then inform evaluation of proarrhythmic actions in silico, using human ventricular action potential reconstructions. Results are then to be confirmed using human (stem cell-derived) cardiomyocytes. This perspective article reviews the rationale, progress of, and challenges for the CiPA initiative, if this new paradigm is to replace existing practice and, in time, lead to improved and widely accepted cardiac safety testing guidelines.

Impact of Pathologists and Evaluation Methods on Performance Assessment of the Kidney Injury Biomarker, Kim-1.

Attempts to characterize and formally qualify biomarkers for regulatory purposes have raised questions about how histological and histopathological methods impact the evaluation of biomarker performance. A group of pathologists was asked to analyze digitized images prepared from rodent kidney injury experiments in studies designed to investigate sources of variability in histopathology evaluations. Study A maximized variability by using samples from diverse studies and providing minimal guidance, contextual information, or opportunities for pathologist interaction. Study B was designed to limit interpathologist variability by using more uniform image sets from different locations within the same kidneys and allowing pathologist selected interactions to discuss and identify the location and injury to be evaluated but without providing a lexicon or peer review. Results from this study suggest that differences between pathologists and across models of disease are the largest sources of variability in evaluations and that blind evaluations do not generally make a significant difference. Results of this study generally align with recommendations from both industry and the U.S. Food and Drug Administration and should inform future studies examining the effects of common lexicons and scoring criteria, peer review, and blind evaluations in the context of biomarker performance assessment.

Modeling and simulation for medical product development and evaluation: highlights from the FDA-C-Path-ISOP 2013 workshop.

Medical-product development has become increasingly challenging and resource-intensive. In 2004, the Food and Drug Administration (FDA) described critical challenges facing medical-product development by establishing the critical path initiative [1]. Priorities identified included the need for improved modeling and simulation tools, further emphasized in FDA's 2011 Strategic Plan for Regulatory Science [Appendix]. In an effort to support and advance model-informed medical-product development (MIMPD), the Critical Path Institute (C-Path) [www.c-path.org], FDA, and International Society of Pharmacometrics [www.go-isop.org] co-sponsored a workshop in Washington, D.C. on September 26, 2013, to examine integrated approaches to developing and applying model- MIMPD. The workshop brought together an international group of scientists from industry, academia, FDA, and the European Medicines Agency to discuss MIMPD strategies and their applications. A commentary on the proceedings of that workshop is presented here.

More methemoglobin is produced by benzocaine treatment than lidocaine treatment in human in vitro systems.

The clinical use of local anesthetic products to anesthetize mucous membranes has been associated with methemoglobinemia (MetHba), a serious condition in which the blood has reduced capacity to carry oxygen. An evaluation of spontaneous adverse event reporting of MetHba submitted to FDA through 2013 identified 375 reports associated with benzocaine and 16 reports associated with lidocaine. The current study was performed to determine the relative ability of benzocaine and lidocaine to produce methemoglobin (MetHb) in vitro. Incubation of 500µM benzocaine with whole human blood and pooled human liver S9 over 5h resulted in MetHb levels equaling 39.8±1.2% of the total hemoglobin. No MetHb formation was detected for 500µM lidocaine under the same conditions. Because liver S9 does not readily form lidocaine hydrolytic metabolites based on xylidine, a primary metabolic pathway, 500µM xylidine was directly incubated with whole blood and S9. Under these conditions MetHb levels of 4.4±0.4% were reached by 5h. Studies with recombinant cytochrome P450 revealed benzocaine to be extensively metabolized by CYP 1A2, with 2B6, 2C19, 2D6, and 2E1 also having activity. We conclude that benzocaine produces much more MetHb in in vitro systems than lidocaine or xylidine and that benzocaine should be more likely to cause MetHba in vivo as well.

EADB: an estrogenic activity database for assessing potential endocrine activity.

Endocrine-active chemicals can potentially have adverse effects on both humans and wildlife. They can interfere with the body's endocrine system through direct or indirect interactions with many protein targets. Estrogen receptors (ERs) are one of the major targets, and many endocrine disruptors are estrogenic and affect the normal estrogen signaling pathways. However, ERs can also serve as therapeutic targets for various medical conditions, such as menopausal symptoms, osteoporosis, and ER-positive breast cancer. Because of the decades-long interest in the safety and therapeutic utility of estrogenic chemicals, a large number of chemicals have been assayed for estrogenic activity, but these data exist in various sources and different formats that restrict the ability of regulatory and industry scientists to utilize them fully for assessing risk-benefit. To address this issue, we have developed an Estrogenic Activity Database (EADB; http://www.fda.gov/ScienceResearch/BioinformaticsTools/EstrogenicActivityDatabaseEADB/default.htm) and made it freely available to the public. EADB contains 18,114 estrogenic activity data points collected for 8212 chemicals tested in 1284 binding, reporter gene, cell proliferation, and in vivo assays in 11 different species. The chemicals cover a broad chemical structure space and the data span a wide range of activities. A set of tools allow users to access EADB and evaluate potential endocrine activity of chemicals. As a case study, a classification model was developed using EADB for predicting ER binding of chemicals.

Comparison of urinary and serum levels of di-22:6-bis(monoacylglycerol)phosphate as noninvasive biomarkers of phospholipidosis in rats.

Phospholipidosis (PLD), an abnormal accumulation of phospholipids within tissues, is observed during the preclinical testing of many pharmaceutical drugs. Diagnosis of PLD is currently based on morphologic criteria. An understanding of the clinical incidence of PLD and its possible relationship to adverse drug reactions has been hampered by the absence of noninvasive biomarkers for PLD. The uncommon phospholipid di-docosahexaenoyl bis(monoacylglycerol) phosphate (di-22:6-BMP) has been proposed as a potential urinary biomarker for PLD, but data on the utility of serum di-22:6-BMP measurements in diagnosing PLD is more limited. In this report, we compared the performance of serum and urinary di-22:6-BMP as biomarkers for PLD in rats treated with the PLD-inducing drugs amiodarone and 4,4'-diethylaminoethoxyhexestrol dihydrochloride or the hepatotoxicant acetaminophen (APAP). Serum levels of di-22:6-BMP showed a higher correlation to a generalized PLD incidence score than did levels in urine, but were unexpectedly elevated in rats with marked levels of APAP-induced liver necrosis. When samples were filtered based on serum ALT or liver histopathology thresholds, the diagnostic accuracy of serum di-22:6-BMP for PLD improved to the high level observed for urinary di-22:6-BMP without sample exclusion. These data help define the potential context-of-use of serum di-22:6-BMP as a non-clinical biomarker of PLD.

Comparison of the diagnostic accuracy of di-22:6-bis(monoacylglycerol)phosphate and other urinary phospholipids for drug-induced phospholipidosis or tissue injury in the rat.

Cationic amphiphilic drugs and aminoglycoside antibiotics can induce phospholipidosis (PLD), an abnormal accumulation of phospholipids in lysosome-derived vesicles, in preclinical studies. The incidence of PLD in patients and its clinical relevance are difficult to assess without noninvasive biomarkers. Di-docosahexaenoyl bis(monoacylglycerol)phosphate (di-22:6-BMP) is a phospholipid that is enriched in lysosomal membranes and a proposed urinary biomarker of drug-induced PLD. The specificity of di-22:6-BMP for PLD was compared to other phospholipid species that can increase in urine with nephrotoxicity. Using liquid chromatography coupled to mass spectrometry, 12 phospholipids were assayed in the urine of rats treated with drugs that induced PLD or caused renal or skeletal muscle injury. In receiver operating curve analyses, urinary di-22:6-BMP was a significantly better predictor of PLD and the least predictive of tissue injury of the phospholipids assayed. The data provide evidence supporting the use of di-22:6-BMP as a urinary biomarker of PLD in rats.

Uniform assessment and ranking of opioid µ receptor binding constants for selected opioid drugs.

The safe disposal of unused opioid drugs is an area of regulatory concern. While toilet flushing is recommended for some drugs to prevent accidental exposure, there is a need for data that can support a more consistent disposal policy based on an assessment of relative risk. For drugs acting at the Mu-opioid receptor (MOR), published measurements of binding affinity (K(i)) are incomplete and inconsistent due to differences in methodology and assay system, leading to a wide range of values for the same drug thus precluding a simple and meaningful relative ranking of drug potency. Experiments were conducted to obtain K(i)'s for 19 approved opioid drugs using a single binding assay in a cell membrane preparation expressing recombinant human MOR. The K(i) values obtained ranged from 0.1380 nM (sufentanil) to 12.486 µM (tramadol). The drugs were separated into three categories based upon their K(i) values: K(i) > 100 nM (tramadol, codeine, meperidine, propoxyphene and pentazocine), K(i)=1-100 nM (hydrocodone, oxycodone, diphenoxylate, alfentanil, methadone, nalbuphine, fentanyl and morphine) and K(i) < 1 nM (butorphanol, levorphanol, oxymorphone, hydromorphone, buprenorphine and sufentanil). These data add to the understanding of the pharmacology of opioid drugs and support the development of a more consistent labeling policies regarding safe disposal.

Biomarkers of endothelial cell activation serve as potential surrogate markers for drug-induced vascular injury.

Drug-induced vascular injury (DIVI) is a nonclinical finding that often confounds the toxicological evaluation of investigational drugs, but there is an absence of qualified biomarkers that can be used to detect and monitor its appearance in animals and patients during drug development and clinical use. It is well known that endothelial cell (EC) activation plays a key role in the expression and evolution of DIVI, and the various immunological and inflammatory factors involved in its expression may serve as potential biomarker candidates. Activated ECs change their morphology and gene expression, generating endothelial adhesion molecules, pro-coagulant molecules, cytokines, chemokines, vasodilators, nitric oxide, and acute-phase reactants. This review provides a brief historical background of EC activation and the search for biomarkers of early EC activation for monitoring DIVI. At present, no biomarkers of EC activation have been qualified to predict DIVI in the nonclinical or clinical context, and a robust pathologic foundation for their use is still lacking. We propose three categories of EC activation biomarkers: recommended surrogate markers, potentially useful markers, and emerging candidate markers. This review alerts pharmaceutical companies, research institutions, and regulatory agencies to the continuing need for reliable biomarkers of EC activation in drug development.

'Impedance matching' of data sets in biomarker research.

The goal of biomarker research in drug development is to identify better ways of monitoring the effects of drugs on biological systems. Biomarker data are used to support decision making at various stages in the drug development process, and are also used to provide information on how drug use might be optimized in different patient populations. The evaluation and qualification of new safety biomarkers includes a rigorous analysis of the ability of a given biomarker to report specific pathological events at the cellular, tissue or systemic level. This evaluation often relies on the mapping of a continuous data set (eg, biomarker levels) onto discrete phenotypic descriptors (eg, pathology scores). The approach has been applied successfully to discover new and improved biomarkers of tissue injury, but may involve uncertainty when used to evaluate the ability of a biomarker to detect early events or events occurring near the threshold of drug action. Alternative approaches based on study endpoints that provide continuous descriptions of a disease state or drug action, coupled with measurements of changes in biological function, may provide a better 'impedance match' between input and output data in biomarker research, and improve the early assessment and prediction of drug safety issues.

Reassessing the validity of surrogate markers of drug efficacy in the treatment of coronary artery disease.

Surrogate markers of disease progression and drug efficacy have become an essential part of cardiovascular drug development. Some surrogate markers, such as LDL-cholesterol (LDL-C), have been studied extensively and are widely accepted as valid indicators of cardiovascular risk and as a basis for regulatory approval. Other markers, such as carotid intima-media thickness (IMT), can provide insights into coronary atherosclerosis, but their utility as surrogate endpoints remains uncertain. The ENHANCE clinical trial, which demonstrated robust, beneficial changes in LDL-C and other biochemical surrogate markers, but no reduction in carotid IMT, has highlighted the need to understand the use and contextual limitations of surrogate markers in guiding cardiovascular drug development and medical decision-making.