A multiscale predictive digital twin for neurocardiac modulation.

Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the ß-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.

A Computational Pipeline to Predict Cardiotoxicity: From the Atom to the Rhythm.

RATIONALE: Drug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation is an accepted surrogate marker for arrhythmia. But QT interval is too sensitive a marker and not selective, resulting in many useful drugs eliminated in drug discovery. OBJECTIVE: To predict the impact of a drug from the drug chemistry on the cardiac rhythm. METHODS AND RESULTS: In a new linkage, we connected atomistic scale information to protein, cell, and tissue scales by predicting drug-binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel. Model components were integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data were used for model framework validation and showed excellent agreement, demonstrating feasibility of a new approach for cardiotoxicity prediction. CONCLUSIONS: We present a multiscale model framework to predict electrotoxicity in the heart from the atom to the rhythm. Novel mechanistic insights emerged at all scales of the system, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundamental cellular and tissue-level arrhythmia mechanisms. Applications of machine learning indicate necessary and sufficient parameters that predict arrhythmia vulnerability. We expect that the model framework may be expanded to make an impact in drug discovery, drug safety screening for a variety of compounds and targets, and in a variety of regulatory processes.

Interdisciplinary collaboration and computer-assisted home healthcare referral in the emergency department: a retrospective cohort study.

AIM: Home healthcare (HHC) provides continuous care for disabled patients. However, HHC referral after the emergency department (ED) discharge remains unclear. Thus, this study aimed its clarification. METHODS: A computer-assisted HHC referral by interdisciplinary collaboration among emergency physicians, case managers, nurse practitioners, geriatricians, and HHC nurses was built in a tertiary medical center in Taiwan. Patients who had HHC referrals after ED discharge between February 1, 2020 and September 31, 2020, were recruited into the study. A non-ED HHC cohort who had HHC referrals after hospitalization from the ED was also identified. Comparison for clinical characteristics and uses of medical resources was performed between ED HHC and non-ED HHC cohorts. RESULTS: The model was successfully implemented. In total, 34 patients with ED HHC and 40 patients with non-ED HHC were recruited into the study. The female proportion was 61.8% and 67.5%, and the mean age was 81.5 and 83.7 years in ED HHC and non-ED HHC cohorts, respectively. No significant difference was found in sex, age, underlying comorbidities, and ED diagnoses between the two cohorts. The ED HHC cohort had a lower median total medical expenditure within 3 months (34,030.0 vs. 56,624.0 New Taiwan Dollars, p = 0.021) compared with the non-ED HHC cohort. Compared to the non-ED HHC cohort, the ED HHC cohort had a lower ≤ 1 month ED visit, ≤ 6 months ED visit, and ≤ 3 months hospitalization; however, differences were not significant. CONCLUSION: An innovative ED HHC model was successfully implemented. Further studies with more patients are warranted to investigate the impact.

Computerized tool and interdisciplinary care for older patients with delirium in the emergency department: a novel model in Taiwan.

AIMS: A computerized tool and interdisciplinary care were implemented to develop a novel model for older patients with delirium in the emergency department (ED). METHODS: We developed a computerized tool using a delirium triage screen and brief confusion assessment in the hospital information system, performed education for the healthcare providers, and developed a continuous care protocol. Comparisons for outcomes between pre- and post-intervention periods were performed. RESULTS: Compared with the pre-intervention period, patients in the post-intervention period had shorter hospitalization stay, lower expenditure of hospitalization, more likely to return home, lower ED revisits of ≤ 3 days, re-hospitalization of ≤ 14 days, and mortality of ≤ 1 month. All mentioned differences were not statistically significant. CONCLUSIONS: A novel model was successfully developed for delirium management in older patients in the ED. Outcome differences were not significant; however, the result is promising, which gives us an important reference in the future.

Mechanisms of flecainide induced negative inotropy: An in silico study.

It is imperative to develop better approaches to predict how antiarrhythmic drugs with multiple interactions and targets may alter the overall electrical and/or mechanical function of the heart. Safety Pharmacology studies have provided new insights into the multi-target effects of many different classes of drugs and have been aided by the addition of robust new in vitro and in silico technology. The primary focus of Safety Pharmacology studies has been to determine the risk profile of drugs and drug candidates by assessing their effects on repolarization of the cardiac action potential. However, for decades experimental and clinical studies have described substantial and potentially detrimental effects of Na+ channel blockers in addition to their well-known conduction slowing effects. One such side effect, associated with administration of some Na+ channel blocking drugs is negative inotropy. This reduces the pumping function of the heart, thereby resulting in hypotension. Flecainide is a well-known example of a Na+ channel blocking drug, that exhibits strong rate-dependent block of INa and may cause negative cardiac inotropy. While the phenomenon of Na+ channel suppression and resulting negative inotropy is well described, the mechanism(s) underlying this effect are not. Here, we set out to use a modeling and simulation approach to reveal plausible mechanisms that could explain the negative inotropic effect of flecainide. We utilized the Grandi-Bers model [1] of the cardiac ventricular myocyte because of its robust descriptions of ion homeostasis in order to characterize and resolve the relative effects of QRS widening, flecainide off-target effects and changes in intracellular Ca2+ and Na+ homeostasis. The results of our investigations and predictions reconcile multiple data sets and illustrate how multiple mechanisms may play a contributing role in the flecainide induced negative cardiac inotropic effect.

Molecular determinants of pro-arrhythmia proclivity of d- and l-sotalol via a multi-scale modeling pipeline.

Drug isomers may differ in their proarrhythmia risk. An interesting example is the drug sotalol, an antiarrhythmic drug comprising d- and l- enantiomers that both block the hERG cardiac potassium channel and confer differing degrees of proarrhythmic risk. We developed a multi-scale in silico pipeline focusing on hERG channel - drug interactions and used it to probe and predict the mechanisms of pro-arrhythmia risks of the two enantiomers of sotalol. Molecular dynamics (MD) simulations predicted comparable hERG channel binding affinities for d- and l-sotalol, which were validated with electrophysiology experiments. MD derived thermodynamic and kinetic parameters were used to build multi-scale functional computational models of cardiac electrophysiology at the cell and tissue scales. Functional models were used to predict inactivated state binding affinities to recapitulate electrocardiogram (ECG) QT interval prolongation observed in clinical data. Our study demonstrates how modeling and simulation can be applied to predict drug effects from the atom to the rhythm for dl-sotalol and also increased proarrhythmia proclivity of d- vs. l-sotalol when accounting for stereospecific beta-adrenergic receptor blocking.

A computational model of induced pluripotent stem-cell derived cardiomyocytes for high throughput risk stratification of KCNQ1 genetic variants.

In the last decade, there has been tremendous progress in identifying genetic anomalies linked to clinical disease. New experimental platforms have connected genetic variants to mechanisms underlying disruption of cellular and organ behavior and the emergence of proarrhythmic cardiac phenotypes. The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) signifies an important advance in the study of genetic disease in a patient-specific context. However, considerable limitations of iPSC-CM technologies have not been addressed: 1) phenotypic variability in apparently identical genotype perturbations, 2) low-throughput electrophysiological measurements, and 3) an immature phenotype which may impact translation to adult cardiac response. We have developed a computational approach intended to address these problems. We applied our recent iPSC-CM computational model to predict the proarrhythmic risk of 40 KCNQ1 genetic variants. An IKs computational model was fit to experimental data for each mutation, and the impact of each mutation was simulated in a population of iPSC-CM models. Using a test set of 15 KCNQ1 mutations with known clinical long QT phenotypes, we developed a method to stratify the effects of KCNQ1 mutations based on proarrhythmic markers. We utilized this method to predict the severity of the remaining 25 KCNQ1 mutations with unknown clinical significance. Tremendous phenotypic variability was observed in the iPSC-CM model population following mutant perturbations. A key novelty is our reporting of the impact of individual KCNQ1 mutant models on adult ventricular cardiomyocyte electrophysiology, allowing for prediction of mutant impact across the continuum of aging. This serves as a first step toward translating predicted response in the iPSC-CM model to predicted response of the adult ventricular myocyte given the same genetic mutation. As a whole, this study presents a new computational framework that serves as a high throughput method to evaluate risk of genetic mutations based-on proarrhythmic behavior in phenotypically variable populations.

A demonstration of modularity, reuse, reproducibility, portability and scalability for modeling and simulation of cardiac electrophysiology using Kepler Workflows.

Multi-scale computational modeling is a major branch of computational biology as evidenced by the US federal interagency Multi-Scale Modeling Consortium and major international projects. It invariably involves specific and detailed sequences of data analysis and simulation, often with multiple tools and datasets, and the community recognizes improved modularity, reuse, reproducibility, portability and scalability as critical unmet needs in this area. Scientific workflows are a well-recognized strategy for addressing these needs in scientific computing. While there are good examples if the use of scientific workflows in bioinformatics, medical informatics, biomedical imaging and data analysis, there are fewer examples in multi-scale computational modeling in general and cardiac electrophysiology in particular. Cardiac electrophysiology simulation is a mature area of multi-scale computational biology that serves as an excellent use case for developing and testing new scientific workflows. In this article, we develop, describe and test a computational workflow that serves as a proof of concept of a platform for the robust integration and implementation of a reusable and reproducible multi-scale cardiac cell and tissue model that is expandable, modular and portable. The workflow described leverages Python and Kepler-Python actor for plotting and pre/post-processing. During all stages of the workflow design, we rely on freely available open-source tools, to make our workflow freely usable by scientists.

When Does the IC50 Accurately Assess the Blocking Potency of a Drug?

Preclinical assessment of drug-induced proarrhythmicity is typically evaluated by the potency of the drug to block the potassium human ether-à-go-go-related gene (hERG) channels, which is currently quantified by the IC50. However, channel block depends on the experimental conditions. Our aim is to improve the evaluation of the blocking potency of drugs by designing experimental stimulation protocols to measure the IC50 that will help to decide whether the IC50 is representative enough. We used the state-of-the-art mathematical models of the cardiac electrophysiological activity to design three stimulation protocols that enhance the differences in the probabilities to occupy a certain conformational state of the channel and, therefore, the potential differences in the blocking effects of a compound. We simulated an extensive set of 144 in silico IKr blockers with different kinetics and affinities to conformational states of the channel and we also experimentally validated our key predictions. Our results show that the IC50 protocol dependency relied on the tested compounds. Some of them showed no differences or small differences on the IC50 value, which suggests that the IC50 could be a good indicator of the blocking potency in these cases. However, others provided highly protocol dependent IC50 values, which could differ by even 2 orders of magnitude. Moreover, the protocols yielding the maximum IC50 and minimum IC50 depended on the drug, which complicates the definition of a "standard" protocol to minimize the influence of the stimulation protocol on the IC50 measurement in safety pharmacology. As a conclusion, we propose the adoption of our three-protocol IC50 assay to estimate the potency to block hERG in vitro. If the IC50 values obtained for a compound are similar, then the IC50 could be used as an indicator of its blocking potency, otherwise kinetics and state-dependent binding properties should be accounted.

A multiscale computational modelling approach predicts mechanisms of female sex risk in the setting of arousal-induced arrhythmias.

KEY POINTS: This study represents a first step toward predicting mechanisms of sex-based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening. We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias. Using the recently solved cryo-EM structure for the Eag-family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S). Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore. ABSTRACT: Female sex is a risk factor for inherited and acquired long-QT associated torsade de pointes (TdP) arrhythmias, and sympathetic discharge is a major factor in triggering TdP in female long-QT syndrome patients. We used a combined experimental and computational approach to predict 'the perfect storm' of hormone concentration, IKr block and sympathetic stimulation that induces arrhythmia in females with inherited and acquired long-QT. More specifically, we developed mathematical models of acquired and inherited long-QT syndrome in male and female ventricular human myocytes by combining effects of a hormone and a hERG blocker, dofetilide, or hERG mutations. These 'male' and 'female' model myocytes and tissues then were used to predict how various sex-based differences underlie arrhythmia risk in the setting of acute sympathetic nervous system discharge. The model predicted increased risk for arrhythmia in females when acute sympathetic nervous system discharge was applied in the settings of both inherited and acquired long-QT syndrome. Females were predicted to have protection from arrhythmia induction when progesterone is high. Males were protected by the presence of testosterone. Structural modelling points towards two plausible and distinct mechanisms of oestrogen action enhancing torsadogenic effects: oestradiol interaction with hERG mutations in the pore loop containing G604 or with common TdP-related blockers in the intra-cavity binding site. Our study presents findings that constitute the first evidence linking structure to function mechanisms underlying female dominance of arousal-induced arrhythmias.

Mechanisms of Calmodulin Regulation of Different Isoforms of Kv7.4 K+ Channels.

Calmodulin (CaM), a Ca(2+)-sensing protein, is constitutively bound to IQ domains of the C termini of human Kv7 (hKv7, KCNQ) channels to mediate Ca(2+)-dependent reduction of Kv7 currents. However, the mechanism remains unclear. We report that CaM binds to two isoforms of the hKv7.4 channel in a Ca(2+)-independent manner but that only the long isoform (hKv7.4a) is regulated by Ca(2+)/CaM. Ca(2+)/CaM mediate reduction of the hKv7.4a channel by decreasing the channel open probability and altering activation kinetics. We took advantage of a known missense mutation (G321S) that has been linked to progressive hearing loss to further examine the inhibitory effects of Ca(2+)/CaM on the Kv7.4 channel. Using multidisciplinary techniques, we demonstrate that the G321S mutation may destabilize CaM binding, leading to a decrease in the inhibitory effects of Ca(2+) on the channels. Our study utilizes an expression system to dissect the biophysical properties of the WT and mutant Kv7.4 channels. This report provides mechanistic insights into the critical roles of Ca(2+)/CaM regulation of the Kv7.4 channel under physiological and pathological conditions.

A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation.

Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain unique receptor-dependent functional responses. How exactly compartmentation is achieved, however, has remained a mystery for more than 40 years. In this study, we developed computational and mathematical models to represent a subcellular sarcomeric space in a cardiac myocyte with varying detail. We then used these models to predict the contributions of various mechanisms that establish subcellular cAMP microdomains. We used the models to test the hypothesis that phosphodiesterases act as functional barriers to diffusion, creating discrete cAMP signaling domains. We also used the models to predict the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Finally, we modeled the anatomical structures in a cardiac myocyte diad, to predict the effects of anatomical diffusion barriers on cAMP compartmentation. When we incorporated experimentally informed model parameters to reconstruct an in silico subcellular sarcomeric space with spatially distinct cAMP production sites linked to caveloar domains, the models predict that under realistic conditions phosphodiesterases alone were insufficient to generate significant cAMP gradients. This prediction persisted even when combined with slow cAMP diffusion. When we additionally considered the effects of anatomic barriers to diffusion that are expected in the cardiac myocyte dyadic space, cAMP compartmentation did occur, but only when diffusion was slow. Our model simulations suggest that additional mechanisms likely contribute to cAMP gradients occurring in submicroscopic domains. The difference between the physiological and pathological effects resulting from the production of cAMP may be a function of appropriate compartmentation of cAMP signaling. Therefore, understanding the contribution of factors that are responsible for coordinating the spatial and temporal distribution of cAMP at the subcellular level could be important for developing new strategies for the prevention or treatment of unfavorable responses associated with different disease states.

A computational model predicts adjunctive pharmacotherapy for cardiac safety via selective inhibition of the late cardiac Na current.

BACKGROUND: The QT interval is a phase of the cardiac cycle that corresponds to action potential duration (APD) including cellular repolarization (T-wave). In both clinical and experimental settings, prolongation of the QT interval of the electrocardiogram (ECG) and related proarrhythmia have been so strongly associated that a prolonged QT interval is largely accepted as surrogate marker for proarrhythmia. Accordingly, drugs that prolong the QT interval are not considered for further preclinical development resulting in removal of many promising drugs from development. While reduction of drug interactions with hERG is an important goal, there are promising means to mitigate hERG block. Here, we examine one possibility and test the hypothesis that selective inhibition of the cardiac late Na current (INaL) by the novel compound GS-458967 can suppress proarrhythmic markers. METHODS AND RESULTS: New experimental data has been used to calibrate INaL in the Soltis-Saucerman computationally based model of the rabbit ventricular action potential to study effects of GS-458967 on INaL during the rabbit ventricular AP. We have also carried out systematic in silico tests to determine if targeted block of INaL would suppress proarrhythmia markers in ventricular myocytes described by TRIaD: Triangulation, Reverse use dependence, beat-to-beat Instability of action potential duration, and temporal and spatial action potential duration Dispersion. CONCLUSIONS: Our computer modeling approach based on experimental data, yields results that suggest that selective inhibition of INaL modifies all TRIaD related parameters arising from acquired Long-QT Syndrome, and thereby reduced arrhythmia risk. This study reveals the potential for adjunctive pharmacotherapy via targeted block of INaL to mitigate proarrhythmia risk for drugs with significant but unintended off-target hERG blocking effects.

In silico prediction of drug therapy in catecholaminergic polymorphic ventricular tachycardia.

KEY POINTS: The mechanism of therapeutic efficacy of flecainide for catecholaminergic polymorphic ventricular tachycardia (CPVT) is unclear. Model predictions suggest that Na(+) channel effects are insufficient to explain flecainide efficacy in CPVT. This study represents a first step toward predicting therapeutic mechanisms of drug efficacy in the setting of CPVT and then using these mechanisms to guide modelling and simulation to predict alternative drug therapies. Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited arrhythmia syndrome characterized by fatal ventricular arrhythmias in structurally normal hearts during ß-adrenergic stimulation. Current treatment strategies include ß-blockade, flecainide and ICD implementation--none of which is fully effective and each comes with associated risk. Recently, flecainide has gained considerable interest in CPVT treatment, but its mechanism of action for therapeutic efficacy is unclear. In this study, we performed in silico mutagenesis to construct a CPVT model and then used a computational modelling and simulation approach to make predictions of drug mechanisms and efficacy in the setting of CPVT. Experiments were carried out to validate model results. Our simulations revealed that Na(+) channel effects are insufficient to explain flecainide efficacy in CPVT. The pure Na(+) channel blocker lidocaine and the antianginal ranolazine were additionally tested and also found to be ineffective. When we tested lower dose combination therapy with flecainide, ß-blockade and CaMKII inhibition, our model predicted superior therapeutic efficacy than with flecainide monotherapy. Simulations indicate a polytherapeutic approach may mitigate side-effects and proarrhythmic potential plaguing CPVT pharmacological management today. Importantly, our prediction of a novel polytherapy for CPVT was confirmed experimentally. Our simulations suggest that flecainide therapeutic efficacy in CPVT is unlikely to derive from primary interactions with the Na(+) channel, and benefit may be gained from an alternative multi-drug regimen.

In silico screening of the impact of hERG channel kinetic abnormalities on channel block and susceptibility to acquired long QT syndrome.

Accurate diagnosis of predisposition to long QT syndrome is crucial for reducing the risk of cardiac arrhythmias. In recent years, drug-induced provocative tests have proved useful to unmask some latent mutations linked to cardiac arrhythmias. In this study we expanded this concept by developing a prototype for a computational provocative screening test to reveal genetic predisposition to acquired long-QT syndrome (aLQTS). We developed a computational approach to reveal the pharmacological properties of I(Kr) blocking drugs that are most likely to cause aLQTS in the setting of subtle alterations in I(Kr) channel gating that would be expected to result from benign genetic variants.Weused themodel to predict themost potentially lethal combinations of kinetic anomalies and drug properties. In doing so, we also implicitly predicted ideal inverse therapeutic properties of K channel openers that would be expected to remedy a specific defect. We systematically performed "in silico mutagenesis" by altering discrete kinetic transition rates of the Fink et al. Markov model of human I(Kr) channels, corresponding to activation, inactivation, deactivation and recovery from inactivation of I(Kr) channels. We then screened and identified the properties of I(Kr) blockers that caused acquired long QT and therefore unmasked mutant phenotypes formild,moderate and severe variants. Mutant I(Kr) channels were incorporated into the O'Hara et al. human ventricular action potential (AP) model and subjected to simulated application of a wide variety of I(Kr)-drug interactions in order to identify the characteristics that selectively exacerbate the AP duration (APD) differences between wild-type and I(Kr) mutated cells. Our results show that drugs with disparate affinities to conformation states of the I(Kr) channel are key to amplify variants underlying susceptibility to acquired long QT syndrome, an effect that is especially pronounced at slow frequencies. Finally, we developed a mathematical formulation of the M54T MiRP1 latent mutation and simulated a provocative test. In this setting, application of dofetilide dramatically amplified the predicted QT interval duration in the M54T hMiRP1 mutation compared to wild-type.

A computational modelling approach combined with cellular electrophysiology data provides insights into the therapeutic benefit of targeting the late Na+ current.

KEY POINTS: The ventricular action potential plateau is a phase of high resistance, which makes ventricular myocytes vulnerable to small electrical perturbations. We developed a computationally based model of GS-458967 interaction with the cardiac Na+ channel, informed by experimental data recorded from guinea pig isolated single ventricular myocytes. The model predicts that the therapeutic potential of GS-458967 derives largely from the designed property of significant potent selectivity for INaL. ABSTRACT: Selective inhibition of the slowly inactivating or late Na(+) current (INaL) in patients with inherited or acquired arrhythmia syndrome may confer therapeutic benefit by reducing the incidence of triggers for arrhythmia and suppressing one component of arrhythmia-promoting cardiac substrates (e.g. prolonged refractoriness and spatiotemporal dispersion of action potential duration). Recently, a novel compound that preferentially and potently reduces INaL, GS-458967 (IC50 for block of INaL = 130 nM) has been studied. Experimental measurements of the effects of GS-458967 on endogenous INaL in guinea pig ventricular myocytes demonstrate a robust concentration-dependent reduction in action potential duration (APD). Using experimental data to calibrate INaL and the rapidly activating delayed rectifier K(+) current, IKr, in the Faber-Rudy computationally based model of the guinea pig ventricular action potential, we simulated effects of GS-458967 on guinea pig ventricular APD. GS-458967 (0.1 µM) caused a 28.67% block of INaL and 12.57% APD shortening in experiments, while the model predicted 10.06% APD shortening with 29.33% block of INaL. An additional effect of INaL block is to reduce the time during which the membrane potential is in a high resistance state (i.e. the action potential plateau). To test the hypothesis that targeted block of INaL would make ventricular myocytes less susceptible to small electrical perturbations, we used the computational model to test the degree of APD prolongation induced by small electrical perturbations in normal cells and in cells with simulated long QT syndrome. The model predicted a substantial dose-dependent reduction in sensitivity to small electrical perturbations as evidenced by action potential duration at 90% repolarization variability in the presence of GS-458967-induced INaL block. This effect was especially potent in the 'disease setting' of inherited long QT syndrome. Using a combined experimental and theoretical approach, our results suggest that INaL block is a potent therapeutic strategy. This is because reduction of INaL stabilizes the action potential waveform by reducing depolarizing current during the plateau phase of the action potential. This reduces the most vulnerable phase of the action potential with high membrane resistance. In summary, by reducing the sensitivity of the myocardial substrate to small electrical perturbations that promote arrhythmia triggers, agents such as GS-458967 may constitute an effective antiarrhythmic pharmacological strategy.

Ranolazine for congenital and acquired late INa-linked arrhythmias: in silico pharmacological screening.

RATIONALE: The antianginal ranolazine blocks the human ether-a-go-go-related gene-based current IKr at therapeutic concentrations and causes QT interval prolongation. Thus, ranolazine is contraindicated for patients with preexisting long-QT and those with repolarization abnormalities. However, with its preferential targeting of late INa (INaL), patients with disease resulting from increased INaL from inherited defects (eg, long-QT syndrome type 3 or disease-induced electric remodeling (eg, ischemic heart failure) might be exactly the ones to benefit most from the presumed antiarrhythmic properties of ranolazine. OBJECTIVE: We developed a computational model to predict if therapeutic effects of pharmacological targeting of INaL by ranolazine prevailed over the off-target block of IKr in the setting of inherited long-QT syndrome type 3 and heart failure. METHODS AND RESULTS: We developed computational models describing the kinetics and the interaction of ranolazine with cardiac Na(+) channels in the setting of normal physiology, long-QT syndrome type 3-linked ΔKPQ mutation, and heart failure. We then simulated clinically relevant concentrations of ranolazine and predicted the combined effects of Na(+) channel and IKr blockade by both the parent compound ranolazine and its active metabolites, which have shown potent blocking effects in the therapeutically relevant range. Our simulations suggest that ranolazine is effective at normalizing arrhythmia triggers in bradycardia-dependent arrhythmias in long-QT syndrome type 3 as well tachyarrhythmogenic triggers arising from heart failure-induced remodeling. CONCLUSIONS: Our model predictions suggest that acute targeting of INaL with ranolazine may be an effective therapeutic strategy in diverse arrhythmia-provoking situations that arise from a common pathway of increased pathological INaL.

In silico screening of the impact of hERG channel kinetic abnormalities on channel block and susceptibility to acquired long QT syndrome.

Accurate diagnosis of predisposition to long QT syndrome is crucial for reducing the risk of cardiac arrhythmias. In recent years, drug-induced provocative tests have proved useful to unmask some latent mutations linked to cardiac arrhythmias. In this study we expanded this concept by developing a prototype for a computational provocative screening test to reveal genetic predisposition to acquired long-QT syndrome (aLQTS). We developed a computational approach to reveal the pharmacological properties of IKr blocking drugs that are most likely to cause aLQTS in the setting of subtle alterations in IKr channel gating that would be expected to result from benign genetic variants. We used the model to predict the most potentially lethal combinations of kinetic anomalies and drug properties. In doing so, we also implicitly predicted ideal inverse therapeutic properties of K channel openers that would be expected to remedy a specific defect. We systematically performed "in silico mutagenesis" by altering discrete kinetic transition rates of the Fink et al. Markov model of human IKr channels, corresponding to activation, inactivation, deactivation and recovery from inactivation of IKr channels. We then screened and identified the properties of IKr blockers that caused acquired long QT and therefore unmasked mutant phenotypes for mild, moderate and severe variants. Mutant IKr channels were incorporated into the O'Hara et al. human ventricular action potential (AP) model and subjected to simulated application of a wide variety of IKr-drug interactions in order to identify the characteristics that selectively exacerbate the AP duration (APD) differences between wild-type and IKr mutated cells. Our results show that drugs with disparate affinities to conformation states of the IKr channel are key to amplify variants underlying susceptibility to acquired long QT syndrome, an effect that is especially pronounced at slow frequencies. Finally, we developed a mathematical formulation of the M54T MiRP1 latent mutation and simulated a provocative test. In this setting, application of dofetilide dramatically amplified the predicted QT interval duration in the M54T hMiRP1 mutation compared to wild-type.

Toward Digital Twin Technology for Precision Pharmacology.

The authors demonstrate the feasibility of technological innovation for personalized medicine in the context of drug-induced arrhythmia. The authors use atomistic-scale structural models to predict rates of drug interaction with ion channels and make predictions of their effects in digital twins of induced pluripotent stem cell-derived cardiac myocytes. The authors construct a simplified multilayer, 1-dimensional ring model with sufficient path length to enable the prediction of arrhythmogenic dispersion of repolarization. Finally, the authors validate the computational pipeline prediction of drug effects with data and quantify drug-induced propensity to repolarization abnormalities in cardiac tissue. The technology is high throughput, computationally efficient, and low cost toward personalized pharmacologic prediction.

A computational model predicts sex-specific responses to calcium channel blockers in mammalian mesenteric vascular smooth muscle.

The function of the smooth muscle cells lining the walls of mammalian systemic arteries and arterioles is to regulate the diameter of the vessels to control blood flow and blood pressure. Here, we describe an in-silico model, which we call the "Hernandez-Hernandez model", of electrical and Ca2+ signaling in arterial myocytes based on new experimental data indicating sex-specific differences in male and female arterial myocytes from murine resistance arteries. The model suggests the fundamental ionic mechanisms underlying membrane potential and intracellular Ca2+ signaling during the development of myogenic tone in arterial blood vessels. Although experimental data suggest that KV1.5 channel currents have similar amplitudes, kinetics, and voltage dependencies in male and female myocytes, simulations suggest that the KV1.5 current is the dominant current regulating membrane potential in male myocytes. In female cells, which have larger KV2.1 channel expression and longer time constants for activation than male myocytes, predictions from simulated female myocytes suggest that KV2.1 plays a primary role in the control of membrane potential. Over the physiological range of membrane potentials, the gating of a small number of voltage-gated K+ channels and L-type Ca2+ channels are predicted to drive sex-specific differences in intracellular Ca2+ and excitability. We also show that in an idealized computational model of a vessel, female arterial smooth muscle exhibits heightened sensitivity to commonly used Ca2+ channel blockers compared to male. In summary, we present a new model framework to investigate the potential sex-specific impact of anti-hypertensive drugs.