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Human-based modelling and simulations are becoming ubiquitous in biomedical science due to their ability to augment experimental and clinical investigations. Cardiac electrophysiology is one of the most advanced areas, with cardiac modelling and simulation being considered for virtual testing of pharmacological therapies and medical devices. Current models present inconsistencies with experimental data, which limit further progress. In this study, we present the design, development, calibration and independent validation of a human-based ventricular model (ToR-ORd) for simulations of electrophysiology and excitation-contraction coupling, from ionic to whole-organ dynamics, including the electrocardiogram. Validation based on substantial multiscale simulations supports the credibility of the ToR-ORd model under healthy and key disease conditions, as well as drug blockade. In addition, the process uncovers new theoretical insights into the biophysical properties of the L-type calcium current, which are critical for sodium and calcium dynamics. These insights enable the reformulation of L-type calcium current, as well as replacement of the hERG current model. Decades of intensive experimental and clinical research have revealed much about how the human heart works. Though incomplete, this knowledge has been used to construct computer models that represent the activity of this organ as a whole, and of its individual chambers (the atria and ventricles), tissues and cells. Such models have been used to better understand life-threatening irregular heartbeats; they are also beginning to be used to guide decisions about the treatment of patients and the development of new drugs by the pharmaceutical industry. Yet existing computer models of the electrical activity of the human heart are sometimes inconsistent with experimental data. This problem led Tomek et al. to try to create a new model that was consistent with established biophysical knowledge and experimental data for a wide range of conditions including disease and drug action. Tomek et al. designed a strategy that explicitly separated the construction and validation of a model that could recreate the electrical activity of the ventricles in a human heart. This model was able to integrate and explain a wide range of properties of both healthy and diseased hearts, including their response to different drugs. The development of the model also uncovered and resolved theoretical inconsistencies that have been present in almost all models of the heart from the last 25 years. Tomek et al. hope that their new human heart model will enable more basic, translational and clinical research into a range of heart diseases and accelerate the development of new therapies.

The 3Rs principle of replacing, reducing and refining the use of animals in science has been gaining widespread support in the international research community and appears in transnational legislation such as the European Directive 2010/63/EU, a number of national legislative frameworks like in Switzerland and the UK, and other rules and guidance in place in countries around the world. At the same time, progress in technical and biomedical research, along with the changing status of animals in many societies, challenges the view of the 3Rs principle as a sufficient and effective approach to the moral challenges set by animal use in research. Given this growing awareness of our moral responsibilities to animals, the aim of this paper is to address the question: Can the 3Rs, as a policy instrument for science and research, still guide the morally acceptable use of animals for scientific purposes, and if so, how? The fact that the increased availability of alternatives to animal models has not correlated inversely with a decrease in the number of animals used in research has led to public and political calls for more radical action. However, a focus on the simple measure of total animal numbers distracts from the need for a more nuanced understanding of how the 3Rs principle can have a genuine influence as a guiding instrument in research and testing. Hence, we focus on three core dimensions of the 3Rs in contemporary research: (1) What scientific innovations are needed to advance the goals of the 3Rs? (2) What can be done to facilitate the implementation of existing and new 3R methods? (3) Do the 3Rs still offer an adequate ethical framework given the increasing social awareness of animal needs and human moral responsibilities? By answering these questions, we will identify core perspectives in the debate over the advancement of the 3Rs.

Objectives: Improvements in human stem cell-derived cardiomyocyte (hSC-CM) technology have promoted their use for drug testing and disease investigations. Several in silico hSC-CM models have been proposed to augment interpretation of experimental findings through simulations. This work aims to assess the response of three hSC-CM in silico models (Koivumäki2018, Kernik2019, and Paci2020) to simulated drug action, and compare simulation results against in vitro data for 15 drugs. Methods: First, simulations were conducted considering 15 drugs, using a simple pore-block model and experimental data for seven ion channels. Similarities and differences were analyzed in the in silico responses of the three models to drugs, in terms of Ca 2+ transient duration (CTD 90 ) and occurrence of arrhythmic events. Then, the sensitivity of each model to different degrees of blockage of Na + (I Na ), L-type Ca 2+ (I CaL ), and rapid delayed rectifying K + (I Kr ) currents was quantified. Finally, we compared the drug-induced effects on CTD 90 against the corresponding in vitro experiments. Results: The observed CTD 90 changes were overall consistent among the in silico models, all three showing changes of smaller magnitudes compared to the ones measured in vitro . For example, sparfloxacin 10 µM induced +42% CTD 90 prolongation in vitro , and +17% (Koivumäki2018), +6% (Kernik2019), and +9% (Paci2020) in silico . Different arrhythmic events were observed following drug application, mainly for drugs affecting I Kr . Paci2020 and Kernik2019 showed only repolarization failure, while Koivumäki2018 also displayed early and delayed afterdepolarizations. The spontaneous activity was suppressed by Na + blockers and by drugs with similar effects on I CaL and I Kr in Koivumäki2018 and Paci2020, while only by strong I CaL blockers, e.g. nisoldipine, in Kernik2019. These results were confirmed by the sensitivity analysis. Conclusion: To conclude, The CTD 90 changes observed in silico are qualitatively consistent with our in vitro data, although our simulations show differences in drug responses across the hSC-CM models, which could stem from variability in the experimental data used in their construction.

Torsades de Pointes (TdP) is a type of ventricular arrhythmia which could be observed as an unwanted drug-induced cardiac side effect, and it is associated with repolarization abnormalities in single cells. The pharmacological evaluations of TdP risk in previous years mainly focused on the hERG channel due to its vital role in the repolarization of cardiomyocytes. However, only considering drug effects on hERG led to false positive predictions since the drug action on other ion channels can also have crucial regulatory effects on repolarization. To address the limitation of only evaluating hERG, the Comprehensive in Vitro Proarrhythmia Assay initiative has proposed to systematically integrate drug effects on multiple ion channels into drug trial to improve TdP risk assessment. It is not clear how many ion channels are sufficient for reliable TdP risk predictions, and whether differences in IC and Hill coefficient values from independent sources can lead to divergent prediction outcomes. The rationale of this work is to investigate the above two questions using a computationally efficient population of human ventricular cells optimized to favor repolarization abnormality. Our blinded results based on two independent data sources confirm that simulations with the optimized population of human ventricular cell models enable efficient in silico drug screening, and also provide direct observation and mechanistic analysis of repolarization abnormality. Our results show that 1) the minimum set of ion channels required for reliable TdP risk predictions are Nav1.5 (peak), Cav1.2, and hERG; 2) for drugs with multiple ion channel blockage effects, moderate IC variations combined with variable Hill coefficients can affect the accuracy of predictions.

Drug-induced changes in cardiac contractility (inotropy) can lead to cardiotoxicity, a major cause of discontinuation in drug development. Preclinical approaches to assess cardiac inotropy are imperfect, with in vitro assays limited to stem cell-derived or adult human primary cardiomyocytes. Human mechanistic in silico modelling and simulations are already successfully applied for proarrhythmia prediction, contributing to cardiac safety assessment strategies in early drug development. In this study, we investigated their ability to predict drug-induced effects on cardiac inotropy. We considered a validation set of 28 neutral/negative inotropic and 13 positive inotropic reference compounds and simulated their effects on cell contractility via ion channel inhibition and perturbation of nine biomechanical modelling parameters, respectively. For each compound, a wide range of drug concentrations was simulated in an experimentally calibrated control population of 323 human ventricular in silico cells. Simulated biomarkers indicating drug-induced inotropic effects were compared with in vitro preclinical data from the literature. Computer simulations predicted drug-induced inotropic changes observed in vitro for 25 neutral/negative inotropes and 10 positive inotropes. Predictions of negative inotropic changes were quantitatively in agreement for 86% of tested drugs. Active tension peak was identified as the biomarker with highest predictive potential. This study describes the validation and application of an in silico cardiac electromechanical model for drug safety evaluation, combining ion channel inhibition data and information on potential inotropic mechanisms to predict inotropic changes. Furthermore, a route for its integration as part of a preclinical drug safety assessment strategy is outlined.

We applied a set of in silico and in vitro assays, compliant with the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm, to assess the risk of chloroquine (CLQ) or hydroxychloroquine (OH‐CLQ)‐mediated QT prolongation and Torsades de Pointes (TdP), alone and combined with erythromycin (ERT) and azithromycin (AZI), drugs repurposed during the first wave of coronavirus disease 2019 (COVID‐19). Each drug or drug combination was tested in patch clamp assays on seven cardiac ion channels, in in silico models of human ventricular electrophysiology (Virtual Assay) using control (healthy) or high‐risk cell populations, and in human‐induced pluripotent stem cell (hiPSC)‐derived cardiomyocytes. In each assay, concentration‐response curves encompassing and exceeding therapeutic free plasma levels were generated. Both CLQ and OH‐CLQ showed blocking activity against some potassium, sodium, and calcium currents. CLQ and OH‐CLQ inhibited IKr (half‐maximal inhibitory concentration [IC50]: 1 µM and 3–7 µM, respectively) and IK1 currents (IC50: 5 and 44 µM, respectively). When combining OH‐CLQ with AZI, no synergistic effects were observed. The two macrolides had no or very weak effects on the ion currents (IC50 > 300–1000 µM). Using Virtual Assay, both antimalarials affected several TdP indicators, CLQ being more potent than OH‐CLQ. Effects were more pronounced in the high‐risk cell population. In hiPSC‐derived cardiomyocytes, all drugs showed early after‐depolarizations, except AZI. Combining CLQ or OH‐CLQ with a macrolide did not aggravate their effects. In conclusion, our integrated nonclinical CiPA dataset confirmed that, at therapeutic plasma concentrations relevant for malaria or off‐label use in COVID‐19, CLQ and OH‐CLQ use is associated with a proarrhythmia risk, which is higher in populations carrying predisposing factors but not worsened with macrolide combination.

Levetiracetam (LEV), a well‐established anti‐seizure medication (ASM), was launched before the original ICH S7B nonclinical guidance assessing QT prolongation potential and the introduction of the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm. No information was available on its effects on cardiac channels. The goal of this work was to “pressure test” the CiPA approach with LEV and check the concordance of nonclinical core and follow‐up S7B assays with clinical and post‐marketing data. The following experiments were conducted with LEV (0.25–7.5 mM): patch clamp assays on hERG (acute or trafficking effects), NaV1.5, CaV1.2, Kir2.1, KV7.1/mink, KV1.5, KV4.3, and HCN4; in silico electrophysiology modeling (Virtual Assay® software) in control, large‐variability, and high‐risk human ventricular cell populations; electrophysiology measurements in human induced pluripotent stem cell (hiPSC)‐derived cardiomyocytes and dog Purkinje fibers; ECG measurements in conscious telemetered dogs after single oral administration (150, 300, and 600 mg/kg). Except a slight inhibition (<10%) of hERG and KV7.1/mink at 7.5 mM, that is, 30‐fold the free therapeutic plasma concentration (FTPC) at 1500 mg, LEV did not affect any other cardiac channels or hERG trafficking. In both virtual and real human cardiomyocytes, and in dog Purkinje fibers, LEV induced no relevant changes in electrophysiological parameters or arrhythmia. No QTc prolongation was noted up to 2.7 mM unbound plasma levels in conscious dogs, corresponding to 10‐fold the FTPC. Nonclinical assessment integrating CiPA assays shows the absence of QT prolongation and proarrhythmic risk of LEV up to at least 10‐fold the FTPC and the good concordance with clinical and postmarketing data, although this does not exclude very rare occurrence of QT prolongation cases in patients with underlying risk factors. Levetiracetam (LEV) QT‐ogram illustrates that no biologically relevant changes (>10% or 10 ms) in QT‐related biomarkers occur up to 10‐ to 30‐fold its free therapeutic plasma concentration (FTPC) in core and follow‐up CiPA/S7B nonclinical assays, and the good concordance of this nonclinical dataset with clinical data (TQT study).

Urinalysis is routinely performed in toxicology studies, for both regulatory and non-regulatory purposes, in species such as rats, dogs, minipigs and non-human primates. Sample collection usually requires animals to be individually housed in a metabolism cage and/or catheterised, raising animal welfare considerations. It is not clear if urinalysis results are being used as part of safety evaluation and how often they play a role in decision-making, as the quality of the data can be highly variable, and there are other assessments (e.g. kidney histopathology) that may provide more detailed and better-qualified information. This article summarises presentations and case studies from a workshop co-organised by the UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) and the Association for Comparative Clinical Pathology (ACCP) in October 2023, discussing the value of urinalysis within pharmaceutical and agrochemical product development and opportunities for refinement. These include performing urinalysis on a case-by-case basis rather than in every repeat-dose toxicology study, using a single species when appropriate and minimising the duration of urine collection periods and single housing. A first step for this 3Rs opportunity would be to collect evidence on the value of urinalysis assessment in toxicology studies and its impact on decision-making, through a data-sharing project highlighting case studies where urinalysis could have been avoided without changing the study outcome.

With many advancements in in silico biology in recent years, the paramount challenge is to translate the accumulated knowledge into exciting industry partnerships and clinical applications. Achieving models that characterize the link of molecular interactions to the activity and structure of a whole organ are termed multiscale biophysics. Historically, the pharmaceutical industry has worked well with in silico models by leveraging their prediction capabilities for drug testing. However, the needed higher fidelity and higher resolution of models for efficient prediction of pharmacological phenomenon dictates that in silico approaches must account for the verifiable multiscale biophysical phenomena, as a spatial and temporal dimension variation for different processes and models. The collection of different multiscale models for different tissues and organs can compose digital twin solutions towards becoming a service for researchers, clinicians, and drug developers. Our paper has two main goals: 1) To clarify to what extent detailed single- and multiscale modeling has been accomplished thus far, we provide a review on this topic focusing on the biophysics of epithelial, cardiac, and brain tissues; 2) To discuss the present and future role of multiscale biophysics in in silico pharmacology as a digital twin solution by defining a roadmap from simple biophysical models to powerful prediction tools. Digital twins have the potential to pave the way for extensive clinical and pharmaceutical usage of multiscale models and our paper shows the basic fundamentals and opportunities towards their accurate development enabling the quantum leaps of future precise and personalized medical software.

High-throughput in vitro drug assays have been impacted by recent advances in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs) technology and by contact-free all-optical systems simultaneously measuring action potential (AP) and Ca2+ transient (CaTr). Parallel computational advances have shown that in silico models can predict drug effects with high accuracy. In this work, we combine these in vitro and in silico technologies and demonstrate the utility of high-throughput experimental data to refine in silico hiPS-CM populations, and to predict and explain drug action mechanisms. Optically-obtained hiPS-CM AP and CaTr were used from spontaneous activity and under pacing in control and drug conditions at multiple doses. An updated version of the Paci2018 model was developed to refine the description of hiPS-CM spontaneous electrical activity; a population of in silico hiPS-CMs was constructed and calibrated using the optically-recorded AP and CaTr. We tested five drugs (astemizole, dofetilide, ibutilide, bepridil and diltiazem), and compared simulations against in vitro optical recordings. Our simulations showed that physiologically-accurate population of models can be obtained by integrating AP and CaTr control records. Thus constructed population of models predicted correctly the drug effects and occurrence of adverse episodes, even though the population was optimized only based on control data and in vitro drug testing data were not deployed during its calibration. Furthermore, the in silico investigation yielded mechanistic insights, e.g. through simulations, bepridil's more pro-arrhythmic action in adult cardiomyocytes compared to hiPS-CMs could be traced to the different expression of ion currents in the two. Therefore, our work: i) supports the utility of all-optical electrophysiology in providing high-content data to refine experimentally-calibrated populations of in silico hiPS-CMs, ii) offers insights into certain limitations when translating results obtained in hiPS-CMs to humans and iii) shows the strength of combining high-throughput in vitro and population in silico approaches.