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Finsberg, H.

Publications and source records attributed to Finsberg, H..

3 recordsLinked to original sources

Drug Proarrhythmic Evaluation in a High Throughput Cardiac New Approach Methodology

Background and PurposeCardiotoxicity is a major cause for drug failure throughout the drug development process, with particular concern for action potential prolongation and arrhythmia. Hence, such liabilities are heavily considered during the early phases of drug design to pre vent dangerous compounds from progressing. New approach methodologies (NAMs) that efficiently examine this risk early in the discovery pipeline should help streamline drug development programs. We developed a cardiac NAM, a 384-well open bath platform consisting of cardiac tissue derived from human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes, enabling high-throughput drug screening while maintaining the structural and functional complexity of 3D cardiac micromuscles. MethodsWe dramatically increased throughput without compromising physiological relevance provided by the 3D micromuscle structure. Our 384-well open bath high-throughput platform allowed evaluation of multiple compounds at a time, enabling us to study the CiPA (comprehensive in vitro proarrhythmia assay) drug panel for proarrhythmia screening. We obtained phenotypic fingerprints of all 28 compounds (9 low, 11 intermediate, and 8 high arrhythmia risk; https://cipaproject.org) in dose-escalation studies around their respective clinical concentrations. The analysis was augmented with an in silico pipeline that used phenotypic biomarkers to invert data into a mathematical model of cellular currents to infer which ion channels were affected upon drug exposure, and then trained a ML model to predict channel block. Results and ConclusionsWe found accurate detection of arrhythmic potential for most of the compounds, and the in silico model inversions were consistent with published values of compound channel block. All the high risk compounds showed action potential duration (APD) prolongation coupled with either action potential abnormalities, early afterdepolarizations (EADs), or beat cessation. For the intermediate risk group, 9 out of 11 compounds caused APD prolongation alone or in combination with EADs while 2 others showed either beat cessation or beat rate change. Augmentation of APD analysis with detailed biophysical modeling and ML tools provided meaningful insight into the mechanisms involved in APD changes. Overall, our cardiac NAM allowed for fast and relevant screening for mechanistic understanding of APD prolongation and proarrhythmic activity, at massively increased throughput compared to other 3D micromuscle models. SummaryCardiotoxicity testing is critical in drug development to prevent arrhythmogenic side effects. Current stringent regulations have greatly reduced market withdrawals; however, these strict evaluations often lead to costly late-stage failures and loss of promising candidates as false positives. We developed a cardiac new approach methodology (NAM), a 384-well open bath cardiac micromuscle platform created from hiPSC-derived cardiomyocytes, enabling high-throughput drug screening while maintaining the structural and functional complexity of 3D cardiac micromuscles. Using the comprehensive in vitro proarrhythmia assay (CiPA) drug panel, we validated the system to accurately detect proarrhythmic potential. Our assay provided phenotypic fingerprints based on mechanical and electrophysiological biomarkers. Integration with computational modeling offered insights into multi-ion channel effects (MICE). Particularly, we identified sodium channel block contributions as a significant factor for poor risk prediction based on traditional parameters. The combined experimental and computational platform can enhance early drug screening, thereby reducing late-stage failures and promoting the progression of low-risk compounds with complex electrophysiological profiles.

pharmacology and toxicology↗

Statistical Atlas-Based Surrogate Model of Biventricular Wall Mechanics

Here we use a statistical atlas of end-diastolic (ED) and end-systolic (ES) biventricular shapes - previously derived from the UK Biobank imaging substudy - to generate meshes for finite element (FE) simulations of ventricular wall mechanics. The models used the Holzapfel-Ogden constitutive law for passive material properties and a time-varying elastance model of systolic tension development. Simulated ED and ES deformations were projected onto the shape atlas and the principal components were used to train a multi-layer perceptron as a surrogate model. The input layer included shape modes of the unloaded ventricular geometry, and material parameters and ventricular pressures at ED and ES. After training with 444 simulations, the surrogate model achieved a mean square error in predicted displacements of < 2 mm and volumetric overlaps with FE-predicted deformed shapes > 97%, demonstrating good fidelity to the simulated ground truth. This approach may enable accurate prediction of ventricular wall mechanics without computationally expensive finite element analysis, offering a more feasible method for rapid, subject-specific cardiac modeling.

bioengineering↗

Improved computational identification of drug response using optical measurements of human stem cell derived cardiomyocytes in microphysiological systems

Cardiomyocytes derived from human induced pluripotent stem cells hold great potential for drug screening applications. However, their usefulness is limited by the relative immaturity of cells electro-physiological properties as compared to native cardiomyocytes in the adult human heart. In this work, we extend and improve on methodology to address this limitation, building on previously introduced computational procedures which predict drug effects for mature cells based on changes in optical measurements of action potentials and Ca2+ transients made in stem cell derived cardiac microtissues. This methodology quantifies ion channel changes through the inversion of data into a mathematical model, and maps this response to a mature phenotype through the assumption of functional invariance of fundamental intracellular and membrane channels during maturation.\n\nHere we utilize an updated action potential model to represent both immature and mature cells, apply an IC50-based model of dose-dependent drug effects, and introduce a continuation-based optimization algorithm for analysis of dose escalation measurements using five drugs with known effects. The improved methodology can identify drug induced changes more efficiently, and quantitate important metrics such as IC50 in line with published values. Consequently, the updated methodology is a step towards employing computational procedures to elucidate drug effects in mature cardiomyocytes for new drugs using stem cell-derived experimental tissues.

biophysics↗