Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop

Abstract

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting.

Keywords: Arrhythmias; Biomarkers; Computational approaches; Computer modelling and simulations; Human electrophysiology; Human-based methods; Stem-cell-derived cardiomyocytes.

Figure 1

Sources of experimental data integrated in computational models of human cardiac electrophysiology, and applications in physiology. Ionic current models are constructed mostly based on voltage/patch clamp data from ex vivo and in vitro preparations. The integration of ionic current models in single cell models, accounting for variability in protein expression and disease remodelling, allows for the simulation of the action potential and electrolyte concentrations in healthy and disease. Additionally, cardiac simulations at the whole organ and body levels require the construction of image-based anatomical models. When coupled to mathematical descriptions of electrical excitation through cardiac tissue, they allow for the high-resolution investigation of arrhythmia mechanisms based on clinical electrophysiology studies, as for the interpretation and identification of arrhythmic-risk biomarkers at the surface potential level. Transmural visualization of ventricular myofibre orientation, adapted from reference with permission. ECG/whole body simulation, adapted from reference with permission.

Figure 2

Computer simulation of the human heart electrophysiology from ion channel to body surface potentials and the electrocardiogram. Simulations are conducted using human biophysically detailed models considering heterogeneity in specific ionic properties (left, colour scale correspond to the maximum conductance of the slow component of the delayed rectifying current) to determine their effect on the spatiotemporal evolution of electrical potentials across the whole torso (middle, extracellular potentials throughout the torso) and on the ECG (right, main leads displayed).

Figure 3

Simulation of the human ventricular action potential and the underlying ionic currents. From top to bottom, time course of the action potential, sodium current (I_Na), L-type calcium current, the rapid and slow component of the delayed rectifying current (I_Kr, I_Ks) and the inward rectifying current (I_K1), the transient outward current (I_to) and the sodium potassium pump (I_NaK) and the sodium calcium exchanger (I_NaCa).

Figure 4

Stem-cell-derived cardiomyocytes have variable phenotypes: current methods of stem cell differentiation produce mixed populations at two distinct levels—gene expression, and post-transcription. This is demonstrated for sarcomeric morphology here, with the panel on the left showing two cells in the field of view positive for the z-disc marker alpha-actinin (white), and the thin filament protein troponin I (magenta). However, further heterogeneity exists even within the cell populations expressing both markers, as only some cells demonstrate ordered sarcomeric units with clear cell polarity (panel on the right). Methods to eliminate (or compensate for) this will be needed to enable small differences between samples to be identified above the noise of the difference within the sample. Scale bar 10 µm. The human ES line OXF2 was grown to confluency on Matrigel and differentiated as described in reference . Cells were dissociated by incubation with trypsin/EDTA (0.05%, Lifetech) for 15 min at room temperature prior to seeding onto 0.1% gelatin coated glass coverslips. Ten days after seeding, cells were fixed in 4% PFA (10 min, room temperature), permeabilized (0.1% Triton X-100 in Tris-buffered saline), and blocked with 2% BSA plus 0.001% sodium azide in TBS-T (1 h RT) and incubated with Primary antibodies (mouse monoclonal anti alpha-actinin, (sigma), and rabbit polyclonal anti-troponin T, prior to washing and incubation with Fab fragment anti-mouse 488, and anti-rabbit 568 (molecular probes). Images were acquired on an upright Leica SP5 confocal with a 63× lens.

Figure 5

Population of human ventricular action potential models calibrated using in vivo electrogram recordings. Each simulated action potential in the population is generated using the O'Hara–Rudy model with ionic conductances sampled in a wide range of possible values. Calibration is then conducted using the in vivo electrograms by selecting the models that yield action potentials with properties such as action potential duration consistent with the electrograms (red traces, accepted models), and rejecting those that are outside range. In this figure, the action potential for the original O’Hara–Rudy model is shown in black.