# Computational modelling for improved translation of cardiac inotropic and lusitropic drug effects from rats to humans

## TL;DR

This study uses computer models to better translate how heart drugs work in rats to how they might work in humans.

## Contribution

A novel computational method is introduced to translate drug effects from rats to humans using cardiomyocyte models.

## Key findings

- Computer models accurately predicted human drug effects using rat data with high coefficients of determination (≥0.997).
- The method showed strong performance for both inotropic and lusitropic biomarkers across drug concentrations.
- Experimental validation with thapsigargin supported the computational predictions.

## Abstract

Telemetered rats are widely used for early drug screenings but pronounced physiological differences between rat and human hearts limit translational relevance. To address this, the study investigates the potential of computer modelling to improve the translation of inotropic and lusitropic drug effects from rats to humans, beginning at the cellular scale. To this end, computer models of rat and human left ventricular cardiomyocytes were constructed to reproduce experimental data. First, global sensitivity analyses identified distinctive differences in inotropic and lusitropic responses to the inhibition of ion channels and transporters in rats and humans. Then, the computer models were used to address the translation challenge by predicting human responses based on sarcomere length and intracellular [Ca2+] data obtained from rats. This process, referred to as computational drug effect translation, involved identifying the drug’s blocking potencies on potential targets. Focussing on the identifiable targets RyR2, SERCA2, and NCX1, evaluations on synthetic data showed high translation accuracy across all biomarkers and drug concentrations. For example, coefficients of determination were ≥ 0.997 for predicted human effects compared to ≤0.771 for rat effects for percentage sarcomere shortening, and ≥ 0.905 compared to ≤0.418 for the time from peak to 90 % relaxation. Evaluations on experimental data collected for thapsigargin largely corroborated these findings. The results demonstrate that computer modelling can improve the translation of inotropic and lusitropic drug effects from rats to humans, offering potential benefits for augmenting the current drug development pipeline.