Development of a Virtual Human Heart to Predict the Pharmacology of Novel Drugs

Sergio Wong (15-SI-002)

Abstract

The threat of a biological attack necessitates continued research into medical countermeasures. However, development of novel drug therapies is often hampered with costly failures in clinical trials because of a persistent inability to predict the effective or harmful effects of drugs. The heart is one major organ in which drug toxicity is particularly problematic and is difficult to predict reliably. We aim to create and utilize a multiscale, human heart model using high-performance computing to predict the toxicity of drugs based on systems pharmacology. Our three-dimensional whole-heart model focuses on the prediction of drugs that are known to cause a prolongation in the heart beat, as well as on drugs that are known to be toxic for the heart in the form of clinically relevant, drug-induced perturbations to an electrocardiogram. We anticipate creating computational models for simulations at the cell, tissue, and organ scale.

We plan to develop a three-dimensional human heart model to demonstrate the usefulness of predicting drug effects on cardiac dynamics for drug design, preclinical screening, and predicting new therapeutics for specific arrhythmia syndromes. Our ultimate goal is to help shorten drug development and mitigate failures in expensive clinical trials. By integrating more complex cellular mechanisms into Livermore's existing whole-heart model, including biological processes other than ion channel currents (the foundation of current cell-level models), as well as features of diseased hearts relevant to idiosyncratic toxicity, our computer model will accurately predict drug-induced cardiac toxicity (see figure) and reveal biochemical mechanisms of toxicity that are manifested in electrophysiological abnormalities. Accurately predicting the pharmacokinetics of a drug candidate will dramatically reduce the time for the U.S. Food and Drug Administration approval of a new drug. This capability can be applied to all fields of pharmacology and toxicology.

Mission Relevance

Our model to predict toxicity of new drug candidates in healthy and diseased hearts is relevant to the Laboratory's core competency in bioscience and bioengineering. The development of platforms and tools to reduce the time required to develop medical countermeasures for new pathogens by addressing key scientific barriers in the drug discovery and development process also supports the strategic focus area in chemical and biological security.

Simulation of cardiac, drug-induced toxicity to accelerate the development of medical countermeasures against biological threats.
Simulation of cardiac, drug-induced toxicity to accelerate the development of medical countermeasures against biological threats.

FY15 Accomplishments and Results

In FY15 we (1) incorporated the O'Hara––Rudy cellular model for cardiac muscle cells into the whole-organ heart model; (2) incorporated the Clancy––Markov model into the cellular mode that captures hERG channel-blocking effects (hERG is an ion channel essential for the cardiac cycle); (3) computed molecular binding kinetics of one enantiomer of the anti-arrhythmia drug ranolazine to the hERG channel (an enantiomer is one of a pair of molecules that are mirror images of each other); (4) established a collaboration between LLNL, Harvard University, and the University of California, Davis; and (5) began measuring the dose response effect of tyrosine kinase inhibitors on cardiac muscle (tyrosine kinases are enzymes responsible for the activation of proteins, and the inhibitors are used in targeted therapies for cancer).