Evidence map›Paper›PMID 29493299›Full record

ArticleComputer methods in biomechanics and biomedical engineering2018

Predicting the cardiac toxicity of drugs using a novel multiscale exposure-response simulator.

Francisco Sahli Costabal, Jiang Yao, Ellen Kuhl

Abstract read
In one paragraph

Article in Computer methods in biomechanics and biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. PersonalizedFrontiers in physiology · 2026
    Article
  2. Article
  3. Effects of cardiac growth on electrical dyssynchrony in the single ventricle patient.Computer methods in biomechanics and biomedical engineering · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. APL bioengineering · 2020
    Review
  9. Article
  10. Article
  11. Article
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  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Francisco Sahli Costabala Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery , Stanford University , CA , USA .
Jiang Yaob Dassault Systèmes Simulia Corporation , Johnston , RI , USA .
Ellen Kuhla Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery , Stanford University , CA , USA .

Funding

Multi-Scale Laws of Myocardial Growth and RemodelingU01HL119578 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUCCIONE, JULIUS MATTEO, KASSAB, GHASSAN S · 2014 to 2018
$3.8M
NHLBI NIH HHS U01 HL119578
6 · The paper itself

Abstract

A common but serious side effect of many drugs is torsades de pointes, a rhythm disorder that can have fatal consequences. Torsadogenic risk has traditionally been associated with blockage of a specific potassium channel and an increased recovery period in the electrocardiogram. However, the mechanisms that trigger torsades de pointes remain incompletely understood. Here we establish a computational model to explore how drug-induced effects propagate from the single channel, via the single cell, to the whole heart level. Our mechanistic exposure-response simulator translates block-concentration characteristics for arbitrary drugs into three-dimensional excitation profiles and electrocardiogram recordings to rapidly assess torsadogenic risk. For the drug of dofetilide, we show that this risk is highly dose-dependent: at a concentration of 1x, QT prolongation is 55% but the heart maintains its regular sinus rhythm; at 5.7x, QT prolongation is 102% and the heart spontaneously transitions into torsades de points; at 30x, QT prolongation is 132% and the heart adapts a quasi-depolarized state with numerous rapidly flickering local excitations. Our simulations suggest that neither potassium channel blockage nor QT interval prolongation alone trigger torsades de pointes. The underlying mechanism predicted by our model is early afterdepolarization, which translates into pronounced U waves in the electrocardiogram, a signature that is correctly predicted by our model. Beyond the risk assessment of existing drugs, our exposure-response simulator can become a powerful tool to optimize the co-administration of drugs and, ultimately, guide the design of new drugs toward reducing life threatening drug-induced rhythm disorders in the heart.

Indexed as

Computer SimulationAction PotentialsCardiotoxicityElectrocardiographyFinite Element AnalysisHeartHumansMagnetic Resonance ImagingMyocytes, CardiacPhenethylaminesPurkinje CellsSulfonamidesdofetilidePhenethylaminesSulfonamidescardiac toxicityearly afterdepolarizationsElectrophysiologyfinite element analysispharmacologytorsades de pointes

Identifiers

PMID29493299
PMCPMC6361171

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.