Evidence map›Paper›PMID 38069976›Full record

ReviewJACC. Clinical electrophysiology2024

Toward Digital Twin Technology for Precision Pharmacology.

Pei-Chi Yang, Mao-Tsuen Jeng, Vladimir Yarov-Yarovoy, L Fernando Santana, Igor Vorobyov, Colleen E Clancy

Open access · hybridAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in JACC. Clinical electrophysiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 4% of its field
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 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Precision cardiac electrophysiology: toward digital twins and beyond.Journal of precision medicine (Amsterdam, Netherlands) · 2025
    Article
  13. Review
  14. Article
  15. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Pei-Chi YangDepartment of Physiology and Membrane Biology, University of California-Davis, Davis, California, USA.
Mao-Tsuen JengDepartment of Physiology and Membrane Biology, University of California-Davis, Davis, California, USA.
Vladimir Yarov-YarovoyDepartment of Physiology and Membrane Biology, University of California-Davis, Davis, California, USA; Department of Anesthesiology and Pain Medicine, University of California-Davis, Davis, California, USA.
L Fernando SantanaDepartment of Physiology and Membrane Biology, University of California-Davis, Davis, California, USA.
Igor VorobyovDepartment of Physiology and Membrane Biology, University of California-Davis, Davis, California, USA; Department of Pharmacology, University of California-Davis, Davis, California, USA. Electronic address: ivorobyov@ucdavis.edu.
Colleen E ClancyDepartment of Physiology and Membrane Biology, University of California-Davis, Davis, California, USA; Department of Pharmacology, University of California-Davis, Davis, California, USA; Center for Precision Medicine, University of California-Davis, Davis, California, USA. Electronic address: ceclancy@ucdavis.edu.
University of California, Davis · US

Funding

Development of the Predictive NeuroCardiovascular SimulatorOT2OD026580 · OD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CLANCY, COLLEEN E, GRANDI, ELEONORA · 2018 to 2021
$5.7M
In silico Safety PharmacologyR01HL128537 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CLANCY, COLLEEN E, SANTANA, LUIS F · 2016 to 2024
$5.7M
Predictive multiscale in silico cardio-pharmacologyU01HL126273 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CLANCY, COLLEEN E · 2015 to 2019
$3.8M
A Systems Biology Approach to Study Cardiac Arrhythmias: iPS Cells and In Silico ModelingR01HL128170 · NHLBI · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO, CLANCY, COLLEEN E · 2015 to 2018
$3.0M
Multi-Scale Modeling of Vascular Signaling UnitsR01HL152681 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CLANCY, COLLEEN E, SANTANA, LUIS F · 2020 to 2023
$2.4M
NHLBI NIH HHS R01 HL128170NHLBI NIH HHS R01 HL128537NHLBI NIH HHS R01 HL152681NHLBI NIH HHS U01 HL126273NIH HHS OT2 OD026580
6 · The paper itself

Abstract

The authors demonstrate the feasibility of technological innovation for personalized medicine in the context of drug-induced arrhythmia. The authors use atomistic-scale structural models to predict rates of drug interaction with ion channels and make predictions of their effects in digital twins of induced pluripotent stem cell-derived cardiac myocytes. The authors construct a simplified multilayer, 1-dimensional ring model with sufficient path length to enable the prediction of arrhythmogenic dispersion of repolarization. Finally, the authors validate the computational pipeline prediction of drug effects with data and quantify drug-induced propensity to repolarization abnormalities in cardiac tissue. The technology is high throughput, computationally efficient, and low cost toward personalized pharmacologic prediction.

Indexed as

Arrhythmias, CardiacInduced Pluripotent Stem CellsHumansIon ChannelsMyocytes, CardiacTechnologyIon Channelsdigital twinsdofetilidehERGiPSC-CMsmoxifloxacin

Identifiers

PMID38069976
PMCPMC12049087
OpenAlexW4389399052

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.