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Antidote Application: An Educational System for Treatment of Common Toxin Overdose

Published: 20 August 2017 Publication History

Abstract

Poisonings account for almost 1% of emergency room visits each year. Time is a critical factor in dealing with a toxicologic emergency. Delay in dispensing the first antidote dose can lead to life-threatening sequelae. Current toxicological resources that support treatment decisions are broad in scope, time-consuming to read, or at times unavailable. Our review of current toxicological resources revealed a gap in their ability to provide expedient calculations and recommendations about appropriate course of treatment. To bridge the gap, we developed the Antidote Application (AA), a computational system that automatically provides patient-specific antidote treatment recommendations and individualized dose calculations. We implemented 27 algorithms that describe FDA (the US Food and Drug Administration) approved use and evidence-based practices found in primary literature for the treatment of common toxin exposure. The AA covers 29 antidotes recommended by Poison Control and toxicology experts, 19 poison classes and 31 poisons, which represent over 200 toxic entities. To the best of our knowledge, the AA is the first educational decision support system in toxicology that provides patient-specific treatment recommendations and drug dose calculations. The AA is publicly available at http://projects.met-hilab.org/antidote/.

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Cited By

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  • (2022)ToxNet: an artificial intelligence designed for decision support for toxin predictionClinical Toxicology10.1080/15563650.2022.2144345(1-8)Online publication date: 14-Nov-2022
  • (2020)An Appraisal of Antidotes’ Effectiveness: Evidence of the Use of Phyto-Antidotes and Biotechnological AdvancementsMolecules10.3390/molecules2507151625:7(1516)Online publication date: 26-Mar-2020
  • (2020)Decision Support for Intoxication Prediction Using Graph Convolutional NetworksMedical Image Computing and Computer Assisted Intervention – MICCAI 202010.1007/978-3-030-59713-9_61(633-642)Online publication date: 29-Sep-2020

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  1. Antidote Application: An Educational System for Treatment of Common Toxin Overdose

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    cover image ACM Conferences
    ACM-BCB '17: Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics
    August 2017
    800 pages
    ISBN:9781450347228
    DOI:10.1145/3107411
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 20 August 2017

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    Author Tags

    1. decision support
    2. medical informatics
    3. poison control centers
    4. toxicity
    5. toxicology

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    ACM-BCB '17 Paper Acceptance Rate 42 of 132 submissions, 32%;
    Overall Acceptance Rate 254 of 885 submissions, 29%

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    Cited By

    View all
    • (2022)ToxNet: an artificial intelligence designed for decision support for toxin predictionClinical Toxicology10.1080/15563650.2022.2144345(1-8)Online publication date: 14-Nov-2022
    • (2020)An Appraisal of Antidotes’ Effectiveness: Evidence of the Use of Phyto-Antidotes and Biotechnological AdvancementsMolecules10.3390/molecules2507151625:7(1516)Online publication date: 26-Mar-2020
    • (2020)Decision Support for Intoxication Prediction Using Graph Convolutional NetworksMedical Image Computing and Computer Assisted Intervention – MICCAI 202010.1007/978-3-030-59713-9_61(633-642)Online publication date: 29-Sep-2020

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