TY - GEN
T1 - Antidote application
T2 - 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2017
AU - Long, Jon B.
AU - Chitkushev, Lou
AU - Zhang, Yingyuan
AU - Zhang, Guanglan
AU - Brusic, Vladimir
N1 - Publisher Copyright:
© 2017 Copyright is held by the owner/author(s).
PY - 2017/8/20
Y1 - 2017/8/20
N2 - 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.methilab.org/antidote/.
AB - 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.methilab.org/antidote/.
KW - Decision support
KW - Medical informatics
KW - Poison control centers
KW - Toxicity
KW - Toxicology
UR - http://www.scopus.com/inward/record.url?scp=85031321624&partnerID=8YFLogxK
U2 - 10.1145/3107411.3107415
DO - 10.1145/3107411.3107415
M3 - Conference contribution
AN - SCOPUS:85031321624
T3 - ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
SP - 442
EP - 448
BT - ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
PB - Association for Computing Machinery, Inc
Y2 - 20 August 2017 through 23 August 2017
ER -