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Pharmacokinetics-Informed Neural Network for Predicting Opioid Administration Moments with Wearable Sensors
UMass Chan Affiliations
Emergency MedicineDocument Type
Conference PaperPublication Date
2024-03-24
Metadata
Show full item recordAbstract
Long-term and high-dose prescription opioid use places individuals at risk for opioid misuse, opioid use disorder (OUD), and overdose. Existing methods for monitoring opioid use and detecting misuse rely on self-reports, which are prone to reporting bias, and toxicology testing, which may be infeasible in outpatient settings. Although wearable technologies for monitoring day-to-day health metrics have gained significant traction in recent years due to their ease of use, flexibility, and advancements in sensor technology, their application within the opioid use space remains underexplored. In the current work, we demonstrate that oral opioid administrations can be detected using physiological signals collected from a wrist sensor. More importantly, we show that models informed by opioid pharmacokinetics increase reliability in predicting the timing of opioid administrations. Forty-two individuals who were prescribed opioids as a part of their medical treatment in-hospital and after discharge were enrolled. Participants wore a wrist sensor throughout the study, while opioid administrations were tracked using electronic medical records and self-reports. We collected 1,983 hours of sensor data containing 187 opioid administrations from the inpatient setting and 927 hours of sensor data containing 40 opioid administrations from the outpatient setting. We demonstrate that a self-supervised pre-trained model, capable of learning the canonical time series of plasma concentration of the drug derived from opioid pharmacokinetics, can reliably detect opioid administration in both settings. Our work suggests the potential of pharmacokinetic-informed, data-driven models to objectively detect opioid use in daily life.Source
Gullapalli BT, Carreiro S, Chapman BP, Garland EL, Rahman T. Pharmacokinetics-Informed Neural Network for Predicting Opioid Administration Moments with Wearable Sensors. Proc AAAI Conf Artif Intell. 2024 Feb;38(21):22892-22898. doi: 10.1609/aaai.v38i21.30326. Epub 2024 Mar 24. PMID: 38646089; PMCID: PMC11027727.DOI
10.1609/aaai.v38i21.30326Permanent Link to this Item
http://hdl.handle.net/20.500.14038/53546PubMed ID
38646089ae974a485f413a2113503eed53cd6c53
10.1609/aaai.v38i21.30326