Advancing an inexpensive, wearable prefrontal cortex fNIRS device and integrated software for assessment of cerebral biomarkers of intoxication in real world settings - Ecological momentary assessment (EMA), the collection of real time repeated sampling of people’s behaviors and experiences in real world settings, has transformed the study of drug use behaviors, enabling detailed predictors of everyday use of drugs to be better understood, allowing study of polysubstance and dispensary cannabis use, and spurring design of just in time interventions. A tool enabling detection and evaluation of brain states associated with drug intoxication in real-world settings could complement and extend self-report EMA work. We recently demonstrated functional near infrared spectroscopy (fNIRS) of the prefrontal cortex (PFC) accurately classifies individuals with impairment due to THC intoxication, differentiating from those who ingested THC with less intoxication and from placebo. While most fNIRS devices are expensive, delicate, and require trained operators, a fNIRS device more like a Fitbit, now widely used in clinical research, that could be worn in participants’ natural environments, including during drug use, could revolutionize the science of cannabis and other drug use and impairment. We are fortunate to have the opportunity to partner with the creator of the FlexNIRS device to build a robust, accurate, wireless cortical fNIRS device designed to assess and monitor neural physiology underlying drug intoxication in real world settings by non-expert users. We propose here to retain the core FlexNIRS attributes of affordability, simplicity, and high signal-to-noise ratio (SNR), and expand its capabilities into an imaging system, featuring a configuration of 8 bicolor sources and 8 detectors to provide 20 source-detector channels covering the PFC. The intended use of this novel iFlexNIRS device is as a personal wearable device tailored for repeated use in real-world settings. Mass produced, the iFlexNIRS will cost less than $100, allowing for broad uptake as a specialized tool to advance the science of intoxication biomarkers to compliment behavioral study of cannabis use and polysubstance use. In Phase 1 we will build the device and accompanying handheld tablet to good manufacturing practice requirements, iterating to meet performance, comfort, and usability metrics. In Phase2, we will demonstrate iFlexNIRS identifies THC intoxication in human subjects and pilot its use in real world settings with dispensary cannabis and polysubstance use, use these data to improve our existing machine learning classifier of impairment derived from prior datasets that we will build into a real-time software platform for real-time data visualization and impairment classification. .
