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Kavita Jeerage (Fed)
Materials Research Engineer
Dr. Jeerage leads the development of reference materials and delivery systems for breath molecules that span a range of volatilities to provide device developers with tools to benchmark performance of novel breathalyzers. These efforts to build standardization infrastructure impact breathalyzers for public safety, workplace safety, law enforcement, clinical diagnosis, and, looking forward, for health monitoring at home. Dr. Jeerage obtained her B.S. in chemical engineering from the University of Minnesota and her Ph.D., also in chemical engineering, from the University of Washington. She serves on the Editorial Board of the Journal of Breath Research and is co-organizing the 2025 Workshop: Building a Path Forward for Meaningful Cannabis Breathalyzer Realization in Boulder, CO, on September 24-25, 2025.
Research Interests:
Developing measurement services for volatile molecules in breath
Reference materials to calibrate breathalyzers are rudimentary beyond a few key applications (e.g., alcohol breathalyzer, hydrogen and methane breath tests). One class of target molecules is the volatile molecules that can indicate the presence of infectious disease organisms, such as the ones responsible for tuberculosis and malaria. We are developing a breath surrogate delivery system to deliver biomarkers of these diseases in gas mixtures that match the major features of exhaled breath in terms of composition, temperature, and humidity. Volatile breath surrogates will enable benchmarking and validation of breath sampling devices and sensors in a controlled laboratory setting and, ultimately, calibration for field deployment. This work is conducted in partnership with the Gates Foundation and the NIST Chemical Sciences Division.
Developing reference materials for low volatility molecules in breath
Drugs of abuse such as tetrahydrocannabinol (THC), the psychoactive molecule found in cannabis, represent another class of target molecules. THC’s low vapor pressure indicates that it may be carried from the lungs in breath aerosols, sub-micrometer fluid particles that are formed from lung fluid by the mechanical action of breathing. While several commercial breath sampling devices have been designed to collect this aerosol phase for offline analysis, there is no standardized method to test the efficacy of such devices. We are developing an aerosol delivery system that will generate aerosol particles with a reproducible size distribution, number density, and a known concentration of drug molecule. Aerosol breath surrogates will enable benchmarking and validation of breath sampling devices and sensors in a controlled laboratory setting.
Determining best strategies for capturing THC from breath
THC is at parts per billion to parts per trillion levels in breath and must be concentrated prior to analysis. Breath THC measurements have been made with filtration devices relying on impaction or interception, and condensation devices. We are studying devices with different modes of action via computational simulations, controlled human studies (food capsule consumption), and field studies with participants who use legal market cannabis products. Three human subjects research protocols are active. This work is conducted in partnership with the National Institute of Justice, the University of Colorado Anschutz Medical, and the University of Colorado Boulder.
Designing statistical methods for interpreting THC breath data
THC is lipophilic, leading to persistence in biological matrices beyond the window of impairment, and complicating the interpretation of breath concentration data. We are mining the rich datasets generated in current studies to directly measure the replicability and uncertainty of breath THC measurements. Breath data includes samples collected after overnight abstinence and after cannabis use, including inhalation, ingestion, and other routes. This work is conducted in collaboration with the National Institute of Justice, the University of Colorado Anschutz Medical, the University of Colorado Boulder, and the NIST Statistical Engineering Division.