title: Dose-dependent model of caffeine effects on human vigilance during total sleep deprivation.
abstract: Caffeine is the most widely consumed stimulant to counter sleep-loss effects. While the pharmacokinetics of caffeine in the body is well-understood, its alertness-restoring effects are still not well characterized. In fact, mathematical models capable of predicting the effects of varying doses of caffeine on objective measures of vigilance are not available. In this paper, we describe a phenomenological model of the dose-dependent effects of caffeine on psychomotor vigilance task (PVT) performance of sleep-deprived subjects. We used the two-process model of sleep regulation to quantify performance during sleep loss in the absence of caffeine and a dose-dependent multiplier factor derived from the Hill equation to model the effects of single and repeated caffeine doses. We developed and validated the model fits and predictions on PVT lapse (number of reaction times exceeding 500 ms) data from two separate laboratory studies. At the population-average level, the model captured the effects of a range of caffeine doses (50-300 mg), yielding up to a 90% improvement over the two-process model. Individual-specific caffeine models, on average, predicted the effects up to 23% better than population-average caffeine models. The proposed model serves as a useful tool for predicting the dose-dependent effects of caffeine on the PVT performance of sleep-deprived subjects and, therefore, can be used for determining caffeine doses that optimize the timing and duration of peak performance.
authors.affiliation: DoD Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, 504 Scott Street, Fort Detrick, MD 21702, USA.
authors.forename: Sridhar
authors.initials: S
authors.lastname: Ramakrishnan
authors.affiliation: DoD Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, 504 Scott Street, Fort Detrick, MD 21702, USA.
authors.forename: Srinivas
authors.initials: S
authors.lastname: Laxminarayan
authors.affiliation: Department of Behavioral Biology, Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD 20910, USA.
authors.forename: Nancy J
authors.initials: NJ
authors.lastname: Wesensten
authors.affiliation: Department of Behavioral Biology, Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD 20910, USA.
authors.forename: Gary H
authors.initials: GH
authors.lastname: Kamimori
authors.affiliation: Department of Behavioral Biology, Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD 20910, USA.
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Balkin
authors.affiliation: DoD Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, 504 Scott Street, Fort Detrick, MD 21702, USA. Electronic address: jaques.reifman.civ@mail.mil.
authors.forename: Jaques
authors.initials: J
authors.lastname: Reifman
mesh_terms: D001288:Attention / Q000187:drug effects*; D002110:Caffeine / Q000008:administration & dosage* / Q000494:pharmacology; D004305:Dose-Response Relationship, Drug; D006801:Humans; D012892:Sleep Deprivation / Q000503:physiopathology*
chemical_list: D002110:Caffeine
keywords: Caffeine model; Cross-study validation; Dose dependency; Individualized model; Pharmacokinetic-pharmacodynamic model