DOI 10.1016/j.jpba.2026.117673
Biosensing technologies for cannabinoid monitoring in pain management: Current methods, clinical needs, and translational challenges.
Аннотация
Cannabinoids such as Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) are increasingly explored for chronic and neuropathic pain management. Still, their clinical use remains limited by variable formulations, uncertain therapeutic ranges, and insufficient concentration-response evidence. Although many cannabinoid detection platforms have been reported, few reviews connect biosensor performance with the clinical requirements of pain management monitoring and therapeutic drug monitoring (TDM). This review summarizes current cannabinoid detection strategies, including conventional analytical methods (such as chromatography, mass spectrometry, and spectroscopy), as well as biosensing platforms such as electrochemical sensors, colorimetric sensors, optical and fluorescence-based platforms, immunoassays, novel material-based sensors, and receptor- or cell-based biological methods. We compare these platforms in terms of target analytes, biological matrices, analytical performance, validation status, and clinical feasibility. Current evidence suggests that portable electrochemical sensors and compact optical/immunoassay platforms are the most promising near-term candidates for point-of-care translation. However, most reported biosensors remain preliminary and require validation in authentic patient samples, comparison with reference methods, improved reproducibility and stability, and stronger links between cannabinoid concentrations, therapeutic response, and adverse effects before routine clinical TDM use.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.