m+Medelevator.RU
← Поиск публикаций
Advanced drug delivery reviews · 2026

Decoding cellular dynamics and microenvironmental responses in organ-on-chip systems through real-time sensing.

СтатьяОбзорНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

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.

Gupta Pooja, Gupta Eshira, Jain Ratnesh, Dandekar Prajakta

Аннотация

Organ-on-Chip (OoC) systems hold extraordinary promise for predictive drug development and disease modeling. Yet, their translational impact is constrained by several challenges, one of which is the inability to monitor cellular microenvironments and tissue behavior in real time, without destructive sampling. In the absence of real-time sensing capabilities, OoC characterization often relies on intermittent or endpoint measurements, where inputs and endpoints are known, but transient cellular mechanisms driving biological responses remain elusive. This ambiguity limits mechanistic insights and complicates model validation essential for pre-clinical decision-making. Integrating sensing capabilities into OoCs resolves this gap by enabling continuous, non-invasive monitoring of multi-parametric cellular and microenvironmental dynamics. This review presents an overview of the current state of real-time OoC sensing, examining how electrochemical, optical, affinity-based, and mechanical sensing modalities capture real-time data related to barrier integrity, metabolic shifts, ion dynamics, biomarker secretion, and contractile force. It discusses data from representative organ systems (brain, gut, liver, kidney, etc.), commercially available platforms, and disease-modeling applications, highlighting enhanced predictive potential relative to the conventional pre-clinical models. Innovations in multi-modal sensors and AI/ML-based data analysis are advancing OoCs toward high-throughput drug safety and efficacy assessments. However, persistent challenges such as sensor miniaturization, lack of standardized calibration protocols, batch-to-batch reproducibility, signal interference in complex media, economic barriers, and lack of binding international regulatory guidelines impede scalable translation. Addressing these gaps through co-ordinated standardization, regulatory harmonization, and infrastructure development is essential to unlock OoCs as routine pre-clinical tools capable of reducing animal use, accelerating therapeutic translation, and improving patient outcomes.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты