Studying the effects of drugs, pollutants, and microplastics on human cells plays a key role in many current applications (Huang et al., 2019). However, in vitro assays often produce inconsistent results, and the toxicity observed in cells may not accurately reflect the synergistic effects found in vivo (Adams et al., 2016). Thus, there is a need for devices that can grow different cell types under optimal conditions in order to obtain relevant physiological information during screening (Choi et al., 2013).
The Challenge
To address the limitations of current screening methods, we propose the development of an automated system that performs sensitivity testing on isolated cells exposed to different chemicals. The goal is to elucidate the mechanisms of interaction and evaluate the consequences on cell viability (Chen et al., 2019). By enabling simultaneous screening of multiple chemicals under microfluidic conditions, we aim to optimize the time to obtain results and improve the efficiency of the screening process (Tan et al., 2010). In addition, the integration of artificial intelligence-based algorithms into image analysis software will provide automated and accurate classification of cellular responses (Lopes et al., 2021).
The Solution: An Innovative Microfluidic Platform
Our proposed microfluidic platform offers several key features to enhance high-capacity screening of cells:
Real-time imaging: An integrated live cell imaging system allows continuous monitoring of cellular responses without the need for frequent imaging. This real-time observation significantly reduces processing time.
Multiwell chip design: The microfluidic chip incorporates a multiwell design, allowing simultaneous testing of different cell types. Each well serves as an independent microfluidic assay, facilitating parallel screening of multiple samples.
Fluorescence analysis: The platform includes the capability for fluorescent cell marking and analysis, enabling the measurement of quantitative parameters such as metabolic activity, apoptosis and gene expression. This provides important information on cellular responses to different chemicals.
AI-based image analysis: Leveraging artificial intelligence-based image analysis software, the platform automates the accurate classification of cellular responses from real-time imaging data. This enables rapid and objective assessment