DeepScreen: An Accurate, Rapid, and Anti-Interference Screening Approach for Nanoformulated Medication by Deep Learning

Adv. Sci., 2018 · DOI: 10.1002/advs.201800909 · Published: July 23, 2018

Simple Explanation

This paper introduces DeepScreen, a novel drug screening system based on a convolutional neural network (CNN) that analyzes single-cell images from flow cytometry. DeepScreen offers improved precision, speed, and resistance to interference compared to traditional experimental methods, while also reducing costs and maintaining high accuracy. The system can identify subtle changes in cell apoptosis and cellular period caused by drug action at very early stages.

Study Duration

2 and 6 hours

Participants

A549 and HEpG2 cells

Evidence Level

Not specified

Key Findings

1
DeepScreen demonstrates high accuracy in assessing the efficacy of drugs and nanoformulated drug systems, achieving accuracies of 0.851, 0.864, and 0.908 in testing mixed cells, HEpG2, and A549 cells, respectively.
2
The system significantly reduces the drug screening time from days to hours, providing a more rapid approach for assessing treatment efficacy.
3
DeepScreen exhibits anti-interference capabilities, maintaining stable accuracy even when testing fluorescent drugs and nanocarrier drug delivery systems, which typically pose challenges for conventional methods.

Research Summary

The study introduces DeepScreen, a deep learning-based drug screening system utilizing convolutional neural networks and flow cytometry single-cell images, to address the limitations of traditional methods in evaluating nanoformulated drugs. The DeepScreen system demonstrates superior precision, rapidity, anti-interference, and cost-effectiveness compared to existing experimental approaches, making it a promising tool for drug detection. Class activation maps generated from DeepScreen indicate its ability to identify and locate tiny variations from cell apoptosis and slight changes of cellular period caused by drug or nanoformulated drug action at very early stages.

Practical Implications

Accelerated Drug Discovery

DeepScreen's rapid screening capabilities can significantly reduce the time required to evaluate drug efficacy, accelerating the drug discovery process.

Improved Accuracy and Reliability

The system's high precision and anti-interference properties lead to more reliable results, particularly for nanoformulated drugs that often present challenges for traditional methods.

Cost Reduction

By automating the evaluation process and reducing the need for manual analysis, DeepScreen offers a cost-effective alternative to conventional drug screening techniques.

Study Limitations

1
The model's focus on cell membrane and nuclei staining may overlook drug actions on other cellular components.
2
The system's reliance on labeled images requires careful selection and preparation of markers and staining methods.
3
The study primarily focuses on in vitro models; further research is needed to validate DeepScreen's applicability to in vivo and clinical settings.

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