Health

Low cost and ease of manufacture enable a wide range of applications in developing countries-ScienceDaily

Electricians, computer scientists, and biomedical engineers at the University of California, Irvine have created a new lab-on-chip that helps study tumor heterogeneity and reduce resistance to cancer treatment.

In the paper published today Advanced biosystemResearchers describe how artificial intelligence, microfluidics, and nanoparticle inkjet printing have been combined with devices that enable the examination and identification of cancer and healthy tissue at the single-cell level. ..

“Cancer cell and tumor heterogeneity can lead to increased treatment resistance and inconsistent results in different patients,” said Kushal Joshi, a former UCI graduate student in biomedical engineering. I am. The team’s new biochip addresses this issue by allowing accurate characterization of various cancer cells from samples.

“Single-cell analysis is essential for identifying and classifying cancer types and studying cell heterogeneity. To design better cancer treatments, tumor initiation, progression, and metastasis “We need to understand,” said Rahim Esfandyarpour, an electrical assistant professor at UCI. Engineering and computer science, and biomedical engineering. “Most of the techniques and techniques traditionally used to study cancer are sophisticated, bulky, expensive, and require highly trained operators and long preparation times.”

His group tackles these challenges by combining machine learning technology with accessible inkjet printing and microfluidics technology to develop low-cost, compact biochips that are easy to prototype and can classify different cell types. He said he had overcome it.

In the device, the sample travels through a microfluidic channel with carefully placed electrodes and monitors the difference in electrical properties between affected and healthy cells in a single pass. UCI researchers’ innovation was to use an inkjet printer to devise a way to prototype key biochip components in about 20 minutes, making them easy to manufacture in a variety of settings. Most of the relevant materials are reusable or cheaper if disposable.

Another aspect of the invention is the incorporation of machine learning for managing large amounts of data generated by small systems. This branch of AI accelerates the processing and analysis of large datasets, finds patterns and associations, predicts accurate results, and helps you make quick and efficient decisions.

By including machine learning in the biochip workflow, the team improved the accuracy of the analysis and reduced reliance on skilled analysts. This could be an attractive technology for healthcare professionals in developing countries as well.

“Nearly 60% of breast cancer deaths are due to lack of early detection programs in resource-poor countries, according to the World Health Organization,” he said. “Our research is of paramount importance in single-cell studies, tumor heterogeneity studies, and perhaps point-of-care cancer diagnosis, especially in cost, constrained infrastructure, and limited access to medical technology. Has potential applications in developing countries. “

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