Future advances of artificial biosensor technology in biomedical applications

Recent advancements in synthetic biology have facilitated the concept of a cell-based and cell-free biosensing platform, which enables the identification of molecular signals encompassing metal/chemical to disease biomarkers. The artificial sensing incorporates the concept of both whole-cell and cell-free biosensing strategies, which include highly regulated natural and synthetic components to exhibit genetically encoded molecular sensing properties. These sensors utilize protein expression to release signalling molecules as the result of received input to facilitate the detection of analytes. Intending to use modified living cells or artificial cells in biosensing, the proposed study highlights the importance of cell-based and cell-free sensors in biomedical and diagnostics. The article's first section will explain the biosensing types including cell-free, cell-based, vesicle-based, and paper-based sensing where sensing relies on cell, cellular components, and cell-free systems which mostly involve transcriptional or translational machinery. It highlights the advantages, disadvantages, and challenges of advancing approaches. The second section of the article elaborates on the principle of sensing and the strategies involved. Though very few studies have been reported on this topic, therefore, the current article focuses on the artificial sensors that have been designed for medical and diagnostic purposes. The review also marks the current and future advancements in the field including artificial intelligence, nanotechnology, stem cells, and omics. Sensing recently has a big impact on disease diagnosis as well as drug development and targeted therapies. While newly developed biology-based diagnostics technologies still have high costs, require highly trained personnel, suffer stability issues and reduce sensor performance. Therefore, this review brings readers' attention to advances and challenges in the following field and promotes the resolution of medical and diagnostics issues in the future.