Trends in Aptasensing and the Enhancement of Diagnostic Efficiency and Accuracy

Abstract

The field of healthcare diagnostics is navigating complex challenges driven by evolving patient demographics and the rapid advancement of new technologies worldwide. In response to these challenges, these biosensors offer distinctive advantages over traditional diagnostic methods, such as cost-effectiveness, enhanced specificity, and adaptability, making their integration with point-of-care (POC) platforms more feasible. In recent years, aptasensors have significantly evolved in diagnostic capabilities through the integration of emerging technologies such as microfluidics, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) systems, wearable devices, and machine learning (ML), driving progress in precision medicine and global healthcare solutions. Moreover, these advancements not only improve diagnostic accuracy but also hold the potential to revolutionize early detection, reduce healthcare costs, and improve patient outcomes, especially in resource-limited settings. This Account examines key advancements, focusing on how scientific breakthroughs, including artificial intelligence (AI), have improved sensitivity and precision. Additionally, the integration of aptasensors with these technologies has enabled real-time monitoring and data analysis, fostering advances in personalized healthcare. Furthermore, the potential commercialization of aptasensor technologies could increase their availability in clinical settings and support their use as widespread solutions for global health challenges. Hence, this review discusses technological improvements, practical uses, and prospects while also focusing on the challenges surrounding standardization, clinical validation, and interdisciplinary collaboration for widespread application. Finally, ongoing efforts to address these challenges are key to ensure that aptasensors can be effectively implemented in diverse healthcare systems.