Artificial Intelligence in Life Sciences - The Next Frontier, Decoding the Secrets of Life

The scientific landscape is being reshaped by emerging technologies and their cutting-edge applications superseded by the State-of-the-art techniques. One such technology revolutionizing the world is Artificial Intelligence (AI). It is a field that encompasses a wide array of computational approaches and algorithms capable of mimicking complex cognitive skills and functions of human. AI encompasses Machine Learning (ML), and ML encompasses Deep Learning (DL), whereas Next Generation Sequencing (NGS) gets benefitted from AI/ML/DL for data analysis. Machine learning has applications in both personalized medicine and gene editing. It can predict patient-specific treatment responses based on genomic data. Moreover, they are instrumental in optimizing gene editing technologies such as CRISPR-Cas9 by predicting on- and off-target effects in test datasets, thereby facilitating the design of guide RNAs (gRNAs) that minimize off-target activity. ML can also be applied to organoid technology. Organoids are three-dimensional structures, cultivated from stem cells, that aim to recreate the intricate cellular arrangements and 3D architectures characteristic of natural organs, there by simplifying the study of organ complexity. Next-generation sequencing (NGS), facilitates the simultaneous sequencing of millions of DNA fragments, as it plays a crucial role in deciphering the genetic heterogeneity of diseases. DL leverages AI to analyse healthcare data and drive improvements in patient care. By leveraging realworld data (RWD), AI can also streamline clinical research and bridge the gap between research and real-world practice. Deep learning models learn from real-world data, enabling them to recognize patterns and predict outcomes in similar real-world situations. AI, encompassing machine learning and deep learning, is transforming various fields, including healthcare, where it complements powerful tools like next-generation sequencing (NGS) to advance disease understanding, personalized medicine, and drug discovery, improving early detection and streamlining clinical research with real-world data.