Publication Details
Abstract
The merging of genomics and Artificial Intelligence (AI) is changing the landscape of biomedical science in a big way. We are moving from traditional methods to a more data-driven approach that emphasises precision medicine and the health of our planet. Genomics serves as a detailed map of life at the molecular level. At the same time, AI, primarily through Machine Learning (ML), helps us make sense of the vast amounts of data generated by technologies such as Whole Genome Sequencing (WGS) and single-cell profiling. This powerful combination is transforming how we diagnose and treat diseases. In the realm of infectious diseases, AI enables us to quickly identify pathogens without culturing them, enabling real-time tracking of threats such as Antibiotic Resistance Genes (ARGs). This capability is crucial in the fight against Antimicrobial Resistance (AMR). When it comes to cancer, AI plays a vital role in analysing complex tumour profiles, including the newly recognised role of the microbiome in cancer, helping identify targeted therapies, unravel drug resistance, and reveal potential new treatment avenues. AI also speeds up preventive measures through techniques such as "reverse vaccinology," which can predict the best antigens for tailored, multi-epitope vaccines. Beyond individual health, this integration is vital to the One Health framework, which emphasises the connection between human health and environmental well-being. For instance, we need to address algorithmic bias caused by data representation gaps, ensure AI systems are understandable to build trust among clinicians, and prioritise robust data security.