"This book, AI and ML in Biotechnology: Revolutionizing Genomics & Drug Discovery, Aims to provide a comprehensive overview of how artificial intelligence and machine learning are transforming these crucial areas of biotechnology. It explores the cutting-edge techniques, tools, and methodologies that are enabling researchers to tackle some of the most pressing challenges in biology and medicine today. From AI-driven genome sequencing to ML-enhanced drug discovery pipelines, this book delves into the technical, practical, and ethical dimensions of these transformative technologies. Our ability to understand, analyse, and modify biological systems is being revolutionised by the merging of biotechnology with Artificial Intelligence (AI) and Machine Learning (ML). Particularly, genomics and drug discovery have benefited greatly from AI and ML, which have eliminated the need for labour-intensive, expensive, and time-consuming traditional methods of analysis that were formerly predominant in these domains. Advances in computing power, big data analytics, and algorithmic advances have opened up new possibilities in various fields, allowing for discoveries that weren't possible before. Turn of the millennium saw the first sequencing of the human genome, an undertaking that required more than a decade and billions of dollars. In just a few of hours, AI-powered technologies can sequence and analyse genomic data, illuminating intricate biological networks and the underlying genetic causes of diseases. By discovering disease-associated genetic variants, forecasting how patients will react to therapies, and even altering genes using tools like CRISPR, AI and ML algorithms are paving the way for precision medicine in genomics. These developments have great potential for revolutionising molecular disease diagnosis, treatment, and prevention. Similarly, artificial intelligence (AI) and machine learning (ML) are transforming the drug discovery process, which was formerly characterised by high prices, long timelines, and uncertain outcomes. Researchers can find potential treatments more quickly and with higher accuracy with the help of machine learning algorithms that can optimise drug candidates, anticipate molecular interactions, and mimic biological processes. This has sped up the process of finding new medications for complicated diseases including cancer, neurological disorders, and uncommon hereditary diseases, and it has also caused a paradigm shift in pharmaceutical research. This book is a great resource for students, researchers, and professionals in the domains of biotechnology, bioinformatics, pharmaceuticals, and computational biology because each chapter provides both basic information and more advanced ideas. To demonstrate the significant influence of AI and ML on genomics and medication discovery, we have integrated real-life case studies, current research results, and practical applications. The merging of artificial intelligence and machine learning could provide answers to some of humanity's most pressing health problems just as a new age in biotechnology is about to dawn. The future holds a lot of potential, but we must also thoroughly examine the social, regulatory, and ethical consequences of emerging technologies. We wish this book well in its mission to illuminate the present state of affairs and to encourage creative problem-solving and ethical progress on this promising new frontier. We are delighted to share this knowledge with you and hope that it sparks further exploration and discovery in the transformative world of AI, ML, and biotechnology. "