The integration of Generative Artificial Intelligence (AI) into biochemistry and clinical chemistry has revolutionized biomedical research, diagnostics, drug discovery, and personalized medicine. This paper explores the transformative role of generative AI in protein structure prediction, clinical diagnostics, laboratory automation, drug design, and synthetic biology. By analyzing current advancements, challenges, and future prospects, this study highlights how AI accelerates scientific breakthroughs and improves clinical outcomes. Despite its potential, challenges such as data privacy, model interpretability, and regulatory compliance remain critical barriers to widespread adoption. This paper underscores the need for ethical and transparent AI integration to fully realize its benefits in biochemical sciences and healthcare.
Keywords: Generative AI, Biochemistry, Clinical chemistry, Drug discovery, Protein structure prediction, Diagnostics, Personalized medicine, Laboratory automation
