Artificial Intelligence in Biotechnology and Pharmaceuticals: Evolution, Applications, and Regulatory Frontiers

Abstract

This review aims to examine how Artificial Intelligence (AI) is revolutionizing the biotechnology and pharmaceutical industries by transforming traditional drug development processes, enhancing precision medicine, and accelerating healthcare innovation. Specifically, it seeks to trace the historical evolution of AI in this field, evaluate its current applications across the drug development pipeline, and assess the challenges and regulatory considerations influencing its integration. Recent advances have demonstrated AI’s profound impact on drug discovery and development, enabled by deep learning, big data analytics, and natural language processing. Key milestones, such as the Human Genome Project and the emergence of AI-driven biotech startups, have catalyzed applications spanning target identification, molecular design, clinical trials optimization, and regulatory workflows. Notable applications include protein structure prediction, image-based diagnostics, real-world data analysis, gene expression modeling, and gene editing using CRISPR. Concurrently, regulatory agencies such as the FDA, EMA, and MHRA are developing guidelines to address AI’s role in healthcare, distinguishing regulated from unregulated use cases. However, challenges persist regarding data privacy, intellectual property, synthetic data validation, and workforce readiness for AI adoption. This review highlights that AI is poised to unlock transformative personalized therapies through the convergence of generative AI, multi-omics data, and genome editing technologies. While the promise of AI in healthcare is vast, realizing its potential requires robust governance frameworks, ethical standards, and interdisciplinary collaboration to ensure responsible innovation, transparency, and regulatory alignment. Addressing these considerations will be critical to accelerate AI-enabled drug development and deliver impactful, patient-centered solutions in the future.

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