Artificial Intelligence-augmented analytical method development and validation in pharmaceutical manufacturing: Current applications, regulatory landscape and future directions

The pharmaceutical, biotechnology, and medical device industries are undergoing a paradigm shift as artificial intelligence (AI) and machine learning (ML) technologies are increasingly integrated into analytical method development, validation, and lifecycle management. Traditional approaches to method development, while well-established under regulatory frameworks such as ICH Q2(R2) and the recently adopted ICH Q14, are often labor-intensive, iterative, and resource-constrained. This review examines the current landscape of AI-augmented analytical method development and validation across diverse pharmaceutical modalities, including small molecules, biologics, ophthalmic emulsions, and lipid nanoparticle-based mRNA vaccine delivery systems. The paper discusses how AI and ML tools, including deep learning, predictive analytics, and computer vision, are being applied to accelerate method optimization, enhance robustness evaluation, predict method performance, and strengthen data integrity throughout the analytical procedure lifecycle. The regulatory context is explored in depth, with particular attention to the ICH Q14 enhanced approach, the analytical target profile concept, and the role of GAMP 5 and ALCOA+ principles in ensuring that AI-driven analytical workflows remain compliant and audit-ready. Key challenges, including model interpretability, validation of AI tools themselves, regulatory acceptance, and data quality, are examined alongside emerging opportunities such as multi-omics integration, generative AI for method design, and predictive bio-cyber resilience frameworks. This review concludes with a set of recommendations for researchers, regulators, and industry practitioners seeking to harness AI for next-generation analytical method development while maintaining the scientific rigor and regulatory compliance that underpin patient safety and product quality.