AI-Driven Personalization in Digital Marketing: Algorithmic Approaches and Applications in the Life Sciences Industry

This paper examines how artificial intelligence (AI) is transforming digital marketing in the life sciences industry, where strict regulations and sensitive data present unique challenges. By combining perspectives from business management, industrial microbiology, and AI, the work explores how advanced personalization strategies—powered by algorithms such as collaborative filtering, reinforcement learning, and neural networks—can deliver more targeted, effective, and compliant marketing campaigns. The study discusses practical applications in pharmaceuticals, biotechnology, and food technology, supported by case-based insights. It also highlights how compliance with frameworks like HIPAA and GDPR can shift from being a constraint to a competitive advantage when applied strategically. Beyond the technical aspects, the paper emphasizes the importance of continuous data integration, ethical responsibility, and innovation in AI deployment. The findings suggest that early adopters of AI-driven personalization in life sciences are positioned to enhance engagement, build trust, and achieve sustainable business growth while improving outcomes for both healthcare professionals and patients.