AI-Enabled Pharmaceutical and Biological Processes: Transforming Cancer Therapy through Intelligent Nanoparticle Design

Abstract

Artificial intelligence (AI) is transforming pharmaceutical and biological sciences by enabling data-driven and precise therapeutic strategies. Cancer therapy remains limited by poor drug specificity, systemic toxicity, and unpredictable pharmacokinetics. The integration of AI with nanotechnology provides innovative solutions by optimizing nanoparticle design, predicting biological interactions, and enhancing targeted drug delivery. Machine learning models support the rational selection of nanoparticle characteristics such as size, surface charge, drug loading efficiency, and ligand functionalization, improving therapeutic efficacy and safety. AI-based In silico modelling enables prediction of drug release behaviour, stability, and nanoparticle-tumour interactions, significantly reducing experimental time and development costs. Both passive and active targeting strategies are enhanced through AI-guided optimization, resulting in improved tumour accumulation and reduced off-target effects. AI-optimized nanoparticles, including polymeric nanoparticles, dendrimers, nanogels, and inorganic nanoparticles, show promising applications in the treatment of breast, lung, brain, colorectal, and prostate cancers. Overall, AI-enabled pharmaceutical and biological processes support precision and personalized cancer therapy.