AI-Driven Drug Development in Inflammatory Diseases

Artificial Intelligence in drug development for inflammatory diseases serves to enhance the overall efficiency, precision, and personalization of the process. AI integrates multi-omics, digital twins, and predictive modelling in order to identify therapeutic targets, accelerate molecular design, and optimize clinical translation of drugs. Machine learning and deep learning models help improve ADMET profiling, toxicity prediction, and the assessment of immunogenicity, while federated learning allows secure data collaboration across different institutions. Multi-modal AI with network pharmacology unravels complex disease mechanisms and supports systems-level drug modelling and optimization of multi-target therapy. Integration with automation, closed-loop experimentation, and quantum computing is bound to accelerate both the processes of discovery and validation. Though ethical and regulatory challenges are at play, AI-driven frameworks will reshape translational medicine in driving equitable and explainable innovation in inflammation therapeutics.