Computer-Aided Drug Design (CADD) is a cutting-edge computational service that empowers pharmaceutical companies, biotechnology firms, and research institutions to accelerate and optimize their drug discovery pipelines. By combining molecular modeling, simulation, and artificial intelligence, CADD enables rational drug design and predictive evaluation of compound properties before synthesis or testing, significantly reducing time and cost. The service covers the full spectrum of in silico discovery. Virtual Screening and Drug Design employ ligand- and structure-based approaches to identify promising candidates and design tailor-made compound libraries. Binding and Selectivity Assessment provides insights into molecular recognition through binding affinity calculations, selectivity predictions, and evaluation of how structural modifications affect target interactions. Through Structural and Biophysical Modeling, including molecular docking, protein structure prediction, molecular dynamics simulations, and quantum mechanics methods, CADD elucidates molecular mechanisms and optimizes stability and conformational behavior. Pharmacophore and QSAR studies establish correlations between chemical structure and biological activity, highlighting essential features for activity and guiding structure–activity relationship (SAR) analyses. Complementing these tools, Predictive Models and AI Approaches leverage machine learning to build ligand- and structure-based predictive models that assess biological activity, toxicity, and pharmacokinetics during lead optimization. Together, these integrated computational capabilities enable hypothesis-driven discovery, improve hit identification and optimization, and de-risk preclinical programs. CADD provides a scalable, science-driven platform that transforms traditional drug discovery into a faster, smarter, and more efficient process—empowering innovators to translate molecular insights into viable therapeutic candidates.