Quantum computing (QC) will revolutionize drug discovery by transforming the challenges of classical computational approaches in molecular modelling, and drug-target interactions. The high computing cost of accurately modeling complex biological systems is another drawback of conventional techniques. However, recent advances in quantum techniques (such as sparse quantization and quantum phase estimation) have drastically reduced computation times and allowed us to complete previously unfeasible calculations in a single day. This chapter discusses the evolving role of QC in pharmaceutical research, specifically its applications in molecular docking, quantum simulations and protein structure prediction. Hybrid quantum–classical models are gaining popularity as a cost-effective means for drug screening, prodrug activation, and covalent interaction studies between theoretical models and experimental work. Further, quantum-inspired methods such as quantum annealing and fault-tolerant systems are driving advances in clinical and personalized medicine. Although current hardware constraints exist, the fast evolution in QC signals a revolution in drug development, enabling a higher accuracy, lower cost, and faster discovery of lifesaving therapeutics. With the continued expansion of interdisciplinary cooperation between quantum computing, bioinformatics, and pharmaceutical sciences, QC is anticipated to revolutionize the future of therapeutics and pharmaceutical development.