Abstract

The pharmaceutical industry stands at the threshold of a computational transformation driven by quantum computing. While artificial intelligence and high-performance classical computing have already reshaped drug discovery pipelines, certain molecular and combinatorial challenges remain computationally prohibitive. Quantum computing, rooted in the principles of quantum mechanics, offers a fundamentally new paradigm capable of simulating molecular interactions, electronic structures, and optimization landscapes with unprecedented fidelity. This narrative review critically examines the current relevance of quantum computing in pharmaceutical research, spanning quantum chemistry simulations, molecular docking refinement, combinatorial optimization, and quantum-enhanced machine learning. It further evaluates hybrid quantum–classical frameworks as the most pragmatic near-term pathway while analyzing technical constraints including hardware noise, error correction, scalability, and workforce preparedness. Beyond immediate applications, the article projects long-term implications for regulatory science, intellectual property, pharmaceutical economics, and global drug accessibility. Positioned at the intersection of pharmacology, computational science, and strategic policy, this paper argues that quantum computing should not be perceived as an immediate replacement for classical methods but as a progressive augmentative force that may redefine the molecular innovation ecosystem over the next decade.