Quantum Computing in Biopharma: Redefining Molecular Design and Predictive Pharmacology

Abstract

The convergence of quantum computing (QC) and biopharmaceutical science promises to revolutionize molecular design and predictive pharmacology. Quantum computing — harnessing principles of superposition, entanglement and quantum algorithms — enables simulation of molecular interactions with a precision and scale beyond the reach of classical methods. This review outlines the fundamental principles of QC, discusses current applications in drug discovery and pharmacology, highlights hybrid quantum-classical approaches and quantum-machine learning (QML), and examines the challenges and future directions. The review suggests that, though currently at a nascent stage, QC could dramatically reduce drug development timelines, improve success rates, and pave the way for personalized medicine and complex biologics design.