Bringing a new drug to market can take over a decade and billions of euros, and even then, most candidates fail before reaching patients. One of the biggest challenges lies in predicting how molecules behave at the atomic level, a task that quickly overwhelms classical computers as molecular complexity increases.
Quantum simulation offers a breakthrough. By modelling molecular interactions directly using the laws of quantum mechanics, quantum computers promise faster, more accurate insights into which compounds are likely to be safe, effective, or toxic, long before clinical trials begin.
Case: Drug discovery and molecular modelling with quantum simulation
At the heart of drug discovery is the need to understand how molecules, drug candidates, proteins and enzymes, interact with each other. Small changes at the quantum level can determine whether a compound becomes a life-saving therapy or a failed trial.
Classical supercomputers are powerful, but they rely on approximations to simulate large molecules and complex reactions. As the size and complexity of a molecular system grows, so does the computational cost… exponentially.
Quantum simulation changes the game. By encoding quantum properties directly into qubits, quantum computers can model the behaviour of atoms, bonds, and reactions with unprecedented fidelity. This opens the door to:
- Predicting molecular binding and toxicity profiles
- Modelling enzyme-ligand interactions in detail
- Screening vast libraries of compounds more efficiently
- Designing drugs for rare or poorly understood diseases
Rather than replacing classical methods, quantum tools are being integrated into hybrid workflows, combining the best of both worlds to speed up the early phases of R&D.
Business value
- Accelerated R&D timelines: Quantum simulation reduces the time it takes to identify viable drug candidates — from years to months in some cases.
- Cost efficiency through digital testing: By simulating molecule behaviour before physical testing, companies can reduce expensive lab work and failed experiments.
- Competitive advantage through innovation: Early access to quantum-powered platforms gives pharmaceutical leaders a head start in developing breakthrough therapies.
- Expanded innovation pipeline: Quantum tools enable researchers to explore novel compounds, rare diseases, and edge cases that are often excluded due to complexity.
Technology readiness
Quantum simulation is still in the early research and pilot phase, with most industrial applications focused on small molecules and reaction pathways. While classical high-performance computing (HPC) remains dominant for large-scale simulations, hybrid quantum-classical workflows are now being tested in pharmaceutical labs.
Leading pharma companies are partnering with quantum hardware providers and software startups to experiment with quantum chemistry tools, refine algorithms, and prepare for future scaling.
As quantum hardware advances, the complexity of molecules that can be accurately simulated will increase, bringing the promise of quantum drug discovery closer to reality.
Leading players and experiments
Roche, Pfizer, and Boehringer Ingelheim are actively working with quantum providers such as IBM, Google, and QC Ware to integrate quantum simulation into early-phase drug research.
AstraZeneca and Merck are exploring quantum tools for structure-based drug design and molecular binding simulations.
Software innovators like Cambridge Quantum and Zapata Computing are developing quantum algorithms tailored to pharmaceutical needs, from molecular docking to toxicity prediction
Discover more use cases here.
