In a two-year collaboration in Singapore, the partners ran qMCMC on Quantinuum’s H2 and Helios trapped-ion systems via the National Quantum Computing Hub.
They said the first experimental realization on physical hardware shows accurate sampling is feasible on NISQ devices, with results posted on arXiv.
The teams are also testing VQE and QPE methods to move beyond benchmarks and integrate higher-fidelity quantum molecular simulations into pharmaceutical research workflows.
If quantum computing slashes drug development costs, will life-saving medicines actually become more affordable for everyone?
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Demonstrating Quantum Advantage in Drug Discovery: qMCMC Runs Successfully on Singapore’s Quantinuum Helios System
Overview
In April 2026, a research team successfully implemented the quantum Markov Chain Monte Carlo (qMCMC) algorithm on Quantinuum's advanced Helios quantum computer, overcoming noise challenges typical of NISQ devices. This breakthrough validated that quantum states accurately represented complex distributions using innovative encoding methods. The achievement was unveiled at Singapore's Quantum Industry Day, highlighting qMCMC's potential to accelerate drug discovery through quadratic speedups. Enabled by a strategic collaboration between CQT, Qubit Pharmaceuticals, and Singapore’s National Quantum Computing Hub—backed by significant government investment—the team set a two-year roadmap to refine algorithms and integrate hybrid quantum-classical workflows. Despite hardware and algorithmic challenges, this effort marks a key step toward practical quantum advantage in pharmaceutical R&D.