Quantum

Shionogi Wins NEDO Award for Quantum-Assisted Drug Discovery

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Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 29/10/2026, 10:04:25 UTC.

Briefings

Shionogi & Co. won first place in the Quality of Life category of Japan's NEDO Challenge for research using quantum computing in drug discovery. A peer-reviewed study published in Scientific Reports in July 2026 showed a quantum-assisted generative AI model produced 97% chemically valid molecular representations versus 73% for a classical model. The award, valued at 40 million yen, supports Shionogi's continued research combining quantum and classical computing to generate drug candidates. Dr. Alan Baratz, CEO of D-Wave, and Dr. Hayato Kunugi, lead author of the study, highlighted the potential to accelerate drug discovery. The NEDO Challenge recognizes quantum applications addressing social and industrial challenges.

Key points

• Shionogi & Co. won first place in the Quality of Life category of Japan's NEDO Challenge for research applying quantum computing to drug discovery.
• A peer-reviewed study published in Scientific Reports in July 2026 found a quantum-assisted generative AI model produced 97% chemically valid molecular representations compared to 73% for a classical model.

Context

Shionogi & Co. is a pharmaceutical company in Japan collaborating with D-Wave Quantum Inc. on research using quantum computing to accelerate drug discovery. The NEDO Challenge, a national R&D organization under Japan's Ministry of Economy, Trade and Industry, recognizes quantum computing applications addressing social and industrial challenges. This award-winning research represents a significant step in applying quantum computing to one of the pharmaceutical industry's most complex challenges.

Limitations

The evidence is limited to a single peer-reviewed study published in Scientific Reports in July 2026. The specific city or region where the research was conducted is not mentioned in the source. The 97% and 73% figures are from the study, but the broader impact of this research on future drug development outcomes is not quantified.

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