July 28, 2026, Singapore – The intersection of artificial intelligence and quantum computing has reached another milestone. A multinational research team, jointly led by the Centre for Quantum Technologies at the National University of Singapore and the Agency for Science, Technology and Research (A*STAR), announced the successful design of the first new candidate drug molecule for Alzheimer's disease using AI and quantum computing collaboration. Phase I clinical trials are planned for early 2027. This breakthrough not only marks a deeper application of AI in drug discovery but also drove the Global AI Barometer Index up 3.2% this month, with individual stocks in the quantum computing + AI sector averaging gains of over 10%.
AI + Quantum: The "Twin Engine" for Drug Discovery
Traditional new drug development takes an average of over 10 years and costs billions of dollars, but the combination of AI and quantum computing is rewriting these rules. The announced candidate drug, code-named QAI-AD01, was initially filtered by AI algorithms from a massive molecular database of about 2 million potential molecules, then the precise interaction energy between molecular target proteins was calculated through a quantum computing simulator, ultimately narrowing the candidate molecules to single digits. The entire screening process took only 8 months, more than 20 times faster than traditional high-throughput screening.
The Singapore team was primarily responsible for algorithm optimization in the quantum computing simulation part. Project lead Professor Chen Zhiyuan from the National University of Singapore said, "The quantum-classical hybrid algorithm we developed can handle complex electronic structure calculations that traditional computers cannot manage, allowing us to more accurately predict the behavior of drug molecules in physiological environments." The research results were published in the journal Nature Computational Science on July 27.
Global AI Barometer Index: Quantum Computing + AI Sector Leads Gains
Stimulated by this news, quantum computing concept stocks generally strengthened during Asian trading on July 28. Shares of local Singapore-listed quantum computing startup Qilimanjaro Quantum Tech rose as much as 15%, closing at SGD 4.27. The Global AI Barometer Index (GBI) gained 2.1% in the week ending July 27, with a total monthly increase of 3.2% in July, of which the quantum computing + AI segment contributed nearly half of the gains.
The index is jointly compiled by LionCity Financial and the Asia-Pacific AI Research Institute, covering 50 core AI-listed companies globally. Among the strongest performers in July's constituent stocks were US quantum computing company IonQ (up 18% monthly), China's iFlytek (up 12% monthly), and Japan's Fujitsu (up 8% monthly). Analysts believe that AI is accelerating its application in fields such as drug discovery and materials science, with quantum computing increasingly playing a role as an accelerator.
Singapore's AI Ecosystem Under Its Smart Nation Strategy
This breakthrough also reflects Singapore's long-term layout in AI and quantum computing. In 2024, the Singapore government announced an investment of SGD 150 million to establish the "Quantum Engineering Program," followed by an additional SGD 200 million in 2025 for AI and quantum fusion research. Currently, Singapore has built one of Asia's largest quantum computing cloud platforms and has established collaborations with multiple global pharmaceutical companies.
Ms. Li Meihua, Director of the Biomedical Sciences Division of the Singapore Economic Development Board, stated, "We are not only focusing on AI applications in finance and logistics but also aiming to position Singapore as an AI-driven new drug R&D center. This collaboration with the international team has validated Singapore's competitiveness in key core technologies." It is understood that multinational pharmaceutical companies involved in the project include Roche and Pfizer, with Singapore as an Asian clinical trial base expected to accelerate translation.
Industry Challenges and Future Outlook
Despite the bright prospects, combining AI and quantum computing in drug discovery still faces challenges. First, the availability of quantum computing hardware: currently only a handful of truly usable quantum computers exist worldwide, and their error rates are relatively high. Second, data privacy concerns: AI algorithms require large amounts of patient data, and regulatory standards vary across countries. Additionally, the path from candidate drug molecules to final market approval still takes several years, and the risk of clinical trial failure remains.
However, Professor Chen Zhiyuan is optimistic about the future: "In the next 3-5 years, AI and quantum computing will become standard tools for new drug R&D. We are exploring extending this methodology to major areas such as cancer and cardiovascular diseases." Analysts from the Global AI Barometer Index have also upgraded their rating on the AI pharmaceutical sub-sector to "overweight," estimating a compound annual growth rate of 45%.
Investment Warning and Market Tips
LionCity Financial reminds investors that AI-related concept stocks are highly volatile, and the commercialization path for quantum computing remains unclear. This article is solely an industry news summary and does not constitute any investment advice. Investors should make prudent decisions based on their own risk tolerance.
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