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CDT Highlights Sarborg’s Expanding Quantum Computing IP Portfolio and Application to Drug Discovery

NAPLES, Fla. and CAMBRIDGE, United Kingdom, Sept. 29, 2026 (GLOBE NEWSWIRE) -- CDT Equity Inc. (Nasdaq: CDT) ("CDT" or the "Company") today notes the announcement from Sarborg Limited regarding the filing of new intellectual property…

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Sep 29, 2026 at 11:00 AM UTC · Updated há 4 dias · 5 min de leitura

CDT Highlights Sarborg’s Expanding Quantum Computing IP Portfolio and Application to Drug Discovery
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NAPLES, Fla. and CAMBRIDGE, United Kingdom, Sept. 29, 2026 (GLOBE NEWSWIRE) -- CDT Equity Inc. (Nasdaq: CDT) ("CDT" or the "Company") today notes the announcement from Sarborg Limited regarding the filing of new intellectual property applying quantum sampling to disease biology and drug discovery. CDT holds 1,290 shares in Sarborg, representing 22.7% of the issued share capital. Sarborg's latest capital raise was at $125,000 per share, implying a fully diluted valuation of approximately $709 million.

A copy of Sarborg's full announcement is available below and at www.sarborg.com/news.

Sarborg Expands Quantum Computing Patent Portfolio, Applying Quantum Sampling to Disease Biology and Drug Targeting

WILMINGTON, De - September 29, 2026 - Sarborg Limited ("Sarborg" or the "Company") today announced the filing of comprehensive novel intellectual property (IP) expanding its quantum computing applications into human drug discovery, utilising the expansive problem-solving efficiency of quantum sampling. Sarborg is also in active discussions with a leading global quantum computing company regarding a partnership to advance these dedicated models on market-leading quantum hardware.

Existing quantum computing work in drug discovery focuses on simulating individual molecules, but Sarborg's novel application applies market-leading quantum computation to disease biology itself: the networks of regulators that switch disease genes on and off. Disease genes are frequently controlled by several regulators acting together, a combinatorial layer that conventional network methods cannot see and that grows rapidly harder to compute at scale. This approach requires the complexity of quantum sampling solutions.

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