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For more than 30 years, Cabling Installation & Maintenance has provided useful, practical information to professionals responsible for the specification, design, installation and management of structured cabling systems serving enterprise, data center and other environments. These professionals are challenged to stay informed of constantly evolving standards, system-design and installation approaches, product and system capabilities, technologies, as well as applications that rely on high-performance structured cabling systems. Our editors synthesize these complex issues into multiple information products. This portfolio of information products provides concrete detail that improves the efficiency of day-to-day operations, and equips cabling professionals with the perspective that enables strategic planning for networks’ optimum long-term performance.

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SciSparc Resolves to Launch Innovative Quantum Computing-Enabled 3D Protein Modeling Initiative to Revolutionize AI Drug Discovery

TEL AVIV, Israel, Sept. 25, 2025 (GLOBE NEWSWIRE) -- SciSparc Ltd. (Nasdaq: SPRC) (the "Company" or "SciSparc"), a specialty clinical-stage pharmaceutical company focusing on the development of therapies to treat disorders of the central nervous system, today announced that the board of directors resolved to initiate the launch of an innovative initiative to advance 3D protein modeling using quantum computing technology (the “Initiative”). This new program aims to transform drug discovery by potentially achieving unprecedented accuracy in predicting protein structures and interactions with their ligands, potentially paving the way for breakthroughs in structural biology and personalized medicine.

Proteins are the building blocks of life and their function often depends on their unique 3D shapes. Knowing a protein’s 3D structure is critical for understanding how it interacts in the body, how to treat a related disease and how to design effective drugs using the highest possible level of accuracy. Traditionally, scientists use computers to predict these 3D structures, but this process is challenging because proteins are dynamic, constantly shifting between different conformations and classical computers often struggle to model these changes accurately.

SciSparc’s new Initiative aims to leverage quantum computing, a cutting-edge technology that uses principles of quantum mechanics to perform calculations far beyond the capabilities of traditional computers. Unlike classical computing methods, quantum computing might simulate the energy dynamics of proteins with greater precision, capturing their complex movements and interactions with their ligands in a much higher accuracy. This initiative focuses on developing quantum-enabled tools to:

  • accurately predict how proteins fold into their 3D shapes;
  • model how proteins interact with potential drugs (protein-ligand interactions); and
  • accelerate the discovery of new drugs by providing highly precise predictions.

SciSparc will form a dedicated research team to integrate quantum computing algorithms into 3D protein modeling with the aim of creating new intellectual property. The Company will collaborate with leading experts in quantum computing and structural biology to build these capabilities. Initial efforts will focus on refining quantum algorithms to simulate protein dynamics and binding interactions, targeting applications in drug discovery for neurological and rare diseases, areas where SciSparc already has expertise. SciSparc expects to incorporate a new wholly owned Israeli subsidiary which will operate the Initiative.

About SciSparc Ltd. (Nasdaq: SPRC):

SciSparc Ltd. is a specialty clinical-stage pharmaceutical company led by an experienced team of senior executives and scientists. SciSparc’s focus is on creating and enhancing a portfolio of technologies and assets based on cannabinoid pharmaceuticals. With this focus, the Company is currently engaged in the following drug development programs based on THC and/or non-psychoactive CBD: SCI-110 for the treatment of Tourette Syndrome, for the treatment of Alzheimer’s disease and agitation; and SCI-210 for the treatment of ASD and status epilepticus. The Company also owns a controlling interest in a subsidiary whose business focuses on the sale of hemp seed oil-based products on the Amazon.com Marketplace.

Forward-Looking Statements:

This press release contains forward-looking statements within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995 and other Federal securities laws. For example, SciSparc is using forward-looking statements when it discusses: the successful launch of the Initiative, that the Company will form a dedicated research team to integrate quantum computing algorithms into 3D protein modeling; the potential benefits and advantages of the new Initiative regarding AI drug discovery; collaborating with leading experts in quantum computing and structural biology; the incorporation of a new subsidiary to operate the Initiative and that the Company’s initial efforts will focus on refining quantum algorithms to simulate protein dynamics and binding interactions.. Because such statements deal with future events and are based on SciSparc’s current expectations, they are subject to various risks and uncertainties and actual results, performance or achievements of SciSparc could differ materially from those described in or implied by the statements in this press release. The forward-looking statements contained or implied in this press release are subject to other risks and uncertainties, including those discussed under the heading “Risk Factors” in SciSparc’s Annual Report on Form 20-F filed with the SEC on April 24, 2025, and in subsequent filings with the SEC. Except as otherwise required by law, SciSparc disclaims any intention or obligation to update or revise any forward-looking statements, which speak only as of the date they were made, whether as a result of new information, future events or circumstances or otherwise.

Investor Contact:
IR@scisparc.com
Tel: +972 3-761-7108


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