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RetinAI Expands Operations with a U.S. Office In Boston and Achieves 21 CFR Part 11 Compliance to Support Research and Clinical Studies

RetinAI Medical AG (“RetinAI”), is a leader in clinical and imaging data management software and advanced analytics for ophthalmology, is excited to announce the launch of its first U.S.-based office, located in Boston, MA. This expansion will support further growth within the U.S. market, building upon existing collaborations with U.S.-based pharmaceutical companies and its partnership with Heidelberg Engineering to distribute RetinAI’s Disease AI Apps for research use in the U.S. The Boston office will be RetinAI’s second location, in addition to its Bern headquarters.

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“Our team is delighted about this natural expansion into the U.S.”

RetinAI also reached another important milestone by achieving 21 CFR Part 11 compliance. This standard is necessary for research or clinical studies conducted in the U.S., and ensures the security and authenticity of electronic data via audit trailing and legally-binding electronic signatures. RetinAI’s global clients can therefore be confident that their RetinAI-assisted, research and clinical studies in the U.S. will have validated and 21 CFR Part 11-compliant processes to collect and analyze data.

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“Our team is delighted about this natural expansion into the U.S.,” said Dr. Carlos Ciller, CEO of RetinAI. “Building on our milestones earlier this year of receiving FDA-clearance for RetinAI’s Discovery Platform and HIPAA-compliance, these new achievements for the U.S. market continue to strengthen our position as a valuable partner for pharma and clinical networks to accelerate workflows in clinical studies and research, while generating a greater level of insights on such an important asset as their data.”

RetinAI partners with experts in ophthalmology to help accelerate data analysis and more effectively achieve target-based research for improved study design, clinical studies and research. RetinAI’s data management platform and models, including AI models for Geographic Atrophy progression prediction, analyze datasets at-scale to gain a deep understanding on biomarker profiles and patient subgroups or outcomes.

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