Insilico Medicine (03696), a generative AI-driven clinical-stage biopharmaceutical technology company, announced today the launch of DORA Community Edition—a free, self-deployable version of its comprehensive AI engine designed for scientific research and content creation. The DORA Community Edition, initiated by Insilico Medicine and launched with support from Microsoft, aims to make cutting-edge research tools more accessible, foster global scientific collaboration, enhance research transparency, and accelerate innovation in biotechnology and academia. In today's era of rapid scientific advancement, writing various research documents—from literature reviews to patent applications and business reports—is often cumbersome and time-consuming. Born in July 2024, during a period of rapid development in large model applications, DORA was developed by Insilico Medicine as an advanced "Agentic AI" tool designed to streamline the writing process for academic papers and other research-related documents. It leverages collaborative multi-agent AI, combinatorially designed prompts, pre-set content generation workflows, and Insilico Medicine's proprietary database to help researchers efficiently generate various professional-grade documents with accurate references. With support from Microsoft and the technical capabilities of Microsoft Foundry, Insilico Medicine recently implemented a significant functional upgrade to DORA. The upgraded DORA can now seamlessly integrate with various Foundry models, including the top-tier O3 Deep Research model, thereby significantly enhancing the efficiency and output quality of scientific content creation. The upcoming DORA Community Edition will be released under the permissive Apache 2.0 open-source license, offering friendly terms for commercial use and secondary development. Developers and researchers worldwide can access the open-source DORA code via GitHub and begin testing immediately: https://github.com/insilicomedicine/DORA. Dr. Alex Zhavoronkov, Founder and CEO of Insilico Medicine, stated, "We believe the future of scientific discovery lies in collaboration, not isolation. By open-sourcing DORA, we are placing a powerful AI tool directly into the hands of global innovators, hoping to build a vibrant ecosystem where the community can collectively enhance research rigor, continuously push the boundaries of biotechnology, and ultimately deliver urgently needed therapies to patients faster." Elena Bonfiglioli, General Manager of Global Health and Life Sciences at Microsoft, commented, "Microsoft is committed to working with partners and customers to drive and accelerate scientific discoveries that benefit individuals, organizations, and industries worldwide. We are delighted to support Insilico Medicine in open-sourcing DORA. By helping researchers retrieve, organize, and synthesize complex scientific information, DORA lowers the barrier to cutting-edge research and expands access to generative AI. As a partner in the Microsoft Discovery preview program, we are working with Insilico Medicine to foster deeper scientific collaboration and support customers in applying AI to achieve meaningful, human-centric impact." In addition to the DORA Community Edition, Insilico Medicine offers a more comprehensive DORA SaaS version for users with higher-level, specialized needs. Compared to the open-source version, DORA SaaS provides access to pre-analyzed "protein-disease association" reports from Insilico's target discovery engine, PandaOmics, enabling deeper domain-specific insights; it also connects to Insilico's data warehouse, supporting instant in-text citations. Furthermore, DORA SaaS includes a richer library of pre-built templates to support various types of scientific content creation. Users can also access and deploy DORA SaaS directly via the Microsoft Marketplace. As early as 2016, Insilico Medicine was the first to systematically propose the concept of using generative AI to design novel molecules in a peer-reviewed journal, laying the foundation for the subsequently commercialized Pharma.AI platform. Since then, Insilico has continuously integrated technological breakthroughs into Pharma.AI, evolving it into a comprehensive generative AI solution spanning biology, chemistry, clinical development, and scientific research. Recently, Insilico Medicine held a Pharma.AI Winter Webinar, announcing the latest advancements in its software product portfolio and outlining its vision for achieving "Pharmaceutical Super Intelligence." By integrating advanced AI and automation technologies, Insilico has significantly improved the efficiency of early-stage drug discovery in practical applications, setting a benchmark for AI-driven drug discovery. Compared to the traditional early drug discovery process, which typically takes an average of 4.5 years, Insilico Medicine nominated 20 preclinical candidate compounds between 2021 and 2024, with an average time of just 12-18 months from project initiation to PCC nomination, requiring the synthesis and testing of only about 60-200 molecules per project.