InveniAI’s AlphaMeld Platform Debuts the Addition of ChatAlphaMeld, A Powerful Tool Designed to Scale Target and Drug Discovery and Development

 InveniAI LLC, a global leader in leveraging AI and machine learning (ML) to transform innovation in drug discovery and development, announces the introduction of ChatAlphaMeld, a game-changing feature on its industry-leading platform, AlphaMel. ChatAlphaMeld, based on GPT-4 by OpenAI, is a revolutionary tool designed to provide expert answers and insights for drug and target discovery within a unique environment that integrates pharmacology with biology to accelerate the innovation and development of precision therapeutics.

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ChatAlphaMeld is modeled to support drug innovation by improving the user experience of existing power users and now opens up the platform to functional stakeholders across the drug discovery and development lifecycle, thereby enabling queries and easier interactions with AlphaMeld and its discovery tools. This advanced AI tool offers valuable insights by highlighting direct and indirect associations between key entities such as genes and targets, pathways, biomarkers, drugs, and diseases and symptoms, allowing the AlphaMeld discovery platform to extract and provide guidance on the functional direction between entities. This enables the turbocharging of hypothesis generation and prioritization for innovative drug programs by using large-scale information and unprecedented speed to increase the probability of clinical and regulatory success.

Krishnan Nandabalan, Ph.D., Chairman, President, and CEO of InveniAI, said, “Continued technology innovation and integration into our drug discovery workflow has been instrumental in the success of AlphaMeld. This evolution has resulted in the identification of numerous programs developed by our collaborators and a recent biotech spinout, Invea Therapeutics. We continue to evaluate powerful open AI platforms like GPT-4 to address innovation bottlenecks and accelerate drug discovery to expeditiously develop solutions for patients eagerly awaiting efficacious treatment options.”

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The ChatAlphaMeld interface harnesses GPT-4 and AlphaMeld’s extensive proprietary knowledgebase, which encompasses 1,968,753,898 edges (or associations) between 649,893,375 nodes (or entities), and includes more than 49,000 drugs, 20,000 genes, 30,000 disease/symptoms, 73,000 expression datasets, 1,400 cell types, 483,000 clinical events, and over a billion scientific literature sentences to triangulate disease-target-drug associations.

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