ImmunoPrecise’s BioStrand(R) Unifies Diverse Data Modalities, Launches AI-Driven Platform For Enhanced Drug Discovery
- The launch of the RAG-based LLM platform by subsidiary BioStrand marks a major breakthrough in creating a comprehensive approach for the interpretation of complex biological data.
- The platform seamlessly integrates with the company's patented HYFT technology and LENSai platform, designed for unprecedented accuracy, interpretability, and data-centric design in generative AI tools.
- BioStrand is well-positioned to become a leader in the AI and healthcare industry in the field of antibodies, with the market for AI in healthcare forecasted to experience significant growth.
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VICTORIA, BC / ACCESSWIRE / November 22, 2023 / ImmunoPrecise Antibodies Ltd. (NASDAQ:IPA), an AI-driven biotherapeutic research and technology company, has announced that its subsidiary, BioStrand®, has launched an advanced Retrieval Augmented Generation (RAG)-based Large Language Model (LLM) platform. This breakthrough platform seamlessly integrates with the company's patented HYFT technology and LENSai platform, and the company reports that it is designed for unprecedented accuracy, interpretability and data-centric design in generative AI tools.
ImmunoPrecise Antibodies is best known for its pioneering work as a Contract Research Organization (CRO) in the biopharmaceutical industry, particularly distinguished for its adeptness in implementing Vertical AI, a concept that intertwines industry-specific knowledge with Artificial Intelligence (AI). With a rich history spanning over two decades, the company not only offers a myriad of specialized services in antibody discovery and development but also integrates Vertical AI, ensuring that AI models are not just theoretically sound but are also embedded with practical, industry-specific insights and data. Unlike generic AI, ImmunoPrecise Antibodies' Vertical AI holds the potential to develop precise, tailored therapies and treatment decisions with the aim of enhancing patient outcomes by identifying patterns and predicting safer and more effective drugs for patients.
Its subsidiary, BioStrand's innovative solution to the Information Integration Dilemma (IID) has resulted in a unique technology design that unifies diverse data modalities - such as sequence data, 3D structural data and scientific literature - within the LENSai Knowledge Graph. This integration allows for efficient data fusion, enabling a comprehensive analysis and interpretation of complex biological data.
The integration of proprietary and patented technologies with LLMs sets BioStrand's drug discovery platform apart. The company reports that biomedical LLMs, particularly those pre-trained on domain-specific vocabulary, outperform traditional tools in various biological data-based tasks and have demonstrated superiority in identifying drug targets, predicting drug-target interactions and assessing molecular properties, including potential safety concerns.
The key features of BioStrand's LENSai Platform include:
- Holistic Integration of Data: LENSai provides a unique and comprehensive view of life sciences data by linking sequence, structure, function, and literature information from the entire biosphere - this is only achievable using their patented HYFT technology.
- Expansive Knowledge Graph: LENSa'is knowledge graph encompasses 25 billion prorelationships and 660 million data objects, ensuring a deep understanding of genes, proteins and biological pathways - and most importantly, one of the biggest challenges in the sciences today, predicting the function (activity) of a molecule.
- Neuro Symbolic Methodology: LENSai combines deep learning and symbolic logic techniques, harnessing the strengths of LLMs and the reasoning capabilities of symbolic systems. This approach is designed to deliver comprehensive and interpretable outcomes for inquiries.
- Retrieval-Augmented Generation (RAG) Integration: LENSai integrates RAG with their patented HYFT technology to enhance the accuracy of generated responses. This synergy bridges the gap between the generative capabilities of LLMs and the concrete data from HYFTs technology is developed to provide more informed and precise answers.
- Traceability and Credibility: LENSai ensures the authenticity and reliability of research outcomes by maintaining references to the original sources of generated results.
This news from ImmunoPrecise Antibodies Ltd. marks progress in the biotherapeutic research industry. The unique technology design of BioStrand, now equipped with a Retrieval-Augmented Generation (RAG)-based Large Language Model (LLM) platform, marks a major breakthrough in creating a comprehensive approach for the interpretation of complex biological data. Designed to be seamlessly integrated with the patented HYFT technology of the company, the company reports that this platform can unify sequence data, 3D structural data, scientific literature and others to deliver comprehensive insights into research that scientists have never had. With full traceability and the ability to cross-check user input to different data types, BioStrand®'s insight is designed to offer unparalleled accuracy and interpretability, making it a strong player in AI-driven drug discovery.
With the launch of this groundbreaking platform, BioStrand has potentially reinforced a position at the forefront of AI-driven biotherapeutic research and technology, empowering more efficient and effective drug discovery processes. The market for AI in healthcare is forecasted to experience growth, with an estimated value of
Featured photo by Julia Koblitz on Unsplash.
Contact:
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SOURCE: ImmunoPrecise Antibodies Ltd.
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