ImmunoPrecise’s BioStrand(R) Unifies Diverse Data Modalities, Launches AI-Driven Platform For Enhanced Drug Discovery

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 LENS^ai 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 LENS^ai 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.