BioStrand Unveils Groundbreaking Retrieval
Augmented Generation (RAG)-Based LLM Platform Integrated with
Patented HYFT Technology
BioStrand's Work Exemplifies the IPA Family's
Investment in Advanced AI, Aiding Partners in Developing New
Biologics for Previously Undruggable Targets
ImmunoPrecise Antibodies Ltd. (NASDAQ: IPA) (“ImmunoPrecise” or
“IPA” or the “Company”), an AI-driven biotherapeutic research and
technology company, announces that its subsidiary, BioStrand®, has
commercially launched its state-of-the-art Retrieval Augmented
Generation (RAG)-based Large Language Model (LLM) platform. This
pioneering platform seamlessly integrates with the Company’s
patented HYFT technology and LENSai platform, signifying a
noteworthy leap in the market as the Company aims at ensuring
unparalleled accuracy, interpretability, and data-centric design in
generative AI tools.
BioStrand's innovative approach to solving the Information
Integration Dilemma (IID) has led to the development of a unique
technology design that encapsulates and unifies diverse data
modalities. This includes syntactical (sequence) data, 3D
structural data, unstructured scientific information (e.g.,
scientific literature), all integrated within a singular framework,
the LENSai Knowledge Graph. This breakthrough facilitates efficient
data fusion, enabling a comprehensive analysis and interpretation
of complex biological data.
Knowledge Graphs and LLMs have been recognized for their
superior performance over conventional approaches in drug
discovery. BioStrand’s integration of their proprietary and
patented technologies with LLM synergizes strengths and addresses
limitations, leading to a more efficient drug discovery platform.
Biomedical LLMs, specifically those pre-trained on domain-specific
vocabulary, outperform traditional tools in many biological
data-based tasks. For instance, for the important step of
identifying drug targets, AI-powered language models have
demonstrated superiority over even the most state-of-the-art
approaches. Furthermore, AI-enabled LLMs are now being utilized
across the drug discovery and development pipeline for predicting
drug-target interactions, molecular properties, and even potential
drug withdrawals due to safety concerns.
Key Features of BioStrand’s LENSai Platform:
- Holistic Integration of Data: LENSai offers a unified approach,
linking sequence, structure, function, and literature information
from the entire biosphere, providing a comprehensive view of life
sciences data.
- Expansive Knowledge Graph: At its core, LENSai boasts a
knowledge graph that maps 25 billion relationships across 660
million data objects, ensuring a deep and interconnected
understanding of genes, proteins, and biological pathways.
- Neuro Symbolic Methodology: A fusion of deep learning and
symbolic logic techniques, a branch of mathematics and
philosophical logic that uses symbols to represent logical
expressions, rather than using words. This approach harnesses the
data-driven strengths of LLMs and the reasoning capabilities of
symbolic systems, offering both adaptability from LLM methods and
transparency from symbolic logic, ensuring comprehensive and
interpretable outcomes for inquiries.
- Retrieval-Augmented Generation (RAG) Integration: LENSai
utilizes RAG to enhance the accuracy of the generated responses of
LLMs. By integrating with the HYFTs technology as its proprietary
knowledge graph, RAG ensures that the platform provides up-to-date
and factual information, reducing the chances of generating
inaccurate or "hallucinated" content. This synergy is designed to
allow LENSai to deliver more informed and precise answers, bridging
the gap between the vast generative capabilities of LLMs and the
concrete data from HYFTs technology.
- Traceability and Credibility: All results generated by LENSai
can be referenced back to their original sources, ensuring
authenticity and reliability in research outcomes.
"I am pleased to share that BioStrand's advanced AI platform has
now integrated a Retrieval Augmented Generation plugin with a Large
Language Model, marking a significant technological advancement.
This integration, viewed through the prism of our patented HYFTs,
not only simplifies complex information but opens a new dimension
of predictive analysis. It notably enhances the platform's ability
to delineate the structure, function, and potential applications of
large molecules, representing a meaningful step towards more
intuitive and insightful data analysis in the life sciences
sector.
"As we focus on advancing drug discovery and development
processes, we have commenced a limited release of our platform
through a well-structured phased rollout strategy extending over
the upcoming year. This approach is aimed at ensuring a smooth
transition into IPA's existing customer offerings while also
allowing us to collect valuable feedback. The feedback garnered
will be instrumental for the ongoing refinement and optimization of
the platform, ensuring it continues to meet the evolving needs of
our clientele," shares Dirk Van Hyfte, MD, PhD, Co-Founder and Head
of Innovation of BioStrand.
LENSai: The Next-Generation Advanced AI Platform
BioStrand has successfully rolled out a next-generation unified
knowledge graph-LLM framework for holistic life sciences research.
At the core of their LENSai platform is a comprehensive and
continuously expanding knowledge graph that maps a remarkable 25
billion relationships across 660 million data objects, linking
sequence, structure, function, and literature information from the
entire biosphere. Their first-in-class technology provides a
comprehensive understanding of the relationships between genes,
proteins, structures, and biological pathways, thereby opening
powerful new opportunities for drug discovery and development. The
platform leverages the latest advances in ontology-driven NLP and
AI-driven LLMs to connect and correlate syntax (multi-modal
sequential and structural data) and semantics (functions).
BioStrand’s unified approach to biomedical knowledge graphs, RAG
models, and LLMs combines the reasoning capabilities of LLMs, the
semantic proficiency of knowledge graphs, and the versatile
information retrieval capabilities of RAG to streamline the
integration, exploration, and analysis of biomedical data,
potentially unlocking a realm of uncharted possibilities.
About ImmunoPrecise Antibodies Ltd
ImmunoPrecise Antibodies Ltd. has several subsidiaries in North
America and Europe including entities such as Talem Therapeutics
LLC, BioStrand BV, ImmunoPrecise Antibodies (Canada) Ltd., and
ImmunoPrecise Antibodies (Europe) B.V. (collectively, the “IPA
Family”). The IPA Family is a biotherapeutic research and
technology group that leverages systems biology, multi-omics
modeling, and complex artificial intelligence systems to support
its proprietary technologies in bioplatform-based antibody
discovery. Services include highly specialized, full-continuum
therapeutic biologics discovery, development, and out-licensing to
support its business partners in their quest to discover and
develop novel biologics against the most challenging targets. For
further information, visit www.ipatherapeutics.com.
Forward Looking Information
This news release contains forward-looking statements within the
meaning of applicable United States securities laws and Canadian
securities laws. Forward-looking statements are often identified by
the use of words such as “potential,” “plans,” “expects” or “does
not expect,” “is expected,” “estimates,” “intends,” “anticipates”
or “does not anticipate,” or “believes,” or variations of such
words and phrases or state that certain actions, events or results
“may,” “could,” “would,” “might” or “will” be taken, occur or be
achieved. Forward-looking information contained in this news
release includes, but is not limited to, statements relating to the
expected outcome on the drug development process of the integration
of IPA’s LENSai in silico humanization platform with its HYFT
technology, and statements relating to IPA’s expected increased
revenue streams and financial growth. In respect of the
forward-looking information contained herein, IPA has provided such
statements and information in reliance on certain assumptions that
management believed to be reasonable at the time.
Forward-looking information involves known and unknown risks,
uncertainties and other factors which may cause the actual results,
performance or achievements stated herein to be materially
different from any future results, performance or achievements
expressed or implied by the forward-looking information. Actual
results could differ materially from those currently anticipated
due to a number of factors and risks, including, without
limitation, the risk that the integration of IPA’s LENSai platform
with its HYFT technology may not have the expected results,
Forward-looking information involves known and unknown risks,
uncertainties and other factors which may cause the actual results,
performance or achievements stated herein to be materially
different from any future results, performance or achievements
expressed or implied by the forward-looking information. Actual
results could differ materially from those currently anticipated
due to a number of factors and risks, including, without
limitation, the risk that the integration of IPA’s LENSai platform
with its HYFT technology may not have the expected results, actual
results could differ materially from those currently anticipated
due to a number of factors and risks, as discussed in the Company’s
Annual Information Form dated July 10, 2023 (which may be viewed on
the Company’s profile at www.sedar.com), and the Company’s Form
40-F, dated July 10, 2023 (which may be viewed on the Company’s
profile at www.sec.gov). Should one or more of these risks or
uncertainties materialize, or should assumptions underlying the
forward-looking statements prove incorrect, actual results,
performance, or achievements may vary materially from those
expressed or implied by the forward-looking statements contained in
this news release. Accordingly, readers should not place undue
reliance on forward-looking information contained in this news
release. The forward-looking statements contained in this news
release are made as of the date of this release and, accordingly,
are subject to change after such date. The Company does not assume
any obligation to update or revise any forward-looking statements,
whether written or oral, that may be made from time to time by us
or on our behalf, except as required by applicable law.
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version on businesswire.com: https://www.businesswire.com/news/home/20231025963840/en/
Investors: investors@ipatherapeutics.com
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