ImmunoPrecise Antibodies (NASDAQ:IPA) Subsidiary BioStrand Introduces Breakthrough AI Model In Life Sciences, Harnessing LLM Stacking And HYFT Technology
ImmunoPrecise Antibodies (NASDAQ:IPA) Subsidiary BioStrand Introduces Breakthrough AI Model In Life Sciences, Harnessing LLM Stacking And HYFT Technology
VICTORIA, BC / ACCESSWIRE / March 8, 2024 / Anyone familiar with the intricacies of life science knows how truly complicated DNA is; without a full understanding of the language of DNA, scientists are often at a standstill when it comes to advanced medicine. That's why the work of companies like ImmunoPrecise Antibodies (NASDAQ:IPA) ("IPA") is important to identifying, preventing and treating diseases.
不列颠哥伦比亚省维多利亚州/ACCESSWIRE /2024年3月8日/任何熟悉生命科学复杂性的人都知道DNA的真正复杂性；如果没有对DNA语言的充分理解，科学家在先进医学方面往往处于停滞状态。这就是为什么像ImmunoPrecise Antibodies（纳斯达克股票代码：IPA）（“IPA”）这样的公司的工作对于识别、预防和治疗疾病很重要的原因。
With over a decade of experience, IPA offers a diverse range of specialized services - including antibody discovery and development - utilizing various cutting-edge techniques and models. The company has also just announced the development of a Foundation AI Model. The model integrates the strengths of Large Language Models (LLMs) with IPA's subsidiary BioStrand's patented HYFT Technology.
凭借十多年的经验，IPA利用各种尖端技术和模型提供各种专业服务，包括抗体发现和开发。该公司还刚刚宣布开发基金会人工智能模型。该模型将大型语言模型（LLM）的优势与IPA的子公司BioStrand的专利HYFT相结合 科技。
BioStrand's Foundation AI Model uses fingerprint patterns found throughout the biosphere to connect different areas of knowledge. This technology forms the backbone of BioStrand's platform, which encompasses a vast knowledge graph mapping billions of relationships across millions of data objects. By linking genetic, structural and functional data with scientific literature, BioStrand provides a comprehensive understanding of the connections between genes, proteins and biological pathways.
BioStrand 的基础人工智能模型使用在整个生物圈中发现的指纹图案来连接不同的知识领域。这项技术构成了BioStrand平台的支柱，该平台包含一个庞大的知识图谱，描绘了数百万个数据对象的数十亿个关系。通过将遗传、结构和功能数据与科学文献联系起来，BioStrand 提供了对基因、蛋白质和生物通路之间联系的全面理解。
The integration of HYFTs with stacked LLMs allows BioStrand's AI model to decipher the language of proteins, providing valuable insights for antibody drug development and precision medicine. LLMs, originally designed for understanding natural language, can also be applied to understand the language of proteins. This enables tasks such as protein structure prediction, antibody optimization and protein mutagenesis.
HYFT与堆叠式LLM的集成使BioStrand的人工智能模型能够破译蛋白质语言，为抗体药物开发和精准医疗提供宝贵的见解。LLM 最初是为理解自然语言而设计的，也可以应用于理解蛋白质语言。这使得蛋白质结构预测、抗体优化和蛋白质突变等任务成为可能。
To effectively analyze the language of proteins, HYFTs are used to identify meaningful units or "words" within protein sequences. This computational capability makes it possible to map and analyze these functional units accurately. These "word boundaries" represent a breakthrough in understanding protein structure and function within the language of proteins. The concept addresses a significant gap in knowledge for researchers and drug developers. By accurately identifying and manipulating functional units within proteins, this innovative approach opens doors to new possibilities in drug discovery, protein-based treatments and synthetic biology.
为了有效分析蛋白质语言，HYFT用于识别蛋白质序列中的有意义的单位或 “单词”。这种计算能力使准确地绘制和分析这些功能单元成为可能。这些 “词语边界” 代表了在理解蛋白质语言中蛋白质结构和功能方面取得的突破。该概念解决了研究人员和药物开发人员在知识方面的巨大差距。通过准确识别和操作蛋白质中的功能单元，这种创新方法为药物发现、基于蛋白质的治疗和合成生物学的新可能性打开了大门。
LLM Stacking
LLM 堆叠
The unique approach called "LLM stacking" that the Advanced Foundation AI employs combines different LLMs intelligently. HYFTs are linked to specific features found in various LLMs, akin to understanding the meaning of a word based on its context. In the life sciences context, these features can include identifying amino acid residues critical for protein binding or detecting sequence variations associated with disease susceptibility. The combination of HYFTs and LLM stacking allows BioStrand to differentiate between binding and non-binding antibodies, even when they share similar HYFT patterns. The sequence diversity harnessed by HYFTs was discovered during the analysis of sequencing data sourced from Talem Therapeutics, an IPA pipeline subsidiary.
高级基础人工智能采用的名为 “LLM 堆叠” 的独特方法智能地结合了不同的 LLM。HYFT 与各种 LLM 中的特定特征相关联，类似于根据上下文理解单词的含义。在生命科学背景下，这些功能可能包括识别对蛋白质结合至关重要的氨基酸残基或检测与疾病易感性相关的序列变异。HYFT和LLM堆叠的组合使BioStrand能够区分结合抗体和非结合抗体，即使它们具有相似的HYFT模式。HYFT利用的序列多样性是在分析来自IPA管道子公司Talem Therapeutics的测序数据时发现的。
"The development of our Foundation AI Model, powered by our unique 'LLM stacking' approach and patented HYFT technology, marks a significant milestone in the field of biotechnological research," stated Dirk Van Hyfte M.D., Ph.D., Co-Founder and Head of Innovation of BioStrand. "This innovation not only expands the boundaries of current biotech research, but also establishes a new standard for the application of AI in solving complex biological challenges."
BioStrand联合创始人兼创新负责人Dirk Van Hyfte博士表示：“我们的基础人工智能模型的开发由我们独特的'LLM堆叠'方法和HYFT专利技术提供支持，标志着生物技术研究领域的一个重要里程碑。”“这项创新不仅扩大了当前生物技术研究的边界，而且为应用人工智能解决复杂的生物挑战建立了新的标准。”
"As the global community recognizes the transformative potential of artificial intelligence in the life sciences," Dr. Hyfte continued, "I am confident that BioStrand's Foundation AI Model will stand at the forefront of innovation and the future of AI-driven solutions in biology and drug discovery."
海夫特博士继续说：“随着全球社会认识到人工智能在生命科学领域的变革潜力，我相信BioStrand的基础人工智能模型将站在生物学和药物发现领域创新和未来人工智能驱动解决方案的最前沿。”
Featured photo by Warren umoh on Unsplash.
精选照片来自 沃伦哈哈 上 Unsplas。
Contact:
联系人：
investors@ipatherapeutics.com
investors@ipatherapeutics.com
SOURCE: ImmunoPrecise Antibodies Ltd.
来源：ImmunoPrecise 抗体有限公司
译文内容由第三方软件翻译。