Dyno Therapeutics Announces Publication in Nature Biotechnology Demonstrating Use of Artificial Intelligence to Generate Unprecedented Diversity of AAV Capsids and Broaden Reach of Gene Therapies

Dyno Therapeutics在Nature Biotechnology上发表论文,展示了利用人工智能产生前所未有的AAV衣壳多样性和拓宽基因治疗的范围

2021-02-12 05:00:13 BioSpace


Approach rapidly generates the functional diversity needed to evade neutralization by the immune system, allowing more patients to benefit from gene therapies CAMBRIDGE, Mass.--(BUSINESS WIRE)-- Dyno Therapeutics, a biotech company applying artificial intelligence (AI) to gene therapy, today announced a publication in Nature Biotechnology that demonstrates the use of artificial intelligence to generate an unprecedented diversity of adeno-associated virus (AAV) capsids towards identifying functional variants capable of evading the immune system, a factor that is critical to enabling all patients to benefit from gene therapies. The research was conducted in collaboration with Google Research, Harvard’s Wyss Institute for Biologically Inspired Engineering and the Harvard Medical School laboratory of George M. Church, Ph.D., a Dyno scientific co-founder. The publication is entitled “Deep diversification of an AAV capsid protein by machine learning.” It is estimated that up to 50-70% of the human population have pre-existing immunity to natural forms of the AAV vectors currently being using to deliver gene therapies. This immunity renders a large portion of patients ineligible to receive gene therapies which rely upon these capsids as the vector for delivery. Overcoming the challenge of pre-existing immunity to AAV vectors is therefore a major goal for the gene therapy field. “The approach described in the Nature Biotechnology paper opens a radically new frontier in capsid design. Our study clearly demonstrates the potential of machine learning to guide the design of diverse and functional sequence variants, far beyond what exists in nature,” said Eric Kelsic, Ph.D., Dyno’s CEO and co-founder. “We continue to expand and apply the power of artificial intelligence to design vectors that can not only overcome the problem of pre-existing immunity but also address the need for more effective and selective tissue targeting. At Dyno, we are making rapid progress to design novel AAV vectors that overcome the limitations of current vectors, improving treatments for more patients and expanding the number of diseases treatable with gene therapies.” The Nature Biotechnology paper describes the rapid production of a large library of distinct AAV capsid variants designed by machine learning models. Nearly 60% of the variants produced were determined to be viable, a significant increase over the typical yield of <1% using random mutagenesis, a standard method of generating diversity. “The more we change the AAV vector from how it looks naturally, the more likely we are to overcome the problem of pre-existing immunity,” added Sam Sinai, Ph.D., Dyno co-founder and Machine Learning Team Lead. “Key to solving this problem, however, is also ensuring that capsid variants remain viable for packaging the DNA payload. With conventional methods, this diversification is time- and resource-intensive, and results in a very low yield of viable capsids. In contrast, our approach allows us to rapidly unlock the full potential diversity of AAV capsids to develop improved gene therapies for a much larger number of patients. This research builds upon previous work published in Science in which a complete landscape of single mutations around the AAV2 capsid was generated followed by evaluation of the functional properties important for in vivo delivery. In parallel with these works, Dyno has established collaborations with leading gene therapy companies Novartis, Sarepta Therapeutics, Roche and Spark Therapeutics to develop next-generation AAV gene therapy vectors with a goal of expanding the utility of gene therapies for ophthalmic, muscle, central nervous system (CNS) and liver diseases. About CapsidMap™ for Designing Optimized AAV Gene Therapies By designing capsids that confer improved functional properties to Adeno-Associated Virus (AAV) vectors, Dyno’s proprietary CapsidMap™ platform overcomes the limitations of today’s gene therapies on the market and in development. Today’s treatments are primarily confined to a small number of naturally occurring AAV vectors that are limited by delivery efficiency, immunity, payload size, and manufacturing challenges. CapsidMap uses artificial intelligence (AI) technology to engineer capsids, the cell-targeting protein shell of viral vectors. The CapsidMap platform applies leading-edge DNA library synthesis and next generation DNA sequencing to measure in vivo gene delivery properties in high throughput. At the core of CapsidMap are advanced search algorithms leveraging machine learning and Dyno’s massive quantities of experimental data, that together build a comprehensive map of sequence space and thereby accelerate the design of novel capsids optimized for gene therapy. About Dyno Therapeutics Dyno Therapeutics is a pioneer in applying artificial intelligence (AI) and quantitative high-throughput in vivo experiments to gene therapy. The company’s proprietary CapsidMap™ platform rapidly discovers and systematically optimizes Adeno-Associated Virus (AAV) capsid vectors that significantly outperform current approaches for in vivo gene delivery, thereby expanding the range of diseases treatable with gene therapies. Dyno was founded in 2018 by experienced biotech entrepreneurs and leading scientists in the fields of gene therapy and machine learning. The company is located in Cambridge, Massachusetts. Visit www.dynotx.com for additional information. View source version on businesswire.com: https://www.businesswire.com/news/home/20210211005156/en/ Media contact: Kathryn Morris The Yates Network kathryn@theyatesnetwork.com 914-204-6412 Source: Dyno Therapeutics View this news release online at: http://www.businesswire.com/news/home/20210211005156/en
该方法能迅速产生避免免疫系统中和所需的功能多样性,使更多的患者从基因治疗中获益 将人工智能(AI)应用于基因治疗的生物技术公司Dyno Therapeutics今天在《自然·生物技术》上发表了一篇文章,展示了利用人工智能产生前所未有的腺相关病毒(AAV)衣壳的多样性,以识别能够逃避免疫系统的功能变异体,这是使所有患者受益于基因治疗的关键因素。这项研究是与谷歌研究公司、哈佛大学Wyss生物工程研究所以及Dyno scientific联合创始人George M.Church博士所在的哈佛医学院实验室合作进行的。该出版物题为《机器学习对AAV衣壳蛋白的深度多样化》。 据估计,高达50-70%的人类对目前用于传递基因疗法的AAV载体的天然形式具有预先存在的免疫力。这种免疫力使得很大一部分患者没有资格接受依赖于这些衣壳作为载体的基因治疗。因此,克服对AAV载体预先存在的免疫力的挑战是基因治疗领域的一个主要目标。 “《自然》生物技术论文中描述的方法打开了衣壳设计的一个全新的前沿。我们的研究清楚地展示了机器学习在指导设计多样化和功能性序列变体方面的潜力,远远超出了自然界存在的情况,“Dyno公司首席执行官兼联合创始人Eric Kelsic博士说。“我们继续扩大和应用人工智能的力量来设计载体,这些载体不仅能够克服预先存在的免疫问题,而且能够满足对更有效和更有选择性的组织靶向的需求。在Dyno,我们在设计新型AAV载体方面取得了快速进展,该载体克服了目前载体的局限性,改善了更多患者的治疗,并扩大了可通过基因疗法治疗的疾病的数量。“ Nature Biotechnology的论文描述了一个由机器学习模型设计的不同AAV衣壳变体的大型库的快速生产。近60%的变异体被确定为可行的,比随机诱变(一种产生多样性的标准方法)的典型产量<1%有显著提高。 Dyno联合创始人、机器学习团队负责人Sam Sinai博士补充说:“我们越是改变AAV载体的自然形态,我们就越有可能克服预先存在的免疫力问题。”“然而,解决这一问题的关键还在于确保衣壳变体在包装DNA有效载荷时仍然可行。用常规方法,这种多样化是时间和资源密集的,并导致活衣壳的产量非常低。相反,我们的方法允许我们迅速释放AAV衣壳的全部潜在多样性,为更多的患者开发改进的基因疗法。 这项研究建立在先前发表在《科学》杂志上的工作基础上,在该工作中,产生了AAV2衣壳周围单个突变的完整景观,随后对体内传递重要的功能特性进行了评估。在开展这些工作的同时,Dyno还与领先的基因治疗公司诺华、萨瑞普塔治疗公司、罗氏和星火治疗公司建立了合作关系,以开发下一代AAV基因治疗载体,目标是扩大基因治疗在眼科、肌肉、中枢神经系统(CNS)和肝脏疾病中的应用。 CapsidMap™在AAV基因治疗优化设计中的应用 通过设计衣壳,赋予腺相关病毒(AAV)载体更好的功能特性,Dyno的专有CapsidMap™平台克服了当今市场上和开发中的基因疗法的局限性。目前的治疗主要局限于少数天然存在的AAV载体,这些载体受到递送效率、免疫力、有效载荷大小和制造挑战的限制。CapsidMap利用人工智能(AI)技术设计病毒载体的细胞靶向蛋白外壳衣壳。CapsidMap平台应用前沿的DNA文库合成和下一代DNA测序技术,高通量地测量体内基因传递特性。CapsidMap的核心是利用机器学习和Dyno的大量实验数据的先进搜索算法,它们共同构建了序列空间的综合图谱,从而加速了为基因治疗优化的新型衣壳的设计。 关于Dyno Therapeutics Dyno Therapeutics是将人工智能(AI)和定量高通量体内实验应用于基因治疗的先驱。该公司专有的CapsidMap™平台快速发现并系统优化腺相关病毒(AAV)衣壳载体,其显著优于当前体内基因递送方法,从而扩大了可用基因疗法治疗的疾病范围。Dyno于2018年由经验丰富的生物技术企业家和基因治疗和机器学习领域的领先科学家创立。该公司位于马萨诸塞州的剑桥。欲了解更多信息,请访问www.dynotx.com。 在businesswire.com上查看源版本:https://www.businesswire.com/news/home/20210211005156/en/ 媒体联系人: 凯瑟琳·莫里斯 耶茨网络 @theyatesnetwork.com 914-204-6412 资料来源:Dyno Therapeutics 请在以下网址联机查看此新闻稿: http://www.businesswire.com/news/home/20210211005156/en