Porton Advanced recently announced a strategic partnership with BioMap to tap into advanced technology's potential in the field of gene therapy. In this collaboration, BioMap will leverage Porton Advanced's unique Adeno-Associated Virus (AAV) vector technology and research data to create models that enhance AAV assembly efficiency and distribution. The primary goal is to use large-scale life science models to expedite the design of AAV vectors and further integrate AI models into gene therapy.
Over the past decade, AAV vectors have played a pivotal role in advancing biotechnology, particularly in the realm of gene therapies. While substantial progress has been made in AAV vector construction and assembly research, the creation of tissue-specific AAV coat proteins, a critical step for unlocking their therapeutic potential, has remained a persistent challenge. The limitations of natural serotype AAVs in meeting clinical demands have spurred scientists to explore innovative AAV development through AI technology, with a particular focus on AI models.
BioMap, conveyed optimism about the future of gene therapies and the honor of collaborating with Porton Advanced to establish an artificially designed gene delivery system. BioMap's extensive pre-trained foundation model, xTrimo, has the capacity to rapidly generate high-performing task models across diverse fields using partners' varied data. The inclusion of Porton Advanced's top-tier AAV vector technology platform and research data is expected to significantly enhance the performance of their models, enabling the innovative design of high-performing AAV vectors.
Porton Advanced, expressed excitement about partnering with BioMap to provide improved solutions for gene therapy research through AI models. While Porton Advanced boasts a well-established CDMO platform, they have also developed proprietary technical platforms, including a novel library of AAV capsid variants called AAVantage®, as well as other gene-editing tools. By leveraging BioMap's cutting-edge AI and biological technology, the two companies plan to construct large-scale life science models and accelerate the integration of scalable experimental platforms and intelligent big data analysis tools to address a broad spectrum of needs, from research and development to production. The collaborative efforts will also facilitate the acceleration of drug research and development, maximizing its industrialization potential.
With the growing volume of data in the gene delivery vector field and the emergence of advanced protein language models, it is widely anticipated that AI will play a pivotal role in gene delivery vector research, driving innovation and significant advancements in human health in this new era.
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