Nanite, Inc., Boston, Massachusetts 02109, USA.
Chem Commun (Camb). 2023 Nov 30;59(96):14197-14209. doi: 10.1039/d3cc04705a.
Materials informatics (MI) has immense potential to accelerate the pace of innovation and new product development in biotechnology. Close collaborations between skilled physical and life scientists with data scientists are being established in pursuit of leveraging MI tools in automation and artificial intelligence (AI) to predict material properties and . However, the scarcity of large, standardized, and labeled materials data for connecting structure-function relationships represents one of the largest hurdles to overcome. In this Highlight, focus is brought to emerging developments in polymer-based therapeutic delivery platforms, where teams generate large experimental datasets around specific therapeutics and successfully establish a design-to-deployment cycle of specialized nanocarriers. Three select collaborations demonstrate how custom-built polymers protect and deliver small molecules, nucleic acids, and proteins, representing ideal use-cases for machine learning to understand how molecular-level interactions impact drug stabilization and release. We conclude with our perspectives on how MI innovations in automation efficiencies and digitalization of data-coupled with fundamental insight and creativity from the polymer science community-can accelerate translation of more gene therapies into lifesaving medicines.
材料信息学（MI）在加速生物技术的创新和新产品开发方面具有巨大的潜力。熟练的物理和生命科学家与数据科学家之间正在建立密切的合作关系，以利用 MI 工具在自动化和人工智能（AI）中进行材料特性预测和 。然而，连接结构-功能关系的大型、标准化和标记的材料数据的稀缺性是需要克服的最大障碍之一。在这篇重点介绍中，重点介绍了聚合物基治疗性递药平台的新兴发展，在这些平台中，团队围绕特定治疗剂生成大型实验数据集，并成功建立了专用纳米载体的设计-部署循环。三个精选的合作案例展示了定制聚合物如何保护和递小分子、核酸和蛋白质，这些案例代表了机器学习理解分子水平相互作用如何影响药物稳定性和释放的理想用例。最后，我们提出了我们的观点，即自动化效率方面的 MI 创新和数据的数字化，再加上聚合物科学界的基本洞察力和创造力，将如何加速更多基因疗法转化为拯救生命的药物。
