Genentech, 1 DNA Way, South San Francisco, CA 94080, United States.
DigiM Solution LLC, 67 South Bedford Street, Suite 400 West, Burlington, MA 01803, United States.
J Pharm Sci. 2021 Oct;110(10):3418-3430. doi: 10.1016/j.xphs.2021.05.016. Epub 2021 Jun 2.
Long-acting implants are typically formulated using carrier(s) with specific physical and chemical properties, along with the active pharmaceutical ingredient (API), to achieve the desired daily exposure for the target duration of action. In characterizing such formulations, real-time in-vitro and in-vivo experiments that are typically used to characterize implants are lengthy, costly, and labor intensive as these implants are designed to be long acting. A novel characterization technique, combining high resolution three-dimensional X-Ray microscopy imaging, image-based quantification, and transport simulation, has been employed to provide a mechanistic understanding of formulation and process impact on the microstructures and performance of a polymer-based implant. Artificial intelligence-based image segmentation and image data analytics were used to convert morphological features visualized at high resolution into numerical microstructure models. These digital models were then used to calculate key physical parameters governing drug transport in a polymer matrix, including API uniformity, API domain size, and permeability. This powerful new tool has the potential to advance the mechanistic understanding of the interplay between drug-microstructure and performance and accelerate the therapeutic development long-acting implants.
长效植入物通常使用具有特定物理和化学性质的载体与活性药物成分 (API) 一起配制,以达到目标作用持续时间所需的每日暴露量。在对这些制剂进行表征时,通常用于表征植入物的实时体外和体内实验由于这些植入物的设计目的是长效的,因此冗长、昂贵且劳动强度大。一种新的表征技术,结合高分辨率三维 X 射线显微镜成像、基于图像的定量分析和传输模拟,已被用于提供对制剂和工艺对聚合物植入物的微观结构和性能的影响的机械理解。基于人工智能的图像分割和图像数据分析被用于将高分辨率下可视化的形态特征转换为数值微观结构模型。然后,使用这些数字模型来计算控制聚合物基质中药物传输的关键物理参数,包括 API 均匀性、API 域大小和渗透性。这个强大的新工具有可能促进对药物-微观结构和性能之间相互作用的机械理解,并加速长效植入物的治疗开发。