Investigation of peptide-polymer interactions in PLGA microspheres

我们目前对配方和原材料变量如何使用的理解存在科学空白 聚乳酸-羟基乙酸共聚微球的制备及其不同水平的研究 多肽-聚合物相互作用和多肽在体外和体外释放过程中的酰化作用 活着。批次之间的差异和不可预测的酰化水平可能会导致药代动力学的差异 寻求模拟长效释放(LAR)的通用长效释放(LAR)制剂的(PK)和生物等效性损失 产品。这种生物等效性的差异可能会导致安全性和有效性的差异。一个关键因素 导致母药丢失的原因是多肽和聚合物之间的相互作用定义不清，这 已被证明是酰化反应的前体。例如，阳离子之间的盐分形成 和酰化不稳定的奥曲肽，在Sandostatin LAR(SLAR)微球产品中发现，与电离的 研究表明，PLGA的羧酸端基团是发生酰化所必需的。我们假设 导致多肽-聚合物相互作用差异的关键的时间依赖因素和 类似组成的微球的酰化反应包括：(A)微球中的小气候pH影响 与阳离子肽结合所需的聚合物羧酸的电离；(B) 聚合物允许多肽渗透到聚合物相中，以及(C)聚合物的结构(STAR 与线性)和末端封顶，影响负责多肽的分子间力的强度和类型- 聚合物相互作用。将开发以下任务来测试我们的假设并结束 前述科学差距：1.开发评估多肽-聚合物相互作用和多肽的技术 与参考产物SLAR的酰化杂质；2.对SLAR的组成进行反向工程；3.创建 作为微胶囊化条件的SLAR的Q1/Q2配方，并确定产品 相对于SLAR的属性。4.创建具有几乎相同组成的SLAR的微球制剂 但具有不同的PLGA结构和相对分子质量，并确定产品属性；5.比较 所有制剂中的多肽-聚合物相互作用、酰化、侵蚀行为和释放动力学，以确定关键 处方和聚合物结构控制多肽的酰化和体外释放动力学的差异； 和6.通过评估PK的关键配方来验证任务1和任务5中观察到的体外差异 从一个新的活体笼子模型中恢复后肌肉注射和直接测量。我们会申请 我们小组在过去20年里开发了一系列新的实验方法来审问 在PLGA中启动奥曲肽酰化所必需的多肽-聚合物相互作用。我们将进一步结合 这一方法与大量严格的和新的体外测试方法来测试配方与 未来对仿制药的监管指导，并验证它们与体内尚不可预测的环境的相关性。

There is a scientific gap in our current understanding of how formulation and raw material variables used to manufacture poly(lactic-co-glycolic acid) (PLGA) microspheres encapsulating peptides lead to differing levels of peptide-polymer interactions and peptide acylation during encapsulation, storage, and release in vitro and in vivo. Batch-to-batch variation and unpredictable acylation levels could lead to differences in pharmacokinetics (PK) and loss of bioequivalence of generic long-acting release (LAR) formulations seeking to mimic LAR products. Such differences in bioequivalence may lead to differences in safety and efficacy. A key factor leading to the loss of parent drug is the poorly defined interaction between the peptide and the polymer, which has been shown to be a precursor to the acylation reaction. For example, salt formation between the cationic and acylation-labile octreotide, found in the Sandostatin LAR (SLAR) microsphere product, with the ionized carboxylic acid end-groups of PLGA has been shown to be necessary for acylation to occur. We hypothesize the key underlying time-dependent factors responsible for differences in peptide-polymer interactions and acylation for microspheres of similar compositions include: (a) microclimate pH in the microspheres affecting ionization of polymer carboxylic acids necessary to bind to a cationic peptide; (b) the extent to which the polymer allows penetration of the peptide into the polymer phase, and (c) the architecture of the polymer (star vs. linear) and end-capping that affect the strength and type of intermolecular forces responsible for peptide- polymer interactions. The following tasks will be developed to test our hypothesis and close the aforementioned scientific gap: 1. Develop techniques for assessing peptide-polymer interactions and peptide acylation impurities with the reference product, SLAR; 2. Reverse engineer the composition of SLAR; 3. Create Q1/Q2 formulations for the SLAR as a function of microencapsulation conditions, and determine product attributes relative to SLAR. 4. Create microsphere formulations with virtually the same composition of SLAR but with different PLGA architecture and molecular weight, and determine product attributes; 5. Compare peptide-polymer interactions, acylation, erosion behavior and release kinetics in all formulations to identify key formulation and polymer architecture controlling differences in peptide acylation and release kinetics in vitro; and 6. Verify in vitro differences observed in Task 1 and 5 by assessing key formulations for PK after intramuscular injection and direct measurements after recovery from a novel in vivo cage model. We will apply a wide range of novel experimental approaches developed by our group over the last 20 years to interrogate the peptide-polymer interactions necessary to initiate octreotide acylation in PLGAs. We will further combine this approach with a large number of rigorous and new in vitro assays to test formulations with relevance to future regulatory guidance to generics and verify their relevance to the not yet predictable in vivo environment.