Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-University, Butenandtstrasse 5-13, Munich D-81377, Germany.
Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-University, Butenandtstrasse 5-13, Munich D-81377, Germany.
Eur J Pharm Biopharm. 2019 Apr;137:131-139. doi: 10.1016/j.ejpb.2019.02.018. Epub 2019 Feb 25.
The formulation of novel therapeutic proteins is a challenging task which aims at finding formulation conditions that will minimize protein degradation during long-term storage. One particularly important and difficult-to-predict protein degradation pathway is the so-called non-native aggregation. The qualitative and quantitative prediction of the latter has been a subject of extensive research over the past two decades. An increasing body of evidence shows that the widely-used short-term biophysical techniques cannot accurately rank formulation conditions in order of their effect on the aggregation during long-term storage of some therapeutic proteins, e.g. monoclonal antibodies. Here we suggest a novel approach for the selection of formulation conditions that will suppress the formation of protein aggregates during long-term storage. We postulate that conditions (i.e. pH, buffer type, ionic strength) that reduce the isothermal aggregation of various denaturant-induced partially folded protein species will be conditions that impede protein aggregation during long-term storage. To test our hypothesis, we developed an isothermal microdialysis-based unfolding/refolding assay, named ReFOLD, which we use to induce moderate aggregation of partially folded proteins. Next, we assessed the relative monomer yield after isothermal unfolding/refolding of two monoclonal antibodies, each formulated in 12 different conditions. Using the proposed approach, we were able to accurately rank the formulations in order of their effect on the amount of protein aggregates detected after storage for 12 months at 4 °C and 25 °C, while widely-used stability-indicating parameters like protein melting and aggregation onset temperatures failed to provide accurate predictive formulation rankings.
新型治疗蛋白的配方是一项具有挑战性的任务，旨在找到能够在长期储存过程中最小化蛋白降解的配方条件。一种特别重要且难以预测的蛋白降解途径是所谓的非天然聚集。在过去的二十年中，对后者的定性和定量预测一直是广泛研究的主题。越来越多的证据表明，广泛使用的短期生物物理技术无法准确地根据其在一些治疗性蛋白的长期储存过程中对聚集的影响对配方条件进行排序，例如单克隆抗体。在这里，我们提出了一种选择配方条件的新方法，该方法可抑制治疗蛋白在长期储存过程中形成蛋白聚集体。我们假设能够降低各种变性剂诱导的部分折叠蛋白物种的等温聚集的条件（例如 pH 值、缓冲液类型、离子强度）将是阻碍蛋白在长期储存过程中聚集的条件。为了验证我们的假设，我们开发了一种基于等温微透析的展开/重折叠测定法，称为 ReFOLD，我们使用该方法诱导部分折叠蛋白适度聚集。接下来，我们评估了两种单克隆抗体在 12 种不同条件下配方后的等温展开/重折叠后的相对单体产率。使用所提出的方法，我们能够准确地根据储存 12 个月后在 4°C 和 25°C 下检测到的蛋白聚集体的量对配方进行排序，而广泛使用的稳定性指示参数，如蛋白熔融和聚集起始温度，无法提供准确的预测性配方排序。
