Predictive Nature of High-Throughput Assays in ADC Formulation Screening

吞吐量 高通量筛选 理论(学习稳定性) 可预测性 计算机科学 预测值 生物系统 化学 色谱法 数学 机器学习 统计 生物 医学 生物化学 电信 无线 内科学
作者
Brittney J. Mills,Malika P Godamudunage,Siyuan Ren,Malabika Laha
出处
期刊:Journal of Pharmaceutical Sciences [Elsevier]
卷期号:112 (7): 1821-1831
标识
DOI:10.1016/j.xphs.2023.03.021
摘要

Utilization of high-throughput biophysical screening techniques during early screening studies is warranted due to the limited amount of material and large number of samples. But the predictability of the data to longer-term storage stability is critical as the high-throughput methods assist in defining the design space for the longer-term studies. In this study, the biophysical properties of two ADCs in 16 formulation conditions were evaluated using high-throughput techniques. Conformational stability and colloidal stability were evaluated by determining Tm values, kD, B22, and Tagg. In addition, the samples were placed on stability and the extent of aggregate formation over the 8-week interval was determined. The rank order of the 16 different formulations in the high-throughput assays was compared to the rank order observed during the stability studies to assess the predictive capabilities of the screening methods. It was demonstrated that similar rank orders can be expected between high-throughput physical stability indicating assays such as Tagg and B22 and traditional aggregation by SEC data, whereas conformational stability read-outs (Tm) are less predictive. In addition, the high-throughput assays appropriately identified the poor performing formulation conditions, which is ultimately what is desired of screening assays.
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