Yang Danlin, Singh Ajit, Wu Helen, Kroe-Barrett Rachel
Department of Immune Modulation and Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877, USA.
Department of Immune Modulation and Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877, USA; The Fu Foundation School of Engineering and Applied Science, Columbia University, New York, USA.
Anal Biochem. 2016 Sep 1;508:78-96. doi: 10.1016/j.ab.2016.06.024. Epub 2016 Jun 27.
The acquisition of reliable kinetic parameters for the characterization of biomolecular interactions is an important component of the drug discovery and development process. While several benchmark studies have explored the variability of kinetic rate constants obtained from multiple laboratories and biosensors, a direct comparison of these instruments' performance has not been undertaken, and systematic factors contributing to data variability from these systems have not been discussed. To address these questions, a panel of ten high-affinity monoclonal antibodies was simultaneously evaluated for their binding kinetics against the same antigen on four biosensor platforms: GE Healthcare's Biacore T100, Bio-Rad's ProteOn XPR36, ForteBio's Octet RED384, and Wasatch Microfluidics's IBIS MX96. We compared the strengths and weaknesses of these systems and found that despite certain inherent systematic limitations in instrumentation, the rank orders of both the association and dissociation rate constants were highly correlated between these instruments. Our results also revealed a trade-off between data reliability and sample throughput. Biacore T100, followed by ProteOn XPR36, exhibited excellent data quality and consistency, whereas Octet RED384 and IBIS MX96 demonstrated high flexibility and throughput with compromises in data accuracy and reproducibility. Our results support the need for a "fit-for-purpose" approach in instrument selection for biosensor studies.
获取可靠的动力学参数以表征生物分子相互作用是药物发现与开发过程的一个重要组成部分。虽然已有多项基准研究探讨了从多个实验室和生物传感器获得的动力学速率常数的变异性,但尚未对这些仪器的性能进行直接比较,也未讨论导致这些系统数据变异性的系统因素。为解决这些问题,我们在四个生物传感器平台上同时评估了一组十种高亲和力单克隆抗体针对同一抗原的结合动力学:通用电气医疗集团的Biacore T100、伯乐公司的ProteOn XPR36、福泰生物公司的Octet RED384以及瓦萨奇微流体公司的IBIS MX96。我们比较了这些系统的优缺点,发现尽管仪器存在某些固有的系统局限性,但这些仪器之间的结合和解离速率常数的排序高度相关。我们的结果还揭示了数据可靠性和样品通量之间的权衡。Biacore T100其次是ProteOn XPR36,表现出优异的数据质量和一致性,而Octet RED384和IBIS MX96则展示了高灵活性和通量,但在数据准确性和可重复性方面有所妥协。我们的结果支持在生物传感器研究的仪器选择中需要采用“适用”方法。