Jani Darshana, Allinson John, Berisha Flora, Cowan Kyra J, Devanarayan Viswanath, Gleason Carol, Jeromin Andreas, Keller Steve, Khan Masood U, Nowatzke Bill, Rhyne Paul, Stephen Laurie
Pfizer Inc., One Burtt Road, Andover, Massachusetts, 01810, USA.
LGC Ltd, Newmarket Road, Fordham, Cambridgeshire, CB7 5WW, UK.
AAPS J. 2016 Jan;18(1):1-14. doi: 10.1208/s12248-015-9820-y. Epub 2015 Sep 16.
Multiplex ligand binding assays (LBAs) are increasingly being used to support many stages of drug development. The complexity of multiplex assays creates many unique challenges in comparison to single-plexed assays leading to various adjustments for validation and potentially during sample analysis to accommodate all of the analytes being measured. This often requires a compromise in decision making with respect to choosing final assay conditions and acceptance criteria of some key assay parameters, depending on the intended use of the assay. The critical parameters that are impacted due to the added challenges associated with multiplexing include the minimum required dilution (MRD), quality control samples that span the range of all analytes being measured, quantitative ranges which can be compromised for certain targets, achieving parallelism for all analytes of interest, cross-talk across assays, freeze-thaw stability across analytes, among many others. Thus, these challenges also increase the complexity of validating the performance of the assay for its intended use. This paper describes the challenges encountered with multiplex LBAs, discusses the underlying causes, and provides solutions to help overcome these challenges. Finally, we provide recommendations on how to perform a fit-for-purpose-based validation, emphasizing issues that are unique to multiplex kit assays.
多重配体结合分析(LBAs)越来越多地用于支持药物开发的多个阶段。与单重分析相比,多重分析的复杂性带来了许多独特的挑战,这导致在验证过程中以及可能在样品分析过程中需要进行各种调整,以适应所有被测量的分析物。这通常需要在选择最终分析条件和某些关键分析参数的验收标准方面进行权衡,具体取决于分析的预期用途。由于多重分析带来的额外挑战而受到影响的关键参数包括最低所需稀释度(MRD)、涵盖所有被测量分析物范围的质量控制样品、可能因某些目标而受到影响的定量范围、实现所有感兴趣分析物的平行性、分析之间的串扰、分析物之间的冻融稳定性等等。因此,这些挑战也增加了验证分析用于其预期用途时性能的复杂性。本文描述了多重LBA遇到的挑战,讨论了潜在原因,并提供了有助于克服这些挑战的解决方案。最后,我们提供了关于如何进行基于目的适用性验证的建议,强调了多重试剂盒分析特有的问题。