NIHR Respiratory BRC, Department of Respiratory Sciences, University of Leicester, Leicester, UK.
JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
MAbs. 2024 Jan-Dec;16(1):2323706. doi: 10.1080/19420862.2024.2323706. Epub 2024 Mar 6.
Antibodies are one of the most important reagents used in biomedical and fundamental research, used to identify, and quantify proteins, contribute to knowledge of disease mechanisms, and validate drug targets. Yet many antibodies used in research do not recognize their intended target, or recognize additional molecules, compromising the integrity of research findings and leading to waste of resources, lack of reproducibility, failure of research projects, and delays in drug development. Researchers frequently use antibodies without confirming that they perform as intended in their application of interest. Here we argue that the determinants of end-user antibody choice and use are critical, and under-addressed, behavioral drivers of this problem. This interacts with the batch-to-batch variability of these biological reagents, and the paucity of available characterization data for most antibodies, making it more difficult for researchers to choose high quality reagents and perform necessary validation experiments. The open-science company YCharOS works with major antibody manufacturers and knockout cell line producers to characterize antibodies, identifying high-performing renewable antibodies for many targets in neuroscience. This shows the progress that can be made by stakeholders working together. However, their work so far applies to only a tiny fraction of available antibodies. Where characterization data exists, end-users need help to find and use it appropriately. While progress has been made in the context of technical solutions and antibody characterization, we argue that initiatives to make best practice behaviors by researchers more feasible, easy, and rewarding are needed. Global cooperation and coordination between multiple partners and stakeholders will be crucial to address the technical, policy, behavioral, and open data sharing challenges. We offer potential solutions by describing our Only Good Antibodies initiative, a community of researchers and partner organizations working toward the necessary change. We conclude with an open invitation for stakeholders, including researchers, to join our cause.
抗体是生物医学和基础研究中最重要的试剂之一,用于识别和定量蛋白质,有助于了解疾病机制,并验证药物靶点。然而,许多用于研究的抗体不能识别其预期的靶标,或识别额外的分子,从而影响研究结果的完整性,并导致资源浪费、缺乏可重复性、研究项目失败以及药物开发延迟。研究人员经常在没有确认抗体在其感兴趣的应用中是否按预期发挥作用的情况下使用抗体。在这里,我们认为,最终用户选择和使用抗体的决定因素是导致这一问题的关键而又未被充分重视的行为驱动因素。这与这些生物试剂的批次间变异性以及大多数抗体缺乏可用的特征描述数据相互作用,使得研究人员更难以选择高质量的试剂并进行必要的验证实验。开放科学公司 YCharOS 与主要的抗体制造商和基因敲除细胞系生产商合作,对抗体进行特征描述,为神经科学中的许多靶标确定了高性能的可再生抗体。这表明了利益相关者共同努力可以取得的进展。然而,他们迄今为止的工作仅适用于可用抗体的一小部分。在存在特征描述数据的地方,最终用户需要帮助才能找到并适当地使用它。虽然在技术解决方案和抗体特征描述方面已经取得了进展,但我们认为,需要采取措施使研究人员更可行、更容易、更有回报地采用最佳实践行为。全球合作和多方合作伙伴及利益相关者之间的协调对于解决技术、政策、行为和开放数据共享方面的挑战至关重要。我们通过描述我们的“Only Good Antibodies”倡议来提供潜在的解决方案,这是一个由研究人员和合作组织组成的社区,致力于实现必要的变革。最后,我们诚邀利益相关者,包括研究人员,加入我们的事业。