提高使用抗体的研究的完整性和可重复性:技术、数据共享、行为和政策方面的挑战。

IF 5.6 2区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
mAbs Pub Date : 2024-01-01 Epub Date: 2024-03-06 DOI:10.1080/19420862.2024.2323706
M Biddle, P Stylianou, M Rekas, A Wright, J Sousa, D Ruddy, M I Stefana, K Kmiecik, A Bandrowski, R A Kahn, C Laflamme, E M Krockow, H S Virk
{"title":"提高使用抗体的研究的完整性和可重复性:技术、数据共享、行为和政策方面的挑战。","authors":"M Biddle, P Stylianou, M Rekas, A Wright, J Sousa, D Ruddy, M I Stefana, K Kmiecik, A Bandrowski, R A Kahn, C Laflamme, E M Krockow, H S Virk","doi":"10.1080/19420862.2024.2323706","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"16 1","pages":"2323706"},"PeriodicalIF":5.6000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936606/pdf/","citationCount":"0","resultStr":"{\"title\":\"Improving the integrity and reproducibility of research that uses antibodies: a technical, data sharing, behavioral and policy challenge.\",\"authors\":\"M Biddle, P Stylianou, M Rekas, A Wright, J Sousa, D Ruddy, M I Stefana, K Kmiecik, A Bandrowski, R A Kahn, C Laflamme, E M Krockow, H S Virk\",\"doi\":\"10.1080/19420862.2024.2323706\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":18206,\"journal\":{\"name\":\"mAbs\",\"volume\":\"16 1\",\"pages\":\"2323706\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936606/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"mAbs\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/19420862.2024.2323706\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"mAbs","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/19420862.2024.2323706","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

摘要

抗体是生物医学和基础研究中使用的最重要试剂之一,用于鉴定和量化蛋白质,有助于了解疾病机制和验证药物靶点。然而,研究中使用的许多抗体并不能识别其预期目标,或者不能识别其他分子,从而损害了研究结果的完整性,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。研究人员经常使用抗体,却不确认它们在相关应用中是否发挥了预期作用。在此,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行为因素,但这一因素尚未得到充分解决。这与这些生物试剂的批次与批次之间的可变性以及大多数抗体可用表征数据的匮乏相互作用,使得研究人员更难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与主要抗体生产商和基因敲除细胞系生产商合作,对抗体进行表征,为神经科学中的许多靶点确定了高性能的可再生抗体。这显示了利益相关者携手合作所能取得的进展。然而,迄今为止,他们的工作只适用于极少一部分可用抗体。在存在表征数据的情况下,最终用户需要帮助才能找到并适当使用这些数据。虽然在技术解决方案和抗体表征方面已经取得了进展,但我们认为还需要采取一些措施,使研究人员的最佳实践行为更加可行、简便和有益。多个合作伙伴和利益相关者之间的全球合作与协调对于解决技术、政策、行为和开放数据共享方面的挑战至关重要。通过介绍我们的 "只有好抗体 "倡议,我们提供了潜在的解决方案,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,我们公开邀请包括研究人员在内的利益相关者加入我们的事业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the integrity and reproducibility of research that uses antibodies: a technical, data sharing, behavioral and policy challenge.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
mAbs
mAbs 工程技术-仪器仪表
CiteScore
10.70
自引率
11.30%
发文量
77
审稿时长
6-12 weeks
期刊介绍: mAbs is a multi-disciplinary journal dedicated to the art and science of antibody research and development. The journal has a strong scientific and medical focus, but also strives to serve a broader readership. The articles are thus of interest to scientists, clinical researchers, and physicians, as well as the wider mAb community, including our readers involved in technology transfer, legal issues, investment, strategic planning and the regulation of therapeutics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信