Evaluation of variation in preclinical electroencephalographic
The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing,...
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| Vydáno v: | PloS one Ročník 19; číslo 10; s. e0309521 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Public Library of Science
29.10.2024
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability. Experiments consisted of a Localisation phase, which aimed to identify the factors that influence between-laboratory variability, a Harmonisation phase to evaluate whether harmonisation of standardized protocols and centralised processing and data analysis reduced variance, and a Ring-Testing phase to verify the ability of the harmonised protocol to generate consistent findings. Indeed, between-laboratory variability reduced from Localisation to Harmonisation and this reduction remained during the Ring-Testing phase. Results obtained in this multicentre preclinical qEEG study also confirmed the complex nature of EEG experiments starting from the surgery and data collection through data pre-processing to data analysis that ultimately influenced the results and contributed to variance in findings across laboratories. Overall, harmonisation of protocols and centralized data analysis were crucial in reducing laboratory-to-laboratory variability. To this end, it is recommended that standardized guidelines be updated and followed for collection and analysis of preclinical EEG data. |
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| AbstractList | The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability. Experiments consisted of a Localisation phase, which aimed to identify the factors that influence between-laboratory variability, a Harmonisation phase to evaluate whether harmonisation of standardized protocols and centralised processing and data analysis reduced variance, and a Ring-Testing phase to verify the ability of the harmonised protocol to generate consistent findings. Indeed, between-laboratory variability reduced from Localisation to Harmonisation and this reduction remained during the Ring-Testing phase. Results obtained in this multicentre preclinical qEEG study also confirmed the complex nature of EEG experiments starting from the surgery and data collection through data pre-processing to data analysis that ultimately influenced the results and contributed to variance in findings across laboratories. Overall, harmonisation of protocols and centralized data analysis were crucial in reducing laboratory-to-laboratory variability. To this end, it is recommended that standardized guidelines be updated and followed for collection and analysis of preclinical EEG data. |
| Audience | Academic |
| Author | Boulanger, Bruno Miljanovic, Nina Song, Dekun Voehringer, Patrizia Platt, Bettina Riedel, Gernot Drinkenburg, Wilhelmus H. I. M Laloux, Clément Seiffert, Isabel Leiser, Steven C Smyk, Magdalena K Kas, Martien J. H Waldron, Ann-Marie Nicholson, Janet R Ahuis, Tim P Aulehner, Katharina Jucker, Mathias Potschka, Heidrun Bray, Jack |
| Author_xml | – sequence: 1 fullname: Ahuis, Tim P – sequence: 2 fullname: Smyk, Magdalena K – sequence: 3 fullname: Laloux, Clément – sequence: 4 fullname: Aulehner, Katharina – sequence: 5 fullname: Bray, Jack – sequence: 6 fullname: Waldron, Ann-Marie – sequence: 7 fullname: Miljanovic, Nina – sequence: 8 fullname: Seiffert, Isabel – sequence: 9 fullname: Song, Dekun – sequence: 10 fullname: Boulanger, Bruno – sequence: 11 fullname: Jucker, Mathias – sequence: 12 fullname: Potschka, Heidrun – sequence: 13 fullname: Platt, Bettina – sequence: 14 fullname: Riedel, Gernot – sequence: 15 fullname: Voehringer, Patrizia – sequence: 16 fullname: Nicholson, Janet R – sequence: 17 fullname: Drinkenburg, Wilhelmus H. I. M – sequence: 18 fullname: Kas, Martien J. H – sequence: 19 fullname: Leiser, Steven C |
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