The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential
A key step in building regulatory acceptance of alternative or non-animal test methods has long been the use of interlaboratory comparisons or round-robins (RRs), in which a common test material and standard operating procedure is provided to all participants, who measure the specific endpoint and r...
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| Format: | Article |
| Language: | English |
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Beilstein-Institut
2024-11-01
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| Series: | Beilstein Journal of Nanotechnology |
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| Online Access: | https://doi.org/10.3762/bjnano.15.121 |
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| author | Dimitra-Danai Varsou Arkaprava Banerjee Joyita Roy Kunal Roy Giannis Savvas Haralambos Sarimveis Ewelina Wyrzykowska Mateusz Balicki Tomasz Puzyn Georgia Melagraki Iseult Lynch Antreas Afantitis |
| author_facet | Dimitra-Danai Varsou Arkaprava Banerjee Joyita Roy Kunal Roy Giannis Savvas Haralambos Sarimveis Ewelina Wyrzykowska Mateusz Balicki Tomasz Puzyn Georgia Melagraki Iseult Lynch Antreas Afantitis |
| author_sort | Dimitra-Danai Varsou |
| collection | DOAJ |
| description | A key step in building regulatory acceptance of alternative or non-animal test methods has long been the use of interlaboratory comparisons or round-robins (RRs), in which a common test material and standard operating procedure is provided to all participants, who measure the specific endpoint and return their data for statistical comparison to demonstrate the reproducibility of the method. While there is currently no standard approach for the comparison of modelling approaches, consensus modelling is emerging as a “modelling equivalent” of a RR. We demonstrate here a novel approach to evaluate the performance of different models for the same endpoint (nanomaterials’ zeta potential) trained using a common dataset, through generation of a consensus model, leading to increased confidence in the model predictions and underlying models. Using a publicly available dataset, four research groups (NovaMechanics Ltd. (NovaM)-Cyprus, National Technical University of Athens (NTUA)-Greece, QSAR Lab Ltd.-Poland, and DTC Lab-India) built five distinct machine learning (ML) models for the in silico prediction of the zeta potential of metal and metal oxide-nanomaterials (NMs) in aqueous media. The individual models were integrated into a consensus modelling scheme, enhancing their predictive accuracy and reducing their biases. The consensus models outperform the individual models, resulting in more reliable predictions. We propose this approach as a valuable method for increasing the validity of nanoinformatics models and driving regulatory acceptance of in silico new approach methodologies for the use within an “Integrated Approach to Testing and Assessment” (IATA) for risk assessment of NMs. |
| format | Article |
| id | doaj-art-ca256c31203b4f4cb5f0eb261041fd31 |
| institution | OA Journals |
| issn | 2190-4286 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Beilstein-Institut |
| record_format | Article |
| series | Beilstein Journal of Nanotechnology |
| spelling | doaj-art-ca256c31203b4f4cb5f0eb261041fd312025-08-20T02:18:24ZengBeilstein-InstitutBeilstein Journal of Nanotechnology2190-42862024-11-011511536155310.3762/bjnano.15.1212190-4286-15-121The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potentialDimitra-Danai Varsou0Arkaprava Banerjee1Joyita Roy2Kunal Roy3Giannis Savvas4Haralambos Sarimveis5Ewelina Wyrzykowska6Mateusz Balicki7Tomasz Puzyn8Georgia Melagraki9Iseult Lynch10Antreas Afantitis11NovaMechanics MIKE, Piraeus 18545, GreeceDrug Theoretics and Cheminformatics (DTC) Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700 032, India Drug Theoretics and Cheminformatics (DTC) Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700 032, India Drug Theoretics and Cheminformatics (DTC) Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700 032, India School of Chemical Engineering, National Technical University of Athens, 9 Iroon Polytechniou, 15780, Athens, Greece School of Chemical Engineering, National Technical University of Athens, 9 Iroon Polytechniou, 15780, Athens, Greece QSAR Lab, Trzy Lipy 3, 80-172 Gdańsk, PolandQSAR Lab, Trzy Lipy 3, 80-172 Gdańsk, PolandQSAR Lab, Trzy Lipy 3, 80-172 Gdańsk, PolandDivision of Physical Sciences and Applications, Hellenic Military Academy, Vari 16672, Greece School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT Birmingham, United Kingdom Entelos Institute, Larnaca 6059, CyprusA key step in building regulatory acceptance of alternative or non-animal test methods has long been the use of interlaboratory comparisons or round-robins (RRs), in which a common test material and standard operating procedure is provided to all participants, who measure the specific endpoint and return their data for statistical comparison to demonstrate the reproducibility of the method. While there is currently no standard approach for the comparison of modelling approaches, consensus modelling is emerging as a “modelling equivalent” of a RR. We demonstrate here a novel approach to evaluate the performance of different models for the same endpoint (nanomaterials’ zeta potential) trained using a common dataset, through generation of a consensus model, leading to increased confidence in the model predictions and underlying models. Using a publicly available dataset, four research groups (NovaMechanics Ltd. (NovaM)-Cyprus, National Technical University of Athens (NTUA)-Greece, QSAR Lab Ltd.-Poland, and DTC Lab-India) built five distinct machine learning (ML) models for the in silico prediction of the zeta potential of metal and metal oxide-nanomaterials (NMs) in aqueous media. The individual models were integrated into a consensus modelling scheme, enhancing their predictive accuracy and reducing their biases. The consensus models outperform the individual models, resulting in more reliable predictions. We propose this approach as a valuable method for increasing the validity of nanoinformatics models and driving regulatory acceptance of in silico new approach methodologies for the use within an “Integrated Approach to Testing and Assessment” (IATA) for risk assessment of NMs.https://doi.org/10.3762/bjnano.15.121consensus modellingread-acrossqsprround-robin testzeta potential |
| spellingShingle | Dimitra-Danai Varsou Arkaprava Banerjee Joyita Roy Kunal Roy Giannis Savvas Haralambos Sarimveis Ewelina Wyrzykowska Mateusz Balicki Tomasz Puzyn Georgia Melagraki Iseult Lynch Antreas Afantitis The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential Beilstein Journal of Nanotechnology consensus modelling read-across qspr round-robin test zeta potential |
| title | The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential |
| title_full | The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential |
| title_fullStr | The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential |
| title_full_unstemmed | The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential |
| title_short | The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential |
| title_sort | round robin approach applied to nanoinformatics consensus prediction of nanomaterials zeta potential |
| topic | consensus modelling read-across qspr round-robin test zeta potential |
| url | https://doi.org/10.3762/bjnano.15.121 |
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