{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T08:04:20Z","timestamp":1773821060961,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T00:00:00Z","timestamp":1701907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"EU project AIDPATH","doi-asserted-by":"publisher","award":["101016909"],"award-info":[{"award-number":["101016909"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"EU project AIDPATH","doi-asserted-by":"publisher","award":["RTC-2017-6578-1"],"award-info":[{"award-number":["RTC-2017-6578-1"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"EU project AIDPATH","doi-asserted-by":"publisher","award":["830121"],"award-info":[{"award-number":["830121"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Spanish Ministerio de Econom\u00eda y Competitividad","award":["101016909"],"award-info":[{"award-number":["101016909"]}]},{"name":"Spanish Ministerio de Econom\u00eda y Competitividad","award":["RTC-2017-6578-1"],"award-info":[{"award-number":["RTC-2017-6578-1"]}]},{"name":"Spanish Ministerio de Econom\u00eda y Competitividad","award":["830121"],"award-info":[{"award-number":["830121"]}]},{"name":"Innovate UK","award":["101016909"],"award-info":[{"award-number":["101016909"]}]},{"name":"Innovate UK","award":["RTC-2017-6578-1"],"award-info":[{"award-number":["RTC-2017-6578-1"]}]},{"name":"Innovate UK","award":["830121"],"award-info":[{"award-number":["830121"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Immune therapy for cancer patients is a new and promising area that in the future may complement traditional chemotherapy. The cell expansion phase is a critical part of the process chain to produce a large number of high-quality, genetically modified immune cells from an initial sample from the patient. Smart sensors augment the ability of the control and monitoring system of the process to react in real-time to key control parameter variations, adapt to different patient profiles, and optimize the process. The aim of the current work is to develop and calibrate smart sensors for their deployment in a real bioreactor platform, with adaptive control and monitoring for diverse patient\/donor cell profiles. A set of contrasting smart sensors has been implemented and tested on automated cell expansion batch runs, which incorporate advanced data-driven machine learning and statistical techniques to detect variations and disturbances of the key system features. Furthermore, a \u2018consensus\u2019 approach is applied to the six smart sensor alerts as a confidence factor which helps the human operator identify significant events that require attention. Initial results show that the smart sensors can effectively model and track the data generated by the Aglaris FACER bioreactor, anticipate events within a 30 min time window, and mitigate perturbations in order to optimize the key performance indicators of cell quantity and quality. In quantitative terms for event detection, the consensus for sensors across batch runs demonstrated good stability: the AI-based smart sensors (Fuzzy and Weighted Aggregation) gave 88% and 86% consensus, respectively, whereas the statistically based (Stability Detector and Bollinger) gave 25% and 42% consensus, respectively, the average consensus for all six being 65%. The different results reflect the different theoretical approaches. Finally, the consensus of batch runs across sensors gave even higher stability, ranging from 57% to 98% with an average consensus of 80%.<\/jats:p>","DOI":"10.3390\/s23249676","type":"journal-article","created":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T08:22:59Z","timestamp":1701937379000},"page":"9676","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Smart Sensor Control and Monitoring of an Automated Cell Expansion Process"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5852-7716","authenticated-orcid":false,"given":"David F.","family":"Nettleton","sequence":"first","affiliation":[{"name":"IRIS Technology Solutions, 08940 Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N\u00faria","family":"Mar\u00ed-Buy\u00e9","sequence":"additional","affiliation":[{"name":"Aglaris Cell, 28760 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Helena","family":"Marti-Soler","sequence":"additional","affiliation":[{"name":"IRIS Technology Solutions, 08940 Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6414-1334","authenticated-orcid":false,"given":"Joseph R.","family":"Egan","sequence":"additional","affiliation":[{"name":"Department of Biochemical Engineering, University College London, London WC1E 6BT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Hort","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Production Technology, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Horna","sequence":"additional","affiliation":[{"name":"Aglaris Cell, 28760 Madrid, Spain"},{"name":"Aglaris Ltd., Stevenage SG1 2FX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miquel","family":"Costa","sequence":"additional","affiliation":[{"name":"Aglaris Cell, 28760 Madrid, Spain"},{"name":"Aglaris Ltd., Stevenage SG1 2FX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elia","family":"Vallejo Ben\u00edtez-Cano","sequence":"additional","affiliation":[{"name":"Aglaris Ltd., Stevenage SG1 2FX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8319-1679","authenticated-orcid":false,"given":"Stephen","family":"Goldrick","sequence":"additional","affiliation":[{"name":"Department of Biochemical Engineering, University College London, London WC1E 6BT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qasim A.","family":"Rafiq","sequence":"additional","affiliation":[{"name":"Department of Biochemical Engineering, University College London, London WC1E 6BT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9163-8306","authenticated-orcid":false,"given":"Niels","family":"K\u00f6nig","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Production Technology, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert H.","family":"Schmitt","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Production Technology, 52074 Aachen, Germany"},{"name":"Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, 52074 Aachen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aldo","family":"R. Reyes","sequence":"additional","affiliation":[{"name":"IRIS Technology Solutions, 08940 Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,7]]},"reference":[{"key":"ref_1","unstructured":"(2023, December 04). AIDPATH: Artificial Intelligence-Driven Decentralized Production for Advanced Therapies in the Hospital. Available online:  https:\/\/cordis.europa.eu\/project\/id\/101016909\/de."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"B\u00e4ckel, N., Hort, S., Kis, T., Nettleton, D.F., Egan, J.R., Jacobs, J.J., Grunert, D., and Schmitt, R.H. (2023, December 04). Elaborating the Potential of Artificial Intelligence in Automated CAR-T Cell Manufacturing. Available online: https:\/\/www.frontiersin.org\/articles\/10.3389\/fmmed.2023.1250508\/full.","DOI":"10.3389\/fmmed.2023.1250508"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"913287","DOI":"10.3389\/fmed.2022.913287","article-title":"Toward rapid, widely available autologous CAR-T cell therapy\u2013artificial intelligence and automation enabling the smart manufacturing hospital","volume":"9","author":"Hort","year":"2022","journal-title":"Front. Med."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"843","DOI":"10.18609\/cgti.2018.087","article-title":"Automated cell expansion: Trends & outlook of critical technologies","volume":"4","author":"Wu","year":"2018","journal-title":"Cell Gene Ther. Insights"},{"key":"ref_5","unstructured":"Yamanaka, H., Murato, Y., and Cizdziel, P.E. (2021). Bioreactor Automation Driven by Real-Time Sensing: Enhancing Productivity through Accurate, Efficient Glucose Control, Yokogawa Corporation of America."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wang, B., Wang, Z., Chen, T., and Zhao, X. (2020). Development of novel bioreactor control systems based on smart sensors and actuators. Front. Bioeng. Biotechnol., 8.","DOI":"10.3389\/fbioe.2020.00007"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Reyes, S.J., Durocher, Y., Pham, P.L., and Henry, O. (2022). Modern Sensor Tools and Techniques for Monitoring, Controlling, and Improving Cell Culture Processes. Processes, 10.","DOI":"10.3390\/pr10020189"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"12868","DOI":"10.1109\/JSEN.2020.3033153","article-title":"A review on soft sensors for monitoring, control, and optimization of industrial processes","volume":"21","author":"Jiang","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7598","DOI":"10.1109\/TNNLS.2021.3085869","article-title":"A deep probabilistic transfer learning framework for soft sensor modeling with missing data","volume":"33","author":"Chai","year":"2021","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5853","DOI":"10.1109\/TII.2021.3053128","article-title":"A survey on deep learning for data-driven soft sensors","volume":"17","author":"Sun","year":"2021","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"16330","DOI":"10.1021\/acs.iecr.0c02398","article-title":"Development of adversarial transfer learning soft sensor for multigrade processes","volume":"59","author":"Liu","year":"2020","journal-title":"Ind. Eng. Chem. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2020.05.028","article-title":"Input selection methods for data-driven Soft sensors design: Application to an industrial process","volume":"537","author":"Curreri","year":"2020","journal-title":"Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2000063","DOI":"10.1002\/aisy.202000063","article-title":"Machine learning-enabled smart sensor systems","volume":"2","author":"Ha","year":"2020","journal-title":"Adv. Intell. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kalsoom, T., Ramzan, N., Ahmed, S., and Ur-Rehman, M. (2020). Advances in sensor technologies in the era of smart factory and industry 4.0. Sensors, 20.","DOI":"10.3390\/s20236783"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3390\/automation2020004","article-title":"Intelligent sensors for real-Time decision-making","volume":"2","author":"Coito","year":"2021","journal-title":"Automation"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Huang, J.W., Zhong, M.X., and Jaysawal, B.P. (2020). Tadilof: Time aware density-based incremental local outlier detection in data streams. Sensors, 20.","DOI":"10.3390\/s20205829"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Yen, H.H., Lin, C.H., and Tsao, H.W. (2020). Time-aware and temperature-aware fire evacuation path algorithm in IoT-enabled multi-story multi-exit buildings. Sensors, 21.","DOI":"10.3390\/s21010111"},{"key":"ref_18","unstructured":"(2023, June 12). COPE Official Website. Available online: https:\/\/www.ipt.fraunhofer.de\/en\/offer\/special-machines\/laboratory-automation\/laboratory-automation-software.html."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1016\/j.procir.2018.03.189","article-title":"Highly modular and generic control software for adaptive cell processing on automated production platforms","volume":"72","author":"Jung","year":"2018","journal-title":"Procedia CIRP"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Garcia-Aponte, O.F., Herwig, C., and Kozma, B. (2021). Lymphocyte expansion in bioreactors: Upgrading adoptive cell therapy. J. Biol. Eng., 15.","DOI":"10.1186\/s13036-021-00264-7"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Hewitt, M.M., Trainor, N., Ostrout, N., and Abraham, E. (2021). Cell therapy manufacturing: Process analytic technologies needed to achieve flexible, feedback-driven automation. Curr. Opin. Biomed. Eng., 20.","DOI":"10.1016\/j.cobme.2021.100358"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e10106","DOI":"10.1002\/amp2.10106","article-title":"Process analytical technologies in cell therapy manufacturing: State-of-the-art and future directions","volume":"4","author":"Wang","year":"2022","journal-title":"J. Adv. Manuf. Process."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Aifuwa, I. (2022). PAT strategies and applications for cell therapy processing. Curr. Opin. Biomed. Eng., 24.","DOI":"10.1016\/j.cobme.2022.100405"},{"key":"ref_24","first-page":"47","article-title":"Using bollinger bands","volume":"10","author":"Bollinger","year":"1992","journal-title":"Stock. Commod."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"8782131","DOI":"10.1155\/2017\/8782131","article-title":"Anomaly detection in smart metering infrastructure with the use of time series analysis","volume":"2017","author":"Andrysiak","year":"2017","journal-title":"J. Sens."},{"key":"ref_26","unstructured":"Nettleton, D., and Hern\u00e1ndez, L. (1999, January 22\u201325). Evaluating reliability and relevance for WOWA aggregation of sleep apnea case data. Proceedings of the EUSFLAT-ESTYLF Joint Conference, Palma, Spain."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1002\/(SICI)1098-111X(199702)12:2<153::AID-INT3>3.0.CO;2-P","article-title":"The weighted OWA operator","volume":"12","author":"Torra","year":"1997","journal-title":"Int. J. Intell. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"113","DOI":"10.12700\/APH.19.2.2022.2.7","article-title":"Determination of critical deformation regions of a lithium polymer battery by dic measurement and wowa filter","volume":"19","author":"Dineva","year":"2022","journal-title":"Acta Polytech. Hung."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/2.53","article-title":"Fuzzy logic","volume":"21","author":"Zadeh","year":"1988","journal-title":"Computer"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"291","DOI":"10.4028\/www.scientific.net\/AMM.573.291","article-title":"Bioreactor control using fuzzy logic controllers","volume":"573","author":"Arulmozhi","year":"2014","journal-title":"Appl. Mech. Mater."},{"key":"ref_31","unstructured":"Nettleton, D., and Hern\u00e1ndez, L. (1999). Improving Questionnaire Screening of Sleep Apnea Cases Using Fuzzy Knowledge Representation and Aggregation Techniques, Universitat Polit\u00e9cnica de Catalunya. Research Report LSI-99-29-R."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.jprocont.2021.05.010","article-title":"Control of an anaerobic bioreactor using a fuzzy supervisory controller","volume":"103","author":"Ghanavati","year":"2021","journal-title":"J. Process Control"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9676\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:34:50Z","timestamp":1760132090000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9676"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,7]]},"references-count":32,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["s23249676"],"URL":"https:\/\/doi.org\/10.3390\/s23249676","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,7]]}}}