Gangadharan, N;
Turner, R;
Field, R;
Oliver, SG;
Slater, N;
Dikicioglu, D;
(2019)
Metaheuristic approaches in biopharmaceutical process development data analysis.
Bioprocess and Biosystems Engineering
, 42
(9)
pp. 1399-1408.
10.1007/s00449-019-02147-0.
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Abstract
There is a growing interest in mining and handling of big data, which has been rapidly accumulating in the repositories of bioprocess industries. Biopharmaceutical industries are no exception; the implementation of advanced process control strategies based on multivariate monitoring techniques in biopharmaceutical production gave rise to the generation of large amounts of data. Real-time measurements of critical quality and performance attributes collected during production can be highly useful to understand and model biopharmaceutical processes. Data mining can facilitate the extraction of meaningful relationships pertaining to these bioprocesses, and predict the performance of future cultures. This review evaluates the suitability of various metaheuristic methods available for data pre-processing, which would involve the handling of missing data, the visualisation of the data, and dimension reduction; and for data processing, which would focus on modelling of the data and the optimisation of these models in the context of biopharmaceutical process development. The advantages and the associated challenges of employing different methodologies in pre-processing and processing of the data are discussed. In light of these evaluations, a summary guideline is proposed for handling and analysis of the data generated in biopharmaceutical process development.
| Type: | Article |
|---|---|
| Title: | Metaheuristic approaches in biopharmaceutical process development data analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s00449-019-02147-0 |
| Publisher version: | http://dx.doi.org/10.1007/s00449-019-02147-0 |
| Language: | English |
| Additional information: | Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: | Biopharmaceutical process development data, Missing data handling, Interactive data visualisation, Meta-feature selection, Data modelling, MULTIVARIATE TIME-SERIES, MISSING VALUES, VISUAL ANALYSIS, IMPUTATION, CLASSIFICATION, DISCOVERY, ANALYTICS |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10109707 |
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