Analysis of Transformed Upstream Bioprocess Data Provides Insights into Biological System Variation.
Clicks: 444
ID: 108931
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
78.9
/100
444 views
283 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #2 of 13 articles by views in biotechnology journal
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
In recent years, multivariate data analysis (MVDA) and modeling approaches have found increasing applications for upstream bioprocess studies (e.g., monitoring, development, optimization, scale-up, etc.). Many of these studies look at variations in the concentrations of metabolites and cell-based measurements. However, these measures are subject to system inherent variations (e.g., changes in metabolic activity) but also intentional operational changes. We propose to perform MVDA and modeling on data representative of the underlying biological system operation, i.e., the specific rates, which are per se independent of the scale, operational strategy (e.g., batch, fed-batch) and biomass content. Two industrial case studies are highlighted to showcase the approach: one HEK medium performance comparison study and one CHO scale-up/-down study. It is shown that analyzing processes in this way reveals insights into behavior of the underlying biological system, which cannot to the same degree be deducted from the analysis of concentrations. This article is protected by copyright. All rights reserved.
| Reference Key |
richelle2020analysisbiotechnology
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Richelle, Anne;Lee, Boung Wook;Portela, Rui M C;Raley, Jonathan;von Stosch, Moritz; |
| Journal | biotechnology journal |
| Year | 2020 |
| DOI |
10.1002/biot.202000113
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.