SwePub
Tyck till om SwePub Sök här!
Sök i LIBRIS databas

  Utökad sökning

onr:"swepub:oai:DiVA.org:umu-201242"
 

Sökning: onr:"swepub:oai:DiVA.org:umu-201242" > Hierarchical time-s...

Hierarchical time-series analysis of dynamic bioprocess systems

Alinaghi, Masoumeh (författare)
Sartorius Corporate Research, Sartorius, Sartorius Stedim Data Analytics, Umeå, Sweden
Surowiec, Izabella (författare)
Sartorius Corporate Research, Sartorius, Sartorius Stedim Data Analytics, Umeå, Sweden
Scholze, Steffi (författare)
Sartorius Stedim Biotech GmbH, Göttingen, Germany
visa fler...
McCready, Chris (författare)
Sartorius Corporate Research, ON, Oakville, Canada
Zehe, Christoph (författare)
Sartorius Corporate Research, Sartorius Stedim Cellca GmbH, Ulm, Germany
Johansson, Erik (författare)
Sartorius Stedim Data Analytics, Umeå, Sweden
Trygg, Johan (författare)
Umeå universitet,Kemiska institutionen,Sartorius Corporate Research, Sartorius, Sartorius Stedim Data Analytics, Umeå, Sweden
Cloarec, Olivier (författare)
Sartorius Corporate Research, Sartorius, Sartorius Stedim Data Analytics, Umeå, Sweden
visa färre...
 (creator_code:org_t)
2022-11-04
2022
Engelska.
Ingår i: Biotechnology Journal. - : John Wiley & Sons. - 1860-6768 .- 1860-7314. ; 17:12
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Background: Monoclonal antibodies (mAbs) are leading types of ‘blockbuster’ biotherapeutics worldwide; they have been successfully used to treat various cancers and chronic inflammatory and autoimmune diseases. Biotherapeutics process development and manufacturing are complicated due to lack of understanding the factors that impact cell productivity and product quality attributes. Understanding complex interactions between cells, media, and process parameters on the molecular level is essential to bring biomanufacturing to the next level. This can be achieved by analyzing cell culture metabolic levels connected to vital process parameters like viable cell density (VCD). However, VCD and metabolic profiles are dynamic parameters and inherently correlated with time, leading to a significant correlation without actual causality. Many time-series methods deal with such issues. However, with metabolic profiling, the number of measured variables vastly exceeds the number of experiments, making most of existing methods ill-suited and hard to interpret. Methods and MajorResults: Here we propose an alternative workflow using hierarchical dimension reduction to visualize and interpret the relation between evolution of metabolic profiles and dynamic process parameters. The first step of proposed method is focused on finding predictive relation between metabolic profiles and process parameter at all time points using OPLS regression. For each time point, the p(corr) obtained from OPLS model is considered as a differential metabogram and is further assessed using principal components analysis (PCA).Conclusions: Compared to traditional batch modeling, applying proposed methodology on metabolic data from Chinese Hamster Ovary (CHO) antibody production characterized the dynamic relation between metabolic profiles and critical process parameters.

Ämnesord

NATURVETENSKAP  -- Biologi -- Biokemi och molekylärbiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Biochemistry and Molecular Biology (hsv//eng)

Nyckelord

bioprocess data
dynamic system
hierarchical analysis
meta-analysis
metabolomics data
time-series analysis
viable cell density (VCD)

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy