Linked Life Data

12325150

Source:http://linkedlifedata.com/resource/pubmed/id/12325150

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2002-9-26
pubmed:abstractText
The performance of an industrial pharmaceutical process (production of an active pharmaceutical ingredient by fermentation, API) was modeled by multiblock partial least squares (MBPLS). The most important process stages are inoculum production and API production fermentation. Thirty batches (runs) were produced according to an experimental planning. Rather than merging all these data into a single block of independent variables (as in ordinary PLS), four data blocks were used separately (manipulated and quality variables for each process stage). With the multiblock approach it was possible to calculate weights and scores for each independent block. It was found that the inoculum quality variables were highly correlated with API production for nominal fermentations. For the nonnominal fermentations, the manipulations of the fermentation stage explained the amount of API obtained (especially the pH and biomass concentration). Based on the above process analysis it was possible to select a smaller set of variables with which a new model was built. The amount of variance predicted of the final API concentration (cross-validation) for this model was 82.4%. The advantage of the multiblock model over the standard PLS model is that the contributions of the two main process stages to the API volumetric productivity were determined.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0006-3592
pubmed:author
pubmed:copyrightInfo
Copyright 2002 Wiley Periodicals, Inc.
pubmed:issnType
Print
pubmed:day
20
pubmed:volume
80
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
419-27
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Multiblock PLS analysis of an industrial pharmaceutical process.
pubmed:affiliation
Center for Biological & Chemical Engineering, Technical University of Lisbon, Av. Rovisco Pais, P-1049-001, Lisbon, Portugal. joao.lopes@ist.utl.pt
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't