Literature DB >> 22888107

Chemometrics applications in biotechnology processes: predicting column integrity and impurity clearance during reuse of chromatography resin.

Anurag S Rathore1, Shachi Mittal, Scott Lute, Kurt Brorson.   

Abstract

Separation media, in particular chromatography media, is typically one of the major contributors to the cost of goods for production of a biotechnology therapeutic. To be cost-effective, it is industry practice that media be reused over several cycles before being discarded. The traditional approach for estimating the number of cycles a particular media can be reused for involves performing laboratory scale experiments that monitor column performance and carryover. This dataset is then used to predict the number of cycles the media can be used at manufacturing scale (concurrent validation). Although, well accepted and widely practiced, there are challenges associated with extrapolating the laboratory scale data to manufacturing scale due to differences that may exist across scales. Factors that may be different include: level of impurities in the feed material, lot to lot variability in feedstock impurities, design of the column housing unit with respect to cleanability, and homogeneity of the column packing. In view of these challenges, there is a need for approaches that may be able to predict column underperformance at the manufacturing scale over the product lifecycle. In case such an underperformance is predicted, the operators can unpack and repack the chromatography column beforehand and thus avoid batch loss. Chemometrics offers one such solution. In this article, we present an application of chemometrics toward the analysis of a set of chromatography profiles with the intention of predicting the various events of column underperformance including the backpressure buildup and inefficient deoxyribonucleic acid clearance.
Copyright © 2012 American Institute of Chemical Engineers (AIChE).

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Year:  2012        PMID: 22888107     DOI: 10.1002/btpr.1610

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  1 in total

Review 1.  Monitoring Quality of Biotherapeutic Products Using Multivariate Data Analysis.

Authors:  Anurag S Rathore; Mili Pathak; Renu Jain; Gaurav Pratap Singh Jadaun
Journal:  AAPS J       Date:  2016-04-04       Impact factor: 4.009

  1 in total

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