Chemometrics application in biotech processes: assessing comparability across processes and scales

BACKGROUND Assessment of process comparability is often required across different phases of manufacturing (Phase I vs Phase II vs Phase III vs Commercial) as well as other key activities during product commercialization (process scale-up, technology transfer, process improvement). In this work, chemometrics was applied to compare two versions of a biotech process and identify process steps where significant differences exist as well as the parameters that cause these differences. RESULTS The dataset used in this analysis consists of data from 229 manufacturing batches. Partial least squares has been used for modeling the data. Scatter plots and variable importance plots have been used for evaluating comparability. Process parameters identified as significant by using chemometrics have been compared against those identified from process characterization using traditional lab scale experimental studies. The comparison has been followed by discussion on the pros and cons of the two approaches. To our knowledge this is the first time that such a comparison has been published for biotech processing. CONCLUSIONS The study further demonstrates the usefulness of chemometrics in defining process comparability and in gathering process understanding from analysis of manufacturing data to supplement traditional lab-scale experimentation. © 2014 Society of Chemical Industry

[1]  Steven Kozlowski,et al.  Considerations for Biotechnology Product Quality by Design , 2008 .

[2]  Anurag S Rathore,et al.  Design of experiments applications in bioprocessing: Concepts and approach , 2014, Biotechnology progress.

[3]  Riccardo Leardi,et al.  Industrial experiences with multivariate statistical analysis of batch process data , 2006 .

[4]  Jarka Glassey,et al.  An assessment of seed quality and its influence on productivity estimation in an industrial antibiotic fermentation. , 2002, Biotechnology and bioengineering.

[5]  Dale E Seborg,et al.  Fault Detection and Diagnosis in an Industrial Fed‐Batch Cell Culture Process , 2007, Biotechnology progress.

[6]  Eric N M van Sprang,et al.  Multivariate data analysis on historical IPV production data for better process understanding and future improvements , 2010, Biotechnology and bioengineering.

[7]  Steven M Cramer,et al.  Improved process analytical technology for protein a chromatography using predictive principal component analysis tools , 2011, Biotechnology and bioengineering.

[8]  Barry Lennox,et al.  Automated Production Support for the Bioprocess Industry , 2002, Biotechnology progress.

[9]  Anurag S Rathore,et al.  Application of near‐infrared (NIR) spectroscopy for screening of raw materials used in the cell culture medium for the production of a recombinant therapeutic protein , 2009, Biotechnology progress.

[10]  Brian D. Kelley,et al.  Scale-Down Models for Purification Processes: Approaches and Applications , 2005 .

[11]  A. Rathore,et al.  Application of Multivariate Data Analysis for Identification and Successful Resolution of a Root Cause for a Bioprocessing Application , 2008, Biotechnology progress.

[12]  Brian Hubbard,et al.  Downstream processing of monoclonal antibodies--application of platform approaches. , 2007, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[13]  Sten Bay Jørgensen,et al.  Supervision of fed-batch fermentations , 1999 .

[14]  Anurag S Rathore,et al.  Optimization of a refolding step for a therapeutic fusion protein in the quality by design (QbD) paradigm. , 2012, Journal of separation science.

[15]  Abhinav A Shukla,et al.  Recent advances in large-scale production of monoclonal antibodies and related proteins. , 2010, Trends in biotechnology.

[16]  Anurag S Rathore,et al.  Roadmap for implementation of quality by design (QbD) for biotechnology products. , 2009, Trends in biotechnology.

[17]  Anurag Rathore,et al.  Use of the design‐of‐experiments approach for the development of a refolding technology for progenipoietin‐1, a recombinant human cytokine fusion protein from Escherichia coli inclusion bodies , 2009, Biotechnology and applied biochemistry.

[18]  Xiangyang Wang,et al.  Defining Process Design Space for Biotech Products: Case Study of Pichia pastoris Fermentation , 2008, Biotechnology progress.

[19]  Xiangyang Wang,et al.  Case Study on Definition of Process Design Space for a Microbial Fermentation Step , 2008 .

[20]  Duncan Low,et al.  Future of antibody purification. , 2007, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[21]  A. Rathore,et al.  Quality by design for biopharmaceuticals , 2009, Nature Biotechnology.

[22]  Anurag S Rathore,et al.  Chemometrics applications in biotechnology processes: Predicting column integrity and impurity clearance during reuse of chromatography resin , 2012, Biotechnology progress.

[23]  Ali Cinar,et al.  Statistical monitoring of multistage, multiphase batch processes , 2002 .

[24]  Anurag S Rathore,et al.  Chemometrics applications in biotech processes: A review , 2011, Biotechnology progress.

[25]  Anurag S. Rathore,et al.  Chemometrics applications in biotech processes: Assessing process comparability , 2012, Biotechnology progress.

[26]  S Vaidyanathan,et al.  Assessment of near-infrared spectral information for rapid monitoring of bioprocess quality. , 2001, Biotechnology and bioengineering.

[27]  I. Karimi,et al.  Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design. , 2010, Journal of biotechnology.

[28]  Jeremy S. Conner,et al.  Application of Multivariate Analysis toward Biotech Processes: Case Study of a Cell‐Culture Unit Operation , 2007, Biotechnology progress.

[29]  A J Morris,et al.  Enhanced bio-manufacturing through advanced multivariate statistical technologies. , 2002, Journal of biotechnology.

[30]  Jeremy S. Conner,et al.  Pattern matching in batch bioprocesses - Comparisons across multiple products and operating conditions , 2009, Comput. Chem. Eng..

[31]  S. Wold,et al.  Partial least squares analysis with cross‐validation for the two‐class problem: A Monte Carlo study , 1987 .