Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24458
Title: Multi-criteria manufacturability indices for ranking high-concentration monoclonal antibody formulations
Authors: Yang, Y
Velayudhan, A
Thornhill, NF
Farid, SS
Keywords: data mining;high-concentration mAb formulation;manufacturability index;viscosity;aggregation;developability assessment
Issue Date: 1-Sep-2017
Publisher: Wiley
Citation: Yang, Y., Velayudhan, A., Thornhill, N.F. and Farid, S.S. (2017) 'Multi-criteria manufacturability indices for ranking high-concentration monoclonal antibody formulations', Biotechnology and Bioengineering, 2017, 114 (9), pp. 2043 - 2056. doi: 10.1002/bit.26329.
Abstract: Copyright © 2017 The Authors. The need for high-concentration formulations for subcutaneous delivery of therapeutic monoclonal antibodies (mAbs) can present manufacturability challenges for the final ultrafiltration/diafiltration (UF/DF) step. Viscosity levels and the propensity to aggregate are key considerations for high-concentration formulations. This work presents novel frameworks for deriving a set of manufacturability indices related to viscosity and thermostability to rank high-concentration mAb formulation conditions in terms of their ease of manufacture. This is illustrated by analyzing published high-throughput biophysical screening data that explores the influence of different formulation conditions (pH, ions, and excipients) on the solution viscosity and product thermostability. A decision tree classification method, CART (Classification and Regression Tree) is used to identify the critical formulation conditions that influence the viscosity and thermostability. In this work, three different multi-criteria data analysis frameworks were investigated to derive manufacturability indices from analysis of the stress maps and the process conditions experienced in the final UF/DF step. Polynomial regression techniques were used to transform the experimental data into a set of stress maps that show viscosity and thermostability as functions of the formulation conditions. A mathematical filtrate flux model was used to capture the time profiles of protein concentration and flux decay behavior during UF/DF. Multi-criteria decision-making analysis was used to identify the optimal formulation conditions that minimize the potential for both viscosity and aggregation issues during UF/DF.
URI: https://bura.brunel.ac.uk/handle/2438/24458
DOI: https://doi.org/10.1002/bit.26329
ISSN: 0006-3592
Appears in Collections:Chemistry

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