Bioprocess and Biosystems Engineering

, Volume 30, Issue 1, pp 1–11

A decision-support model for evaluating changes in biopharmaceutical manufacturing processes

Authors

  • S. Chhatre
    • The Advanced Centre for Biochemical EngineeringUniversity College London
  • R. Francis
    • Process Development GroupProtherics U.K. Limited
  • K. O’Donovan
    • Process Development GroupProtherics U.K. Limited
  • N. J. Titchener-Hooker
    • The Advanced Centre for Biochemical EngineeringUniversity College London
  • A. R. Newcombe
    • Process Development GroupProtherics U.K. Limited
    • The Advanced Centre for Biochemical EngineeringUniversity College London
Original Paper

DOI: 10.1007/s00449-006-0086-8

Cite this article as:
Chhatre, S., Francis, R., O’Donovan, K. et al. Bioprocess Biosyst Eng (2007) 30: 1. doi:10.1007/s00449-006-0086-8

Abstract

A simulation is described that evaluates the impacts of altering bio-manufacturing processes. Modifications designed to improve production levels, times and costs were assessed, including increasing feed volumes/titres, replacing initial downstream stages with packed or expanded bed affinity steps and removing ion exchange steps. Options were evaluated for manufactured product mass, COG, batch times and development costs and timescales. Metrics were combined using multi-attribute-decision-making techniques generating a single assessment metric for each option. The utility of this approach was illustrated by application to an FDA-approved process manufacturing rattlesnake anti-venom (Protherics U.K.). Currently, ovine serum containing anti-venom IgG is purified by precipitation/centrifugation, prior to antibody proteolysis by papain. An ion exchanger removes FC, before affinity chromatography yields the final anti-venom. An expanded bed affinity column operating with an 80% higher IgG titre, 66% higher feed volume and without the ion exchanger delivered the best multi-attribute-decision-making value, potentially providing the most desirable alternative.

Keywords

BioprocessIntegrated modellingPolyclonal antibodyProcess changeSimulation

Abbreviations

MA

Actual product mass (g FAB)

M0

Lowest product mass set to represent the zero bound in normalisation (g FAB)

M1

Highest product mass set to represent the one bound in normalisation (g FAB)

Ni

Normalised value of the ith performance metric (–)

OR

Overall Rank (–)

wi

Weighting of the ith performance metric (–)

Copyright information

© Springer-Verlag 2006