Get access

Medium Term Planning of Biopharmaceutical Manufacture using Mathematical Programming

Authors

  • Kais Lakhdar,

    1. The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, UK
    Search for more papers by this author
  • Yuhong Zhou,

    1. The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, UK
    Search for more papers by this author
  • James Savery,

    1. BioPharm Services UK, Lancer House, East Street, Chesham, Bucks HP5 1DG, UK
    Search for more papers by this author
  • Nigel J. Titchener-Hooker,

    1. The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, UK
    Search for more papers by this author
  • Lazaros G. Papageorgiou

    Corresponding author
    1. Centre for Process Systems Engineering, UCLDepartment of Chemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, UK
    • Centre for Process Systems Engineering, UCLDepartment of Chemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, UK. Tel: +44 20 7679 2563. Fax: +44 20 7383 2348
    Search for more papers by this author

Abstract

Regulatory pressures and capacity constraints are forcing the biopharmaceutical industry to consider employing multiproduct manufacturing facilities running on a campaign basis. The need for such flexible and cost-effective manufacture poses a significant challenge for planning and scheduling. This paper reviews the problem of planning and scheduling of biopharmaceutical manufacture and presents a methodology for the planning of multiproduct biopharmaceutical manufacturing facilities. The problem is formulated as a mixed integer linear program (MILP) to represent the relevant decisions required within the planning process and is tested on two typical biopharmaceutical industry planning problems. The proposed formulation is compared with an industrial rule based approach, which it outperforms in terms of profitability. The results indicate that the developed formulation offers an effective representation of the planning problem and would be a useful decision tool for manufacturers in the biopharmaceutical industry particularly at times of limited manufacturing capacity.

Ancillary