A decision-support tool for strategic decision-making in biopharmaceutical manufacture
The need for software tools to support decision-making relating to biomanufacture is becoming increasingly critical in order to accelerate the time-to-market and reduce costs. The main objective of this thesis is the design and implementation of a decision-support tool that integrates both the business and process perspectives of biopharmaceutical manufacture to aid the evaluation of manufacturing alternatives. The tool, designated BioPharmKit, was built on the platform of the simulation package Extend Industrial Suite (Imagine That Inc., San Jose, USA). As an illustration, the tool was used to evaluate manufacturing alternatives for the production of monoclonal antibodies derived from mammalian-based processes. The functionalities of such a tool to model cost summation, perform mass balance calculations, simulate resource handling, and incorporate uncertainties are demonstrated via two industrial-related case studies. The first case study was based upon the assessment of pooling strategies in perfusion culture of mammalian cells to deliver a therapeutic protein for commercial use. The analysis in this study addressed the trade-offs between investing in a plant with a smaller downstream process (DSP) capacity and employing more frequent pooling of the broth for purification or opting for a plant with a larger DSP capacity and less frequent pooling of broth. The feasibility of each manufacturing option was evaluated based on the annual throughput, resource utilisation profiles and cost of goods per gram (COG/g). Project appraisal was based on expected output values and the likelihood of achieving or exceeding critical threshold indicators generated using Monte Carlo simulations. Critical drivers that may affect the decision were identified through scenario analyses to improve the robustness of the decision-making process. In the second case study, the decision-support tool developed was employed to evaluate the economic feasibility of fed-batch and perfusion cultures. The trade-offs between the relative simplicity and high titres of fed-batch systems and the high productivity but greater complexity of perfusion processes were analysed. The study aimed to investigate the relative economics of the two operational modes by examining key performance metrics such as the COG/g and the net present value (NPV). Another major objective of this study was to compare the relative usefulness and limitations of the decision tree and Monte Carlo simulations, which are typical tools used for risk analysis to aid decision-making in situations subject to uncertainty. Although the decision tree analysis provided a simple approach for decision-making based on the expected values of performance metrics, it does not explicitly consider the underlying uncertainty in each contributory estimate. The Monte Carlo simulation method was more time-consuming but provided a more complete estimation of process uncertainties subject to fluctuating product titres and process yields. The examples illustrate the benefits of using the tool to investigate the cost effectiveness of different manufacturing alternatives and may assist the process of decision-making in the context of both business and process drivers. It is envisaged that such a tool might be employed in early process development, hence contributing to transparent planning and project management decisions.