This study was designed to evaluate the effect of shear on the supercoiled circular (SC) form of plasmid DNA. The conditions chosen are representative of those occurring during the processing of plasmid-based genes for gene therapy and DNA vaccination. Controlled shear was generated using a capillary rheometer and a rotating disk shear device. Plasmid DNA was tested in a clari®ed alkaline lysate solution. This chemical environment is characteristic of the early stages of plasmid puri®cation. Quantitative data is reported on shear degradation of three homologous recombinant plasmids of 13, 20 and 29 kb in size. Shear sensitivity increased dramatically with plasmid molecular weight. Ultrapure plasmid DNA redissolved in 10 mM Tris/ HCl, 1 mM EDTA pH 8 (TE buffer) was subjected to shear using the capillary rheometer. The shear sensitivity of the three plasmids was similar to that observed for the same plasmids in the clari®ed alkaline lysate. Further experiments were carried out using the 20 kb plasmid and the rotating disk shear device. In contrast with the capillary rheometer data, ultrapure DNA redissolved in TE buffer was up to eight times more sensitive to shear compared to plasmid DNA in the clari®ed alkaline lysate. However, this enhanced sensitivity decreased when the ionic strength of the solution was raised by the addition of NaCl to 150 mM. In addition, shear damage was found to be independent of plasmid DNA concentration in the range from 0.2 lg/ml to 20 lg/ml. The combination of shear and air-liquid interfaces caused extensive degradation of the plasmid DNA. The damage was more evident at low ionic strength and low DNA concentration. These ®ndings show that the tertiary structure of plasmid DNA can be severely affected by shear forces. The extent of damage was found to be critically dependent on plasmid size and the ionic strength of the environment. The interaction of shear with air-liquid interfaces shows the highest potential for damaging SC plasmid DNA during bioprocesses.

This paper presents the application of a decision-support tool, SIMBIOPHARMA, for assessing different manufacturing strategies under uncertainty for the production of biopharmaceuticals. SIMBIOPHARMA captures both the technical and business aspects of biopharmaceutical manufacture within a single tool that permits manufacturing alternatives to be evaluated in terms of cost, time, yield, project throughput, resource utilization, and risk. Its use for risk analysis is demonstrated through a hypothetical case study that uses the Monte Carlo simulation technique to imitate the randomness inherent in manufacturing subject to technical and market uncertainties. The case study addresses whether start-up companies should invest in a stainless steel pilot plant or use disposable equipment for the production of early phase clinical trial material. The effects of fluctuating product demands and titers on the performance of a biopharmaceutical company manufacturing clinical trial material are analyzed. The analysis highlights the impact of different manufacturing options on the range in possible outcomes for the project throughput and cost of goods and the likelihood that these metrics exceed a critical threshold. The simulation studies highlight the benefits of incorporating uncertainties when evaluating manufacturing strategies. Methods of presenting and analyzing information generated by the simulations are suggested. These are used to help determine the ranking of alternatives under different scenarios. The example illustrates the benefits to companies of using such a tool to improve management of their R&D portfolios so as to control the cost of goods.

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.

Fed-batch and perfusion culture dominate mammalian cell culture production processes. In this paper, a decision-support tool was employed to evaluate the economic feasibility of both culture modes via a case study based upon the large-scale production of monoclonal antibodies. The trade-offs between the relative simplicity but higher start-up costs of fed-batch processes and the high productivity but higher chances of equipment failure of perfusion processes were analysed. Deterministic analysis showed that whilst there was an insignificant difference (3%) between the cost of goods per gram (COG/g) values, the perfusion option benefited from a 42% reduction in capital investment and a 12% higher projected net present value (NPV). When Monte Carlo simulations were used to account for uncertainties in titre and yield, as well as the risks of contamination and filter fouling, the frequency distributions for the output metrics revealed that neither process route offered the best of both NPV or product output. A product output criterion was formulated and the options that met the criterion were compared based on their reward/risk ratio. The perfusion option was no longer feasible as it failed to meet the product output criterion and the fed-batch option had a 100% higher reward/risk ratio. The tool indicated that in this particular case, the probabilities of contamination and fouling in the perfusion option need to be reduced from 10% to 3% for this option to have the higher reward/risk ratio. The case study highlighted the limitations of relying on deterministic analysis alone.

The article examines how a small set of easily implemented micro biochemical engineering procedures combined with regime analysis and bioprocess models can be used to predict industrial scale performance of biopharmaceutical protein downstream processing. This approach has been worked on in many of our studies of individual operations over the last 10 years and allows preliminary evaluation to be conducted much earlier in the development pathway because of lower costs. It then permits the later large scale trials to be more highly focused. This means that the risk of delays during bioprocess development and of product launch are reduced. Here we draw the outcomes of this research together and illustrate its use in a set of typical operations; cell rupture, centrifugation, filtration, precipitation, expanded bed adsorption, chromatography and for common sources, E. coli, two yeasts and mammalian cells (GS-NSO). The general approach to establishing this method for other operations is summarized and new developments outlined. The technique is placed against the background of the scale-down methods that preceded it and complementary ones that are being examined in parallel. The article concludes with a discussion of the advantages and limitations of the micro biochemical engineering approach versus other methods.

Biopharmaceutical manufacture is subject to numerous risk factors that may affect operational costs and throughput. This paper discusses the need for incorporating such uncertainties in decision-making tools in order to reflect the inherent variability of process parameters during the operation of a biopharmaceutical plant. The functionalities of a risk-based prototype tool to model cost summation, perform mass balance calculations, simulate resource handling, and incorporate uncertainties in order to evaluate the potential risk associated with different manufacturing strategies are demonstrated via a case study. The case study is based upon the assessment of pooling strategies in the perfusion culture of mammalian cells to deliver a therapeutic protein for commercial use. Monte Carlo simulations, which generate random sample behaviors for probabilistic factors so as to imitate the uncertainties inherent in any process, have been applied. This provides an indication of the range of possible output values and hence enables trends or anomalies in the expected performance of a process to be determined.

Demands within the pharmaceutical sector to cut costs and improve process efficiencies have grown considerably in recent years. Major challenges exist for companies trying to establish financially viable and robust manufacturing processes for increasingly complex therapeutics. These issues have driven the investigation of miniaturised process-design techniques by which to identify suitable operating conditions using small volumes of feed material typical of that available in the early stages of bioprocess development. Such techniques are especially valuable for the optimisation of chromatographic separations, which often represent a significant percentage of manufacturing costs and hence for which there is a pressing need to determine the best operating policies. Several methods employing microlitre volumes of sample and resin have been explored recently, which are aimed at the high-throughput and cost-effective exploration of the design space for chromatographic separations. This methodology paper reviews these microscale approaches and describes how they work, gives examples of their application, discusses their advantages and disadvantages and provides a comparative assessment of the different methods, along with a summary of the challenges that remain to be overcome in relation to these techniques.

Time to market, cost effectiveness, and flexibility are key issues in today's biopharmaceutical market. Bioprocessing plants based on fully disposable, presterilized, and prevalidated components appear as an attractive alternative to conventional stainless steel plants, potentially allowing for shorter implementation times, smaller initial investments, and increased flexibility. To evaluate the economic case of such an alternative it was necessary to develop an appropriate costing model which allows an economic comparison between conventional and disposables-based engineering to be made. The production of an antibody fragment from an E. coli fermentation was used to provide a case study for both routes. The conventional bioprocessing option was costed through available models, which were then modified to account for the intrinsic differences observed in a disposables-based option. The outcome of the analysis indicates that the capital investment required for a disposables-based option is substantially reduced at less than 60% of that for a conventional option. The disposables-based running costs were evaluated as being 70% higher than those of the conventional equivalent. Despite this higher value, the net present value (NPV) of the disposables-based plant is positive and within 25% of that for the conventional plant. Sensitivity analysis performed on key variables indicated the robustness of the economic analysis presented. In particular a 9-month reduction in time to market arising from the adoption of a disposables-based approach, results in a NPV which is identical to that of the conventional option. Finally, the effect of any possible loss in yield resulting from the use of disposables was also examined. This had only a limited impact on the NPV: for example, a 50% lower yield in the disposable chromatography step results in a 10% reduction of the disposable NPV. The results provide the necessary framework for the economic comparison of disposables and conventional bioprocessing technologies.