Economic analysis of royalactin production under uncertainty: Evaluating the effect of parameter optimization.

Royalactin is a protein with several different potential uses in humans. Research, in insects and in mammalian cells, has shown that it can accelerate cell division and prevent apoptosis. The method of action is through the use of the epidermal growth factor receptor, which is present in humans. Potential use in humans could be to lower cholesterolemic levels in blood, and to elicit similar effects to those seen in bees, e.g., increased lifespan. Mass production of Royalactin has not been accomplished, though a recent article presented a Pichia pastoris fermentation and recovery by aqueous two-phase systems at laboratory scale as a possible basis for production. Economic modelling is a useful tool with which compare possible outcomes for the production of such a molecule and in particular, to locate areas where additional research is needed and optimization may be required. This study uses the BioSolve software to perform an economic analysis on the scale-up of the putative process for Royalactin. The key parameters affecting the cost of production were located via a sensitivity analysis and then evaluated by Monte Carlo analysis. Results show that if titer is not optimized the strategy to maintain a low cost of goods is process oriented. After optimization of this parameter the strategy changes to a product-oriented and the target output becomes the critical parameter determining the cost of goods. This study serves to provide a framework for the evaluation of strategies for future production of Royalactin, by analyzing the factors that influence its cost of manufacture. © 2015 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 2015

Challenges of developing decision-support LCA tools in the biopharmaceutical industry

The biopharmaceutical industry has been slow in carrying out LCA analyses. However, as the industry matures, the level of scrutiny placed on this industry by international governments will increase and hence, there is an urgent need for the industry to implement decision-support tools for the decision-making processes. Decision-support tools based on life cycle assessment (LCA) can be potentially used for application in the biopharmaceutical industry as an aid to decision making. This paper sets out the challenges associated with developing such decision-support LCA tools. This paper highlights that in order for the industry to overcome these challenges and successfully develop decision-support LCA tools, they require a broader understanding of the biopharmaceutical manufacturing processes and LCA methodology

Integrated economic and experimental framework for screening of primary recovery technologies for high cell density CHO cultures

Increases in mammalian cell culture titres and densities have placed significant demands on primary recovery operation performance. This article presents a methodology which aims to screen rapidly and evaluate primary recovery technologies for their scope for technically feasible and cost-effective operation in the context of high cell density mammalian cell cultures. It was applied to assess the performance of current (centrifugation and depth filtration options) and alternative (tangential flow filtration (TFF)) primary recovery strategies. Cell culture test materials (CCTM) were generated to simulate the most demanding cell culture conditions selected as a screening challenge for the technologies. The performance of these technology options was assessed using lab scale and ultra scale-down (USD) mimics requiring 25-110mL volumes for centrifugation and depth filtration and TFF screening experiments respectively. A centrifugation and depth filtration combination as well as both of the alternative technologies met the performance selection criteria. A detailed process economics evaluation was carried out at three scales of manufacturing (2,000L, 10,000L, 20,000L), where alternative primary recovery options were shown to potentially provide a more cost-effective primary recovery process in the future. This assessment process and the study results can aid technology selection to identify the most effective option for a specific scenario

Economic analysis of Uricase production under uncertainty: Contrast of chromatographic purification and aqueous two-phase extraction (with and without PEG recycle)

Uricase is the enzyme responsible for the breakdown of uric acid, the key molecule leading to gout in humans, into allantoin, but it is absent in humans. It has been produced as a PEGylated pharmaceutical where the purification is performed through three sequential chromatographic columns. More recently an aqueous two-phase system (ATPS) was reported that could recover Uricase with high yield and purity. Although the use of ATPS can decrease cost and time, it also generates a large amount of waste. The ability, therefore, to recycle key components of ATPS is of interest. Economic modelling is a powerful tool that allows the bioprocess engineer to compare possible outcomes and find areas where further research or optimization might be required without recourse to extensive experiments and time. This research provides an economic analysis using the commercial software BioSolve of the strategies for Uricase production: chromatographic and ATPS, and includes a third bioprocess that utilises material recycling. The key parameters that affect the process the most were located via a sensitivity analysis and evaluated with a Monte Carlo analysis. Results show that ATPS is far less expensive than chromatography, but that there is an area where the cost of production of both bioprocesses overlap. Furthermore, recycling doesn't impact the cost of production. This study serves to provide a framework for the economic analysis of Uricase production using alternative techniques. This article is protected by copyright. All rights reserved

Simplex-based optimization of numerical and categorical inputs in early bioprocess development: Case studies in HT chromatography

Bioprocess development studies often involve the investigation of numerical and categorical inputs via the adoption of Design of Experiments (DoE) techniques. An attractive alternative is the deployment of a grid compatible Simplex variant which has been shown to yield optima rapidly and consistently. In this work, the method is combined with dummy variables and it is deployed in three case studies wherein spaces are comprised of both categorical and numerical inputs, a situation intractable by traditional Simplex methods. The first study employs in silico data and lays out the dummy variable methodology. The latter two employ experimental data from chromatography based studies performed with the filter‐plate and miniature column High Throughput (HT) techniques. The solute of interest in the former case study was a monoclonal antibody whereas the latter dealt with the separation of a binary system of model proteins. The implemented approach prevented the stranding of the Simplex method at local optima, due to the arbitrary handling of the categorical inputs, and allowed for the concurrent optimization of numerical and categorical, multilevel and/or dichotomous, inputs. The deployment of the Simplex method, combined with dummy variables, was therefore entirely successful in identifying and characterizing global optima in all three case studies. The Simplex‐based method was further shown to be of equivalent efficiency to a DoE‐based approach, represented here by D‐Optimal designs. Such an approach failed, however, to both capture trends and identify optima, and led to poor operating conditions. It is suggested that the Simplex‐variant is suited to development activities involving numerical and categorical inputs in early bioprocess development

Estimating preferences for modes of drug administration: The case of US healthcare professionals

BACKGROUND: There are hidden drug administration costs that arise from a mismatch between end-user preferences and how manufacturers choose to formulate their drug products for delivery to patients. The corollary of this is: there are "intangible benefits" from considering end-user preferences in manufacturing patient-friendly medicines. It is important then to have some idea of what pharmaceutical manufacturers should consider in making patient-friendly medicines and of the magnitude of the indirect benefits from doing so. OBJECTIVES: This study aimed to evaluate preferences of healthcare professionals in the US for the non-monetary attributes of different modes of drug administration. It uses these preference orderings to compute a monetary valuation of the indirect benefits from making patient-friendly medicines. METHODS: A survey collected choice preferences of a sample of 210 healthcare professionals in the US for two unlabelled drug options. These drugs were identical except in the levels of attributes of drug administration. Using the choice data collected, statistical models were estimated to compute gross welfare benefits, measured by the expected compensating variation, from making drugs in a more patient-friendly manner. RESULTS: The monetary value of end-user benefits from developing patient-friendly drug delivery systems is: (1) as large as the annual acquisition costs per full treatment episode for some biologic drugs; and (2) likely to fall in the "high end" of the distribution of the direct monetary costs of drug administration. CONCLUSIONS: An examination of end-user preferences should help manufacturers make more effective and efficient use of limited resources for innovations in drug delivery system, or manufacturing research in general

Optimisation-based Framework for Resin Selection Strategies in Biopharmaceutical Purification Process Development

This work addresses rapid resin selection for integrated chromatographic separations when conducted as part of a high-throughput screening (HTS) exercise during the early stages of purification process development. An optimisation-based decision support framework is proposed to process the data generated from microscale experiments in order to identify the best resins to maximise key performance metrics for a biopharmaceutical manufacturing process, such as yield and purity. A multiobjective mixed integer nonlinear programming (MINLP) model is developed and solved using the ε-constraint method. Dinkelbach's algorithm is used to solve the resulting mixed integer linear fractional programming (MILFP) model. The proposed framework is successfully applied to an industrial case study of a process to purify recombinant Fc Fusion protein from low molecular weight and high molecular weight product related impurities, involving two chromatographic steps with 8 and 3 candidate resins for each step, respectively. The computational results show the advantage of the proposed framework in terms of computational efficiency and flexibility. This article is protected by copyright. All rights reserved

Effects of bed compression on protein separation on gel filtration chromatography at bench and pilot scale

BACKGROUND: Poorly packed chromatography columns are known to reduce drastically the column efficiency and produce broader peaks. Controlled bed compression has been suggested to be a useful approach for solving this problem. Here the relationship between column efficiency and resolution of protein separation are examined when preparative chromatography media were compressed using mechanical and hydrodynamic methods. Sepharose CL-6B, an agarose based size exclusion media was examined at bench and pilot scale. The asymmetry and height equivalent of a theoretical plate (HETP) was determined by using 2% v/v acetone, whereas the void volume and intraparticle porosity (ε p ) were estimated by using blue dextran. A protein mixture of ovalbumin (chicken), bovine serum albumin (BSA) and γ'- globulin (bovine) with molecular weights of 44, 67 and 158 kDa, respectively, were used as a 'model' separation challenge. RESULTS: Mechanical compression achieved a reduction in plate height for the column with a concomitant improvement in asymmetry. Furthermore, the theoretical plate height decreased significantly with mechanical compression resulting in a 40% improvement in purity compared with uncompressed columns at the most extreme conditions of compression used. CONCLUSION: The results suggest that the mechanical bed compression of Sepharose CL-6B can be used to improve the resolution of protein separation