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Plasmid DNA, mRNA and Viral Vectors – the Building Blocks of Cell and Gene Therapy Processing

The growing pipeline of cell and gene therapy therapies has led to an increase in demand for gene delivery vehicles such as plasmid DNA (pDNA), messenger RNA (mRNA) and viral vectors. They can be used as stand-alone treatments or can be used as starting materials required for further processing of cell and gene therapeutics. When used as starting materials, they have been shown to have a significant impact on the cost of final cell and gene therapy products[i],[ii],[iii].

Determining the amount of pDNA, mRNA and viral vector to manufacture and selecting the right scale of operation to meet requirements is foundational to predictable manufacturing costs and timely production for final cell and gene therapy product. As viral vectors are frequently generated through transient expression routes, which depend on the availability of two, three or four pDNA constructs, considerations of requirements of this starting material need to be considered. The same approach goes for mRNA-based therapeutics that have had increased visibility due to potential Covid-19 vaccine. This class of therapeutics begins with the generation of pDNA containing the corresponding sequence for the mRNA construct and therefore also heavily reliant on the effective and reliable generation of pDNA. As several mRNA vectors encoding for different target proteins can be used in one therapy simultaneously, each of these would also require a specific pDNA template. For a given marketed cell therapy product, annual requirements are estimated at 100-1000g for each pDNA vector[iv], and a total of 109-1015 viral particles[v]. Biosolve Process can be used to model each specific pDNA construct, mRNA process, as well as both stable or transiently transfected viral vector manufacturing processes. BioSolve Process can estimate scale requirements to meet future demands and associated manufacturing costs, whilst considering any intrinsic expression titer and yield variations.

Plasmid DNA production is commonly done by recombinant E. coli fermentation where there are significant issues with batch-to-batch consistency and variability in expression titer. This is also the case for adeno-associated viruses (AAV) and lentiviruses, commonly used in the development of CAR-T cell therapy products. Even though most virus production is undertaken by adherent cells, it is desirable to develop stable suspension cell lines that can increase the productivity of viral particles and minimize the amount of costly pDNA and other reagents used in the transfection process. Downstream operations in current viral vector production processes result in low virus recovery and purification yields. Alternative methods for clarification and particle capture that do not affect viral potency are required[vi]. Messenger RNA starts with generation of linearized pDNA and it is produced via in vitro transcription, purification and subsequently introduced into cells. The process is in essence a chemical synthesis with potency of final product highly dependent on purification process. Novel technologies and an array of different processing criteria can be considered using Biosolve Process model to help pre-screen solutions that will have the biggest impact on overall process costs and influence upon scaling-up.

Many cell therapy companies are outsourcing the manufacture of these starting materials, but with few specialized contract manufacturing organizations (CMOs) and their limited capacity, it creates a supply chain bottleneck, posing additional risks whilst also coming with high price tag. At the same time CMOs are being asked to provide a set cost on a per Kg of pDNA, which is driving efficiencies across the board. This trend is expected to extend to mRNA and viral vectors production, when used as starting materials. Given the relatively small-scale of these processes, the introduction of single-use technologies has increasingly been adopted by CMOs and producers alike as one of the answers to help streamline production; using single-use bioreactors[vii], mixing bags, prepacked columns, disposable filtration systems, amongst others. Biosolve Process model has been used extensively to provide estimates of bioprocess manufacturing costs and to help drive process efficiencies by highlighting key cost drivers and hence areas to focus improvement efforts on. Biosolve Process may also aid in the decision on whether to manufacture in house or outsource, considering internal capabilities such as the requirement of GMP quality/regulatory requirements which may be a burden to smaller companies.

For viral vectors it is expected that the industry standard production models will move away from adherent and/or cell factories and into suspension-based upstream processes. The trend is also to move towards continuous processing approaches to meet increasing demands. This is expected to transform the field in the next few years with the promise to reduce manufacturing costs further. Biosolve Process model also has been used to model continuous bioprocesses with emphasis on perfusion cultures and continuous chromatography[viii],[ix],[x][xi].

We at Biopharm Services provide Biosolve Process web based demonstrations to potential users and support with training to existing clients.  We are in the process of getting pDNA, mRNA, viral vector and cell therapy processes to be genericized for users’ use. If there is something you would like to consider please contact us at info@biopharmservices.com.

[i] A.G. Lopes, R. Noel, A. Sinclair. Cost Analysis of Vein-to-vein CAR T-Cell Therapy: Automated Manufacturing and Supply Chain. Cell and Gene Ther Insights 2020 (in press)

[ii] Spink K, Steinsapir A. The long road to affordability: a cost of goods analysis for an autologous CAR-T process. Cell Gene Ther Insights 2019; 4: 1105–16

[iii] E. Cameau, A. Pedregal, C. Glover. Cost modelling comparison of adherent multi-trays with suspension and fixed-bed bioreactors for the manufacturing of gene therapy products. Cell & Gene Therapy Insights 2019; 5(11), 1663–1675

[iv] T. Hitchcock. Manufacturing Plasmid DNA: Ensuring Adequate Supplies for Gene and Cell Therapies. BioProcess International, Oct 2016

[v]  J. Rininger, A. Fennell, L. Schoukroun-Barnes, C. Peterson, J. Speidel. Capacity Analysis for Viral Vector Manufacturing: Is There Enough? BioProcess International, Dec 2019. (https://bioprocessintl.com/manufacturing/emerging-therapeutics-manufacturing/capacity-analysis-for-viral-vector-manufacturing-is-there-enough/)

[vi] R. Carbonell, A. Mukherjee, J. Dordick, C.J. Roberts. A Technology Roadmap For Today’s Gene Therapy Manufacturing Challenges. Cell & Gene, Guest Column, April 18, 2019  (https://www.cellandgene.com/doc/a-technology-roadmap-for-today-s-gene-therapy-manufacturing-challenges-0001)

[vii] A.G. Lopes, T.S. Castineinas, A. G. Hitchcock, D.C. Smith. Cost-Effective Process Development for Plasmid DNA Manufacture: Evaluation of Single-Use Technologies to Support Escherichia coli Culture. Bioprocess International, October 2015

[viii] K. Pleitta, B. Somasundarama, B. Johnsonb, E. Shavea, L.H.L. Lua. Evaluation of process simulation as a decisional tool for biopharmaceutical contract development and manufacturing organizations. Biochemical Engineering Journal 150 (2019) 107252

[ix] J. Hummel, M. Pagkaliwangan, X. Gjoka, T. Davidovits, R. Stock, T. Ransohoff, R. Gantier, M. Schofield. Modeling the Downstream Processing of Monoclonal Antibodies Reveals Cost Advantages for Continuous Methods for a Broad Range of Manufacturing Scales. Biotechnol. J. 2019, 14, 1700665

[x] D. Pollard, M. Brower, Y. Abe, A.G. Lopes, A. Sinclair. Standardized Economic Cost Modeling for Next-Generation MAb Production. BioProcess International, Sep 2016. (https://bioprocessintl.com/business/economics/standardized-economic-cost-modeling-next-generation-mab-production/)

[xi] J. Walthera, R. Godawata, C. Hwanga, Y. Abe, A. Sinclair, K. Konstantinov. The business impact of an integrated continuous biomanufacturing platform for recombinant protein production. Journal of Biotechnology, Volume 213, 10 November 2015, Pages 3-12.