Statistical analysis of quantification data on three or more replicates is advised. Users need to determine how to apply statistical analysis on the data using a separate tool. Benjamini-Hochberg multiple hypothesis test has been used to determine significant regulated PTM peptide groups in 15N metabolic labeled samples . A standardized statistic pipeline for protein quantification is still lacking, particularly a pipeline that can leverage quantification ratios of each peptide from a protein. Our current work flow uses a median value, which takes advantage of the quantification ratios of each peptide but is less affected by outliers than using the mean. However, the statistical power utilizing quantifications from these multiple peptides from single protein has not been explored and awaits development in the future. A targeted quantification strategy is recommended for further analysis of proteins of interest because this provides more accurate quantification and is less likely to have missing values, particularly in the 15N labeled samples . In addition to targeted analysis, data-independent acquisition can also be utilized, which can be done in label free samples or combined with 15N metabolic labeling in the future. DIA benefits from having few missing values, but more efforts will be needed to deconvolve the mixed MS2 spectra in DIA datasets. 15N metabolic labeling has been utilized in studies of analyzing protein synthesis and degradation . These studies are based on incomplete and often low incorporation rates which result in very broad satellite peak distributions and cause 15N labeled peptide isotope clusters to overlap with 14N labeled peptide clusters. As Protein Prospector doesn’t deconvolve the 15N distribution from the 14N distributions , the presented work flow will not provide accurate quantification in this type of study. On the other hand, for chase studies that analyze the assembly kinetics in vitro ,hydroponic indoor growing system the presented work flow can be applied because the proteins involved have a very high labeling efficiency.

This work flow can be also applied to the quantification of post-translational modification with a slight modification. The users will include related PTM search parameters into data search. Instead of reporting median number at protein level, ratios from each peptide are reported and then compared across different replicates. This study represents original research on the manufacture of plant-made biologics and plant-made industrial products through application of analytical modeling tools in silico. The main goal of this study was to evaluate unit operations in two plant-made bio-manufacturing processes and estimate the cost of goods of the active ingredient and the impact of those costs on the cost of the final product. A secondary but equally important goal was to compare the manufacturing cost of plant-produced AI to the cost of the same AI manufactured by predecessor technologies. Much progress has been made towards the development of manufacturing infrastructure for plant-made pharmaceuticals , which typically consist of recombinant proteins applied as vaccine antigens, therapeutic enzymes, or monoclonal antibodies. Progress has also been made in the manufacture of plant-based biologics, biochemicals, and bio-materials for industry, food, and other applications. Significant and industrially relevant advances in gene expression and bio-processing methods have been achieved during the past two decades, as reviewed in several prior studies. Yet, to date, only three PMP products have been approved by regulatory agencies for commercial sale, including an anti-caries antibody , an animal health vaccine , and a therapeutic enzyme to manage a metabolic disorder. This relative scarcity of PMP products reflects the magnitude of the challenges in creating a new manufacturing industry. The development of the plant-based platform has slowly progressed through a multinational “labor of love” in the absence of the levels of investment originally made by the biopharmaceutical industry , which resulted in elevation of fermentation-based systems to their current level of dominance.Interestingly, beginning in 2009, the US Defense Advanced Research Projects Agency’s Blue Angel program made several multi-million dollar investments at various sites with the goals of accelerating the scale up of the PMP infrastructure and assessing production of relevant volumes of pandemic influenza candidate antigens as a model product to test the plant-based platform .

This was a shared investment initiative, and as a result of federal and state government and private investments, the expanded PMB manufacturing capacity should now support production of at least several of the many plant-made vaccines, bio-therapeutics, bio-materials, and bio-catalysts that are under development by companies and institutions worldwide . Although capacity expansion helped companies that would manufacture their own or partnered products , these investments also helped expand capacity at PMP contract development and manufacturing organizations such as Kentucky Bio-Processing . This was important to our modeling because the decision to construct a new dedicated manufacturing facility versus contracting services from a CDMO could yield very different cost-of-goods projections. Fundamental to the commercial introduction of PMB products is the availability of an efficient plant-based manufacturing infrastructure that is at a minimum competitive with and ideally superior to traditional animal cell and microbial fermentation systems as well as to extraction from raw materials from natural sources. The cost to manufacture any product is of paramount importance to its market acceptability, availability to those who need it most, and to the profitability of the product for its manufacturer. While plant based technologies are often assumed to offer significant cost advantages relative to cell-based fermentation, such assumptions are based on the lower upstream capital investments required for plant growth, lower cost of media, no adventitious agent removal, and other factors. However, few of these studies have listed engineering process assumptions or analyzed unit operations adequately; reports such as those of Evangelista et al. and Nandi et al. are exceptions. Therefore, results of recent technoeconomic evaluations for PMP/PMB/PMIP have not been widely available in the public literature. To analyze and quantify the cost efficiency of plant based manufacturing, we chose two enzymes representing active ingredients for diverse product classes and derived for each AI the bulk product and perdose or per-unit costs. The first target analyzed is human butyrylcholinesterase , an enzyme that can act as a bio-scavenger to counteract the effects of cholinesterase inhibitors such as sarin and that is a candidate for bio-defense countermeasures in several countries. While this product would encounter market dynamics that are different from other commercial products, it is nevertheless designed to satisfy an important component of public safety and merits review. Currently, BuChE is extracted from outdated human blood supplies, but it can also be made recombinantly in cell culture, transgenic animals, and plant systems.

The second case study focuses on the cellulase complex, a mixture of 4–6 enzymes used to saccharify cellulosic feed stocks for the production of ethanol as a fuel extender. This target was selected for study because, for more than 30 years, the cost of cellulases has been a major impediment to the economic viability of cellulosic ethanol programs. Cellulases were also selected because they represent an extremely costsensitive product class on which to conduct case studies. We reasoned that if plant-based manufacturing showed economic promise for this class, then the economically advantageous production of less cost-sensitive bio-therapeutics and other products might also be anticipated. In contrast to BuChE, which consists of a purified molecule, the cellulase complex would be expressed in plants that are cultivated near the cellulosic feed stock and the bio-ethanol refinery and stored as silage without purification; the semidried catalyst biomass is mixed on demand with the cellulosic feed stock to initiate saccharification followed by fermentation. This approach varies significantly from previous approaches in which cellulase enzymes are produced via fermentation processes using native or engineered microorganisms. For the cellulase case study,vertical rack system the plant-based cellulase production process is compared with a recent technoeconomic analysis of cellulase enzymes produced from Trichoderma reesei fermentation using steam-exploded poplar as a nutrient source.The technoeconomic modeling for both case studies was performed using SuperPro Designer, Version 9.0 , a software tool for process simulation and flow sheet development that performs mass and energy balances, equipment sizing, batch scheduling/debottlenecking, capital investment and operating cost analysis, and profitability analysis. This software has been used to estimate cost of goods in a variety of process industries including pharmaceuticals produced by fermentation and plantmade pharmaceuticals. It is particularly useful at the early, conceptual plant design stage where detailed engineering designs are not available or warranted. SuperPro Designer was chosen because it has built-in process models and an equipment cost database for typical unit operations used in the biotechnology industry, such as bioreactors, tangential flow ultrafiltration and diafiltration, chromatography, grinding/homogenization, and centrifugation. There are some unit operations and processes used in the case studies that are currently not included in SuperPro Designer, such as indoor or field plant cultivation, plant harvesting, vacuum agroinfiltration, and screw press/disintegrator. For the butyrylcholinesterase case study, SuperPro Designer’s “Generic Box” unit procedure was used to model these unit operations. For the cellulase case study, the indoor unit operations were modeled with the same software while the field production calculation and costs were tracked in Microsoft Excel spreadsheets. Unless otherwise noted, the costs of major equipment, unit operation-specific labor requirements and costs , pure components, stock mixtures, heat transfer agents, power and consumables used in the analyses were determined using the SuperPro Designer built-in equipment cost model and default data banks. For the cellulase case study, the program’s parameters such as water costs and total capital investment distributed cost factors were set to be the same as those used in the model described in Klein-Marcuschamer et al.; this SuperPro Designer model is also available at the Joint Bioenergy Institute technoeconomic analysis wiki site . Additional case study specific design parameters were selected based on experimental data from journal articles, patent literature, the authors’ laboratory, interviews with scientists and technologists conducting the work cited, technical specification sheets or correlations, heuristics, or assumptions commonly used in the biotechnology and/or agricultural industry.

The case study models were based on a new “greenfield” facility, operating in batch mode, although annual production costs neglecting the facility dependent costs were also determined to predict annual production costs using an existing facility. For the butyrylcholinesterase case study, annual operating time of 7920 hours for the facility was used with indoor grown Nicotiana benthamiana plants. For the cellulase case study, since the tobacco plants are grown in the field, it is assumed that plant growth occurs for 215 days of the year and the indoor facility is in operation for 127 days per year . For comparative purposes in the cellulase case study, the laboratory/QA/QC costs were neglected since they were neglected in the JBEI model and such costs are likely to be a minor component for the industrial enzyme case study. The following items were also neglected in both case studies: land costs, upfront R&D, upfront royalties, and regulatory/certification costs as these can vary widely.For the butyrylcholinesterase case study, the process flow sheet was split into separate modules to better understand the contributions of various process segments.Process flow and unit operations were derived from published methods and results from a number of sources as indicated in each case study, and from interviews with leading gene expression, agronomy, and manufacturing scientists and engineers who have participated in the development and scale-up of the processes described. On the basis of this information, the SuperPro Designer software was applied to calculate material inputs and outputs, bulk, and per-dose or per-unit costs.The two AI classes evaluated in these studies are produced in Nicotiana host plants. Nicotiana species, notably N. tabacum, N. excelciana, and N. benthamiana, are preferred hosts for PMB manufacture due to their metabolic versatility, permissiveness to the propagation of various viral replicons, and high expression yields achievable with a wide range of targets, as reviewed by Pogue et al., De Muynck et al., Thomas et al., Gleba et al., and others. Use of these hosts for production of clinical trial materials is also familiar to FDA and other regulatory agencies, thus facilitating Nicotiana’s acceptance in regulation-compliant manufacturing.The enzyme is a globular, tetrameric serine esterase with a molecular mass of approximately 340 kDa and a plasma half-life of about 12 days; the plasma 1/2 is largely a function of correct sialylation. BuChE has several activities, including the ability to inactivate organophosphorus nerve agents before they can cause harm.