When should I start using bioreactors?
Many of Culture’s clients have questions pertaining to the right time to transition to bioreactors when developing a bioproduct for commercialization. This next series of blog posts focuses on several early-stage scenarios where bioreactors can be used to not only develop the framework for a project, but also accelerate progress at project stages often considered too early for bioreactors.
Part 1 - Determining Commercial Viability
The commercial viability of any bioproduct should be assessed via techno-economic analysis (TEA) prior to starting any large-scale work. A TEA develops a financial model based on specifics of the process to determine whether the targeted cost of a product is feasible from a process and strain engineering perspective. To develop a comprehensive analysis, there are a number of inputs required to build an accurate model.
While some of the TEA inputs, such as the growth rate of a host strain, can be determined based on publicly available data or institutional knowledge, there is often great value in performing preliminary experiments to validate assumptions empirically. The cost of bringing a new bioproduct to market is large, and experimental validation of some key assumptions at the outset of a program can help avoid costly mistakes months or even years into development. Here, we have outlined many areas where preliminary work in bioreactors can be immensely valuable. These are ideal studies to be performed in Culture’s cloud bioreactors.
There are a number of different model organisms used in industrial bioprocesses, including Saccharomyces cerevisiae, Escherichia coli, and Pichia pastoris. Beyond the common model organisms, there is a dizzying array of microbes that have the potential to produce different natural products under various conditions. Incredibly, there is a virtually infinite number of products that can be produced by microbes with the enzyme function prediction tools and modern genetic engineering techniques available today.
The ideal microbe for the production of any bioproduct will be determined by a combination of the physiology of the organism (e.g. native fluxes to precursors, substrate compatibility), the genetic tools available for the modification of the organism, and the relative complexity of the proposed metabolic pathway. Often, there are several candidate organisms for the production of a molecule and several factors may influence which organism is best suited for a particular product.
Empirical testing of different baseline strain performance metrics can help inform whether an organism will perform as modeled in an initial TEA. While genetic engineering can change strain phenotypes, a baseline assessment can help determine whether or not an organism will likely meet the performance metrics required for a commercially viable process. These tests can be performed with a single or multiple host candidate(s) to verify downstream suitability.
Some of the factors that may be tested to assess the suitability of a strain for large-scale biomolecule production include:
Microbial growth rates of a candidate host can be tested in a bioreactor to determine if the growth phase of the host will fit within the modelled timing. A major factor in determining the overall cost of a bioprocess is the run time, and if a wildtype or early production strain does not meet the required specific growth rate (μ) metrics, then a mature production strain will likely also fall short.
Substrate uptake rates
The production of a biomolecule will be a function of substrate uptake rates (qs) and how that substrate is assimilated by the microbe into biomass, maintenance, and ultimately, product. A TEA will have a targeted productivity (qp) of the biomolecule created in order to achieve the desired titer within the modelled run time. From this and the modelled metabolic pathway, the substrate uptake rates required to achieve the modelled productivity can be determined. If the substrate uptake rate is lower than the required productivity when taking into account other requirements, it will be difficult to achieve the desired biomolecule productivity.
Suitability for manufacturing-scale reactors
Bioreactors at manufacturing scale have a number of constraints due to the sheer size of the reactors. In order to determine if an organism and the proposed process are feasible from a scalability standpoint, preliminary studies can be performed in smaller bioreactors. For example, large reactors typically have upper limits on oxygen transfer rates. Testing if oxygen uptake rates at the desired biomass are consistent with rates standard for large scale reactors can help determine whether or not the process will be viable at scale.
In addition, microbes slated for manufacturing-scale processes should display a level of process robustness aligned with the conditions encountered at manufacturing scale. Robustness tests, particularly for novel microorganisms where there is little data available, can inform whether the microbe can withstand the challenging conditions encountered at scale, such as extended hold times between scales, many generations before reaching production scale, and oscillations in process setpoints. Simulating these parameters in small-scale bioreactors can help determine whether or not a microbe is well suited to the rigors of a large-scale production environment.
Raw material requirements
One of the significant inputs into a TEA are the raw material costs required for the proposed cultivation. Several of these materials, especially components such as trace metals or vitamins, can be costly, and the amount required can significantly impact the overall cost of the process and economics of the model. Empirical determination of yield coefficients, or the amount of each substrate consumed to generate a defined amount of biomass, can help estimate media costs for a process. Additionally, many bioprocesses require the use of raw substrates that are relatively unrefined in comparison to lab-grade chemicals. These industrial grade substrates may contain impurities or seasonal variation. Where possible, it is worthwhile to determine if the proposed organism can utilize substrates used in the TEA without any negative impact on growth. Testing various sources or lots of the proposed substrate can also determine whether a microbe may demonstrate performance variability depending on the source of the substrate.
Many bioproducts must be produced at relatively high titers in order to reach commercial viability. However, these concentrations may have negative, toxic impacts on the microbes that produce them. Product toxicity can place an upper limit on the titers of a product produced by a microbe or dramatically decrease the rate at which the product is produced. Both have an impact on the economics of a process, and it is important to factor product toxicity into economic models. While process or strain engineering efforts can be used to mitigate toxicity, they are rarely able to completely eliminate the impact of a toxic product. Additionally, early indications of product toxicity can be used as a signal to include these mitigation measures in long-term project plans.
While toxicity studies can be performed in shake flasks or microtiter plates, they may not fully demonstrate the impact of product toxicity in the milieu of a bioreactor. These other platforms typically support much lower levels of biomass and have limited pH control. Additionally, toxicity studies in these platforms are most often performed as spike-in studies using high concentrations of the product of interest. This is not reflective of the bioreactor process, where high cell densities are typically producing product at a slower rate in a controlled environment. Therefore, in order to have a more accurate assessment of potential product toxicity, studies should be performed in an environment comparable to manufacturing-scale reactors.
While preliminary studies of an early production strain or even a wildtype microbe may not be completely reflective of the behavior of a commercial production strain, experiments can provide empirical data to inform inputs into a TEA and provide early indications that a shift in strategy may be required for long term success. Importantly, introducing bioreactors early in process development is well justified given the substantial cost required to commercialize a bioprocess.
It is important to remember that the relatively high proportion of bioprocesses that fail to scale are due to factors that may be revealed by experimentally derived data points used to inform a TEA.