At the core of the biotechnology industry is the development of fermentation processes, generating useful end products via complex fermentations. Maintaining optimal conditions for these processes is key to ensuring high quality and low costs, but complications often arise due to unintended variations in process variables - with one significant variable being parameter gradients.
Gradients in cultivation conditions have been shown to happen in large-scale processes due to limitations in mixing. Since gradients have the ability to significantly affect a microorganism’s metabolism, leading to altered productivity, yield, and profitability, examining how these gradients relate to process quality is of interest from both economic and technical perspectives.
If unintended and unforeseen gradients are allowed within the reactor during production, there are likely to be detrimental effects to the performance of the process, which has a direct effect on the profitability of the product line. As process and organization maturity increases, the understanding of how these gradients affect the process outcomes should also increase, leading to more effective tactics for tracking and adjusting relevant variables within the process. However, actively allocating resources to understanding and resolving gradients at an earlier stage of process development can help boost process maturity and improve process efficiency and time to market.
From a financial perspective, it is also significantly more beneficial to conduct preventive rather than corrective action, to avoid delays and subsequent financial burdens from occurring. Improving process quality via the measurement and control of key gradients therefore also presents a strong business case, by enhancing economic performance of the process.
Given these benefits, which efficient and cost-effective methods to resolve potential gradient concerns, or understand processes well enough to avoid them in the first place should an organization evaluate? Options could include employing advance sensors that can analyze the fluid flow, such as flow-following sensors, modeling the conditions with CFD, or conducting processes in more standardized and easily configurable vessels, such as single-use bioreactors.
Even though measuring and regulating potential gradients in fermentation processes is likely to increase capital expenditure in initial phases of development, it should lower operating costs in the long term. Firstly, because detection and of gradients may reduce profit loss associated with delays, and secondly
Firstly, because detection and resolution of gradients may avoid difficulties in scaling up that lead to slower time to market. Secondly, avoiding variability issues once the process is in full production should result in a direct increase in yield and quality, and therefore a direct increase in the bottom line of the production.
Having a consistently high level of process quality, by controlling variables such as gradients, therefore simultaneously serves as a technical and financial benefit. By properly taking account of gradience in bioreactors, companies can establish production processes characterized by lower downtime, fewer faulty batches, and more competitive operating costs.
For companies, putting effort into understanding why gradients occur and their effects on a process and where gradients occur could be a substantial expenditure, but one that can also result in having fewer issues during development and production. Ultimately, these potential technical and financial benefits likely outweigh the required costs, making the case for investing in understanding gradients clear even in the most mature process.