Although bioreactor scale-up has been practiced for more than a century, successful implementation continues to rely on careful engineering analysis and biological understanding. Miscalculations in mixing time or other scale-dependent parameters can compromise product quality, process stability, and operational costs. The challenge becomes even greater when considering the scaling requirements of adherent cell systems, where conventional bioreactor scale-up strategies often reveal their limitations.
One of the obvious differences between a culture flask and a stirred tank, which has a direct impact on mixing time, is the presence of an impeller — bioreactor’s main agitating component, primarily chosen based on the manufactured cell culture (1). © Green Elephant Biotech.
Production-scale stainless steel bioreactors, frequently exceeding 10,000 L, remain standard equipment for large-scale manufacturing of biologics, particularly monoclonal antibodies (mAbs). One prominent example is adalimumab — commercially known as Humira®, widely used for chronic inflammatory conditions such as rheumatoid arthritis and Crohn’s disease. Since its introduction, the therapy has generated more than USD 231 billion in revenue, illustrating the enormous economic scale associated with biologics manufacturing (2).
Development and production of biologics rely heavily on chemical engineering principles, including heat and mass transfer, fluid dynamics, and reaction kinetics. These parameters have to be carefully manipulated to ensure efficient nutrient transport, metabolite removal, and ultimately product recovery (3).
Scaling from high-throughput bioreactors of 15-250 mL to vessels of several thousand liters will inevitably alter physical, chemical, and biological parameters within a culture system. To manage these changes, commonly applied scale-up criteria include maintaining constant power per unit volume (P/V), oxygen transfer coefficient (kLa), impeller tip speed (Vt), and mixing time (Tm), also referred to as homogenization time (3).
Mixing time represents the time required for a bioreactor’s contents to reach a homogeneous state, largely depending on turbulence intensity and bulk fluid circulation within the vessel (3). In practice, scale-up decisions are often informed by historical performance data from existing reactor systems, as maintaining uniformity of multiple parameters is rarely possible given technological limitations and biological variability.
Mixing time can absolutely determine the success of a bioprocess
Within cell culture workflows, bioreactor parameters are typically divided into two categories: scale-independent parameters and scale-dependent parameters. Scale-independent factors, including pH, temperature, dissolved oxygen, and media composition, remain relatively consistent across different reactor sizes. On the other hand, scale-dependent parameters depend on vessel geometry and directly influence fluid dynamics and mixing performance (3).
Mixing time is widely used to characterize stirring efficiency and is influenced by factors, such as agitation rate, impeller design, impeller diameter, along with the distance between the impeller and the bottom of the vessel. Measurement of mixing time commonly involves introducing a tracer substance — an acid, base, or concentrated salt solution — into the reactor and monitoring its concentration at a defined location within the tank.
After tracer addition, mixing time (here, Ct) is defined as the point at which the concentration of the tracer approaches its final uniform value (Cf), expressed mathematically as ∣C(t) − Cf∣ < 0.05–0.10 × (Cf − Ci) (3). When mixing time is used as the primary scale-up criterion, it provides valuable insight into mixing efficiency and its effect on cell viability (4).
Insufficient mixing can lead to cell sedimentation and localized zones of nutrient depletion, including oxygen deficiency. These gradients can promote the generation of reactive oxygen species (ROS), triggering cellular stress responses and potentially leading to senescence (4). Nevertheless, perfect mixing distribution is rarely achievable in industrial-scale reactors due to the high energy input required or the shear sensitivity of many cell types (3).
A successful system must balance shared hydrodynamic forces
Mixing time is closely linked to other scale-dependent parameters within a bioreactor system. For instance, when mixing time in a bioreactor is multiplied by impeller speed, dimensionless mixing time provides an estimate of the number of impeller revolutions required for homogeneous mixing. This metric enables comparison of mixing efficiency between geometrically similar reactors of different sizes during bioreactor scale-up (4).
Other closely related parameters include agitation or the mechanical mixing of the culture medium, and aeration – the introduction of gas into the system. Higher impeller speeds generally increase agitation intensity and fluid velocity, thereby shortening mixing time. Similarly, increased aeration generates bubble-induced turbulence, promoting circulation and further reducing mixing time (5).
Although the oxygen transfer rate (OTR) describes the rate at which oxygen is supplied to the culture, and mixing time governs how quickly oxygen is distributed throughout the vessel, both parameters depend on the same hydrodynamic forces. Increased agitation similarly breaks larger gas bubbles into smaller ones, increasing the gas-liquid interface and the oxygen transfer coefficient (kLa) (3).
During scale-up, however, larger vessels typically exhibit longer mixing times than smaller reactors. Maintaining equivalent oxygen transfer performance under identical power inputs therefore becomes challenging, illustrating a previously mentioned scale-up paradox (6). If mixing remains too slow relative to oxygen demand, localized oxygen depletion zones emerge, possibly causing irreversible damage to the manufactured product.
Mixing time may be a constraint, but adherent cell manufacturing is a challenge
While bioreactor scale-up alleviates the labor and spatial demands associated with operating hundreds of flasks, the inherent complexity of biological systems ensures that large-scale cultivation remains one of the most challenging aspects of the biopharmaceutical industry. Engineering equivalence between scales can improve mechanical efficiency, but it does not automatically guarantee biological equivalence (7).
The mismatch that may arise between mixing time and oxygen delivery illustrates why process performance must always be evaluated in the context of biological requirements rather than purely engineering targets. Failure to account for these interactions can lead to costly process failures, with development setbacks potentially exceeding USD 1-2 billion depending on the therapy under production (8).
Moreover, scale-up is not universally applicable. For therapies derived from anchorage-dependent cells, such as HEK293, Vero, HeLa, and induced pluripotent stem cells (iPSCs), mixing time in bioreactor is only one part of the challenge. In such cases, upstream manufacturing strategies often favor scale-out rather than scale-up (9).
Adherent cell systems face additional constraints, including limited growth surface area, restricted scalability relative to capital investment, and potential variability between batches. While adapting adherent cell lines to suspension culture may appear as an attractive alternative, this process introduces financial, operational, and regulatory challenges, particularly if implemented late in development (9).
Mixing time remains one of the most informative parameters in bioreactor scale-up, reflecting how an effective use of hydrodynamic forces directs the distribution of nutrients, gases, and metabolites throughout a culture system. The true significance of mixing time, however, emerges when interpreted alongside oxygen transfer, agitation dynamics, and biological demand.
Large-scale reactors provide the capacity required for commercial biologics production, but they also magnify the consequences of subtle imbalances between engineering design and cellular physiology. The increasing relevance of adherent cell therapies highlights the limits of traditional scale-up logic. When biological requirements dictate growth on surfaces rather than in suspension, simply expanding capacity through ever-larger vessels may no longer represent the most practical path forward.
CellScrew® is no exception to this discussion
Green Elephant Biotech team believes that understanding how parameters like mixing time interact with both physical and biological systems represents a critical factor in evolving and improving biomanufacturing processes.
The CellScrew® series supplies defined mixing and OTR for reproducible results akin to bench-top bioreactors in a number of cell lines. Discover the application notes in CHO-K1 and HEK293 by our R&D group and your cell manufacturing opportunities with CellScrew® today.
References:
- Magelli, D, Montante, G, Pinelli, D, Paglianti, A, Mixing time in high aspect ration vessels stirred with multiple impellers (2013), Chem Eng Sci 101, pp. 712-20. doi: 10.1016/j.ces.2013.07.022.
- Humira (adalimumab). (2022). The Pharmaceutical Accountability Foundation. Available https://www.pharmaceuticalaccountability.org/humira-adalimumab/#:~:text=Adalimumab (Humira): Introduction&text=Adalimumab (brand name: Humira),231 billion in global sales (Accessed 05 March 2026).
- Lessons in Bioreactor Scale-Up: Part 1 — Exploring Introductory Principles. (2024). Muhammad Arshad Chaudhry, BioProcess International. Available https://www.bioprocessintl.com/bioreactors/lessons-in-bioreactor-scale-up-part-1-mdash-exploring-introductory-principles (Accessed 05 March 2026).
- Lessons in Bioreactor Scale-Up, Part 2: A Refresher on Fluid Flow and Mixing. (2024). Muhammad Arshad Chaudhry, BioProcess International. Available https://www.bioprocessintl.com/bioreactors/lessons-in-bioreactor-scale-up-part-2-a-refresher-on-fluid-flow-and-mixing (Accessed 05 March 2026).
- Madhuri, PS, Moukthika, BS, Sumanth, N, Vinusha, KS, Ganduri, VSRK, Effects of agitation and aeration in mixing time determination for viscous suspensions using Double Indicator System (2016), Research J Pharm and Tech 9, pp. 1971-77. doi: 10.5958/0974-360X.2016.00403.0.
- Bisgaard, J, Muldbak, M, Tajsoleiman, T, Rydal, T, Rasmussed, T, Huusom, JK, Gernaey, KV, Characterization of mixing performance in bioreactors using flow-following sensor devices (2021), Chem Eng Res Des 174, pp. 471-85. doi: 10.1016/j.cherd.2021.08.008.
- The Myth of Bioreactor Scale-Up: A Biology-First Approach to Achieving Robust Manufacturing. (2026). Naveenganesh Muralidharan, BioProcess International. Available https://www.bioprocessintl.com/bioreactors/the-myth-of-bioreactor-scale-up-a-biology-first-approach-to-achieving-robust-manufacturing (Accessed 06 March 2026).
- Batch Failure Rates in Biomanufacturing. (2008). Eric S. Langer, Genetic Engineering & Biotechnology News. Available https://www.genengnews.com/insights/batch-failure-rates-in-biomanufacturing/ (Accessed 06 March 2026).
- Baghirzade, R, Adherent versus suspension based platforms: what is the near future of viral vector manufacturing (2021), Cell Gene Ther Insights 11, pp. 1365-71. doi: 10.18609/cgti.2021.180.
