Bioreactor Design Data and Mode-of-Operation Selection: 04-BS-13, Undated paper, Q1

Question 1: Bioreactor Design Data and Mode-of-Operation Selection (20 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

(a) Data needed to design a bioreactor. Bioreactor design translates a target production rate into a vessel size, geometry, and set of operating conditions, so the designer needs data in five broad categories:

Reaction kinetics. The growth kinetics of the organism (μ_max, K_s in a Monod model, any substrate/product inhibition constants), the specific rates of substrate uptake and product formation (q_s, q_p), and the yield coefficients (Y_X/S, Y_P/S) that link growth to substrate consumption and product formation.
Stoichiometry and mass balances. The elemental/electron balance for the organism-substrate-product system (so oxygen demand, CO₂ evolution, and heat generation can be predicted), and the required nutrient medium composition (carbon, nitrogen, phosphate, trace elements).
Transport requirements. Oxygen transfer rate (OTR) needed to match the peak oxygen uptake rate (OUR) — this sets the required k_La and hence agitation/aeration design; heat transfer requirements (metabolic heat plus any mechanical/agitation heat, against the achievable cooling-jacket or coil area); mixing time and shear tolerance of the organism (critical for shear-sensitive mammalian or filamentous cultures).
Physical/operating constraints. Working volume vs. total vessel volume (headspace for foam/aeration), sterilizability (materials of construction, in-place steam sterilization pressure rating), pH and temperature control range and the acid/base or cooling/heating capacity needed to hold them, and the rheology of the broth (Newtonian vs. non-Newtonian/viscous, which changes the required impeller type and power input, as in Q6 below).
Economic/scale-up data. Target production rate and batch cycle time (turnaround for cleaning/sterilization/charging), scale-up correlations (constant P/V, constant tip speed, or constant k_La, depending on which is rate-limiting), and downstream processing constraints that set the maximum practical broth concentration.

(b) Choice of reactor mode — two reasons each.

Mode	Reason 1	Reason 2
Batch	Simple to operate, sterilize, and validate — no continuous sterile feed/effluent handling is needed, which lowers contamination risk and capital cost for small-volume or high-value products (e.g. many pharmaceuticals).	Well suited to unstable or genetically engineered strains, since the population is grown fresh each run and there is no long-term selection pressure for non-producing revertants, and it allows a single well-defined product specification per lot (important for regulatory batch release).
Fed-batch	Lets substrate be fed slowly to avoid substrate inhibition, catabolite repression, or overflow metabolism (e.g. avoiding the Crabtree effect/ethanol overflow in yeast at high glucose), so higher final cell/product densities are reached than in batch.	Allows the specific growth rate to be controlled directly via the feed rate (quasi-steady-state), which is valuable for producing secondary metabolites or recombinant proteins whose formation is optimal at a sub-maximal, controlled μ rather than at μ_max.
Chemostat (continuous)	Operates at a true steady state (constant μ, x, s), which is ideal for physiological/kinetic studies because a single dilution rate D fixes μ = D and lets every other state variable be measured at a reproducible operating point.	Gives continuous, uninterrupted production without repeated turnaround (charge/sterilize/harvest) time, maximizing volumetric productivity for commodity products, provided the strain is stable enough not to be out-competed by non-producing mutants over long run times.

Check

This part is a design-knowledge/short-list question with no numerical data in the source; the categories and reasons above follow the standard bioprocess-engineering framework (Shuler & Kargi Ch. 1, 9) rather than any exam-specific figure.

Topic: Bioreactor design-data checklist and reactor-mode (batch/fed-batch/chemostat) selection.

Key relations: Monod kinetics (μ_max, K_s), yield coefficients Y_X/S/Y_P/S, OTR vs. OUR matching, scale-up at constant P/V or k_La.

Why this works: Every design decision (vessel size, impeller, cooling area) traces back to one of the five data categories; picking a reactor mode is really about which kinetic/economic constraint (contamination risk, substrate inhibition, steady-state reproducibility) dominates for that specific process.

Common pitfall: Treating reactor-mode choice as purely about scale rather than about the underlying kinetics (e.g. choosing batch for a process with strong substrate inhibition, when fed-batch would avoid it).

Source: Shuler & Kargi, Bioprocess Engineering: Basic Concepts, Ch. 1, 9.

Question 1 of 9: Bioreactor Design Data and Mode-of-Operation Selection

Question 1: Bioreactor Design Data and Mode-of-Operation Selection (20 marks)