hd
Scaling up is used to develop an industrial bioprocess from the knowledge acquired in the laboratory scale (based on mathematical and physical models).
1-It can be done in two ways: Increasing the number of reactors: there is no risk of scaling errors because they are exactly the same, but nevertheless there is a great expense of $ with the follow-up and of all the bottles. Increase the volume of the reactor to the required (more logical): you can not do the scaling directly, but you have to describe and understand the complete nature of the process.
2- The process changes with the scale: It is difficult to maintain homogeneity in large systems, There are changes over time in the reactor, volumes …, The phenomena of mass, energy and transport have to be taken into account, Time of response: is the time that the system needs to react to a stimulus in a certain way. This varies with scaling.,Changes within the hydrodynamic regime
3- Phenomena involved in scale changes: Phenomena non scale-dependent: Thermodynamic equilibrium and reaction, and kinetic parameters and rates.Phenomena scale-dependent: transport phenomena that involves mass (diffusion and distribution coefficients), heat (properties and parameters) and momentum (fluid dynamic).
4- SCALING UP procedure: 1. I get the result on a laboratory scale 2. I do the experiments in a small pilot plant 3. I do the experiments in a larger pilot plant 4. I do the experiments in an industrial plant where production is obtained.If any of these steps does not work, the hypothesis must be reexamined and new data defined.
5- Varying the dimensions on a larger scale changes the physical environment of the cell that involves: Nutrients, Oxygen, Shear forces, pH, Temperature,Viscosity. The starting point to scalate is to want to reproduce the same conditions based on what I consider most important.
6- scaling up:
Based on the mass transport, shear stress on cells and homogeneity (mixing time) we need to stablish which SCALE UP CRITERIA is going to take control of the process and which will remain constant. The dependence with operational conditions and vessel geometry is different employing each criteria. Thanks to this criteria we can look for the rate limiting step and determine the OPERATIONAL CONDITIONS AND GEOMETRICAL PARAMETERS.
1)POWER INPUT: It is the amount of power that is transferred to a volume from agitator shaft (impeller shaft) and impellers. – Aerated or – Not aerated 2)IMPELLER TIP SPEED: It is related to the shear rate produced by the impellers that move the cell culture media. These first two criteria take into account the shear stress on the cells. If scale-up based on constant P / V tip speed is attempted, and mixing time will decrease. 3)MIXING TIME: Amount of time that the reactor needs to obtain a homogeneous environment. It is very important in viscous broth. If you want the mixing time to be constant, you need the environment to be homogeneous. 4)SUPERFICIAL GAS VELOCITY: It is the volume of gas in the vessel. It is necessary to make sure that enough oxygen is supplied to the cells. It is tremendously difficult to scale bubbling columns. 5)LIQUID CIRCULATION RATE: An impeller serves a dual function of pumping around of liquid inside the bioreactor vessel, and local turbulent micro‐mixing. 6)REYNOLD NUMBER: The heat transfer coefficient is a function of impeller Reynolds number. This is especially important for thermophilic organisms. 7)VOLUMETRIC MASS TRANSFER COEFFICIENT (KLa): This criterion is usually applied to aerobic systems where oxygen concentration is most important and affects metabolism of the microbial cell. //Depending on the phenomenon that you consider important (mass transfer, shear stress or homogeneity) you choose a scaling criterion or another, and each criterion leads to a different operating situation. For some criteria you have a different dependency than for other criteria. All the criteria studied are for stirred tanks because they are the most studied ->WE DO NOT HAVE A LOT OF QUANTITATIVE INFORMATION.
7- Goal of scaling up methodology: The goal is not to lose yield. Everything I have done in the lab I get with the same degree of conversion and productivity on a larger scale. Also achieving that changes in the scale have not a negative effect on the cell physiology and biological response. If the lines overlap it means that the behavior is the same and that KLa has the same value on a small and large scale
8- Scaling down methodology: It is an alternative method to solve Scaling up problems. I assume that there are limitations on an industrial scale that I do not have on a laboratory scale and instead of optimizing the industrial operation where it does not affect the limitations, you put an operation in the laboratory where you assume the limitations that are going to be on an industrial scale. The parameters are evaluated easier and costs less money.Characteristics: Regimen analysis: based on characteristic times is a valuable tool in process optimization as it identifies and gives information about the rate limiting mechanisms and the rate‐limitations and concentration gradients.1)Identify the significant process variables.2) Quantification of the process variables.3) Derivation of rate constants ‐‐> times4) Find out the slowest rate that governs the overall process rate. Parameters that affect the characteristic times are: fluid dynamic, mixing, transfer and reaction. Simulation of the rate-limiting mechanism(s): Looking for predicting the bioreactor performance: dynamic response of the cells to the micro‐environment changes in the selected bioreactor.