Accelerated Upstream Process Optimization Using a QbD Approach
APC applied its BioACHIEVE® process
development technology platform to improve
the process performance of a Chinese Hamster
Ovary (CHO) mammalian cell bioprocess
operated in a 2.5 L bench-top bioreactor, by
optimising the bioreactor feed profile by moving
from a traditional bolus to a PAT-enabled
continuous feeding strategy in order to prevent
nutrient depletion and deliver a stable macroenvironment for the cells. Typically, the initial
phase involved advanced monitoring of the current process with appropriate PAT
technologies. The nutrient, by-product and
biomass concentrations in the CHO mammalian
cell culture was determined online using Raman
spectroscopy coupled with chemometric partial
least squared (PLS) modelling.
Based on the process knowledge garnered, the
CPPs for the process were identified and process
models which describe their trajectories and
behaviours were developed. The model was
developed to ultimately be a principal
component of a model predictive control (MPC)
algorithm for the closed-loop feedback control
of glucose concentration in the bioreactor. Prior
to implementing the process model as part of
the MPC strategy, a series of process simulations
were run. The simulation results gave direction
to the experimental design during process
development by providing a virtual environment
in which to test and optimise a variety of
Overall, application of the glucose set-point
control strategy resulted in a 1.5 fold increase in
peak viable cell density (VCD) and the integral of
the viable cell density (IVC) which is directly
related to increased titre.
- They are non-invasive and non-destructive.
- Do not consume the analyte or require sampling.
- No consumables.
- Are capable of monitoring several analytes simultaneously.
- Provide continuous real-time measurements.
- Do not interfere with the cellular metabolism or bioreactor environment.
- Chemometric calibration models are necessary to translate the Raman spectra into useful information.
- Expertise in PLS model building.
- Validated reference method.
- Continuous verification and validation of the built PLS models
The principal goal of process development and control under this APC paradigm is to provide:
- Greater Process Understanding
- Streamlined Optimization
- Process Reproducibility