Biomedical Engineering Reference
In-Depth Information
potentially impact the in vivo activity of a molecule. The molecule can be altered by
conducting stress studies to induce higher level of aggregation; oxidation, deamidation,
and the glycosylation pattern can be varied as well. The impact of changes in the
molecular structure on the biological activity can then be evaluated via various bioassays.
This study is referred to as structure-activity relationship. The evaluation of in vitro
activity is often the relatively easiest means of determining the CQAs. However, in vitro
assessments can only provide an understanding of the potential changes in the activity of
the molecule, and the correlation between this change in activity and the impact of
efficacy in patients is often unclear. Further assessment of the molecule in animal studies
to evaluate clearance, efficacy, and safety is often a good indicator of the behavior of the
molecule in human trials and is a better tool for understanding the CQAs. Additional
details of the determination of the CQA can be found in Chapter 4.
1.3 AN OVERVIEW OF DESIGN SPACE
After defining the CQAs, the next and more critical step is the development of a
manufacturing process that will yield a product with the desired CQAs [4, 5]. During the
process development, several process parameters are routinely evaluated to assess how
they could impact product quality [6]. The design space for the process eventually
evolves from such a study. For example, during the cell culture development, ranges for
process inputs such as temperature, pH, and the feed timing can be evaluated to determine
if operating within a certain range of temperature and pH has an impact on product
quality. The design of experiments (DOE) is conducted in a manner so as to evaluate the
impact of the multiple variables (multivariate) and also to understand if and how changes
in one or more of the process inputs have an effect on the product quality and/or if a
process input is independent of changes in other inputs.
The design space (process range) is then established for each of the above process
inputs. This can be further explained using an example of a design space for a purification
column. If a column used to purify a protein is expected to reduce the level of protein
aggregate to 2%, the various column operating parameters such as flow rate, pH and
strength of the buffer, load volume, and so on are evaluated such that operating within a
certain range of these parameters yields an aggregate level of less than or equal to 2%. If it
turns out that pH above 6 or below 4 results in aggregate levels above 2%, then the design
space for the pH of the buffer is defined as between 4 and 6. One can similarly envision a
design space for the flow rate and other inputs for the particular purification step.
Eventually, the entire production process for amoleculewill have a defined design space,
and operating within that design space should lead to a product of acceptable quality.
Operating beyond the design space of a particular process input may result in an
unacceptable product quality.
Since the production process for a biomolecule entails multiple steps starting from
the cell culture process to the final purification and eventually to the formulation and fill
in the desired container, the development of a design space for a particular step is not
usually independent of other steps in the production process. Since the output of one step
becomes the input for the next step, the development of the design space for a process
