Concluding Remarks and Future Perspectives
A mechanobiological conceptual
framework with quantification of uncertainties is required for designing
and optimizing stem cell bioprocesses to improve process performance,
reduce process variability, and ensure consistent product quality. Based
on the knowledge of potential sources of noise and variability in a
bioprocess, it is possible to systematically categorize the main sources
of intrinsic disorder at the bioprocess site and cellular noise and,
therefore, act directly to reduce them. Here, we focused on recent
advances in the development of stem cell mechanobiology and discussed
the necessity for mechanobiological consideration in supporting the
development and implementation of successful bioprocessing. We discussed
the necessity for and the design principles of a criteria and indicators
for assessing the intrinsic disorder in continuous bioprocessing.
With the help of the conceptual
framework, we determined the effects of the input variability on the
performance indicators and compared them between the operations, as well
as identified the mode most robust against the input variations. The
proposed criteria and indicators based on mechanobiological
considerations in this review ensure the coverage of many growth
patterns under uncertainty and identify biological indicators important
for a wide range of processes that are reflected in bioprocess
efficiency. The effectiveness and applicability of this new proposed
conceptual framework and methodology are demonstrated through a case
study. The conceptual framework-based optimization of bioprocess
consists of three main steps: (i) identification of culture operation
parameters, (ii) identification of associated risks and requirements for
risk mitigation, and (iii) translation of operation parameters into
technical requirements (Figure 5 ).The assessment and prediction
indicators of bioprocess effectiveness link in vitro attributes, such as
combination with the existing indicators for cell productivity and
survival during cell-based production process, with the working proposal
for an improved assessment of stem cell potency, and thus provide a
basis for establishing the cell quality prior to their therapeutic
application. This procedure can be repeated iteratively at the design
stage of each operating procedure, and the best process control
trajectories can be developed by numerical optimization techniques. This
allows for getting closer to the optimal bioprocess by solving problems
related to intrinsic disorder at the continuous bioprocessing site.
Although many questions regarding
quantitative evaluation tools and technologies in multi-stage stem cell
bioprocessing remain unanswered, we hope that using such a conceptual
framework can make the bioprocess design even more rational and
quantitative. Since a conceptual framework can guide research by
providing a visual representation of theoretical constructs and
variables of interest, this approach can potentially be characterized
more effectively and predicted more accurately. Its functionality can be
maximized, and engineering specifications imposed by clinical or
industrial translation will hopefully present a lower barrier, improving
the chances for the translational success of bioprocesses. The
technological and computational advances have facilitated the
quantification of mRNA and protein level under different simulation
environments; however, major challenges remain associated with robust
measurement, statistical analysis, and experimental validation. The
application of these new mechanical force estimation technologies along
with biological indicators provides an opportunity to both learn new
strategies for stem cell bioprocessing and educate others on new ways of
implementing these technologies. Altogether, proposed conceptual
framework will play an increasingly important role in stem cell
bioprocesses, which will ultimately lead to the application of models in
several fields of the process development chain as well more advanced
automation and integrated process development in the near future.