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.