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Background: Human mesenchymal stromal cells (hMSCs) have become attractive candidates for advanced medical cell-based therapies. An in vitro expansion step is routinely used to reach the required clinical quantities. However, this is influenced by many variables including donor characteristics, such as age and gender, and culture conditions, such as cell seeding density and available culture surface area. Computational modeling in general and machine learning in particular could play a significant role in deciphering the relationship between the individual donor characteristics and their growth dynamics., Methods: In this study, hMSCs obtained from 174 male and female donors, between 3 and 64 years of age with passage numbers ranging from 2 to 27, were studied. We applied a Random Forests (RF) technique to model the cell expansion procedure by predicting the population doubling time (PDT) for each passage, taking into account individual donor-related characteristics., Results: Using the RF model, the mean absolute error between model predictions and experimental results for the PDT in passage 1 to 4 is significantly lower compared with the errors obtained with theoretical estimates or historical data. Moreover, statistical analysis indicate that the PD and PDT in different age categories are significantly different, especially in the youngest group (younger than 10 years of age) compared with the other age groups., Discussion: In summary, we introduce a predictive computational model describing in vitro cell expansion dynamics based on individual donor characteristics, an approach that could greatly assist toward automation of a cell expansion culture process., (Copyright © 2019 International Society for Cell and Gene Therapy. Published by Elsevier Inc. All rights reserved.)

Background Aims: With the increasing scale in stem cell production, a robust and controlled cell expansion process becomes essential for the clinical application of cell-based therapies. The objective of this work was the assessment of a hollow fiber bioreactor (Quantum Cell Expansion System from Terumo BCT) as a cell production unit for the clinical-scale production of human periosteum derived stem cells (hPDCs)., Methods: We aimed to demonstrate comparability of bioreactor production to standard culture flask production based on a product characterization in line with the International Society of Cell Therapy in vitro benchmarks and supplemented with a compelling quantitative in vivo bone-forming potency assay. Multiple process read-outs were implemented to track process performance and deal with donor-to-donor-related variation in nutrient needs and harvest timing., Results: The data show that the hollow fiber bioreactor is capable of robustly expanding autologous hPDCs on a clinical scale (yield between 316 million and 444 million cells starting from 20 million after ± 8 days of culture) while maintaining their in vitro quality attributes compared with the standard flask-based culture. The in vivo bone-forming assay on average resulted in 10.3 ± 3.7% and 11.0 ± 3.8% newly formed bone for the bioreactor and standard culture flask respectively. The analysis showed that the Quantum system provides a reproducible cell expansion process in terms of yields and culture conditions for multiple donors., (Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.)