A meta-analysis of biological variation in blood-based therapy as a precursor to bio-manufacturing

Mobilization and Apheresis Collection Strategies to Reduce Platelet Loss in G-CSF Mobilized Healthy Adult Donors

Granulocyte-colony stimulating factor (G-CSF) mobilizes hematopoietic progenitor cells (HPC) into the peripheral blood. Donor peripheral blood platelet loss has been observed during both G-CSF mobilization and apheresis collection. This study evaluates two strategies to reduce donor platelet loss, preserve product CD34+ cell yield and collection efficiency and increase volume of whole blood (WB) processed. One hundred and two adults healthy donors were mobilized with either standard dose G-CSF (9.5-12 mcg/kg/day × 4 days) or lower dose G-CSF (7.5-10 mcg/kg/day × 4 days) according to their pre-mobilization platelet count. Apheresis centrifugal force was adjusted by lowering the packing factor (PF) setting on the apheresis instrument. Between-group differences were observed in absolute donor platelet loss (p = 0.04) favoring lower G-CSF dosing, while percent donor platelet loss trended towards significance (p = 0.10). Lowering PF from the manufacturer's default of 4.5 to 4.0 demonstrated between-group differences in absolute donor platelet loss (p < 0.05), percent donor platelet loss (p < 0.001), and apheresis product platelet content (p < 0.001). No differences were observed in the product CD34+ cell content and CD34+ cell collection efficiency when PF was reduced to 4.0. Additionally, a higher volume of WB could be processed due to reduced donor platelet loss. Together, these two strategies may mitigate the risk of cumulative platelet loss in G-CSF mobilized healthy donors undergoing apheresis collection, thereby increasing the likelihood of completing the target total blood volume to be processed while maintaining donor safety.

Assessment of Protocol Impact on Subjectivity Uncertainty When Analyzing Peripheral Blood Mononuclear Cell Flow Cytometry Data Files

Measured variability of product within Cell and Gene Therapy (CGT) manufacturing arises from numerous sources across pre-analytical to post-analytical phases of testing. Operators are a function of the manufacturing process and are an important source of variability as a result of personal differences impacted by numerous factors. This research uses measurement uncertainty in comparison to Coefficient of Variation to quantify variation of participants when they complete Flow Cytometry data analysis through a 5-step gating sequence. Two study stages captured participants applying gates using their own judgement, and then following a diagrammatical protocol, respectively. Measurement uncertainty was quantified for each participant (and analysis phase) by following Guide to the Expression of Uncertainty in Measurement protocols, combining their standard deviations in quadrature from each gating step in the respective protocols. When participants followed a diagrammatical protocol, variation between participants reduced by 57%, increasing confidence in a more uniform reported cell count percentage. Measurement uncertainty provided greater resolution to the analysis processes, identifying that most variability contributed in the Flow Cytometry gating process is from the very first gate, where isolating target cells from dead or dying cells is required. This work has demonstrated the potential for greater usage of measurement uncertainty within CGT manufacturing scenarios, due to the resolution it provides for root cause analysis and continuous improvement.

Establishing the variation of blood metrics within UK Biobank to inform cell therapy manufacturing processes

Aim: Understanding blood component variation as a function of healthy population metrics is necessary to inform biomanufacturing process design. Methods: UK Biobank metrics were examined for variation in white blood cell count as an analog to potential manufacturing starting material input. Results: White blood cell count variation of four orders of magnitude (6.65 × 10⁹ cells/l) was found. Variation increased with age, increased with weight up to 80 kg then decreased. Health state showed a greater absolute number of participants with elevated count. Female range was greater than male. Cell count/distributions were different between centers. Conclusion: This variation and range of process input signals a requirement for new strategies for manufacturing process design and control.