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BACKGROUND When manufacturing chimeric antigen receptor (CAR) T cells using anti‐CD3/anti‐CD28 beads, ex vivo T‐cell expansion is dependent on the composition of leukocytes used in the manufacturing process. We investigated the effects of leukocyte composition on CAR T‐cell expansion and characteristics using an alternative manufacturing method. METHODS Anti–B‐cell maturation antigen and CD19‐CAR T cells were manufactured using autologous peripheral blood mononuclear cell (PBMNC) concentrates. The PBMNCs were enriched for lymphocytes using density gradient separation, which were used for CAR T‐cell culture initiation. T‐cell expansion was stimulated with soluble anti‐CD3 and interleukin‐2. RESULTS Fifty‐one CAR T‐cell products were evaluated; 28 anti–B‐cell maturation antigen (BCMA) CAR T cells produced for 24 patients and 27 CD19 CAR T cells produced for 24 patients. CAR T‐cell expansion was reduced when greater quantities of monocytes were present in the post–density gradient separation PBMNCs. In addition, the ratio of CD4 to CD8 cells in the CAR T‐cell products after 7 days of culture was dependent on the quantity of monocytes, RBCs, and neutrophils in the post–density gradient separation PBMNCs. Greater quantities of monocytes and RBCs were associated with a greater proportion of CD4+ cells and greater quantities of neutrophils were associated with a greater proportion of CD8+ cells. CONCLUSIONS The composition of leukocytes used to manufacture CAR T cells can affect cell expansion and the composition of CAR T‐cell products. More uniform or complete lymphocyte enrichment of PBMNCs improves the consistency of final CAR T‐cell products.

Background and objectives Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open‐source software tailored for this purpose and describe its validation with three blood group systems. Materials and methods The DTM‐Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long‐read NGS platform. Results Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases. Conclusion DTM‐Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM‐Tools is open‐source and in continuous development.