A novel predictive algorithm to personalize autologous T-cell harvest for chimeric antigen receptor T-cell manufacture |
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| Affiliation: | 1. University College London Cancer Institute, London, UK;2. Department of Hematology, University College London Hospital, London, UK;3. Cancer Research UK & University College London Cancer Trials Center, University College London, London, UK;1. Department of Hematology, St. Jude Children''s Research Hospital, Memphis, Tennessee, USA;2. Department of Bone Marrow Transplantation and Cellular Therapy, St. Jude Children''s Research Hospital, Memphis, Tennessee, USA;1. CReATe Fertility Center, Toronto, Ontario, Canada;2. Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada;3. Department of Obstetrics and Gynecology, University of Toronto, Toronto, Ontario, Canada;4. Department of Physiology, University of Toronto, Toronto, Ontario, Canada;1. Gastroenterology Unit, Department of Medicine, Azienda Ospedaliera Universitaria Integrata Policlinico G.B. Rossi and University of Verona, Verona, Italy;2. Division of Surgery and Cell Therapy Unit, Institute for Health Research, Jiménez Díaz Foundation University Hospital, Madrid, Spain;3. Laboratory of Advanced Cellular Therapies, Hematology Unit, Vicenza Hospital, Vicenza, Italy;1. IdiPAZ, Hospital La Paz Institute for Health Research, La Paz University Hospital, Madrid, Spain;2. Biostatistics Department, La Paz University Hospital, Madrid, Spain;3. Histocompatibility Unit, Transfusion Center of Madrid, Madrid, Spain;4. Cell Therapy Unit, Hematology Department, La Paz University Hospital, Madrid, Spain;5. Pediatric Hemato-oncology Department, La Paz University Hospital, Madrid, Spain;6. Faculty of Medicine Autonomous, University of Madrid, Madrid, Spain;1. Pediatrics, University of California, San Francisco, San Francisco, California, USA;2. Crispr Therapeutics AG, Boston, Massachusetts, USA;3. ISCT Immune-Gene Therapy Committee, ISCT, Vancouver, California, USA;1. Developmental Biology and Cancer Department, UCL GOS Institute of Child Health, London, UK;2. Centre for Cell, Gene & Tissue Therapeutics, Royal Free London NHS Foundation Trust, London, United Kingdom;3. Department of Zoology, Faculty of Science, South Valley University, Qena, Egypt;4. Cancer Institute, UCL, London, United Kingdom;5. Department of Plastic Surgery, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom |
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| Abstract: | ![]()
Background aimsThe most widely accepted starting materials for chimeric antigen receptor T-cell manufacture are autologous CD3+ T cells obtained via the process of leukapheresis, also known as T-cell harvest. As this treatment modality gains momentum and apheresis units struggle to meet demand for harvest slots, strategies to streamline this critical step are warranted.MethodsThis retrospective review of 262 T-cell harvests, with a control cohort of healthy donors, analyzed the parameters impacting CD3+ T-cell yield in adults with B-cell malignancies. The overall aim was to design a novel predictive algorithm to guide the required processed blood volume (PBV) (L) on the apheresis machine to achieve a specific CD3+ target yield.ResultsFactors associated with CD3+ T-cell yield on multivariate analysis included peripheral blood CD3+ count (natural log, ×109/L), hematocrit (HCT) and PBV with coefficients of 0.86 (95% confidence interval [CI], 0.80–0.92, P < 0.001), 1.30 (95% CI, 0.51–2.08, P = 0.001) and 0.09 (95% CI, 0.07–0.11, P < 0.001), respectively. The authors’ model, incorporating CD3+ cell count, HCT and PBV (L), with an adjusted R2 of 0.87 and root-mean-square error of 0.26 in the training dataset, was highly predictive of CD3+ cell yield in the testing dataset. An online application to estimate PBV using this algorithm can be accessed at https://cd3yield.shinyapps.io/cd3yield/.ConclusionsThe authors propose a transferrable model that incorporates clinical and laboratory variables accessible pre-harvest for use across the field of T-cell therapy. Pending further validation, such a model may be used to generate an individual leukapheresis plan and streamline the process of cell harvest, a well-recognized bottleneck in the industry. |
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| Keywords: | cell manufacture |
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