Expanding access to haploidentical transplantation : Clinical feasibility of a centralized nationwide distribution model for fresh TCRα/β-depleted grafts in France
Bibliographic record
Abstract
Abstract Introduction: TCRα/β and CD19 depletion is an in vitro graft engineering method developed for haploidentical hematopoietic stem cell transplantation (haplo-HSCT) in non-malignant pediatric diseases, such as immune deficiencies and Fanconi anemia. It avoids the need for in vivo T-cell depletion using toxic alkylating agents. Studies on TCRα/β and CD19 depletion consistently show very low or zero toxic mortality, even in patients with DNA repair disorders. This method preserves innate and adaptive immune effectors—such as dendritic cells, NK cells, and γ/δ T lymphocytes—which support engraftment, infection control, and GVL in malignant indications. The indications for this depletion strategy are increasingly recognized in patients at high risk of toxicity, those with DNA repair disorders, and for primary or rescue haplo-HSCT. However, the complexity of this method limits its availability to a few highly specialized centers. Furthermore, implementing such a process and obtaining regulatory approval is a resource-intensive endeavor that requires sufficient volume of activity. To address these limitations, we established a centralized platform for the real-time nationwide distribution of fresh TCRα/β-depleted grafts in France, prioritizing bringing the cells to the patients, rather than the patients to the cells. Methods: The single-cell therapy unit at Necker-Enfants Malades Hospital, AP-HP, Paris—an accredited facility—performed central processing of peripheral blood stem cell grafts using the CliniMACS TCRα/β depletion system (Miltenyi Biotec). Donor apheresis products were transported fresh to the central facility, processed under strict quality standards in accordance with JACIE-EBMT guidelines, and then delivered by dedicated courier, high-speed train, or air to 10 participating transplant centers across France. The target delivery time from product release to patient infusion was ≤6 hours. Feasibility was assessed based on transport logistics, processing performance (CD34+ cell recovery, TCRα/β depletion efficiency), and adherence to key timeframes. We also compared graft quality based on the apheresis location (on-site at the processing facility vs. off-site collections) and delivery conditions (short-distance vs. long-distance transport by train or air). Results: Between 2014 and July 31, 2025, 48 fresh TCRα/β-depleted grafts were successfully manufactured. Of these, 17 were shipped to 9 transplant centers. Patients underwent HSCT for inborn errors of immunity (n=33), Fanconi anemia (n=9), congenital thrombocytopenia (n=2), Shwachman-Diamond syndrome (n=2), and myelodysplastic syndrome (n=2). Despite variability in apheresis product composition, 46 (96%) of the products met predefined quality specifications. Two transplants required a second apheresis and CD34+ selection due to low CD34+ mobilization.The median CD34+ cell recovery was >88%, with a median TCRα/β depletion of –3.9 log.Thirteen transplants were shipped over long distances. Transport was carried out by dedicated medical couriers using conventional or high-speed trains and specific flights depending on geographic location. All grafts (100%) were infused within the 6-hour window. No transport-related incidents or product losses were recorded. Clinical data (median follow-up of 84 months; range 1–342) showed similar engraftment rate and an acceptable safety profile in both shipped and non-shipped transplants. Conclusion/discussion: This nationwide experience confirms the feasibility and reliability of a centralized platform for producing fresh TCRα/β-depleted grafts, supported by a strong logistics network that enables timely delivery by train or air. Our model demonstrates that advanced fresh graft engineering can safely be expanded beyond highly specialized centers through coordinated national infrastructure. Importantly, this project was made possible through close collaboration within the pediatric group of the French Society of Bone Marrow Transplantation and Cell Therapy (SFGM-TC), which ensured its operational success. This collaborative framework also facilitates future technology transfer and implementation in other centers interested in adopting the platform locally.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".