Genetic Findings of Potential Donor Origin in Cells Used for Cell and Gene Therapy: Recommendations from the World Marrow Donor Association
Bibliographic record
Abstract
• Testing of cell and gene therapy products may identify unexpected genetic findings of donor origin • Deciphering whether variants are donor in origin versus introduced via manufacturing is key • Guidelines with recommendations for robust donor consent and disclosure were developed • While aimed for donor registries, recommendations are adaptable for donors recruited through other mechanisms Manufacturing cell and gene therapy products derived from donor cells may involve genetic and other testing that identifies unexpected findings of potential donor origin. Testing may be done to assess the safety of the product or manufacturing process, assess gene transduction efficiency or aspects of cell expansion, and may also be performed in recipients of cell and gene therapy products following infusion to monitor the effects of treatment. Tests that could identify unexpected findings in donor cells include chromosomal karyotyping, targeted tests for specific gene mutations or rearrangements, large gene panels or whole genome sequencing which could detect mutations or cytogenetic abnormalities of relevance to donors. Deciphering whether variants are of donor origin as opposed to introduced via manufacturing processes is key, as is having a framework for protecting donors that includes procedures for ensuring robust donor consent and appropriate pathways for disclosure of clinically relevant and actionable results. Building upon recent recommendations from the World Marrow Donor Association (WMDA) regarding unexpected findings of potential donor origin following allogeneic hematopoietic cell transplantation, an expert group was assembled to review available evidence and develop a framework to apply to healthy volunteer donors who provide cells for manufacturing of allogeneic cell and gene therapy products. These guidelines aim to provide recommendations for pre-donation consenting, and a framework for informing and managing care of donors when findings of potential donor origin are identified. Since many cellular therapies remain under development, donors who provide cells for any aspect of research and development of CGT products require special consideration. Realizing that cellular therapy may involve commercial entities and donors that are recruited within conventional stem cell registries or through other mechanisms, we have made suggestions on how recommendations can be adapted.
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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 | 0.055 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".