ACCELERATE and European Medicines Agency Paediatric Strategy Forum for medicinal product development of checkpoint inhibitors for use in combination therapy in paediatric patients
Bibliographic record
Abstract
The third multistakeholder Paediatric Strategy Forum organised by ACCELERATE and the European Medicines Agency focused on immune checkpoint inhibitors for use in combination therapy in children and adolescents. As immune checkpoint inhibitors, both as monotherapy and in combinations have shown impressive success in some adult malignancies and early phase trials in children of single agent checkpoint inhibitors have now been completed, it seemed an appropriate time to consider opportunities for paediatric studies of checkpoint inhibitors used in combination. Among paediatric patients, early clinical studies of checkpoint inhibitors used as monotherapy have demonstrated a high rate of activity, including complete responses, in Hodgkin lymphoma and hypermutant paediatric tumours. Activity has been very limited, however, in more common malignancies of childhood and adolescence. Furthermore, apart from tumour mutational burden, no other predictive biomarker for monotherapy activity in paediatric tumours has been identified. Based on these observations, there is collective agreement that there is no scientific rationale for children to be enrolled in new monotherapy trials of additional checkpoint inhibitors with the same mechanism of action of agents already studied (e.g. anti-PD1, anti-PDL1 anti-CTLA-4) unless additional scientific knowledge supporting a different approach becomes available. This shared perspective, based on scientific evidence and supported by paediatric oncology cooperative groups, should inform companies on whether a paediatric development plan is justified. This could then be proposed to regulators through the available regulatory tools. Generally, an academic-industry consensus on the scientific merits of a proposal before submission of a paediatric investigational plan would be of great benefit to determine which studies have the highest probability of generating new insights. There is already a rationale for the evaluation of combinations of checkpoint inhibitors with other agents in paediatric Hodgkin lymphoma and hypermutated tumours in view of the activity shown as single agents. In paediatric tumours where no single agent activity has been observed in multiple clinical trials of anti-PD1, anti-PDL1 and anti-CTLA-4 agents as monotherapy, combinations of checkpoint inhibitors with other treatment modalities should be explored when a scientific rationale indicates that they could be efficacious in paediatric cancers and not because these combinations are being evaluated in adults. Immunotherapy in the form of engineered proteins (e.g. monoclonal antibodies and T cell engaging agents) and cellular products (e.g. CAR T cells) has great therapeutic potential for benefit in paediatric cancer. The major challenge for developing checkpoint inhibitors for paediatric cancers is the lack of neoantigens (based on mutations) and corresponding antigen-specific T cells. Progress critically depends on understanding the immune macroenvironment and microenvironment and the ability of the adaptive immune system to recognise paediatric cancers in the absence of high neoantigen burden. Future clinical studies of checkpoint inhibitors in children need to build upon strong biological hypotheses that take into account the distinctive immunobiology of childhood cancers in comparison to that of checkpoint inhibitor responsive adult cancers.
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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 | 0.023 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 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".