Paediatric Strategy Forum for medicinal product development of multi-targeted kinase inhibitors in bone sarcomas
Bibliographic record
Abstract
The eighth Paediatric Strategy Forum focused on multi-targeted kinase inhibitors (mTKIs) in osteosarcoma and Ewing sarcoma.The development of curative, innovative products in these tumours is a high priority and addresses unmet needs in children, adolescents and adults.Despite clinical and investigational use of mTKIs, efficacy in patients with bone tumours has not been definitively demonstrated.Randomised studies, currently being planned or in progress, in front-line and relapse settings will inform the further development of this class of product.It is crucial that these are rapidly initiated to generate robust data to support international collaborative efforts.The experience to date has generally indicated that the safety profile of mTKIs as monotherapy, and in combination with chemotherapy or other targeted therapy, is consistent with that of adults and that toxicity is manageable.Increasing understanding of relevant predictive biomarkers and tumour biology is absolutely critical to further develop this class of products.Biospecimen samples for correlative studies and biomarker development should be shared, and a joint academic-industry consortium created.This would result in an integrated collection of serial tumour tissues and a systematic retrospective and prospective analyses of these samples to ensure robust assessment of biologic effect of mTKIs.To support access for children to benefit from these novel therapies, clinical trials should be designed with sufficient scientific rationale to support regulatory and payer requirements.To achieve this, early dialogue between academia, industry, regulators, and patient advocates is essential.Evaluating feasibility of combination strategies and then undertaking a randomised trial in the same protocol accelerates drug development.Where possible, clinical trials and development should include children, adolescents, and adults less than 40 years.To respond to emerging science, in approximately 12 months, a multi-stakeholder group will meet and review available data to determine future directions and priorities.þ e Phase 1/2, solid tumours dependent on KIT or PDGFRA signalling Cabometyx â /Cometriq â , cabozantinib, Ipsen pharma/ Exelixis VEGFR2, MET and AXL, RET, ROS1, TYRO3, MER, KIT, TRKB, FLT3 and TIE-2 þ e Monotherapy, combination and planned in front-line in osteosarcoma (COG) Dovitinib, Oncoheroes/Allarity FGFR, VEGFR, PDGFR and other RTKs.e Z Phase IB-2 osteosarcoma (DRP â biomarker-driven) Lenvima â /Kisplyx â , lenvatinib, Eisai GmbH VEGFR1, VEGFR2, VEGFR3 and FGFR1, 2, 3 and 4, PDGFRa, KIT and RET þ þ Monotherapy, combination (with chemotherapy and other targeted therapy) and randomised phase 2 (OLIE) Nexavar â , sorafenib, Bayer CRAF, BRAF and mutant BRAF and KIT, FLT-3, RET, RET/PTC, VEGFR1, VEGFR2, VEGFR3, PDGFR-b.e e Phase 1 and 2 e limited activity in paediatric phase I and combinations studies which included osteosarcoma and Ewing (Completed) Surufatinib, HUTCHMED VEGFR1, 2, 3, FGFR1 and CSF-1 e e Phase 1/2 in osteosarcoma, Ewing, and soft tissue sarcoma in combination with gemcitabine Stivarga â , regorafenib, Bayer RET, VEGFR1, VEGFR2, VEGFR3, KIT, PDGFR-a, PDGFR-b, FGFR1, FGFR2, TIE2, DDR2, Trk2A, Eph2A, RAF-1, BRAF, BRAFV600E, SAPK2, PTK5, Abl, and CSF-1 eþ e Monotherapy, combination and planned in front-line in Ewing sarcoma (INTER EWING-1) Votrient â , pazopanib, Novartis a VEGFR1, VEGFR2, VEGFR3, PDGFRa and PDGFRb; and c-K þ e Phase 2 single agent closed early due to lack of sufficient signal in Ewing and osteosarcoma [87] PIP, Paediatric Investigation Plan; WR, Written Request.a Company not present.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".