Abstract IA16: Accelerating innovation for children with cancer in the new regulatory environment
Notice bibliographique
Résumé
Abstract Over the last 20 years, several pieces of regulation have been launched, in the US and in Europe, to mandate and incentivize the development of safe and effective medicines for children. It has been a success in several pediatric specialties such as rheumatology, infection diseases, cardiovascular diseases, allergy, and several rare pediatric diseases. In oncology, the landscape of pediatric drug development has significantly changed, but very few new anticancer medicines have been approved for the treatment of pediatric malignancies over the last 10 years as compared to the high number of anticancer drugs approved for the treatment of cancer in adults: dinutuximab for neuroblastoma, blinatumomab and tisagenlecleucel for acute lymphoblastic leukemia, and larotrectinib for NTRK positive malignancies. So far, the regulations mandated the pediatric development of any drug if the indicated disease in adults occurred in children. If not, a waiver was issued and the company did not have to study the drug in children. In oncology, malignancies in children and in adults are different, but the same drugs are used to treat both, and often the same biologic alterations (targets) are found in both adult and pediatric malignancies. Too many oncology drugs have been waived. In addition, the pediatric trials of oncology products as part of Pediatric Investigation Plans and Pediatric Study Plans started late in the life cycle of product development and often close to or after the marketing authorization. There is a crucial need to improve and accelerate new drug development for children and adolescents with cancer. The goal is to drive pediatric oncology drug developments through science (using biology, preclinical evaluation, and precision medicine), to better meet patients’ unmet medical needs and to facilitate prioritization among all compounds in development. The FDA Race for Children Act is setting a new regulatory environment that will improve the situation by asking pediatric development of oncology products if their target is “directed at a molecular target that the Secretary determines to be substantially relevant to the growth or progression of a pediatric cancer.” In addition, over the last 5 years, the value of having all stakeholders, i.e. academia, parents, industry and regulators, working together has been demonstrated by ACCELERATE, the international multistakeholder platform (www.accelerate-platform.org). Accelerating innovation for pediatric cancers is urgently needed and feasible in the new regulatory environment and requires international cooperation of all stakeholders. Citation Format: Gilles Vassal. Accelerating innovation for children with cancer in the new regulatory environment [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA16.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,037 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,012 | 0,008 |
| Science ouverte | 0,003 | 0,009 |
| Intégrité de la recherche | 0,011 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,058 | 0,017 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».