Background: The Research to Accelerate Cures and Equity (RACE) for Children Act of 2017 authorized the Food and Drug Administration (FDA) to require pediatric clinical trials for new oncology drugs with relevant molecular targets. This study reviewed oncology drug approvals within the first year after the new legislation came into effect, to evaluate the impact on development of molecularly targeted oncology drugs for pediatric cancers.

Research Design And Methods: For new oncology drugs approved by the FDA between 08/18/2020 and 08/18/2021, drug approval packages, letters, and prescribing information were reviewed for the submission and approval dates, indication, and molecular target of the drug, and post-marketing requirements that included pediatric clinical trials.

Results: Within the 1-year period, 17 new oncology drugs were approved, but only 5 had been submitted after 08/18/2020. Three of the 5 (60.0%) had requirements for pediatric trials under the RACE Act. None of the 12 submitted prior to 08/18/2020 had pediatric trial requirements, but 10 (83.3%) had molecular targets that would have made them candidates under the RACE Act.

Conclusions: Early evidence suggests that the RACE Act was effective at closing the loopholes of previous legislation and creating new opportunities for innovation in developing therapies for childhood cancers.

Download full-text PDF

Source
http://dx.doi.org/10.1080/14737140.2022.2032664DOI Listing

Publication Analysis

Top Keywords

oncology drugs
20
race children
8
development molecularly
8
molecularly targeted
8
targeted oncology
8
pediatric clinical
8
molecular targets
8
drugs approved
8
pediatric
6
oncology
6

Similar Publications

Quantitative structure-property relationship (QSPR) modeling has emerged as a pivotal tool in the field of medicinal chemistry and drug design, offering a predictive framework for understanding the correlation between chemical structure and physicochemical properties. Topological indices are mathematical descriptors derived from the molecular graphs that capture structural features and connectivity, playing a crucial role in QSPR analysis by quantitatively relating chemical structures to their physicochemical properties and biological activities. Lung cancer is characterized by its aggressive nature and late-stage diagnosis, often limiting treatment options and significantly impacting patient survival rates.

View Article and Find Full Text PDF

Lung cancer is the leading cause of cancer-related fatalities globally, accounting for the highest mortality rate among both men and women. Mutations in the epidermal growth factor receptor (EGFR) gene are frequently found in non-small cell lung cancer (NSCLC). Since curcumin and CB[2]UN support various medicinal applications in drug delivery and design, we investigated the effect of curcumin and CB[2]UN-based drugs in controlling EGFR-mutant NSCLC through a dodecagonal computational approach.

View Article and Find Full Text PDF

Blood clots (BCs) play a crucial biomechanical role in promoting osteogenesis and regulating mesenchymal stem cell (MSC) function and fate. This study shows that BC formation enhances MSC osteogenesis by activating Itgb1/Fak-mediated focal adhesion and subsequent Runx2-mediated bone regeneration. Notably, BC viscoelasticity regulates this effect by modulating Runx2 nuclear translocation.

View Article and Find Full Text PDF

Fragment-Based Drug Discovery: Small Fragments, Big Impact - Success Stories of Approved Oncology Therapeutics.

Bioorg Chem

January 2025

Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal, Academy of Higher Education, Manipal, Karnataka 576104, India.

Fragment-Based Drug Discovery (FBDD) has revolutionized drug discovery by overcoming the challenges of traditional methods like combinatorial chemistry and high-throughput screening (HTS). Leveraging small, low-molecular-weight fragments, FBDD achieves higher hit rates, reduced screening costs, and faster development timelines for clinically relevant drug candidates. This review explores FBDD's core principles, innovative methodologies, and its success in targeting diverse protein classes, including previously "undruggable" targets.

View Article and Find Full Text PDF

The rapid development of artificial intelligence (AI) based tools in pathology laboratories has brought forward unlimited opportunities for pathologists. Promising AI applications used for accomplishing diagnostic, prognostic and predictive tasks are being developed at a high pace. This is notably true in thoracic oncology, given the significant and rapid therapeutic progress made recently for lung cancer patients.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!