Drug development costs can be significantly reduced if proven "platform" technologies are allowed to be used without having to validate their use. The most recent US Food and Drug Administration (FDA) guideline brings more clarity, as well as a greater focus on the most complex technologies that can now be used for faster drug development. The FDA has highlights the use of lipid nanoparticles (LNPs) to package and deliver mRNA vaccines, gene therapy, and short (2-20 length) synthetic nucleotides (siRNA). Additionally, monoclonal antibody cell development is targeted. The FDA provides a systematic process of requesting platform status to benefit from its advantages. It brings advanced science and rationality into regulatory steps for the FDA's approval of drugs and biologicals.
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http://dx.doi.org/10.3390/pharmaceutics16070918 | DOI Listing |
Clin Cancer Res
January 2025
United States Food and Drug Administration, Silver Spring, Maryland, United States.
On April 23, 2024, FDA granted accelerated approval to tovorafenib, a type II RAF kinase inhibitor, for the treatment of patients 6 months of age and older with relapsed or refractory pediatric low-grade glioma (pLGG) harboring a BRAF fusion or rearrangement, or BRAF V600 mutation. Efficacy was evaluated in FIREFLY-1 (NCT04775485), a single-arm, open-label, multicenter trial that enrolled patients 6 months to 25 years of age with relapsed or refractory pLGG with an activating BRAF alteration who had received prior systemic therapy. The major efficacy outcome measure was radiologic overall response rate (ORR), defined as the proportion of patients with complete response, partial response, or minor response as determined by blinded independent central review using Response Assessment in Pediatric Neuro-Oncology (RAPNO) criteria.
View Article and Find Full Text PDFMetab Brain Dis
January 2025
Section of Osteimmunology and Oral Immunology, Laboratory of Dental Reseach. FES Iztacala, National Autonomous University of Mexico (UNAM), México, Mexico State, México.
Unlabelled: LCN2 has an osteokine important for appetite regulation; in type 2 diabetes (T2D) it is not known whether appetite regulation mediated by LCN2 in the brain is altered. In this work, we focus on exploring the role of blocking LCN2 in metabolic health and appetite regulation within the central nervous system of mice with T2D.
Material And Methods: 4-week-old male C57BL/6 mice were used, divided into four experimental groups: intact, T2D, TD2/anti-LCN2, and T2D/IgG as isotype control.
Clin Pharmacokinet
January 2025
College of Pharmacy, Kyungsung University, 309, Suyeong-ro, Nam-gu, Busan, 48434, Republic of Korea.
Background And Objective: Telmisartan exhibits significant pharmacokinetic (PK) variability, but it remains unclear whether its PK profile is altered in hypertensive patients. This study aimed to characterize telmisartan PKs by conducting a meta-analysis and developing a pooled population PK model based on data from healthy subjects and hypertensive patients.
Methods: Relevant literature was identified by a systematic approach.
Inflammation
January 2025
Research Center for Food and Cosmetic Safety and Center for Drug Research and Development, Chang Gung University of Science and Technology, Kweishan, Taoyuan, Taiwan.
Atopic dermatitis (AD) is a multifaceted inflammatory skin condition characterized by the involvement of various cell types, such as keratinocytes, macrophages, neutrophils, and mast cells. Research indicates that flavonoids possess anti-inflammatory properties that may be beneficial in the management of AD. However, the investigation of the glycoside forms for anti-AD therapy is limited.
View Article and Find Full Text PDFAging Clin Exp Res
January 2025
Department of Spine Surgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China.
Objective: This study aims to analyze adverse drug events (ADE) related to romosozumab from the second quarter of 2019 to the third quarter of 2023 from FAERS database.
Methods: The ADE data related to romosozumab from 2019 Q2 to 2023 Q3 were collected. After data normalization, four signal strength quantification algorithms were used: ROR (Reporting Odds Ratios), PRR (Proportional Reporting Ratios), BCPNN (Bayesian Confidence Propagation Neural Network), and EBGM (Empirical Bayesian Geometric Mean).
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