The United States Food and Drug Administration (FDA or USFDA) is a federal agency of the Department of Health and Human Services. The FDA is responsible for protecting and promoting public health through the control and supervision of food safety, tobacco products, dietary supplements, prescription and over-the-counter pharmaceutical drugs (medications), vaccines, biopharmaceuticals, blood transfusions, medical devices, electromagnetic radiation emitting devices (ERED), cosmetics, animal foods & feed and veterinary products.The FDA's primary focus is enforcement of the Federal Food, Drug, and Cosmetic Act (FD&C), but the agency also enforces other laws, notably Section 361 of the Public Health Service Act, as well as associated regulations. Much of this regulatory-enforcement work is not directly related to food or drugs, but involves such things as regulating lasers, cellular phones, and condoms, as well as control of disease in contexts varying from household pets to human sperm donated for use in assisted reproduction.The FDA is led by the Commissioner of Food and Drugs, appointed by the President with the advice and consent of the Senate. The Commissioner reports to the Secretary of Health and Human Services. Robert Califf is the current commissioner, as of 17 February 2022[update].The FDA has its headquarters in unincorporated White Oak, Maryland. The agency also has 223 field offices and 13 laboratories located throughout the 50 states, the United States Virgin Islands, and Puerto Rico. In 2008, the FDA began to post employees to foreign countries, including China, India, Costa Rica, Chile, Belgium, and the United Kingdom.
Lagging pediatric safety and effectiveness data increase the risks to children associated with off-label drug use. The objective of this study was to delineate the frequency of, and reasons behind, delays in the completion of mandated pediatric postmarketing requirement (PMR) studies. Publicly accessible and internal US Food and Drug Administration (FDA) data were aggregated to characterize pediatric PMRs issued from 2012 to 2024, including relevant dates, durations, and deferral extension (DE) requests. Sponsor size, and clinical trial enrollment status were also examined. There were 1160 pediatric PMRs identified, 459 of which were associated with 1176 DE requests. Despite a significant decline in the annual number of PMRs issued (slope [95
Establishing credibility of computational modeling of medical devices is critical when an incorrect decision could cause patient harm. Uncertainty quantification (UQ) can impart credibility by providing an estimate of the model uncertainty due to variability in the input parameters. To perform UQ, non-deterministic simulations are performed where model inputs are represented by probability density functions (PDFs). Computational modeling of medical devices, however, is typically constrained by limited sample sizes and sparse experimental data. As a result, it is generally not possible to definitively characterize the true input distributions for UQ. The sparse data must instead be fit with an assumed PDF. While the assumption of a Gaussian distribution is common, other PDFs may be more appropriate depending on the context. In this study, we investigate the influence of input PDF choice on output uncertainty from non-deterministic finite element simulations of a nitinol medical device. We first characterize the geometry, material properties, and the experimental test conditions. We then perform a screening study to determine the relative importance of each parameter on our primary quantity of interest (QOI), peak strain amplitude. Next we perform three UQ studies, each using one of three different PDF types: Gaussian, gamma, and uniform. By sampling the input parameter PDFs using a Latin hypercube approach, we perform non-deterministic simulations to predict the output distributions. Our results show that use of uniform distributions yields output predictions with the largest variance and is thus the most conservative choice unless infrequent events are of interest. In contrast, we show that for conservative predictions of extreme events, a better choice is to use Gaussian or gamma distributions with asymptotic tails of finite probability that are neglected when using uniform distributions.
Detection of N-nitrosamines (NA) in pharmaceuticals became a point of interest due to the mutagenic and carcinogenic potential of some compounds of this class, and their identification as nitrosated forms of marketed drugs, otherwise known as NA Drug Substance-Related Impurities (NDSRIs). The Ames test is used to assess the mutagenic potential of drug impurities, including NAs. Concerns over the sensitivity of the Ames test, as recommended in Organization for Economic Co-operation and Development Test Guideline 471, in predicting the rodent carcinogenic potential of NAs has prompted optimization of several test parameters used for detecting the mutagenicity of NAs (e.g. methods used for metabolic activation and the selection of tester strains). In order to discuss optimal Ames test conditions for the evaluation of NAs, including NDSRIs, the Office of New Drugs in the US Food and Drug Administration's Center for Drug Evaluation and Research and the Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee co-organized and co-sponsored a workshop entitled "Nitrosamines: Ames Data Review and Method Development Workshop". The workshop featured five sessions addressing charge questions pertinent to the Ames test conditions and performance through the presentation of data and panel discussions. This report outlines the key takeaway points from the workshop.
On Oct 7 and 8, 2024, the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) co-hosted a workshop titled "Scientific and Regulatory Considerations for Assessment of Immunogenicity Risk for Generic Peptide and Oligonucleotide Drug Products". Stakeholders from the FDA, industry, academia, and contract research organizations convened to discuss strategies for advancing risk assessment methodologies and regulatory frameworks for complex generic products. By assembling experts from various sectors, the workshop explored various available strategies for immunogenicity risk assessment, providing valuable insights to support the development and assessment of generic peptide and oligonucleotide drug products. The discussions fostered a deeper understanding of how these methodologies can inform regulatory decision-making and enhance the development of safer and more effective therapeutics.
This Viewpoint describes the US Food and Drug Administration’s intended label updates and removal of black box warnings for menopausal hormone therapy based on current evidence.
