Dataset Information

Global Substance Registration System: consistent scientific descriptions for substances related to health.

ABSTRACT: The US Food and Drug Administration (FDA) and the National Center for Advancing Translational Sciences (NCATS) have collaborated to publish rigorous scientific descriptions of substances relevant to regulated products. The FDA has adopted the global ISO 11238 data standard for the identification of substances in medicinal products and has populated a database to organize the agency's regulatory submissions and marketed products data. NCATS has worked with FDA to develop the Global Substance Registration System (GSRS) and produce a non-proprietary version of the database for public benefit. In 2019, more than half of all new drugs in clinical development were proteins, nucleic acid therapeutics, polymer products, structurally diverse natural products or cellular therapies. While multiple databases of small molecule chemical structures are available, this resource is unique in its application of regulatory standards for the identification of medicinal substances and its robust support for other substances in addition to small molecules. This public, manually curated dataset provides unique ingredient identifiers (UNIIs) and detailed descriptions for over 100 000 substances that are particularly relevant to medicine and translational research. The dataset can be accessed and queried at https://gsrs.ncats.nih.gov/app/substances.

SUBMITTER: Peryea T

PROVIDER: S-EPMC7779023 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Global Substance Registration System: consistent scientific descriptions for substances related to health.

Peryea Tyler T Southall Noel N Miller Mitch M Katzel Daniel D Anderson Niko N Neyra Jorge J Stemann Sarah S Nguyễn Ðắc-Trung ÐT Amugoda Dammika D Newatia Archana A Ghazzaoui Ramez R Johanson Elaine E Diederik Herman H Callahan Larry L Switzer Frank F

Nucleic acids research 20210101 D1

The US Food and Drug Administration (FDA) and the National Center for Advancing Translational Sciences (NCATS) have collaborated to publish rigorous scientific descriptions of substances relevant to regulated products. The FDA has adopted the global ISO 11238 data standard for the identification of substances in medicinal products and has populated a database to organize the agency's regulatory submissions and marketed products data. NCATS has worked with FDA to develop the Global Substance Regi ...[more]

PMID: 33137173

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Project description:BACKGROUND:Science studies have been a field of research for different knowledge areas, and they have been successfully used to analyse the construction of scientific knowledge, practice and dissemination. In this study, we aimed to verify how the Zika epidemic has moulded the scientific articles published worldwide by analysing international collaborations and the knowledge landscape through time, as well as research topics and country involvement. METHODOLOGY:We searched the Web of Science (WoS), Scopus and PubMed for studies published up to 31st December 2018 on Zika using the search terms "zika", "zkv" or "zikv". We analysed the scientific production regarding which countries have published the most, on which topics, as well as country level collaboration. We performed a scientometric analysis of research on Zika focusing on knowledge mapping and the scientific research path over time and space. FINDINGS:We found two well defined research areas divided into three subtopics accounting for six clusters. With regard to country analysis, the USA and Brazil were the countries with the highest numbers of publications on Zika. China entered as a new player focusing on specific research areas. When we took into consideration the epidemics and reported cases, Brazil and France were the leading research countries on related topics. As for international collaboration, the USA followed by England and France stand out as the main hubs. The research areas most published included public health-related topics from 2015 until the very beginning of 2016, followed by an increase in topics related to the clinical aspects of the disease in 2016 and the emergence of laboratory research in 2017/2018. CONCLUSIONS:Mapping the response to Zika, a public health emergency, demonstrated a clear pattern of the participation of countries in the scientific advances. The pattern of knowledge production found in this study represented varying country perspectives, research capacity and interests based first on their level of exposure to the epidemic and second on their financial positions regarding science.

Project description:BackgroundFurther improvements in population health in low- and middle-income countries demand high-quality care to address an increasingly complex burden of disease. Health facility surveys provide an important but costly source of information on readiness to provide care. To improve the efficiency of health system measurement, we applied unsupervised machine learning methods to assess the performance of the service readiness index (SRI) defined by the World Health Organization and compared it to empirically derived indices.MethodsWe drew data from nationally representative Service Provision Assessment surveys conducted in 10 countries between 2007 and 2015. We extracted 649 items in domains such as infrastructure, medication, and management to calculate an index using all available information and classified facilities into quintiles. We compared three approaches against the full item set: the SRI, a new index based on sequential backward selection, and an enriched SRI that added empirically selected items to the SRI. We evaluated index performance with a cross-validated kappa statistic comparing classification using the candidate index against the 649-item index.Results9238 facilities were assessed. The 49-item SRI performed poorly against the index using all 649 items, with a kappa value of 0.35. New empirically derived indices with 50 and 100 items captured much more information, with cross-validated kappa statistics of 0.71 and 0.80, respectively. Items varied across the indices and in sensitivity analyses. A 100-item enriched SRI reliably captured the information from the full index: 83% of the facilities were classified into correct quintiles of service readiness based on the full index.ConclusionA facility readiness measure developed by global health experts performed poorly in capturing the totality of readiness information collected during facility surveys. Using a machine learning approach with sequential selection and cross-validation to identify the most informative items dramatically improved performance. Such approaches can make assessment of health facility readiness more efficient. Further improvements in measurement will require identification of external criteria-such as patient outcomes-to guide and validate measure development.

Dataset Information

Global Substance Registration System: consistent scientific descriptions for substances related to health.

Publications

Global Substance Registration System: consistent scientific descriptions for substances related to health.

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