Dataset Information

CDCDB: A large and continuously updated drug combination database.

ABSTRACT: In recent years, due to the complementary action of drug combinations over mono-therapy, the multiple-drugs for multiple-targets paradigm has received increased attention to treat bacterial infections and complex diseases. Although new drug combinations screening has benefited from experimental tests like automated high throughput screening, it is limited due to the large number of possible drug combinations. The task of drug combination screening can be streamlined through computational methods and models. Such models require up-to-date databases; however, existing databases are static and consist of the data collected at the time of their creation. This paper introduces the Continuous Drug Combination Database (CDCDB), a continuously updated drug combination database. The CDCDB includes over 40,795 drug combinations, of which 17,107 are unique combinations consisting of more than 4,129 individual drugs, curated from ClinicalTrials.gov, the FDA Orange Book^®, and patents. To create CDCDB, we use various methods, including natural language processing techniques, to improve the process of drug combination discovery, ensuring that our database can be used for drug synergy prediction. Website: https://icc.ise.bgu.ac.il/medical_ai/CDCDB/ .

SUBMITTER: Shtar G

PROVIDER: S-EPMC9163158 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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CDCDB: A large and continuously updated drug combination database.

Shtar Guy G Azulay Louise L Nizri Omer O Rokach Lior L Shapira Bracha B

Scientific data 20220602 1

In recent years, due to the complementary action of drug combinations over mono-therapy, the multiple-drugs for multiple-targets paradigm has received increased attention to treat bacterial infections and complex diseases. Although new drug combinations screening has benefited from experimental tests like automated high throughput screening, it is limited due to the large number of possible drug combinations. The task of drug combination screening can be streamlined through computational methods ...[more]

PMID: 35654801

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Project description:BackgroundMigrations in temperate systems typically have two migratory phases, spring and autumn, and many migratory ungulates track the pulse of spring vegetation growth during a synchronized spring migration. In contrast, autumn migrations are generally less synchronous and the cues driving them remain understudied. Our goal was to identify the cues that migrants use in deciding when to initiate migration and how this is updated while en route.MethodsWe analyzed autumn migrations of Arctic barren-ground caribou (Rangifer tarandus) as a series of persistent and directional movements and assessed the influence of a suite of environmental factors. We fitted a dynamic-parameter movement model at the individual-level and estimated annual population-level parameters for weather covariates on 389 individual-seasons across 9 years.ResultsOur results revealed strong, consistent effects of decreasing temperature and increasing snow depth on migratory movements, indicating that caribou continuously update their migratory decision based on dynamic environmental conditions. This suggests that individuals pace migration along gradients of these environmental variables. Whereas temperature and snow appeared to be the most consistent cues for migration, we also found interannual variability in the effect of wind, NDVI, and barometric pressure. The dispersed distribution of individuals in autumn resulted in diverse environmental conditions experienced by individual caribou and thus pronounced variability in migratory patterns.ConclusionsBy analyzing autumn migration as a continuous process across the entire migration period, we found that caribou migration was largely related to temperature and snow conditions experienced throughout the journey. This mechanism of pacing autumn migration based on indicators of the approaching winter is analogous to the more widely researched mechanism of spring migration, when many migrants pace migration with a resource wave. Such a similarity in mechanisms highlights the different environmental stimuli to which migrants have adapted their movements throughout their annual cycle. These insights have implications for how long-distance migratory patterns may change as the Arctic climate continues to warm.

Project description:Conducting systematic reviews of clinical trials is arduous and resource consuming. One potential solution is to design databases that are continuously and automatically populated with clinical trial data from harmonised and structured datasets. We aimed to map publicly available, continuously updated, topic-specific databases of randomised clinical trials (RCTs). We systematically searched PubMed, Embase, the preprint servers medRxiv, ArXiv, and Open Science Framework, and Google. We described seven features (access model, database architecture, data input sources, retrieval methods, data extraction methods, trial presentation, and export options) and narratively summarised the results. We did not register a protocol for this review. We identified 14 continuously updated clinical trial databases, seven related to COVID-19 (first active in 2020) and seven non-COVID databases (first active in 2009). All databases, except one, were publicly funded and accessible without restrictions. They mainly employed methods similar to those from static article-based systematic reviews and retrieved data from journal publications and trial registries. The COVID-19 databases and some non-COVID databases implemented semi-automated features of data import, which combined automated and manual data curation, whereas the non-COVID databases mainly relied on manual workflows. Most reported information was metadata, such as author names, years of publication, and link to publication or trial registry. Two databases included trial appraisal information (risk of bias assessments). Six databases reported aggregate group level results, but only one database provided individual participant data on request. We identified few continuously updated trial databases, and existing initiatives mainly employ methods known from static article -based reviews. The main limitation to create truly live evidence synthesis is the access and import of machine-readable and harmonised clinical trial data.

Dataset Information

CDCDB: A large and continuously updated drug combination database.

Publications

CDCDB: A large and continuously updated drug combination database.

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