MPRINT knowledge base (Silver version)
The Obstetric and Pediatric Pharmacology and Therapeutics Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) established the Maternal and pediatric Precision in Therapeutics (MPRINT) Hub to serve as a national resource for conducting and fostering research in pregnant, lactating, and pediatric patients.
The aim of the silver version of the MPRINT knowledge base is to assist researchers in easily and quickly discovering published maternal and pediatric research. The BioBERT deep learning model was trained using a comprehensive maternal and pediatric study corpus. Subsequently, a thorough screening of PubMed abstracts was conducted using the established deep learning model to predict the publication study types and relevant populations. Users can retrieve studies on the drugs and/or diseases mentioned in this article.
MPRINT knowledge base (Gold version)
The Obstetric and Pediatric Pharmacology and Therapeutics Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) established the Maternal and Pediatric Precision in Therapeutics (MPRINT) Hub to serve as a national resource for conducting and fostering research in pregnant, lactating, and pediatric patients.
The gold version of the MPRINT knowledge base aims to provide expert-curated knowledge from published maternal and pediatric studies. It primarily provides drug pharmacokinetic parameters and epidemiology evidence. Each piece of knowledge is well annotated with demographic information (e.g., pregnancy stage and exposure).
DrugCombo
DrugCombo is a comprehensive knowledge base that integrates drug toxicity data and pharmacokinetic data for single drugs and drug combinations from the United States Food and Drug Administration (FDA) Adverse Event Report System (FAERS), drug labeling from the National Library of Medicine’s DailyMed website, published study results in PubMed, and the DrugBank database. DrugCombo is the first such database to contain crucial data, such as the maximum tolerable dose (MTD), dose-limiting toxicity (DLT), and dose range, for Phase I clinical trial design as well as pharmacokinetic evidence of drug interactions among cancer drugs. Currently, DrugCombo integrates 8577 drug/target interactions and 8797 drug interactions from DrugBank, 3995 severe adverse drug events (ADEs), 95,535 common ADEs from drug labels, ,816,030 ADEs from FAERS, and MTD and DLTs from 2592 Phase I trials.
SLKB
Synthetic lethality knowledge base (SLKB) is dedicated to curating CRISPR double knockout experiments (CDKO) aiming to identify synthetic lethal (SL) interactions between two genes. SL identification is highly context dependent, differing across pathways, gene targets, cell lines, and CDKO libraries. SLKB analysis pipeline, additionally distributed as a python package, allows SL score calculation for CDKO studies. Via SLKB, users can analyze their own CDKO data and browse their results.
SLKB documentation: https://slkb.docs.osubmi.org/