Pharmacology Knowledge Base

The Maternal and Pediatric Precision in Therapeutics (MPRINT) knowledge base is a crucial maternal and pediatric research informatics infrastructure. The silver version of the MPRINT knowledge base aims to assist researchers in discovering published maternal and pediatric research easily and quickly. The deep-learning model was trained using a comprehensive maternal and pediatric study corpus. Subsequently, PubMed abstracts were thoroughly screened using the established deep learning model to predict the publication study types and relevant populations. Users can retrieve studies based on the drugs, diseases, specific populations, and study types. 

Reference: PMID: 36625779, https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2835

Contact: Lang Li

The Maternal and Pediatric Precision in Therapeutics (MPRINT) knowledge base is a crucial maternal and pediatric research informatics infrastructure. 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 epidemiological evidence. Each piece of knowledge is well-annotated with relevant information, including demographic information, therapeutics, and other risk factors.

Reference: PMID: 36625779, https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2835

Contact: Lang Li

DrugCombo is a comprehensive knowledge base that integrates drug toxicity and pharmacokinetic data for single drugs and drug combinations from the United States Food and Drug Administration 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 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.  It also provides pharmacokinetic evidence of drug interactions between cancer drugs and other relevant knowledge. DrugCombo currently integrates 8577 drug/target interactions and 8797 drug interactions from DrugBank, 3995 severe adverse drug events (ADEs), 95,535 common ADEs from drug labels, 1,816,030 ADEs from FAERS, and MTD and DLTs from 2592 Phase I trials.

Reference: https://doi.org/10.1158/1538-7445.AM2023-6573 , https://doi.org/10.1200/JCO.2023.41.16_suppl.1571 

Contact: Lang Li

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.

Reference: PMID: 37889037

Contact: Lang Li

CTKG is a knowledge graph integrating a wide variety of information from clinical trials (e.g., interventions, drug side effects, disease symptoms). Together with computational tools to learn from knowledge graphs, CTKG faciliates knowledge discovery from clinical trials, and many relevant tasks such as information retrieval, drug repurposing, etc. 

Reference: PMID: 35304504

Contact: Xia Ning, Access Ning Lab

DRKG is a very large and comprehensive knowledge graph integrating a wide variety of entities, including drugs, diseases, symptoms, genes, proteins, etc. Together with computational tools to learn from knowledge graphs, DRKG facilitates drug repurposing, among other tasks such as information retrieval, etc. 

Reference: https://github.com/gnn4dr/DRKG/blob/master/DRKG%20Drug%20Repurposing%20Knowledge%20Graph.pdf 

Contact: Xia Ning