We are making drugs safer through the analysis of data. Everyday millions of us or our loved ones take medications to manage our health. We trust in these prescriptions to improve our lives and give us hope for a healthier future. Often, however, these drugs have harmful side effects or dangerous interactions. Adverse drug reactions are experienced by millions of patients each year and cost the healthcare industry billions of dollars. In the Tatonetti Lab we use advanced data science methods, including artificial intelligence and machine learning, to investigate these medicines. Using emerging resources, such as electronic health records (EHR) and genomics databases, we are working to identify for whom these drugs will be safe and effective and for whom they will not. Browse our databases, contribute to our projects, and join us on this journey to make precision pharmacology a realty.
Tatonetti Lab pre-releases NSIDES
An updated version (NSIDES pre-release v0.1) of our OFFSIDES/TWOSIDES databases is now available. As with the previous versions, this database contains adverse drug effects for single drugs (OFFSIDES) and drugs used in combination with others (TWOSIDES). This version (v0.1) of OFFSIDES contains adverse event predictions for over 9 million drug-event pairs from 3,394 drugs and 17,552 adverse events. Approximately 125,000 of those drug-event pairs are statistically significant (~36 significant adverse events per drug). For TWOSIDES, over 222 million drug-drug-event triplets are evaluated with 5.7 million significant putative drug interactions. The full release of NSIDES will contain drug-drug-drug and higher order interactions of drugs as well and is currently being computed. The data are made available in csv format and as an MYSQL database dump.
Download the data.
Thanks to Dr. Rami Vanguri for leading the project and Michael Zietz for organizing the release data and information!
Tatonetti Lab goes to Houston for ASHG 2019
Dr. Tatonetti and Phyllis Thangaraj will be presenting at the American Society for Human Genetics Annual Conference, Oct 15-19. Dr. Tatonetti will be giving an invited talk on the use of EHR data for genetic analysis in the session “What about the phenotype? Integrating Electronic Health Records to Drive Discovery in Precision Health” and Phyllis will be giving a Platform Presentation on improving the power of genome-wide association studies by assigning model probabilities of stroke to the UKBiobank. See you in Houston!
Phyllis presents and takes top poster prize at MD-PhD Symposium
Phyllis Thangaraj, MD/PhD Candidate in the lab, presents her work on developing automated stroke phenotyping algorithms for the electronic health records at Columbia’s 14th Annual MD-PhD Student Research Symposium on April 25th, 2019. In addition, she was one of five poster competition winners! Read more about Phyllis in this feature article.