MPRINT Hub

Bio

Dr. Lang Li, Professor and Chair of Biomedical Informatics at Ohio State University, serves as MPI of MPRINT's Knowledge, Data, Model, and Research Coordination Center. Dr. Li and his team have been developing the MPRINT Knowledgebase Portal, which houses thousands of curated pharmacology research papers for pediatric and maternal patient populations. The data curation process is significantly enhanced by AI/ML technologies. In the Silver version of MPRINT Knowledgebase (Knowledge Portal (Silver)), all the pharmacology publications are automatically extracted from PubMed for both pediatric and maternal patient populations. This allows user to browse patient subpopulations and study types, such as pharmacokinetics studies, clinical trials, and epidemiology studies. In the Gold version of MPRINT knowledgebase (Knowledge Portal), more detailed data are manually curated from PubMed, including but not limit to study designs, drug effects in patient subpopulations, and risk factors for drug effect. The ultimate goal of MPRINT knowledgebase is to allow researchers to query pharmacology data in maternal and pediatric patient populations, identify knowledge gap, and promote translational pharmacology research.

As the Chair of the Department of Biomedical Informatics and a leader to over 100 faculty, staff, and trainees, Dr. Li brings significant leadership acumen to his role. Beside NICHD, Dr. Li’s translational pharmacoinformatic research is extensively funded by NCI, NLM, and NIA. His NCI supported DrugCombo knowledgebase (Drug Combo) integrates much needed maximum tolerable dose and dose limiting toxicity data from drug combination Phase I trial design. Supported by NLM, Dr. Li conducts translational research which generates pharmacogenetics hypotheses from drug interactions, and these pharmacogenetic hypotheses will be further tested using biobank data. Dr. Li is internationally known for his drug interaction research. Using large-scale electronic health record data and pharmacometrics models, Dr. Li discovers and validates drug interaction evidence in many drug classes, including lipid lower medications, anti-diabetes, anti-coagulants, and anti-hypertension drugs.