Toward predictive models for drug-induced liver injury in humans: are we there yet?

Drug-induced liver injury (DILI) is a frequent cause for the termination of drug development programs and a leading reason of drug withdrawal from the marketplace. Unfortunately, the current preclinical testing strategies, including the regulatory-required animal toxicity studies or simple in vitro tests, are insufficiently powered to predict DILI in patients reliably. Notably, the limited predictive power of such testing strategies is mostly attributed to the complex nature of DILI, a poor understanding of its mechanism, a scarcity of human hepatotoxicity data and inadequate bioinformatics capabilities. With the advent of high-content screening assays, toxicogenomics and bioinformatics, multiple end points can be studied simultaneously to improve prediction of clinically relevant DILIs. This review focuses on the current state of efforts in developing predictive models from diverse data sources for potential use in detecting human hepatotoxicity, and also aims to provide perspectives on how to further improve DILI prediction.

Money, sex, and drugs: a case study to teach the genetics of antibiotic resistance.

The goal of the work reported here was to help students expand their understanding of antibiotic resistance, the Central Dogma, and evolution. We developed a unit entitled "Ciprofloxacin Resistance in Neisseria gonorrhoeae," which was constructed according to the principles of scientific teaching by a team of graduate students, science faculty, and instructors. A variety of activities and assessments were used, including a case study, short lectures, and group problem-solving. Implementation of "Ciprofloxacin Resistance in Neisseria gonorrhoeae" in a college freshman seminar suggests these materials are useful in increasing understanding of complex biological topics and improving problem-solving abilities.