Abstract

Concurrent Toxicity and Efficacy Evaluations in Multi-Organ Functional Human-on-a-Chip Systems

James Hickman, Professor, University of Central Florida

The current drug development process is inefficient, taking years from target compound identification to marketable drug, and costs up to 2 billion dollars during the process. The considerable attrition-rate of drug candidates at all stages of development to a significant extent arises from the poor predictive nature of preclinical models for efficacy and toxicity, especially the inability to translate efficacy between preclinical and clinical situations. Systems capable of directly measuring organ function, biomarker release, and most importantly the synergistic interactions between organs, especially the generation of liver metabolites would be ideal. Body-on-a-chip systems utilize function based cell models that accurately capture and predict multi organ complexity in response to administered compound within correctly scaled and physiologically relevant platforms. This data can then theoretically be used to produce relevant modeling information related to drug responses in clinical settings, and thereby provide accurate predictions of a compound’s patient specific toxicology and efficacy. We have demonstrated functional human models to evaluate multi-organ toxicity in 2-, 3- and 4-organ systems under continuous flow conditions in a serum-free defined medium utilizing a pumpless platform for 28 days with cardiac, muscle, cancer, neuronal and liver modules. The pharmacological relevance of these integrated modules was evaluated with drugs and compared to human and animal data and these results will be presented. There currently is also a focus at the NIH, FDA and EMA to understand how one could validate these systems such that qualification could be granted for their use to augment and possibly replace animal studies. This talk will also give results of six workshops held at NIH as a collaboration between the American Institute for Medical and Biological Engineering (AIMBE) and NIH to explore what is needed for validation and qualification of these new systems.