zPREDICTA is developing organ-specific, physiologically-relevant 3D cell culture models providing a 1-to-1 reconstruction of human tissues. This is the only available 3D culture approach that comprehensively accounts for the major components of the cellular and extracellular tissue microenvironment preserving the critical interactions between a tumor and its surroundings. Clinical study data demonstrate the high correlation between drug efficacy measured in our platform and the clinical response. The ability of the zPREDICTA platform to reliably predict clinical outcomes offers superior compound attrition management, empowering researchers to exclude ineffective compounds while selecting agents with a high probability of success in the clinic. Our approach is compatible with any drug class, multiple tissue/cell types and a wide variety of readouts. Our customers are using these models for efficacy screening of anticancer compounds, including immuno-oncology agents, evaluation of mechanisms of drug resistance, the rescue of failed drug candidates, assessment of off-target toxicity, and a multitude other applications.
Training and experience: - B.S., Genetics w/ psychology minor, University of California, Davis (1998) - Ph.D., Molecular & Cellular Biology, City of Hope National Medical Center (2003) - Postdoctoral fellow, Lawrence Berkeley National Labs (2004-2006) - Postdoctoral fellow, University of Alberta Cross Cancer Institute (2006-2008) - Assistant professor, Purdue University Department of Biology (2008-2014) - Scientific Founder & CEO, zPREDICTA, Inc. (2014-present)