Speaker Profile

Ph.D., CSO, Ibex Medical Analytics

Biography
Daphna has focused her career on personalized medicine, and drives all scientific and regulatory activities at Ibex Medical Analytics, a digital health company using AI and Big Data to create a new modality in cancer diagnostics. Prior to joining Ibex, Daphna served as Head, Personalized Medicine and Diagnostics at Teva Pharmaceuticals, where she supported the discovery, development, differentiation, and led repurposing of Teva’s pipeline drugs, in collaboration with the Israeli healthcare sector and multinational companies. Prior to that, Daphna led biomarker and diagnostic development activities within the pipeline of multiple top-10 pharma and fortune 500 companies. She served in several roles with increasing responsibility at Selventa, a system's biology company focused on personalized medicine, and founded the Israeli branch of the company, as Global Head of Diagnostics. Daphna trained as post-doc at Harvard University, after receiving her PhD in Medical Sciences from the Technion.


AI & Data Science Showcase:
Ibex Medical Analytics

Ibex Medical Analytics develops AI-based cancer diagnostics in pathology, including diagnostic tools for the pathology lab, and algorithmic markers for personalized medicine.

AI-based Prognosis of 5 Year Survival in Prostate Core Needle Biopsies
Using thousands of slides from >500 Maccabi Healthcare patients, we identified multi-feature AI-based algorithmic markers in prostate biopsies that predict 5 year survival. Together with explanatory features associated with pre-biopsy PSA levels, these can support drug development and treatment.

 Session Abstract – PMWC Silicon Valley


The PMWC 2020 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.