The 7th Annual PREDiCT: Tumor Models Boston summit will be held on July 16 – 18 2019 in Boston, MA. For its anticipated return, Tumor Models Boston rebrands alongside its sister events in San Francisco, London and Asia (previously in Shanghai, new location tbc) to become PREDiCT: Tumor Models Boston as part of the PREDiCT: Tumor Models Series.
PREDiCT: a Renowned Series of Events Set to Support Scientists in Preclinical Cancer Research
Tumor models utilization has been progressing and evolving rapidly over the last 6 years amongst pharma and biotech. The adoption of such pre-clinical models has armed decision making and boosted scientists’ confidence to translate candidates into clinic at a faster pace.
The PREDiCT series aims at helping the pre-clinical oncology community to improve predictability and translatability of pre-clinical model studies, empowering better clinical decisions and fast tracking oncology development programs. The PREDiCT community serves as a dedicated and unique platform for tumor model users, developers and researchers to share their latest data and experience to improve cancer research.
This year’s meeting in Boston will host 130+ senior pre-clinical leaders, who are committed to improving their model selection, validation and application during pre-clinical studies, in particular immuno-oncology areas which requires a much more robust and sophisticated emerging model technique to support preclinical evidence.
A Unique Chance to Network with the Field’s Experts
Taking place in the biotech hub Boston, Tumor Model Boston Summit will welcome 39 tumor model pioneers including AstraZeneca, Kleo Pharmaceuticals, Dicerna, Crown Bioscience, Sanofi, Eisai, Novartis, The Jackson Laboratory and many others. The industry’s giants are set to reveal their first hand data and journey:
- the role of humanized and PDX models,
- microenvironment studies,
- CRISPR powered organoid strategies and
- the real potential of 3D models for immune-tumor interactions.
The 3-day summit will enable preclinical and translational scientists to make informed decisions of cancer R&D, enhancing predictability and translatability of early discoveries into clinic.