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HiNZ Webinar 23 June 2017
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Professor Jack London: A Data-Driven Approach to Research in the Precision Medicine Era


12.30pm to 1.30pm, Friday 23 June 2017

  • This one hour webinar is free for anyone to attend.
  • You can view the webinar live or view on-demand later.
  • If you wish to watch it on-demand, rather than live, please still register for the webinar.
  • Available to everyone - you don't need to be a HiNZ member to register.

Register now


Professor London recently spoke at sell-out HISA seminars in Australia and was highly rated by attendees for his insightful presentation. This is your opportunity to hear him for free, without leaving your desk.


Expert speaker

Professor Jack London has worked for 40 years in biomedical informatics research and system development in the domains of bioinformatics, medical informatics, and health care information technology.


Dr. London is a Research Professor of Cancer Biology at Thomas Jefferson University, and Director of Informatics in Jefferson’s Sidney Kimmel Cancer Center. His work has encompassed: computer simulation of biochemical systems, radiology image archiving and communications systems (PACS), hospital information, clinical trials management and telemedicine systems, and tissue banking applications. His focus in recent years has been on pathology and research data analytics (warehouse, data mining). A current project integrates clinical, biospecimen, genomic, and cancer registry data to support researchers in hypothesis generation and cohort definition, including predicting patient accrual to proposed clinical trials.


Webinar content

In this one hour webinar, you will learn how Thomas Jefferson University and Sidney Kimmel Cancer Center (Philadelphia, PA United States) is facilitating clinical trial collaboration with pharmaceutical companies and CROs through a cloud-based research platform for cohort analysis and site selection. 

Members of the TriNetX platform are connected in a federated model with an interoperable terminology mapping. Pharma and CROs can query the aggregate de-identified cohort to determine whether and where an eligible patient population exists. The participating healthcare organizations can query their own data, and that of any other collaborating member for their own trial feasibility or hypothesis generation studies.

The webinar will include an overview and a live demonstration of protocol design using the TriNetX platform.


Register now

This one hour webinar is free for anyone to attend.

You can view the webinar live or view on-demand later.

Register now.


Questions? email Kim at HiNZ


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