|Early Abstract Submission Deadline||April 19, 2019|
|Early Notification of Acceptance||April 25, 2019|
|Notification of Acceptance for Delayed Submissions (after April 19, 2019)||May 6, 2019|
|Early Bird Registration Rate Deadline||May 8, 2019|
|Workshop||June 20, 2019|
High-performance computing has become central to the future success of precision medicine. Catalyzed by the dramatic increase in the volume of research and clinical data available through sequencing and advanced imaging techniques, clinical data available through medical records and mobile health devices, research data from automated platforms, combined with molecular simulations and the rapid adoption of deep learning approaches has created a convergence shaping the frontiers of computing and precision medicine. New approaches to drug discovery, data sharing, aggregation and safeguards, use of machine learning models in research and clinical contexts has identified new challenges and opportunities in these rapidly evolving frontiers.
The Third HPC Applications in Precision Medicine workshop aims to bring together the computational and life sciences communities to share experiences, examine current challenges, and discuss future opportunities for shaping the future for HPC applications in precision medicine.
High-performance computing has become integral to the future success of precision medicine. Catalyzed by the dramatic increase in the amount of research and clinical data available through advanced such technologies as next generation sequencing, advanced imaging, and mobile health monitoring, multiple new approaches are in development to ascend to the potential for precision medicine prevention, detection, diagnostics, treatment and surveillance.Coupled with the rapidly developing capabilities in artificial intelligence, advances in data aggregation, sharing and security, and emerging predictive and prescriptive models, a compelling frontier emerges where high-performance computing enables important improvements in patient outcomes and new innovations accelerating towards a precision medicine future. The HPC Applications in Precision Medicine workshop aims to bring together the breadth of communities including clinical, pharmaceutical, mobile health, health information systems, data security, computational and data science domains to share experiences, examine current challenges, and explore future opportunities for high-performance computing enabled applications in precision medicine. In the workshop, we bring together individuals from across the globe with these interests and more to share insights, experiences and showcase new capabilities in this rapidly evolving field.
The workshop is expected to attract those researchers, thought leaders, clinicians, data engineers and scientists, health information leaders, computational innovators across academia, industry and non-profit organizations globally to identify challenges and opportunities in computational precision medicine, sharing both common and unique perspectives to seed future collaborative solutions. Leaders in large-scale computing, deep learning, modeling and simulation join the community with glimpses into the future. The workshop also draws individuals from the breadth of precision medicine application areas spanning research to clinical application in areas including drug discovery, preclinical validation, diagnostics, health monitoring, precision biomarker development, prevention and early detection, treatment determination and population studies, interested in the computational and data challenges and opportunities created in precision and predictive medicine.
The initial workshop organizing committee has spearheaded the identification of presenters from both Europe, US and Asia. The committee was strongly supported by colleagues in identifying the slate of presenters for past workshops and has support for the same in developing the program for the 2019 workshop.
Eric Stahlberg – Frederick National Laboratory for Cancer Research
Jan Nygard – Cancer Registry of Norway
Christian Bolliger – ETH Zurich
Thomas Steinke – Zuse Institute Berlin
Sunita Chandrasekaran - University of Delaware