AWS Announces Intent to Accelerate Cancer Moonshot
According to a Dec. 8 blog, Amazon Web Services (AWS) announced it will be expanding its work with the Children’s Brain Tumor Network (CBTN) at three of CBTN’s primary clinical sites— Children’s Hospital of Philadelphia (CHOP), Seattle Children’s Hospital, and University of California San Francisco—to accelerate President Biden’s Cancer Moonshot initiative.
We reported on Feb. 2 that President Biden announced via a press release that the Cancer Moonshot is being reignited with renewed White House leadership. In 2016, as Vice President, Joe Biden launched the Cancer Moonshot with the mission to accelerate the rate of progress against cancer.
The initiative’s goals are to reduce the death rate from cancer by at least 50 percent over the next 25 years and to improve the experience of patients and families living with and surviving cancer.
The AWS blog says that “Among all childhood cancers, brain tumors are the leading cause of death. Clinicians and researchers need better access to multiple types of data in order to identify an optimized, individualized treatment approach for each child and develop the next generation of therapies. Today, CBTN—which runs via a coordinating center at CHOP—has data sharing agreements with 32 institutions around the globe. At these institutions, patients are enrolled on local institutional review board (IRB)-approved protocols through which consent is provided for the sharing of de-identified clinical data, demographics, and medical history information. As a result, more than 30 types of de-identified brain and spinal cord tumor clinical and molecular data, biospecimens, diagnosis and treatment data, imaging data, and cell-lines are available at no cost to academic researchers. This open science model enables scientists around the globe to work together on finding treatments, saving time, and building on existing research rather than replicating it and keeping it siloed within the walls of their institutions.”
Further, “However, aggregation and curation of this data currently lacks automation, meaning that a clinical research coordinator often has to manually extract the required data elements from varied and disparate electronic health record (EHR) and other systems in order to get them into a unified database. This process is costly and prone to human error. It is also time-intensive and diverts precious resources away from direct patient care and other higher-value activities. The use of cloud-based technologies can streamline this—reducing the time it takes for newly enrolled patients’ data to be entered and analyzed in the database from months to near real-time.”
AWS, according to the blog, is applying its capabilities in secure semi-federated clinical data ingestion to develop standards-based application programming interfaces (API) to achieve this goal. AWS and its partners’ analytics expertise and machine learning tools will be applied to find undiscovered patterns in certain patient groups.
