Bio-IT World Announces 2017 Best Practices Awards Winners
May 25, 2017 | BOSTON—Bio-IT World announced the winners of the 2017 Best Practices Awards this morning at the Bio-IT World Conference and Expo. Entries from Maccabi Healthcare System, Rady Children’s Institute for Genomic Medicine, Allotrope Foundation, Earlham Institute, Biomedical Imaging Research Services Section (BIRSS), and Alexion Pharmaceuticals were honored.
Since 2003, the Bio-IT World Best Practices Awards has honored excellence in bioinformatics, basic and clinical research, and IT frameworks for biology and drug discovery. Winners were chosen in four categories, and two discretionary awards this year as well.
“Looking back at the fourteen years since our first Best Practices competition, I am amazed by how far the bio-IT field has come. I continue to be inspired by the work done in our field,” said Bio-IT World Editor Allison Proffitt. “The Bio-IT World Community is increasingly open, and the partnerships and projects showcased here prove our dedication to collaborative excellence.”
Bio-IT World debuted the Best Practices Awards at the second Bio-IT World Conference & Expo in 2003, hoping to not only elevate the critical role of information technology in modern biomedical research, but also to highlight platforms and strategies that could be widely shared across the industry to improve the quality, pace, and reach of science. In the years since, hundreds of projects have been entered in the annual competition, and over 80 prizes have been given out to the most outstanding entries.
This year, a panel of eleven invited expert judges joined the Bio-IT World editors in reviewing detailed submissions from pharmaceutical companies, academic centers, government agencies, and technology providers.
The awards ceremony was held at the Seaport World Trade Center in Boston, where the winning teams received their prizes from Proffitt, veteran judge Chris Dwan, and Philips Kuhl, president of conference organizer Cambridge Healthtech Institute.
2017 Bio-IT World Best Practices Award Winners:
Clinical IT & Precision Medicine:
Maccabi Healthcare System nominated by Medial EarlySign
Identifying High-Risk, Under-the-Radar Patients
In October 2015, Maccabi Healthcare System joined forces with Medial EarlySign to implement advanced AI and machine learning algorithms to uncover the “hidden” signals within electronic medical records (EMRs) and identify unscreened individuals at high risk of harboring Colorectal Cancer. The system used existing EMR Data only, including routine blood counts.
ColonFlag evaluated nearly 80,000 outpatient blood count tests results collected over one year, and flagged 690 individuals (approximately 1%) as highest risk population for further evaluation. Of those, 220 colonoscopies were performed, of which 42% had findings including 20 cancers (10%).
Informatics:
Rady Children’s Institute for Genomic Medicine nominated by Edico Genome
Precision medicine for newborns by 26-hour Whole Genome Sequencing
Genetic diseases, of which there are more than 5,000, are the leading cause of death in infants, especially in Neonatal Intensive Care Units (NICU) and Pediatric Intensive Care Units (PICU). The gateway to precision medicine and improved outcomes in NICUs/PICUs is a rapid genetic diagnosis. Diagnosis by standard methods, including whole genome sequencing (WGS), is too slow to guide NICU/PICU management. Edico Genome, Rady Children’s Institute for Genomic Medicine, and Illumina have developed scalable infrastructure to enable widespread deployment of ultra-rapid diagnosis of genetic diseases in NICUs and PICUs. First described in “A 26-hour system of highly sensitive WGS for emergency management of genetic diseases” in September 2015, we have now improved and implemented this infrastructure at Rady Children’s Hospital (RCH). Among the first 48 RCH infants tested, 23 received diagnoses and 16 had a substantial change in NICU/PICU treatment. We are currently equipping other children’s hospitals to emulate these results.
Knowledge Management:
Allotrope Foundation
The Allotrope Framework: A holistic set of capabilities to improve data access, interoperability and integrity through standardization, and enable data-driven innovation
The Allotrope Framework is comprised of a technique-, vendor-, and platform-independent file format for data and contextual metadata (with class libraries to ensure consistent implementation); Taxonomies and Ontologies- an extensible basis of a controlled vocabulary to unambiguously describe and structure metadata; and Data Models that describe the structure of the data.
Member companies, collaborating with vendor partners, have begun to demonstrate how the Framework enables cross-platform data transfer, facilitates finding, accessing and sharing data, and enables increased automation in laboratory data flow with a reduced need for error-prone manual input. The first production release is available to members and partners (as of Q4 2015), and phased public releases of the framework components will become available beginning mid-2017.
IT infrastructure/HPC:
Earlham Institute
Improving Global Food Security and Sustainability By Applying High-Performance Computing To Unlock The Complex Bread Wheat Genome
One of the most important global challenges to face humanity will be the obligation to feed a world population of approximately nine billion people by 2050. Wheat is grown on the largest area of land of any crop at over 225 million hectares, and over two billion people worldwide are dependent on this crop as their daily staple diet. Unfortunately, the six primary crop species see up to 40% loss in yield due to plant disease. Furthermore, a changing climate, increased degradation in arable land, reduction in biodiversity through rainforest destruction, and increasing sea levels all contribute to declining crop yields that greatly undermines global food security and sustainability. A solution to this grand challenge is to unlock the complex genomics of important crops, such as bread wheat, to identify the genes that underlie resistance to disease and environmental factors. One of the toughest crops to tackle, bread wheat has a hugely complex genome and is five times bigger than the human genome, with 17 billion base pairs of DNA. By exploiting leading-edge HPC infrastructure deployed at the Earlham Institute (EI), scientists have now assembled the genomic blueprint of the bread wheat genome for the very first time. By analyzing this wheat assembly, breeders worldwide can now begin to explore new variations of wheat that exhibit the very traits that will help improve its durability in the face of dogged disease and climate change.
Judges’ Choice:
Biomedical Imaging Research Services Section (BIRSS) nominated by SRA International
Biomedical Research Informatics Computing System (BRICS)
The Biomedical Research Informatics Computing System (BRICS) is a dynamic, expanding, and easily reproducible informatics ecosystem developed to create secure, centralized biomedical databases to support research efforts to accelerate scientific discovery, by aggregating and sharing data using Web-based clinical report form generators and a data dictionary of Clinical Data Elements. Effective sharing of data is a fundamental attribute in this new era of data informatics. Such informatics advances create both technical and political challenges to efficiently and effectively use biomedical resources. Designed to be initially un-branded and not associated with a particular disease, BRICS has been used so far to support multiple neurobiological studies, including the Federal Interagency Traumatic Brain Injury Research (FITBIR) program, the Parkinson's Disease Biomarkers Program (PDBP), and the National Ophthalmic Disease Genotyping and Phenotyping Network (eyeGENE). Supporting the storage of phenotypic, imaging, neuropathological, and genomics data, the BRICS instances currently have more than 31,500 subjects.
Editor's Choice:
Alexion Pharmaceuticals nominated by EPAM Systems
Alexion Insight Engine
The Alexion Insight (AI) Engine is a decision support system that provides senior executives and corporate planning staff answers to business and scientific questions across a landscape of approximately 9,000 rare diseases. The AI Engine filters and sorts across key criteria such as prevalence, clinical trials, severity, and onset to prioritize in real-time diseases of interest for targets, line extensions, and business development activity. Over a period of two years Alexion worked with EPAM to develop the AI Engine. The system integrates data from several external data sources into a cloud-based, Semantic Web database. Gaps and errors in publicly available data were filled and corrected by a team of expert curators. The engine supports an interactive, web-based interface presenting the rare disease landscape. The AI Engine has reduced the amount of time required to produce recommendations to senior management on promising disease candidates from a few months to mere minutes.
Honorable Mention:
Fermenta - B.
IoT in the new approach in agriculture : BioPass - Road map for developing and achieving open standards reflecting best solutions in organic farming
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