Information Technology Program
Individualized medicine, from the early stages of discovery to final applications for patients, relies heavily on information technology resources.
In the laboratory, next-generation sequencing requires large amounts of computational resources, including high-speed servers for identifying genomic variants and storing petabytes (millions of gigabytes) of data.
As promising findings are discovered, Mayo Clinic physicians and scientists need information technology applications for validating and optimizing new laboratory tests and managing clinical trials.
Ultimately, physicians will use Mayo's electronic medical record (EMR) to order new genomic-based tests, retrieve test results, and access new and improved decision-support tools that guide clinicians and patients toward individually appropriate therapies.
Areas of focus
Pharmacogenomic decision support
The Information Technology Program provides the review process, knowledge engineering and implementation of clinical decision-support rules for pharmacogenomic drug and gene-variant combinations.
These rules are implemented in Mayo Clinic's EMR systems — GE Centricity Enterprise and Cerner Millennium — to alert physicians to relevant drug-gene interactions at the point of care and provide recommendations for optimal treatment and dosing.
Next-generation sequencing workbench
The next-generation sequencing workbench provides workflow management and variant review and annotation for aiding clinical interpretation of pathogenic or benign variants, or variants of unknown significance for next-generation DNA sequencing laboratory tests.
Laboratory results are communicated through interpretative reports, and discrete results are transmitted to the EMR environment and medical reference laboratory clients. This is a key diagnostic application that enables improved and scalable genetic panel testing.
Medical genome facility and bioinformatics support
These projects provide computational and storage infrastructure for supporting the primary and secondary analysis of next-generation DNA sequencing. Software engineering and optimization methods are applied to the scientific workflows for improving robustness and scaling of new bioinformatics methods.
Verification and validation are performed as bioinformatics workflows are translated into clinical laboratories. These bioinformatics methods enable new biomarker discovery, diagnostics and treatment opportunities.
Next-generation sequencing portal
The Bioinformatics Core at Mayo Clinic processes large amounts of samples from different next-generation sequencing experiments. With multiple analysts working on the primary and secondary processing of the samples, which belong to various investigators and projects, it is a challenge to track the sample and project metadata, quality-control information, and location of analysis results.
The next-generation sequencing portal is the centralized location for accessing next-generation sequencing data, metadata and associated tools. The portal is an operational "base camp" where different groups can ask questions about sequencing data and get answers quickly without communicating by email.
The portal also has dashboard views of both primary and secondary analysis processes, which makes it possible to track the progress of ongoing runs and projects as well as the history of previously completed runs.
Biological Annotation Data Repository (BioR)
BioR consolidates and centralizes the access and query of biological annotation data. It simplifies the process of downloading, formatting and querying diverse sets of annotations that can be located at local or remote data repositories.
The system then facilitates comprehensive annotation of the large number of molecular data sets produced by high-throughput platforms — next-generation sequencing, proteomics and metabolomics — allowing users to navigate complex biological feature trees and resolve indirect relationships that may exist among annotation sources.
BioR also serves as a source for internally developed annotations that may be generated from experiments done locally or manual annotation of disease-causing single nucleotide polymorphisms (SNPs).
Mayo Clinic Biobank data management infrastructure
The Information Technology Program provides the data management infrastructure for managing biospecimens, such as in the Mayo Clinic Biobank, and specific next-generation sequencing results for research projects.
This infrastructure enables the governance of biospecimens and in silico genomic data for enabling new research and disease control groups.
Variant exploration application
The variant exploration application offers Mayo Clinic investigators a user-friendly tool to explore the genomic variations within their next-generation sequencing (NGS) samples. Through this application they are able to upload all the variants from a given set of NGS samples in addition to the genomic annotation they chose.
Investigators can quickly filter, sort and visualize their samples – allowing them to identify genomic variations of interest.
Large-scale variant management data infrastructure
The Center for Individualized Medicine, through its Information Technology Program, has joined Oracle's Strategic Development Partnership to collaborate on expanding Oracle's Translational Research Center product to centrally manage trillions of unique genetic variants for Mayo Clinic patients.
This partnership allows Mayo to provide strategic direction and influence on future functionality of the Translational Research Center solution. In addition, it allows Mayo early access to innovative technologies.
This resource will help the Center for Individualized Medicine manage genomic variants for multiplexed panels and whole-exome and whole-genome testing, leveraging the enormous amount of genomic data generated through laboratory testing of our patients. The goal is to develop a single infrastructure that can support individualized medicine activities spanning research and clinical practice, complete with privacy and security controls.
Making the Connections That Make Genomics Work
James D. Buntrock, director, Information Technology Program