Digital tools to enable clinical genomics Melbourne Genomics Health Alliance
Melbourne Genomics Health Alliance Medical Medical Scientist Masters of Genetic Clinical Health service Workforce Variant Curator Genetic Trainee Clinician CPD Online CPD Specialist curation CPD Genomics and Counsellor Bioinformatics research development Cross-training Projects workshops modules Immersion workshops Health training Bursaries workforce Patient Evaluation Impact of Flagship Process Flagship Health preferences, Impact on Additional Baby Beyond Workforce Implementation Data Sharing Genomics (x11) (x 11) Economics (x8) experience & Genetic Services Findings Service Hearing program Factors value New Human Additional Additional Data Access and Innovation Chromium Lab accreditation Prototype Superbugs Implementation Implementation Genome Findings clinical Findings analysis Release policies & adoption Technology framework systems report format Framework tools (TBD) Reference Build service service and procedures Clinical Variant curation Genome Research Requirements & Bioinformatics Data SMART on FHR Agnostic pipeline GenoVic Procurement tool Orchestration Data Security Environment Design platform Governance feasibility study proof of concept implementation Service Proof of Concept implementation Support and Experts-in- Dissemination of Dissemination Leadership Ambassador Immersion Stakeholder Community contribute residence results: of results: program visitor program engagement engagement nationally and program government public internationally 2
GenoVic Data & Technology
Common Clinical Genomic Workflow LABORATORY CLINIC CLINIC & LABORATORY PERFORM BIOINFORMATIC MULTIDISCIPLINARY RETURN GENERATE CLINICAL PATIENT COLLECT DNA SEQUENCE DNA PERFORM CURATION TEAM REVIEW REPORT RESULTS ANALYSIS 4
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Glacier FHIR API’s Place Order View Order Get Order Status Report Details Lab Portal Lab Portal Lab LIMS RMH Monash VCGS 7
GenoVic LTS Full Workflow TRANSFER LAB VCF API CURATION VCF DATA FASTQ FHIR FHIR LAB PREP REPORT DNA
Adoption In Use • The Victoria Clinical Genetics Services at the Royal Childrens Hospital • The Royal Melbourne Hospital and the Australian Genome Research Facility Onboarding • Monash Health and the Australian Genome Research Facility 9
User Engagement Data & Technology
Product Shortlist Alliance evaluation Limited RFP and suppliers Issued shortlist completed December 2016 Pre- August 31 st 2016 Workshop #1 Workshop #3 Open Limited Product Qualification Q&A Closed Implementation & August 16 th 2016 Discovery Operations Dialogue RFP (EOI) September 14 th - October 5 th -6 th 15 th 2016 2016 1 2 3 EOI Supplier Alliance evaluation Response Due and supplier August 22 nd assessment EOI Briefing Workshop #2 Product invitation 2016 completed Session and Info Solution Deep Dive to participate in October 2016 Pack Released September 20 th -21 st Open Dialogue August 9 th 2016 2016 September 1 st 2016 Dates may be subject to change Melbourne Genomics Health Alliance | Supplementary Information Material 11
Variant curation tool selection • Pilot – evaluation of each tool’s functionality and usability • RFQ – evaluation of written response submitted by vendors 12
Evaluation Team members Name Role Organisation Melanie O’Keefe Observer AGRF Thomas Mikeska Observer Austin Mat Wallis Evaluator Austin Dong Anh Khuong Evaluator MCRI Quang Asif Alam Observer Monash Greg Corboy Evaluator Monash Vivien Vasic Observer Monash Kumar Amit Observer Peter Mac Jayamala Pamar Evaluator RMH JP Plazzer Evaluator RMH Manny Sigalas Evaluator RMH Miriam Fanjul Evaluator VCGS Fernandez Sebastian Lunke Evaluator VCGS Dean Phelan Evaluator VCGS Hazel Phillimore Observer VCGS 13
Summary of variant curation tool pilot 28 scenarios Evaluated quantitatively for experience and requirements Qualitative information (comments) If scenario couldn’t be completed How the tool could be improved Other comments Melbourne Genomics Health Alliance | Document Name Here 14
Scenarios Curation Pilot Survey Content This is a set of scenarios that the Alliance may be using to assess the curation tool in line with the requirements. This can be used to help guide the planning of the training that will be delivered to the assessors. Singleton Filtering Basic • A single sample is imported with easy to find pathogenic variants. Pre-configured filtering is applied and the relevant Leveraging Alliance requirements variants are marked for curation. 1. Results are imported into the curation tool and are ready for filtering. • 2. The user finds the relevant sample to work on. Ensures coverage & consistency 3. The regions of interest and gene panels are assigned to the sample. 4. QC data is assessed. 5. GAP data is processed. • Real world processes 6. The sample is approved for the variant filtering to proceed. 7. The user reviews the default filtering and is presented with enough information to understand how it works. 8. The default filtering is applied and the variants of interest are identified. 9. Any variants that are not defined correctly are manually corrected (HGVS). • Scenarios cover 10. The variants are marked as requiring curation. 11. Some variants are marked as not for curation with justification. 12. A manager checks these variants to curate and amends them if required. • System Configuration 13. A final approval is given for the variants of interest and they can now be curated. Singleton Curation Basic A single sample with variants that have easily available evidence to support a diagnosis. • Quality 1. A sample is ready to be curated with previously approved variants for curation. 2. The user finds this sample and picks the first variant to work on. 3. The user undertakes the curation process where the annotations provided by the curation tool are reviewed. • Assay Setup 4. The annotations are weighted and classified into the relevant categories of the curation process (ACMG guidelines or custom weighting matrix) until there is sufficient evidence for a diagnosis. 5. The documentation for classifying variants is reviewed. 6. Variant specific comments are added and along with reportable comment. • Variant Filtering 7. The variant is given a proposed classification. 8. A text summarizing all the evidence used for the classification of the variant is added to the variant. 9. The remaining variants are curated until no more are remaining. • 10. The sample is marked for a multi-disciplinary team meeting (MDT) to discuss further. Variant Curation 11. After MDT a confirmed classification is added to the variants. 12. These variants are sent to the lab to be confirmed by additional sequencing eg Sanger sequencing if required. 13. The results of the confirmation is recorded if applicable. • 14. A summary text considering all the variants for the case is added to the report. Communication 15. The sample is approved for reporting by a manager. Singleton Filtering Complex A single sample with difficult to identify pathogenic variants that required manual filtering steps to be undertaken. The target region is expanded. The use of multiple annotations is required to identify variants of interest, eg Clinvar. This is the same process as the basic filtering except for the following: 1. The user adds additional gene panels to the sample to expand the target region. 2. The user adds individual genes to the sample to expand the target region. 3. The user modifies the filtering process to use additional annotations. 15
Additional Functionality • Pilot made clear that software required additional functionality • Worked with evaluation team to articulate and prioritise extra features • Critical item were incorporated into a statement of work for the vendor to deliver • Other features incorporated in vendor roadmap 16
Benefits Data & Technology
Benefits Management Information Management Support improvement in patient outcomes and disease prevention for Victorians through secure and ethical use and sharing of reliable genomic information Benefit 3: Accelerated Benefit 1: Minimise the cost Benefit 2: Improved patient research and translation and waste in administering and family outcomes health care into patient care Increase in the appropriate use of Increased curation speed Availability of genomic data genomics Reduction in number of systems Reduction in the number of Increase in detection rates required to consent for research manual processes and clinical care Reduction in the duplication of Reduction in unnecessary clinical Increased availability of genomic patient data (double handling) management for patients information for future research Increase the ease of access to Reduction in the ordering of information for clinicians & patients Increased adoption of research unnecessary and/or duplicate on genomics testing & results back into clinical practice tests interpretation Increase in the number and /or Reduction in time and effort value of grants using genomics associated with finding results data from Alliance research 18
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