Technology to Enable the Clinical Genomics Revolution

Technology to Enable the Clinical Genomics Revolution Session 100, February 13, 2019 Kate Birch, Data & Technology Program Manager, Melbourne Genomics Health Alliance and CSIRO 1 Conflict of Interest

Kate Birch, BSc(Hons) MIS CHIA, has no real or apparent conflicts of interest to report.

2 Agenda • From clinical genetics to clinical genomics • Melbourne Genomics Health Alliance • In clinical practice, is genomics better than standard care? • Technology to enable genomics • Patients views on data sharing

3 Learning Objectives • Recognize the need for whole-of-system change in the implementation of clinical genomics • Demonstrate evidence for the utility and economics of genomics as a front line test • Distinguish the different requirements for the implementation of technology in emerging versus established areas of clinical practice • Contrast the differences in data sharing preferences and concerns between patient populations and well populations

4 From genetics to genomics

• Genetics scrutinizes the functioning and composition of the single gene where as • Genomics addresses all genes and their inter relationships in order to identify their combined influence on the growth and development of the organism World Health Organisation

5 Cost of sequencing a human genome

6 Phimister et al., NEJM 366: 757-9, 2012 From genetics to genomics

Integration with microbiome, proteomics, metaboloimics... Whole genome

Whole exome

Large panels Small panels Single gene

7 From genetics to genomics

Integration with microbiome, proteomics, metaboloimics... Whole genome

Whole exome

Large panels Small panels Single gene

8 An analogy…..

Shred them. Read each piece and reconstruct the story. Find the typos.

1000 copies of War and Peace = a single genome Do they change the meaning of the sentence?

9 Research Clinical care

10 10 We know what we are doing… it will just happen

But it typically takes 17 years!!

Half of Evidence Based Practices ever reach widespread clinical use Morris et al 2011

11 Slide by Dr Stephanie Best 12

Only 2% of US genomic data is used for clinical care Erik Jylling - Executive Vice President Health Politics at Danish Regions

12 Challenges to Overcome

• Lack of evidence of effectiveness • Lack of funding for clinical testing • Unprepared workforce • Concerns about ethical and legal issues • Inadequate infrastructure • Fragmentation and silos • Lack of agreement about investment and priorities

Manolio et al, 2015

13 14

Challenge: Create whole of system change

14 The Australian Health Care System Complex and fragmented

Health service funding and responsibilities Australia’s Health 2014, AIHW

15 Slide by Australian Genomics 16

Melbourne Genomics Health Alliance

16 17

The Melbourne Genomic Health Alliance set out to make Victoria a world leader in the translation and use of clinical genomics in healthcare

17 Genomic medicine in healthcare

The benefits for patients and the community

Faster diagnosis Targeted therapy Better manage Improved prognosis “Precision Medicine” disease risk and preventative care

18 Approach

19 Head-to-head comparison in the ‘real world’

First line test Right patient, right test, right time

A test of last resort

X 20 21

In clinical practice, is genomics better than usual care?

Yes, often.

21 Flagships: evidence to guide the use of genomics

2014-2015 2016-2018 2017-2019 • AML • Complex care • Controlling superbugs • Childhood syndromes • Congenital deafness • Bone marrow failure • Focal epilepsy • Dilated cardiomyopathy • Complex neurological and • Hereditary colorectal • Immunology neurodegenerative diseases cancer • Advanced solid cancers • Genetic kidney disease • Hereditary neuropathy • Advanced lymphoma (non- Hodgkin) • Perinatal autopsy

Right way Acceptable Equitable Right patient Right test Right Effective time

22 Evaluation questions Data collection

Impact of test on: • Clinical & cost data • Diagnostic yield & clinical management • CRF and chart review • Health outcomes (health system perspective) • Hospital costings • Family outcomes • Medicare & Pharmaceutical Benefit Scheme • Policy and process • Participant measures • Reanalysis of data • Surveys at baseline (pre-result) and post • Data sharing for research result • Additional (secondary) findings • Interviews and focus groups • Singletons vs Trios • Health professionals • Pre-test counselling • Participants • Adoption • Other • How can appropriate clinician decision- • Recorded consultations making be supported • Genetic counsellor notes 23 More diagnoses than usual

Childhood Focal Hereditary Syndromes Epilepsy Colorectal Ca. n=80 n=40 n=35 Diagnostic Rate Singleton 58% 13% 14% WES Usual care 14% 0% 14%

Stark et al. Perucca et al. 2016 2017

24 Melbourne Genomics study: an Internationally-Recognised Real-World Case-Study “It is a game changer, both in terms of patient outcomes and economic sustainability.”

Backgroun • Childhood syndromes patients (101 Take- When Exome Seq was used: d children). Home • Five times more patients were • Royal Children’s Hospital Melbourne. Messages diagnosed. • Patients received both: • The cost per patient was reduced by A. Traditional diagnostic tests. 75%. B. Exome Test. • Four times more patients had improved care Five times the diagnosis at oneNB. No patients quarter required novel expensive treatments. the cost Implication Exomes as a diagnostic test: NumbersExperimental finding Traditional Exome s • Provides spectacular diagnostic Diagnostics power. • Significantly reduces average patient Rate of diagnosis 11% 55% costs. • Improves critical management care. Average cost per $27,040 $6,003 patient Patients with improved 4% 16% 25 care outcomes Most cost effective early in patient care

26 Reproductive outcomes

Recurrence risk 50% 25% 25% 25% <1% <1% <1% <1% <1%

Diagnosis group N=48 Reproductive PGD PND PND PND PND - - - - intervention

Recurrence risk ~10% ~10% No diagnosis group N=32 Reproductive TOP intervention 27 28 Technology to enable clinical genomic

29 Access to Genomic Information

Develop and implement a single set of standards, policies and procedures to support a common infrastructure for the management and use of genomic data by stakeholders in Victoria.

30 Ideal end state in an unconstrained environment

Policy & Process People Technology

7. Identity & Access Management 1. Standardised policy and processes for data 8. Clinical Tools 9. Diagnostic Tools 10. Patient Tools 5. Staff to management & access Electronic manage the Clinician (data governance) Orders and Analysis Consent data Knowledge Results (Pipeline) Tools Results Clinical Decision Support Curation Tools Tools Education 2. Standardised policy & processes for patient consent 6. Staff to 11. Data Access Tools manage the technology 12. Master 13. Genomic Data Repository 3. Standardised policy and Patient Index processes for test ordering & reporting 14. Data Integration

LIMS 4. Change control process EMR Public variant (genomic (clinical data) curation data sequencing data) 31 Traditional Software Selection

Configuration Requirements Software Selection andIt should definitely be black. Post- and Analysis Evaluation Purchase Purchase It should definitelyCustomisation be green. Colour is unimportant.

Business User System ? Requirements Requirements Requirements

Commercial and Organisational Last week it needed toView be to future Contractual Requirements black, but now it absolutelyRequirements Requirements must be green.

32 33 Diagnostic Tools Approach

LOVD EOI

Cpipe Prototype Future Workshop learnings needs s SeqLine Pilot r

Prototype Define Requirements Procure • New software • What we’ve learnt we • Rigorous • Existing software need? • In depth • Open source tool • What we can see we’ll • Hands on • Supported the first need soon? Alliance funded • What we predict we’ll tests need in the future? 34 35 GenoVic is unique, but not new

GenoVic

36 A clinical system for genomics Providing end-to-end modular cloud services for multiple laboratories

entity & Access Management

9. Diagnostic Tools 10. Patient Tools

Analysis Consent (Pipeline) Tools Results

Curation Tools Education

11. Data Access Tools

13. Genomic Data Repository

14. Data Integration Investigation

LIMS Public variant (genomic curation data 37 sequencing data) Patient’s views on data sharing

38 39

39 40

40 Melbourne41 Genomics Health Alliance | Document Name Here

41 Research by… Principal funder Executive Director Alliance members A/Prof Clara Gaff Penny Gleason Dr Christine Walker Evaluation Team Dr Melissa Martyn Dr Emily Forbes Anaita Kanga- Pariaba Nessie Mupfeki

Clinical team Elly Lynch Genetic Counsellors Sophie Beck

42 GenoVic team Clinical consent for data sharing

• No choice: ‘Anonymised’ data is shared Those who did not agree were significantly more likely to be parents • Opt in: to share re-identifiable dataconsenting for children p=0.001 98% agree

43 Survey respondents – Administered after genetic counselling, before results received • 87% response rate • 31 days median time from testing consent to survey return – Characteristics • No significant differences to larger cohort

44 Recall is high

• Vast majority of patients accurately recall their data sharing decision

• Vast majority of patients understand anonymised data may be shared

45 Information about data sharing was satisfactory

• Majority received enough information

• Most had no remaining concerns about data sharing

46 Genomics Privacy

How difficult do you think it would be for Ease of someone to be identified from their identification stored genome sequence? & Level of concern if How concerned would you be if identified someone identified you from your stored data?

47 Genomics Privacy

Ease of Patients with suspected Easy Difficult Difficult Easy identification hereditary conditions significantly more likely to I am I am I’m not I’m not Level of concern if concerned concerned worried worried be concerned about being identified identified

Trend towards patients having panel testing to be less concerned

48 How broadly should data be shared?

Patient trust in sharing data High trust Alliance Members Over half said that the country Australian not-for- would influence their decision profit Overseas not-for-profit

I don't care about the Pharmaceutical country as long as it was being used in an ethical Government way and for research that would be beneficial ie not to discriminate against Other Industry certain groups and not for Low trust eugenics etc

49 No clear preference for one model of consent No permission

Opt in each time Opt out each time

Control Ongoing use unless opt out

Permanent reuse Permissiveness 50 Australian Genomics Dynamic Consent

51 Overall most are informed, accepting and permissive BUT

No concern with..medical professionals. Greatly concerned if shared more widely .e,g insurers, employers Cancer, agreed to share

I strongly believe it is I only want to help an invasion of my cancer research. I privacy and sensitive don’t want to …be information shared for any other Hereditary, agreed to purposes Cancer, agreed to share share 52 Melbourne Genomics – 2013-2015

CEOs/Leadership Paul Ekert Zornitza Stark Simon Sadedin Genetic Counsellors Gareth Goodier (RMH) Monique Ryan Tiong Tan John-Paul Plazzer Gemma Brett Christine Kilpatrick (RCH) Charlotte Slade Paul Ekert Charlotte Anderson Emma Creed Stephen Smith (University of Melbourne) Alison Trainer Christiane Theda Anthony Marty Ella Wilkins Doug Hilton (WEHI) Genomics & Bioinformatics Advisory David Amor Peter Georgeson Health Economics Kathryn North (MCRI) Graham Taylor / Alicia Oshlack (Chair) Maie Walsh Denis Bauer Khurshid Alam Lynne Cobiac (CSIRO) Melanie Bahlo Patrick Yap Harriet Dashnow Deborah Schofield Sue Forrest (AGRF) Denis Bauer Epilepsy Guido Grazioli Rupendra Shrestha Paul James Patrick Kwan Richard Sinnott Steering Group Andrew Lonie Terry O’Brien Glenn Tesla James Angus (Chair) Simon Sadedin Ingrid Scheffer Clare Sloggett Julian Clark Kirby Siemering Piero Perucca Clinical Systems - MCRI & REDCAP Sue Forrest Paul James Jane Halliday Clara Gaff (Exec Director) Data Access Advisory Susan Donath Trevor Lockett / David Hansen Yousef Kowsar Laboratories Leanne Mills Andrew Sinclair Kurt Lackovic CTP Ross Dunn Mike South Steven Manos Paul Waring Luke Stephens Paul Waring / Jon Emery Candice McGregor Graham Taylor BIOGRID Ingrid Winship Owen O’Neill Tiffany Cowie Maureen Turner Gayle Philip Sebastian Lunke Leon Heffer Advisory Groups Bernie Pope Renata Marquis-Nicholson Alice Johnstone Information Management Advisory Melissa Southey Greg Corboy David Hansen (Chair) Advanced Users Group Michael Christie Working Groups Terry Brennan Arthur Hsu Patient-entered data tool Ken Doig Flagships VCGS Patient survey Rowan Gronlund Research access AML Graham Taylor Andrew Lonie Damien Bruno Education symposium Fernando Martin-Sanchez Andrew Roberts Evaluation Ian Majewski Steven Nasioulas Wayne Mather Belinda Chong Information requirements Emeline Ramos Seong Lin Khaw Reporting Francoise Merchinaud Shannon Cowie Brenda White Melanie Smith Database users Edward Chew Pipeline platform CMT Clare Love Community Advisory Monique Ryan Chris Guest Ingrid Winship (Chair) Paul James AGRF Louisa Di Pietro Sue Forrest Project Team Tim Day Clara Gaff (Exec Director) Heather Renton Lynette Kiers Kirby Siemering Margaret Sahhar Melanie O’Keefe Tim Bakker (Info Mgmt) Adrienne Sexton Michele Cook (Admin) Janney Wale CRC Matthew Tinning Christine Walker Lavinia Gordon Ivan Macciocca (Clinical) Alex Boussioutas Karen Meehan (Comms) Liat Watson Finlay Macrae Rust Turakulov Stephen Wilcox Natalie Thorne (Bioinf) Alison Trainer Evaluation Team Clinical Interpretation Ingrid Winship Information Systems Emily Forbes & Reporting Advisory Michael Bogwitz Melissa Martyn Paul James (Chair) CS CPIPE / MG LOVD VLSCI Nessie Mupfeki Damien Bruno Sue White Andrew Lonie Bill Wilson

53 Melbourne Genomics – 2016-2019 Alliance Board Tony Papenfuss Seth Masters Zornitza Stark Gayle Philips Catherine Walter (Chair) Simon Sadedin Mimi Tang Ella Wilkins Denis Bauer Christine Kilpatrick (RMH) Paul James Ingrid Winship Mathew Wallis Harriet Dashnow Andrew Stripp (Monash Health) Zornitza Stark David Power Guido Grazioli Dale Fisher (PeterMac) Information Management Advisory/GenoVic Kathy Nicholls Richard Sinnott Christine Kilpatrick (RCH) Project Control Group Lymphoma Peter Kerr Glenn Tesla Shitij Kapur (UoM) David Hansen (Chair) Stephen Opat Clare Sloggett Doug Hilton (WEHI) Wayne Mather Miles Prince Perinatal autopsy Clinical Systems - MCRI & REDCAP Kathryn North (MCRI) Rowan Gronlund Gareth Gregory George McGillivray Jane Halliday Rob Grenfell (CSIRO) Kevin Ericksen Michael Dickinson Jacqueline Collett Susan Donath Irene Kourtis (AGRF) Tony Papenfuss Eliza Hawkes Ian Simpson Leanne Mills Sue Shilbury (Austin Health) Michael Carolan Piers Blombery Trishe Leong Ross Dunn Anna Burgess (DHHS observer) Erminia Schiavone Jan Pyman Luke Stephens Kris Jenkins Solid Cancers Alison Yeung BIOGRID Executive Management Committee Mike South Jayesh Desai Natasha Brown Maureen Turner Clara Gaff (Chair) Angela Watt Kortnye Smith Sue White Leon Heffer David Hansen Andrew Lonie Sophie Beck Sue Walker Alice Johnstone Andrew Sinclair Clara Gaff Dong Anh Khuong Quong Richard King Malcolm Smart Hui Gan Laboratories Julian Clark Paul Eckert CTP Working Groups Felicity Topp Flagships 2016-2018 Ben Solomon Paul Waring Patient-entered data tool Fergus Kerr Congenital Deafness Ben Markman Graham Taylor Patient survey Peter McDougall David Amor Tiffany Cowie Research access Ingrid Winship Lilian Downie Sebastian Lunke Education symposium Sean Grimmond Valerie Sung Flagships 2017-2019 Renata Marquis-Nicholson Evaluation Kirby Siemering Libby Smith Bone marrow failure Greg Corboy Information requirements Paul Fennessy (DHHS observer) Bibi Gerner Piers Blombery Michael Christie Reporting Matthew Hunter David Ritchie Arthur Hsu Database users Advisory Groups Kerryn Saunders Francoise Mechinaud VCGS Pipeline platform Clinical Adoption Advisory Natasha Brown Anthea Greeway Graham Taylor Curation tool pilot evaluators Fergus Kerr (Chair) Melissa Wake Andrew Grigg Damien Bruno Curation tool RFQ evaluators Cate Kelly Rachel Burt Erica Wood Steven Nasioulas Analysis tool user group Sylvia Metcalfe Jane Halliday Paddy Barbaro Belinda Chong Curation tool user group Don Campbell Zeffie Poulakis Controlling Superbugs Shannon Cowie Information architecture reference group Lindsay Grayson Elizabeth Rose Lindsay Grayson Melanie Smith Margaret Kelaher Ben Howden Clare Love Genetic Counsellors Noel Cranswick Complex Care in Children Norelle Sherry Chris Guest Gemma Brett Jayesh Desai Sue White Jason Kwong AGRF Emma Creed Zornitza Stark Tony Korman Sue Forrest Anna Jarmolowicz Community Advisory Tiong Tan Caroline Marshall Kirby Siemering Ivan Macciocca Jane Bell (Chair) Alison Yeung Mark Chan Melanie O’Keefe Ellie Prawer Louisa Di Pietro Matthew Hunter Monica Slavin Matthew Tinning Giulia Valente Heather Renton Katrina Harris Marcel Leroi Lavinia Gordon Kirsty West Margaret Sahhar Rust Turakulov Health Economics Janney Wale Dilated Cardiomyopathy Complex neurological Stephen Wilcox Khurshid Alam Christine Walker Paul James Patrick Kwan Deborah Schofield Liat Watson Jay Ramchand Sam Berkovic Information Systems Rupendra Shrestha Matthew Wallis Martin Delatycki CPIPE / MG LOVD VLSCI Melbourne Genomics Health Alliance Program Diagnostic Advisory David Hare Dennis Velakoulis Team Richard King (Chair) Omar Farouque Michael Fahey Andrew Lonie Kirby Siemering Melanie Bahlo Simon Sadedin Sebastian Lunke Immunology Rick Leventer John-Paul Plazzer Melanie O’Keefe Jo Douglass Amy Schneider Charlotte Anderson 54 Vivien Vasic Charlotte Slade Anthony Marty Michael Christie Vanessa Bryant Genetic kidney disease Peter Georgeson Andrew Fellowes Jo Smart Catherine Quinlan Michael Milton Suzanne Svobodova Sara Barnes Sue White Juny Kesumadewi Please use this blank slide if more space is required for charts, graphs, etc.

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