Towards a processual perspective on architecture Building an Information Infrastructure for Personalized Medicine (Paper presented at NOKOBIT 2014) Margunn Aanestad1, Johan Sæbø1, Thomas B. Grünfeld2 1) Institutt for Informatikk, UiO 2) Oslo Universitetssykehus

• «National DNA sequencing data platform for healthcare»

• Cross-disciplinary research project supported by VERDIKT in the Norw. Research Council

• Collaboration between OUS and UiO – OUS: Dept. of Medical Genetics, Stab IKT – UiO: Norwegian Sequencing Center, IFI, USIT,

Faculty of Law

genAP

• Project title: National DNA sequencing data platform for healthcare

• High Throughput Sequencing (HTS) – (or Whole Genome Sequencing or Next Generation

Sequencing) – Replaces older sequencing technologies that give a partial

view (e.g. targetted to one or more genes) – Expectations/incentives:

• Store a person’s sequence and make it available for later query

• Share competency and infrastructure nationally • Increased clinical usage (Personalized medicine)

Rapid evolution of sequencing technologies The Human Genome Project: - Full sequencing of one human genome - Sanger sequencing - 13 years, $3 billion

HTS: - A few days - Jan 2014: $1000

Research

Patient-oriented

Germline mutations

Somatic mutations

New mutations Cancer research

Known mutations

Cancer therapy (targetted)

DNA-sekvens

Varianter

Funksjonelle varianter

Kliniske relevante varianter

Pilot case #1

Pilot case #2

Pilot case #3

Deployment of NGS in HC

”Rare diseases” Diagnostics

Pharmacogenetics / treatment guidance

Cancer (Diagnostics and treatment

guidance)

Microbiology

Predictive/ risk assessment

•Improved / more cost effective diagnostics •Post natal screening? •Sub-grouping assessing genetic factors

•Mapping of oligo/ polygenic conditions/ risks (”Common disorders( •Improved prognostics/ preventative care

•Specific viral and bacterial diagnostics •Possibly later microbiome mapping?

•Sub- grouping / ”improved histology” •CUP’s •Identify optimal drugs (Or excluding non-effective)

•Pharmacokinetics and pharmacodynamics •Pre-surgery: connective tissue disorders and coagulopathies

•Limited experience with normal variation, variable populations •Variable quality of phenotype- genotype relation •Variable expressivity/ penetrance

•Very complex relations, long way to go before we ”beat traditional methods” •Unknown value/ trade off of interventions

•Still expensive compared to current technologies •Microbiomology still ”unknown territories”

•Tumor cell line is unstable: What are we looking at? •Very complex molecular biology

•Current NGS tech. not optimal for CYP typing •Limited experience with multifactorial pharmacokinetics / dymanics •For CT/Coag. disorders see ”rare diseaes”

Examples Challenges

WGS integrated part of EPR

Deployment in screening

(Eg. newborns)

Easier to analyze all,

than 3-5 genes

Offer for those who ”really

need it”

Possible development of full ”whole genome sequencing”

”Sport” for ”the rich and famous”

Fra Henry T. Greely, director Centre for Law and Biosciences, Stanford University

•The first scientists etc. •Mini-solution ”23andme”

•Patients with challenging diagnostics •New causative genes

•Allows for re-use of sequencing (DNA static over life) •Later in-silico analysis

•Simplifies existing methods •Allows for re-use

•”Everybody” routinely analyzed •Integrated expert systems in EPR

Vision for «automated system»:

Genom-data

Hva er CYP3A5, CYP3A4 og POR?

CYP3A5 *1/*3 CYP3A4 *18/*1b POR *28/*28

Genetiker eller legespesialist kan finne ethvert gen bare ved å slå opp i en database

Help to design treatment

Genom-data

Hvordan doserer jeg Marevan for akkurat denne

pasienten?

Et øyeblikk Bzzbzz.. CYP2C9..bzzbzz..

VCORKC1

Bzzbzz.. CYP2C9*1..bzzbz

z..VCORKC1*3

A simple example

Almenpraktiker

Assisted diagnostics

Genom-data

Er dette den arvelige formen

for kardio-myopati?

Et øyeblikk Bzzbzz.. MYH7..bzzbzz… TNNT2..TPM1…

Bzzbzz.. MYH7..bzzbzz… TNNT2..TPM1…

Hei! Den varianten har jeg aldri sett før!

Hjelp meg, Kjære genetiker!

Hm… stoppkodon midt i myomet, det kan umulig gå bra

Ok.

A more complicated example

Almenpraktiker

Genetiker

Status for genAP

• Secure High-Performace Computing infrastructure at USIT (TSD) – Secure computational storage

USIT (UiO) Tungregne-gruppa TSD2: Tjeneste Sensitive Data Forsknings- infrastruktur for prosjekter underlagt: Helseforsknings-, Bioteknologi-, Helseregister- eller Person- opplysningsloven

Status for genAP

• Secure High-Performace Computing infrastructure at USIT – TSD - Secure computational storage

• Presentation of genetic information to clinicians: – Prototype evaluated (Lærum m.fl., JAMIA 2014),

(domain: farmacogenetics)

• Improve the interpretation capacity in the lab – Partial automatisation/better IT support in hte

interpretation process

SeqScape

MS Access

Worksheet (print + manual write)

Mutation tableAlamut

Alamut/browser

Alamut/browser

Browser

AlamutBrowser

Answer/addas class 1

NO

Mutation table(now: print - soon: text

àExcel)

Resequence

Evaluate Sanger

Bad amplicons Common variants(het/hom)

New variants(het/hom) Preclassified

<1 year ago?

YES

On shortlist:common? NO

YES

Lookup inAccess DB

Sanger Sequences Answer withsame classification

Specific to Sanger

Variant DB:classification

+ ref

Artefacts:QV<30 and/or

electropherogram

Project: 4samples

Template: 30bp intron

Paper archive

Technical

Nomen-claturecheck

Report

Evaluatefrequency:

>~10%(lower for genot)

Common?

YES

Answer/addas class 1

Inheritance mode?

Homozygous?(hemizygous?)

Heterozygous?

Add note(+class 1)

YES/NO

Dominant

Recessive

YES/NO

Evaluatefrequency:

>1%(lower for genot)

dbSNP

YES

YES

Add note(+class 2)

Possible carrier/comp heteroz

NO

Report

LOVDGoogleOther

BIC

Reported? YES

Evaluate trustedmutation DB Classified?

Evaluate non-trustedmutation DB/search

VUS/NO

Find references

PubMed

BRCA1/BRCA2?

YES

NO

Answer/addas class 1

Answer/addas class 5

Neutral

Pathogenic

NO

Report

Segregation

Evidence fromreference

Sequencing >90% of genesequenced?

Consistent w/conclusion?

Abnormal proteinfunction?

Abnormal splicing/expression?

Protein

RNA

+5

Reference<10 years?

-5

+2

-1

+2

-1

0

-1

0

-1

Ref age

SUM >0(good reference)?

Add note(+ class 3)

YES Add note(+ class 4)

Add note(+ class 2)

Classification?

>1 independentgood refs?

Classification?YES

Answer/addas class 5

NO

NO

VUS

Neutral

Pathogenic

Report

Neutral

Pathogenic

VUS/conflicting

YES

NO

YES

YES

YES

YES

NO

NO

NO

NO

Report

PolyPhen-2SIFT

SSFLMaxEntScanNNSPLICE

HSF

Mutation type?

Last exonimportant?

+/- 2 bp from exon?

Frameshift

Missense

Any(splice site)

Nonsense>50 bp 5' of

intron?

Answer/addas class 4

Check splice predictionNO

YES

3/4 predict change? Add note(+class 2)NO

Check pathogenicityprediction

YES

SNPs3D

YES

Same for all prog?

Predictedpathogenic?

NOYES

Add note(+class 3)

YES

NO

NO

NO

In last protein-encoding exon?

YES

NO

Note: + class 21 good reference

Note: + class 41 good reference

Pat DBExtract var Pat predFreqinher

Answer withsame classification

Answer: class 1common

Answer: class 1documented

Answer: class 4crucial site

Note: Possible carrier

Note: + class 3bad reference

Answer: class 5documented

Note: + class 3non-conclusive

reference(s)

Note: + class 3predicted splice site

change

Note: + class 2no predicted splice site

change

Note: + class 2missense predicted non-

pathogenicby all

Note: + class 3missense predicted

pathogenic atleast onceOther class 4/5

found?

Note: + class 33'-end nonsense/

frameshift

Note: +class 2recessive +

heterozygous

Note: +class 1dominant + homozygous

Evaluate other sequencevariants same gene

Note: Possiblecomp heterozYES

Class 3/4/5?

YES

Evaluate downstreamanalyses

NO

Answer: class 2

Eval ref

Answer: class 1documented

Answer: class 5documented

Note: problem areas oftenvisible as present in all 4

samples, but notregistered

With sufficientpopulation size; not a

patient pop

Latest dbSNP build notin Alamut, checks web if

variant not found

With sufficientpopulation size; not a

patient pop

Always check BIC

Note: in addition toinheritance, frequency cut-off

should be based onprevalence data and/or

frequency of knownpathogenic variants (adjusted

for each gene/diagnosis)

Note: X-linkedinheritance is a thirdpossibility for other

cases (esp. forgeneral genetics)

Also possible:HGMD Pro,IARC, other

LSDBs

Note: choice ofprograms subject to

discussion

BRCA2...

NMD. Maquat 2004,PMID 15040442

Sample loading and QC

Frequency and inheritance External databases

References

Pathogenicity prediction

Final evaluation and report

Matching against in-house DB

Mapping of the interpretation prosess:

Redesign of IT systems in use

Gene Variant (HGVS) Source Reference(s) Previous evaluations? High quality evidence?

Hide completed

BRCA1 c.38T>C HGMD Pro, LOVD

Van Hausen et al 2012 PMID: 23709336

-

BRCA1 c.38T>C HGMD Pro Elsing et al 2011 PMID: 22904364

-

BRCA1 c.376A>G HGMD Pro Vindaloo et al 2013 PMID:23934762

For BRCA1 c.1275C>T: mceike, 12.08.2013. View

BRCA1 c.483T>G

Manual: mceike

Mansanaar et al 2011 PMID:22334712

-

BRCA1 c.1435C>G HGMD Pro Vindaloo et al 2013 PMID:23934762

mceike, 12.08.2013. Yes, pathogenic

Evaluate

Evaluate

Evaluate

Evaluate

Edit

Perform additional query

Add reference

PMID First author OR

Year

Title

Add

Journal

Choose gene…

Choose variant…

References

References - evaluate

Category YES NO Score

Reference evaluation

Evaluation

Variants with reference hits

External DB Frequency VarDB Prediction

Relevance Is reference relevant?

Selected reference: Van Hausen et al 2012 (PMID:23709336)

Variant: BRCA1 c.38T>C

+5

+5

…

…

0

0

Protein

RNA

Gene coverage

Age of evidence (auto)

Segregation Consistent with conclusion?

Abnormal protein function?

Abnormal splicing/ protein expression?

>90% of gene sequenced?

Reference <10 years?

Variant BRCA1 c.38T>C High quality evidence count

SUM

Conclusion: High quality evidence?

YES NO

0

SUGGESTED

Additional comments

IRRELEV/VUS

Finish

Conclusion Does reference sup- port pathogenicity?

0

PATHOGENIC

NEUTRAL

More complex topics get pop-up help with link to full documentation

Choose gene… Scholar

Choose variant…

PubMed (opens in browser)

When unchecked: evaluation options dimmed

If selecting other than suggested - prompt for confirmation and to fill in comment

Automatically fetched from reference details

If NO/VUS: all remaining evaluation points greyed out, no score given. Suggest “IRRELEVANT”

Sample 000001A loaded | Gene panel: Breast and ovarial cancer v1.0 | Test: Full

Sample

Pop-up instead of right pane

VUS

Gene Variant (HGVS) Norvariome ESP6500 1000G Contradictory information Filter out : Select all

BRCA1 c.434A>C 0.0234 - - -

BRCA1 c.2311T>C - 0.0446 - -

Gene Variant (HGVS) Norvariome ESP6500 1000G Contradictory information Filter out : Select all

BRCA1 c.873T>C - 0.0079 - -

BRCA1 c.1067A>G - 0.0053 - Warning: entry found in HGMD Pro

Details for variant BRCA1 c.1067A>G

HGVS cDNA c.1067A>G Observed genotype CA HGMD Pro Disease-associated

polymorphism Effect Missense SIFT TOLERATED MutationTaster Polymorphism

View raw

View all

View external record

genAP analysis workbench

VarDB Sample Options | Sign out | Help External DB Prediction References Report

Next Previous

Frequency

Neutral variants (>0.008)

Sample 000001A loaded | Gene panel: Breast and ovarial cancer v1.0

Probably neutral variants (0.001-0.008)

Only variants with frequency >0.008 are shown.

Filter

Mockup v0.1

Removes checked variants from further analysis, adds to report.

Pathogenicity prediction tools

Extracting, adding and scoring of references

Report with all details, suggested classification and export tools

External databases

In-house database Sample loading

BIC ClinVar dbSNP HGMD Pro

SeqScape

Analysis workbench

Details for selected variant.

NOKOBIT paper theme

• The project: a case of «emerging architecture» • Processual perspective on architectural

development – Process shapes the architecture – Time perspective (short/long horizon) – Implications for organizing

Scaling down of ambitions • From an exclusive focus on HTS

– To building solutions for «old» sequencing technologies

• From a national scope – to a regional scope – to a hospital scope – to a departmental scope

• From generic exspert system – To a system for spesific ‘gene panels’ (for simple and well

mapped areas, i.e. monogenic & dominant)

• From a ‘common infrastructure’ (or platform) – To a support system for interpretation (improved

production rate and quality)

«Architecting»

• Architecture as structure -> the process of defining and realising the architecture

• Two aspects: – Balancing immediate needs with long-term wishes – Architecture and learning -> the drawbacks of

«premature» architecture • “Architecture is a hypothesis about the future” (Foote and

Yoder 2000)

Method

• Participant observation (working meetings, clinical interpretation work), interviews, document analysis…

• Architecture sketches throughout the project – Represents an evolving understanding of

challenges, components, scope and scale – «Scaling off» (deferring some parts) – «Deepening» (concretization, realization)

”Strawman” arkitektur (Sept 2011)

EXOM base med varians

filer

EXOM base funksjonell annotering

Klinisk algoritme/

Ekspert system

Gradert tilgang avhengig av klinisk spørsmål/ bruk og tillatelser

Brukere PASIENTER

Pleietjeneste?

Allmennlege

Spesialister

•Pediater

•Nevrolog

•Etc

Spesial IT systemer

Ekspert/ Med. genetiker

Tillatelse til bruk fra pasient

LOGG for queries, bruker og tillatelser

SAMTYKKE

LOGG

Imagined system

Kuraterte databaser:

klinisk relevans

OPPDATERING

Offentlige genomdata

ANNOTERING

GENOMDATA PASIENTER

Funksjonell relevans Rådata

PASIENT

Genetisk veiledning

Tilpasset medisinering/

behandling

Diagnostisk støtte

...

Diagnose: • ukjent • usikker Medisinering:

• effekt • bivirkninger Risiko:

• familiær • relatert ...

Komplisert/ sensitivt

IKKE-GENETIKERE

Pleietjeneste

Almenlege

Spesialist

...

EKSPERT

Medisinsk genetiker

LOGG

Diagnostikk

Farmako-genetikk

Prognostikk

EKSPERT-SYSTEM

Fleksibelt

ANALYSE-SYSTEM

GR

AD

ERT TILG

AN

G

Architecture for platform

Updated overview of system (from Feb 2014)

The emerging architecture: • Bottom-up (from the concrete setting) and

shaped by what is possible to do: – Who (clinicians) are interested to join? – In what clinical domains are there low-hanging

fruits, with low risk and high gain? • The HTS performance for that domain • The knowledge about gene-disease relations • The volume and ‘status’ of patients affected

– What do others (externals) do? And not do? – What do project members want to do…etc.

Architecture workshop 28.3.2014

Examples in paper:

• Curated database of variants – From a patient-centered to a variant-centered design

• Choice of implementation domains – Pharmacogenetics -> other domains

• «External» dependencies: – Development of HTS – Change of clinical systems at OUS

• From specific to generic – From code t config-files – Pilot -> routine (NHN/USIT?)

Emerging architecture

Backward compatibility (installed base)

Future compatibility (strategic vision)

Context compatibility (opportunistic actions)

Shearing Layers (diff. rate of change)

• Stewart Brand (1994): «How Buildings Learn» – Site (the geographical location) – Structure (the load bearing elements) – Skin (the exterior surface) – Services (the circulatory and nervous systems of a

building, such as its heating plant, wiring, and plumbing) – Space Plan (walls, flooring, and ceilings) – Stuff (includes lamps, chairs, appliances, and paintings).

Motivation • The reason for our interest in these

processes is that we believe there will be implications for scalability when design is driven by local and immediate concerns, as well as implications for generalisability when design is driven by particularity of (local) needs. We think it is significant to examine whether (and how) choices of diversifying and/or generifying the solution remain open over time, or not.

Summing up the paper’s argument

• Processual perspective on evolution of architecture – The process shapes the architecture – Temporal perspective (short/long horizon) – Architecture -> Organizing

Commercial solution: Cartagenia

Mulig mellomløsning: Storvolumprøver (F. eks BRCA etc)

Panel med relativt få gener

Viktig med ”100% sensitivitet”, - alle varianter må vurderes

Hastighet og ettersporbarhet viktig: Låste prosedyrer

Småvolumprøver (Skreddersydde paneler for sjeldne / uklare tilstander) Ofte store / spesialdesignede paneler

Evt triosekvensering på fulleksom

100% sensitivitet uansett umulig, HTS uansett bedre enn Sanger/ målrettede sekvenser

Fleksibilitet viktigere enn ”streng reproduserbarhet

Egen-utviklet FFI løsning (Evt ORC)

Kommersiell fleksibel løsning

Hvor setter vi grensen

for bruk av hvilken

applikasjon?

Bredde proprietær løsning

Koble mot ORC modul

Mulig migrasjonsløp?

Utvikle FFI for BRCA++

Med økende volum/ erfaring per indikasjon,

”låse paneler”

Anvende komm. Løsing på trio og lavvolum, få

erfaringer med nye paneler

Fase nye indikasjoner

over på egen FFI løsning

Fortsette med nye indikasjoner på

”utviklingsbasis”

Fase nye indikasjoner

over på egen FFI løsning

Viktige risikomomenter og trade off’s Dersom vi lener oss veldig på en ekstern/ kommersiell løsing blir det meget krevende å bytte leverandør om de ”skrur til” sin prisingsmodell

”Microsoft effekt”: Om veldig mange aktører går for en ekstern løsning ender vi de facto opp i en ”lock in” på system nivå pga. utvekslingsgrensesnitt, kompatabilitet osv.

Andre open source aktører (F. eks Clin var) kan utvikle gode tolkningsløsninger som mange velger, og således overflødiggjøre vår innsats (men ikke læringen)

Innføring og bruk an ekstern/ kommersiell løsing begrenser egenlæring, øker avhengighet.

Er vi komfortable med det klniske ansvaret for en ikke CE merket løsing for diagnostisk bruk?

Vi har neppe kapasitet på kort sikt til også å håndtere aCGH etc

MEN: Vi bør raskest mulig ha en løsning for tolkere som avhjelper arbeidssituasjonen gitt økte volumer. Må også være Sanger kompatibel.

Viktig jurisk innspill: Det kan bli avgjørende å utvikle en database som er ”ubrukelig” for andre formål enn helse. Dette neppe mulig med ekstern/ kommersiell løsning

Relevant trends in the practice domain:

• Gartner: – Rapid Architected Application Development – Emergent Architecture (middle-out EA, light-

weight EA) • «architect the lines, not the boxes»

• Software Engineering: – Evolutionary software architecture – Emergent software architecture

Links

– Rapid Architected Application Development • http://www.gartner.com/it-glossary/raad-rapid-architected-

application-development

– Emergent Architecture • http://www.gartner.com/newsroom/id/1124112

– Evolutionary software architecture • http://link.springer.com/article/10.1007/s10270-012-0301-

9#page-1

– Emergent software architecture • http://link.springer.com/article/10.1007/s10270-012-0301-

9#page-1