8. Science at the Bench and the Bedside: Less of a Tightrope, More of a Super Highway

Enabling Science

IDBS and Translational Medicine

Enabling ScienceSlide 2 © IDBS 2012

Enabling ScienceSlide 3 © IDBS 2012Right Treatment to the Right Group at the Right Time

Drug toxic but beneficial

Drug NOT toxic and NOT beneficial

Same diagnosis, same prescription

Patient group

Drug NOT toxic and beneficial

Drug toxic but NOT beneficial


Health Science Ecosystem: Driven by Data

Medical Research

Centre

Pharma and Biotech

Healthcare Provider Healthcare

Payer

Diagnostic company

Patient dataand samples

High qualityPatient dataand samples Clinical Trial

Candidates and Outcomes data

CompanionDiagnostics

Molecular assaysfor disease and

safety predictions

Predictive modelsand Comparative

Effectiveness

New drugEffectiveness

Data

Outcomes analysis

Outcomes data

http://www.idbs.com/






Advanced Clinical

ResearchDiagnostics

Pharma and Biotech

We are privileged to work with:


Stratification: Some Common Problems Cohort selection is complex and

users are unable to interactively explore and define cohorts

Clinical / Patient data are not easily connected to research data

Multiple sources of clinical information from EHR, patient history, pathology, HL7, CDISC, EDC, CTMS

Clinical data can be of poor quality

Need to support regulatory and clinical compliance e.g. Pseudonymisation


IC50


It is possible to solve these problems

10 years clinical

trials data

Omics Data

ResearchData

NormalisationQuality scoreLongitudinalDisease

Outcomes analysis

BiomarkerAnalysis

Comp.Effect.

Trial Simulation


Data Landscape NOT Data Warehouse

Data from disparate stores can be located and analysed in situ

New data types easily indexed for ‘future-proofing and flexibility’

Can be readily mirrored for ‘up-time’ security

Demands all data to be moved and stored centrally

New data types demand new data models

Becomes huge very quickly

NOT


Read and count the Fs – 5 secs

FINISHED FILES ARE THE RESULTOF MANY YEARS OF SCIENTIFIC STUDY COMBINED WITH THE EXPERIENCE OF MANY YEARS


How many F’s


FINISHED FILES ARE THE RESULTOF MANY YEARS OF SCIENTIFIC STUDY COMBINED WITH THE EXPERIENCE OF MANY YEARS


Computers don’t tend to miss stuff

They can help with analysis They can remove the human factor where

neededBut not replace it where it is needed

Decision Support not Decision Making


Surfing the Omics wave


What Happens in a NGS Study

Study Design

Dosing & Sample

Collection

NGS and Analysis

Reporting


NGS Workflow leveraging the Biomolecular Hub

Single end (SE) readsPaired end(PE) readsDirectional SE reads

Raw Reads

IDBS Biomolecular Hub

Raw Readscsfasta, fastq, fasta

Reference sequence

Alignment(Bowtie, BWA, SOAP)

SNP

In/Del

SAM/BAM

SNP report

In/Del report

Genomeviewer

Downstream analysis

Feature filesAnnotation files

RNA-seq

ChIP-seq

Exome-seq

Whole Genome

http://www.illumina.com/index.ilmn









Ethics and Consent Management, Clinical Data Collection, Sample Collection, Banking, Omics Processing and Analysis

Sample Collection (from patient)

Aliquots and storage

... ... End Repair Concentration

estimation (pico green)

Not just data harmonisation – but process harmonisation


How very similar to ...

Pharmacology, BA, PK, Formulations, QA, QC, ...

The interesting aspect here is it is a language or “meta data” and process issue not a technology issue

If you have the right technology and data management – “the case is solved”


The same is true in most areas

Allow data normalisation against many different ontologies science, disease, research, clinical (ontologies/taxonomies)

Allow data exploration in any number of tools (standards and openness)

Streamlines analytical workflows – empowering scientists

Psedonymisation of patient data and importantly re-identification of patients based on security


Collaboration

I cant see CRO and collaborators data next to my internal results

All my data is in Excel, I cant find anything or search it

I cant share my cohorts with colleagues easily

I need to share data securely with my partners

I want to generate and validate my reports more quickly


Case Study Advanced Clinical Research

Improved speed, quality and volume of oncology research will deliver enhanced patient outcomes

Supports partner collaboration across the organisation, external collaborators and industry

High quality data sets and cohort tools will make King’s an attractive partner for clinical trials

King’s Health Partners is a £3 billion academic health science centre comprising multiple hospitals and research groups. As part of a major business initiative King’s and IDBS have developed an enterprise-scale translational research platform to deliver increased levels of highly innovative research through an improved ability to integrate and analyse clinical, image and ‘omics data across the partners.

King’s Health Partners is a pioneering collaboration between King’s College London and Guy’s and St Thomas’, King’s College Hospital and South London and Maudsley NHS Foundation Trusts.


ACROPOLIS – an example health science ecosystem powered by IDBSLead by IDBSHosted UK National infrastructure for translational

medicine and collaboration in Cancer Initially - Consortium of Kings Health Partners,

Manchester AHSC, Roche Pharmaceuticals, PA Consulting, CRUK, NIHR

Once delivered - Roll out to all other cancer centres in UK

Based on the IDBS translational medicine platform


Acorns and Oak trees


Some IDBS Translational Science / Research / Medicine Case Studies Medimmune

◦ Biomarker discovery and qualification Daiichi Sankyo

◦ Population PK / PD simulation and biomarker analysis of historical trial and omics data Large Pharma

◦ Analysis of historical trial and omics data Large Pharma

◦ Omics Data indexing and analysis Windber Research Institute

◦ Biomarker discovery and clinical risk assessment in Cancer Barts and the London Hospital

◦ Adaptive Clinical Trial Design, Patient recruitment and Execution using Translational Medicine knowledge in CV treatments

Dana Farber Cancer Institute◦ Translational Medicine Research data capture and collaboration for multiple myeloma and lung

cancer Imperial NHS Trust

◦ All of the above and more over the next 7 years for all diseases◦ Biomarker Discovery for use in Clinical treatment of CV disease

Kings Health Partners ◦ All of the above over the next few years◦ Starting in Cancer moving to all disease areas


Forward Looking

Clinical decision support◦ Take all the data

landscape◦ Learning models◦ Deliver tools to help

make decisions

◦ No longer chasing a dream


Ambition is becoming reality

Science at the Bench and the Bedside: making it less of a tightrope and more of a super highway


Translational Medicine – a long road aheadSomething I am very used to - St Malo to Biarritz

in 6 days then the Tourmalet !



IDBS Brings Together the Pieces of the Translational Puzzle

Clinical Data

TranslationalScience

Sample

‘omics

Study /Research

Public and Proprietary

Clinical


Special Thanks to name but a few

WindberDana Faber MedimmuneCardiff UniversityBartsKings Health Partners Imperial NHS TrustGenomic HealthMayo ClinicRocheCelera …

CustodixOracleOrion HealthGoogle Images !

IDBS◦ Everyone

Education

8. Science at the Bench and the Bedside: Less of a Tightrope, More of a Super Highway