st andrews, may 2013 · 2019-04-09 · clinical laboratory genomics & transcriptomics cell...

St Andrews, May 2013 The roadmap continues

• Welcome • Fire alarms • Undergraduate examinations • Workgroups

Implementation of systems medicine across Europe

► Stakeholders meetings – big picture, systems biology to medicine

► Workshops – large, flexible

► Achievement to date

► Challenge – tractable clinical questions

Implementation of systems medicine

► Stakeholders meetings – big picture, systems biology to medicine

► Workshops – large, flexible

► Achievement to date

► Challenge – tractable clinical questions

“Systems biology...is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different....It means changing our philosophy, in the full sense of the term”. Denis Noble

Systems what? ► Biology – big model, dynamical,

comprehensive datasets, explanation and prediction, integrative

► Medicine – towards 4P: prevention,

predictive, participatory: incomplete datasets, imperfect quality, tractable problems, models and analysis

The purpose of the St Andrews meeting ► Inform the roadmap document – the European

standard, future goals, future funding, close working with the Commission, benefit to all

► Everyone to contribute – small numbers, people

with relevant insights into problems, rather than just systems expertise

► Diagnosis, taxonomy, treatment, discovery,

participation, prediction, economics, education, personalisation, prevention and public health

8

• “ The patient has a voice “ – Pim de Boer

• “ A new paradigm for cancer treatment “ –

Francis Lévi

• Focussed outputs – iterative modelling – Drieke Vandamme

CASyM is funded by the European Union; 7th Framework Programme under the Health Coorporation Theme and Grant Agreement # 305033

A new paradigm for cancer treatment Francis Lévi

Chronotherapy Unit, Department of Medical Oncology Paul Brousse hospital, Villejuif (France)

UMRS 776 Rythmes Biologiques et Cancers

But how efficiently can we use these data?

Metabolomics Proteomics Imaging Clinical laboratory

Genomics & Transcriptomics

Cell Biology & Molecular Biology

Technology Platforms

Pathology & Biomarkers

MS-data Images Biochemical data

Metabolomics data

Gene array dataSequencing data101

102

103

100

FACS dataTissue

microarrays

What can Systems Biology do for Medicine? We can produce more data on patients than ever before

Walter Kolch

http://www.bmbf.de/index.php



http://www.bmbf.de/en/index.php

Roadmap for Systems Medicine

2 years

5 years

10 years

Clinical needs

SysBio

Systems Medicine Paradigm

shift

Clinical practice

&RTD




http://www.bmbf.de/en/index.php

• Rhythmic biology The mammalian Circadian Timing System

• Circadian disruption (or induction) on cancer Biomarkers

• Cancer chronotherapeutics Shifting treatment paradigm

• Conclusions & perspectives

Rest-activity rhythm

Molecular clocks in

peripheral organs

• Cell cycle & DNA repair • Metabolism • Drug detoxification • Angiogenesis

Circadian biomarkers

Lévi et al. Annu Rev Pharm Toxicol 2010

Body Temperature

rhythms

Cortisol, melatonin rhythms

Day/night Chronic jet lag

Disease processes

Treatment effects

Meal timing

Clock gene mutations

The Circadian Timing System

Drugs →

Drugs →

Lévi et al. Annu Rev Pharm Toxicol 2010 Bjarnason et al. Am. J Pathology 2001

hBmal1

0.2

0.4

0.6

0.8

1

0.0 08 12 16 20 00 04

hPer1 hBmal1

Clock gene transcription rhythms in human oral mucosa

Time (clock hours) CCG

Clock-Controlled genes

- Drug metabolism and detoxification Cyp3a, Ces1-3, UGT1A1, GST-π, Upa, Dpyd,… -Drug transport Abcb1a/b, Abcc2, Abcg2,… - Drug targets TS, Top1, Top2,… -Cell cycle, apoptosis, repair Wee1, P21, P53, c-Myc, Bcl-2, Bax, Mdm2, cyclin D, Tip60,…

The Molecular Clock System

In vitro circadian biology & pharmacology

Cell culture Circadian synchronisation

•50% FCS or • Dexamethasone

Samples every 4 h for 48-72 h

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3 12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

12 1 2

7 6 5 4 8

9 10

11

3

2 h



• Cancer chronotherapeutics Shifting treatment paradigm


Rest-activity circadian biomarker before chemotherapy

Rest-activity monitoring Computation of I<O

I<O prediction of overall survival in 436 patients with mCRC

Circadian disruption: I<O less than 97.5%

I<O = 100%

I<O = 77.6%

Lévi et al. Submitted

Circadian disruption on chemotherapy

Circadian disruption on chemotherapy in mice 12 anticancer drugs according to dose and circadian timing

R24 = 0,48

Before irinotecan

PS = 0 After irinotecan

R24 = -0,04

PS = 3 Asthenia grade 3 Anorexia grade 3

(38) (39)

Circadian disruption

Innominato et al. Int J Cancer 2012

Rest-activity circadian biomarker during chemotherapy



• Cancer chronotherapeutics Shifting treatment paradigm through CTS integration

into drug scheduling and delivery


Chronotolerance vs Chronoefficacy

Ortiz-Tudela et al. Handbook of Exp Pharm 2013

L-Alanosine

Vinorelbine

Pirarubucin

Oxaliplatin

Gemcitabine

Interleukin-2 Doxorubucin

Irinotecan Cytarabine

Docetaxel

Seliciclib

Interferon-β 5-fluoro-2'-deoxyuridine

0 12 24

0

12

24

5-Fluorouracil

Circadian timing of best tolerance (ZT hours)

Circ

adia

n tim

ing

of b

est e

ffica

cy (Z

T,ho

urs)

Combination chronotherapeutics

Fold increase in life span (vs untreated controls)

Ortiz –Tudela et al. Handbook of Exp Pharm 2013

-20

0

20

40

60

80

100

120

4 pm 12 pm 8 am 4 pm

5-FU profil

[5-F

U]

(% o

f max

con

cent

ratio

n)

Time (h)

10 pm 10 am

04 am

5-FU

Optimal fixed drug delivery profile

Lévi, Altinok, Goldbeter In: Cancer Systems Biology 2011

Host?

Cell cycle, 22 h Variability, 5% Circadian entrainment

Tumor?

Cell cycle, 18 h Variability, 15% No circadian entrainment

Oncologist Patient Consultation

Care Unit Programmation Pharmacy

Coordination

Personnalized medical care plan Prescription, verification

Home

Home Care

Chronotherapy Unit, Hôpital Paul Brousse, Villejuif 1990-2013: ~ 3 000 patients

Research & Development Family

doctor

Education • health care personnels • patients

Giacchetti et al. J Clin Oncol 2006; Ann Oncol 2012 Innominato et al. Chronobiology Int 2011 Int J Cancer 2012; Cancer 2013

Conventional chemotherapy

Chronotherapy

564 patients first line treatment for metastatic colorectal cancer 36 centers, 10 countries

Time (months)0 12 24 36 48 60 72 84 96 108 120

Pro

po

rtio

n a

live

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0 None (G0)Mild (G1-2)Severe (G3-4)

Time (months)0 12 24 36 48 60 72 84 96 108 120

Pro

po

rtio

n a

live

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9


FOLFOX2

p < 0.0001

chronoFLO4

p = 0.36

Neutropenia Neutropenia

Time (months)0 12 24 36 48 60 72 84 96 108 120

Pro

po

rtio

n a

live

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9


chronoFLO4

p = 0.36

Neutropenia

Innominato et al. Chronobiology Int 2011

FOLFOX2 chronoFLO4

CTS toxicity

No CTS toxicity

p = 0.136

CTS toxicity

No CTS toxicity

p < 0.0001

Circadian Timing System Toxicity : BWt loss & asthenia Innominato et al. Cancer 2013

Tolerability Coordinated peripheral clocks

Predictable optimal timing

Drug detoxification

Circadian physiology Rest-activity Body temperature Hormones & cytokines Feeding pattern

Tumor inhibition

Anticancer drug

Toxicity

Disruption

Poor coordination

Tumor progression

Poor detoxification

Unpredictable optimal timing Lévi et al.

Annu Rev Pharm Toxicol 2010

CTS integration for treatment optimization

21

Systems cancer chronotherapeutics

Ballesta et al. PLOS Comput Biol 2011 Ortiz –Tudela et al. Handbook of Exp Pharm 2013

Rest-activity rhythm Cancer processes

Treatment effects Temperature rhythm

Multidrug chronotherapy effects on circadian biomarkers

Cancer Chronotherapy Pilot 40 patients: BWt, symptoms, rest-activity rhythm

Actigraph Data

Home Gateway

Tele-health System (SARA)

Tele-health Data

GPRS or IP Network

Remote Service Provider

Tele-health Service (SARA) Hydra

Middlew

are

Medical Web App

Contact Centre

Social Response

Medical Response

Technical Provider

Chronochemotherapy at home in 2 patients with metastatic colorectal cancer receiving Irinotecan, Oxaliplatin, 5Fluorouracil, Leucovorin (chronoIFLO4)

Daily teletransmission of rest-activity patterns during multidrug chronotherapy at home

97.8%

Patient 1 Patient 2

96.8%

98.9%

99.1%

98.7%

99.2%

I<O I<O

Toward a shift in paradigm of cancer treatments

►Conventional chemotherapy principle: The more the toxicity, the better the efficacy

►Chronotherapeutics principle: The better the tolerability, the better the efficacy (personalized model-based drug delivery)

CASyM is funded by the European Union; 7th Framework Programme under the Health Cooperation Theme and Grant Agreement # 305033

The patient has a voice

dr. Pim de Boer

Lung Foundation Netherlands / Longfonds

Leiden University Medical Center

Patient empowerment

► “Nothing about us without us” (B. de Szemere. Hungary, from 1848 to 1860. R. Bentley, London. 1860. p173; J.I. Charlton.

Nothing about us without us. Disability oppression and empowerment. University of California

Press, Berkeley CA. 1998; many patient organisations now)

► “My right knee”. (D.M. Berwick. Improving patient care. My right knee. Ann Intern Med 2005, 142: 121-125)

1. No needless death; 2. No needless pain; 3. No provision of helplessness; 4. Not keeping

waiting; 5. No waste of resources => need for contract MD-patient to improve quality of HC.

► “Don’t look at me but SEE me. Don’t listen to me but HEAR me”

(L. Engelen. The patient as partner. Scouting expedition by the UMC St Radboud. BSvL, Houten

NL. 2012)

Patients are not disease subjects only need for holistic views;

often patients tell more behind their words.

► Reflection interviews (mirror interviews)

See yourself being treated in a hospital. How are you treated, how did you feel, were you being

listened to and attended for when you asked the doctors or nurses, etc. HuMedSci

Consultancy

Patient involvement: definition

Patient participation or involvement in research:

taking part in any of the processes of formulation,

passage and implementation of research

Why is patient involvement needed?

► Normative argument:

(Multimorbid) patients are affected by their own treatments

► Instrumental argument:

* more relevance of the research

* better quality of the research

* better results and chances for societal implementation

► Legitimacy:

Democratic decision making in research, its policy & budgetting

“Patients are experts in living with and treatment of their own disease(s)”

Patient empowerment HuMedSci Consultancy

Theoretical framework Problem identification

Problem definition

Approach- methodology

Execution of research Interpretation & evaluation

com

mu

nic

atio

n

Adaptation

Knowledge transfer

Implementation Research

“Patient” as co-producer/leader Society science

health care

politics

public

individuals groups

communities

operational

strategic

Based on: D Wilcox, 1994; D Winstanley, 1995; C Hart, 1997; G Chanan, 1999; Franklin & Sloper, 2005

HuMedSci Consultancy

industry

Patient as partner: co-decider

consultant-advisor information carrier

subject in study decoration

Examples of best practices – 1: research

http://www.lindalliance.org/

http://www.ubiopred.eu http://www.patientsacademy.eu

ECAB protocol review process Our experienced treatment advocates, expert patients and community advisors read and review trial protocols and informed patient consent forms from the patients’ perspective…

Examples of best practices – 2: health care

http://www.involve.org.uk

COPD standard of care

patient version (NL)

Practical approaches: examples

How to run a patient organisation,

how to involve patients in research, which tools

are needed (a grid supplied), communication,...

See EPF: http://www.eu-patient.eu

How to evaluate documents or protocols,

tools to participate in councils or advisory

boards, training on the use,...

See e.g.: http://www.pgosupport.nl

Appraisal criteria include domains:

relevance; QoL; QoC; ethics-safety; information-communication

G Teunissen et al. J Participat Med 2013, 5: e16

http://www.eu-patient.eu/



http://www.pgosupport.nl/

Practical approaches: what did we learn?

IMI U-BIOPRED & PROactive projects; Longfonds PAB:

+ patients being listened to for needs and wishes

+ project adaptation relevant to patients/participants

+ patient partnership = being taken seriously, no tokenism

-- expectations: lack of clarity on role charter & protocol

-- involvement: communication; function within/outside project

-- travel for meetings: disease; work; no or small budget in project

-- language barrier: esp. for non-English speaking patients

-- visibility: patients and researchers unknown to each other

-- knowledge: specific tasks need specific knowledge training

Systems medicine and patients as a partner

- THE patient doesn‘t exist – stratification is needed

but inform patient community first on need for stratification

- Patients expect a holostic view MDs (should) learn to provide this

systems medicine will add to this view

- Needs and wishes of patients: e.g. early diagnostics, psychosocial

and multi-morbidity aspects, polypharmacy, and prevention

- Involvement of patients as partner from the beginning

- Safety and privacy issues: databanks, personal data, third party use

- Ethical issues: all data used? burden of testing? consent for what?

- Communication and dissemination: feedback, informing, etc.

Consequences of patient as a partner

- Time and effort involved in process: invest now routine later

- Inventory of needs-wishes of (groups of) patients

- More time for interaction MD - (chronic) patient needed (> 3 min.)

- Explore new ways of interaction (digital; shared decision making;

all inclusive; style language; age; info finding; involve relatives etc.)

- Involve all stakeholders to gain support (include prim. care; pts;

health governments, healthcare insurers)

- Adapted curricula for students (para- and medical) regarding

engagement

- We continuously learn from each other

Thanks to:

VU University – Athena Institute:

Janneke Elberse

Jacqueline Broerse

Longfonds:

Patient advisory board

Truus Teunissen

Dorothee Laan

PROactive:

Patient Input Platform

Ethics Board

Thierry Troosters (KU Leuven)

U-BIOPRED:

Patient Input Platform

Ethics Board

Safety Monitoring Board

Peter Sterk (AMC Amsterdam)

Dr. W.I. de Boer E: [email protected]

HuMedSci Consultancy

CASyM is funded by the European Union;

7th Framework Programme under the Health Coorporation

Theme and Grant Agreement # 305033

Round table methodology Stakeholder conference St.Andrews

What outputs do we need?

► Current state of the art ► Clinical needs ► Opportunities for Systems Medicine ► Prioritized actions in short, middle and long term (2,5 and 10 years)

How will we get them ? ► Brainstorm: State of the art (45min)

► Identification of priority issues (45min) • Every participant writes down 2 priority issues on a post-it • all priority issues are put on a time-line • From these priority issues 2 are selected by the group

► Definition of actions /strategy (45min)

► Wrap-up and detailing of at least 1 priority action (45min) (aim, duration, SWOT analysis, expertise needed,…)

► After the coffee break RT leaders present the results, time for discussion

Who? ► 1 round table leader, expert in the field leads discussions manages the group synthesis of proposals ► 1 note-taker document the discussion will assist the round table leader ► 1 facilitator Keep time ensure the method is respected

What are the big questions in non-cancer lung disease (particularly chronic obstructive lung disease) and how might Systems Medicine address them?

RT N° 1

IMPA

CT

LOW

M

IDD

LE

SHORT TERM MID TERM LONG TERM

HIG

H

1-2 years 2-4 years > 4 years


RT N° 1

PRIORITY ISSUES

ACTIONS

EXPECTED RESULTS


RT N° 1

STRENGTHS WEAKNESSES

OPPORTUNITIES THREATS


Questions?

CASyM – a brief overview Marc Kirschner on behalf of the CASyM Consortium

What is CASyM?

CASyM Coordinating Action Systems Medicine - Implementation of Systems Medicine across Europe Launched by the EC under the FP7 programme Preparing for the future research and innovation activities in systems medicine. Coordination Dr. Marc Kirschner, Project Management Jülich (PtJ), Forschungszentrum Jülich GmbH, Germany Duration 4 years - 1 November 2012 – 30 October 2016

What is CASyM?

CASyM is tasked with formulating a European wide

implementation strategy (road map) for Systems Medicine

► The road map is driven by clinical needs: It aims to identify areas

where a systems approach will address clinical questions and solve

clinical problems.

Inclusive – a concept, not a club ► Fostering partnerships, integration, open network and concerted

actions.

22 PARTNERS & 11 COUNTRIES: GERMANY UNITED KINGDOM FRANCE SWEDEN LUXEMBOURG NETHERLANDS SLOVENIA IRELAND ICELAND ISRAEL ITALY

http://www.sbi.uni-rostock.de/home/

http://www.st-andrews.ac.uk/

http://www.ox.ac.uk/

http://www.uni-lj.si/en/

http://www.fnr.lu/

http://www.neuron-eranet.eu/_img/teaser/CSO-MOH_klein_rdax_140x50.jpg

http://www.unige.it/

http://www.bayertechnology.com/

http://www.sanofi.de/l/de/de/index.jsp

http://wwwen.uni.lu/

http://www.lyonbiopole.org/index-en.html

http://www.inserm.fr/index.php

http://www.liu.se/?l=en

http://www.zonmw.nl/nl/

Expertise represented in CASyM

Public funding bodies and ministries

Clinical Centers,

Hospitals, Schools of Medicine

SysMed Institutes and

Research Cluster

Universities and Systems

Biology Centers

Industry and SMEs

Objectives of CASyM

Clinical needs

Engagement of all relevant stakeholders

(open network)

Interaction with key

national and European initiatives.

Systems Medicine road development

Work packages of CASyM

WP1 - Conceptual framework for the Systems Medicine road map: Stakeholders, target areas, structure, integration

WP2 - Education & multidisciplinary training: Training concepts, workshops, summer schools, CPD courses

WP3 - Technologigal and methodological basis: Clinical relevant questions

WP4 - Strengthening innovation activities: Fostering “win-win” academia-industry relationships

WP5 - Integration of national efforts: Implementation of relevant funding schemes

WP6 - Dissemination: Central website, publications, publicity, sustainability

WP7 - Management: Administrative management

The vision of CASyM

Harnessing the advances in biology, computational biology and Systems Biology for the benefit of the patient.

Science can produce more patients data than ever before







Metabolomics data

Gene array data Sequencing data 101

102

103

100

FACS data Tissue

microarrays

But how efficiently can these data be used?







Metabolomics data

Gene array dataSequencing data101

102

103

100

FACS dataTissue

microarrays

Systems Biology Approaches can provide the Heads-Up-Display that allows the clinician to navigate patients’ data for making optimal decisions about diagnosis and therapy.

Clinical samples

Mutation data

Pathway mapping

RASSF1A

APOPTOSIS

Mitogens Growth factors

Receptor receptor

Ras

RAFPP

P

P

MEKP

ERKPP

MST2

LATS1

PROLIFERATION

p53p73

Patients’ samples

Pathway literature

Clinical literature

Evidence & data

Clinical data

Over

all su

rviva

l

Survival in months

Dukes’ B (N=34)

Dukes’ A (N=24)

RKIP weak/negative

Dukes’ C (N=55)

0.5

P values:A vs. B: 0.70B vs. C: 0.03A vs. C: 0.08

Dukes’ Stage Survival Time Standard Error 95% Confidence IntervalA Mean: 59 months 7 46 - 72

Median: 72 months 14 44 - 100 B Mean: 70 months 7 56 - 84

Median: not applicableC Mean: 49 months 7 36 - 62

Median: 36 months 10 17 - 55

Signalling networks

Plasma membrane EGFR Frizzled

WntEGF

β-cat

β−cat/APC*/Axin*/GSK3β

β-cat*/APC*/Axin*/GSK3β APC*/Axin*

/GSK3β

Dshi Dsha

2

β-cat/TCF

TCF

Axin a

Slug

E-cadLPDM

SOS/Grb2

RasRas-GTP

Raf-1Raf-1*

MEKMEKpp

ERKERKppRKIPp RKIP

Snail

E-cad

c

c

GSK3β

2

SnailSlug

PKCδ

GSK3β

2

4

4

Slug

E-cad

RKIP

Axin

ERK pathway

Gene regulation

∅

∅

TranscriptionStoichiometric conversionTranscriptional repressionInhibitionFacilitationEnzymatic catalysis

DegradationConstitutive protein synthesis

Line connection

APC/Axin/GSK3β

GSK3β

Axin

∅

APC/Axin

APC

β−cat/APC a

β−cat*

∅

Wnt pathway

EMT (metastasis)

x1 x2

x3

x4

x5

x7

x8

x9

x10x11

x12

x13

x14

x15

x16

x18

x19x20

x21x22

x23x24

x25x26 x27

x28

x29

x30x31

x27

x5

x17

x13

x5

∅

∅ ∅

RKIP

GSK3β*x6

v1

v2

v3

v4v5 v6

v7v8

v9

v10

v11

v12

v13

v14

v15

v16

v17

v28

v29v30

v31

v32

v33v34

v35

v37

v36

∅

∅

v19v20

v21 v22

v23

v24v25

v26

v27

v38

v39

v40v41

v42

v43v44

v45v46

v47v18 ∅

Notation

∅

Omic profiles

Multidimensional inputs

Computational models Patient

stratification

Therapy response

P=0.0002

Survival in months

Overa

ll sur

vival

0.5

5 year survival: 82%

5 year survival: 48%

Prognosis

Validation

Virtual patients

Personalised diagnostics

Improved diagnostics & therapies

Personalised therapies &

A vision for Systems Medicine

How will CASyM contribute to this vision? ► CASyM will develop a road map for the implementation of

Systems Medicine

2 years

5 years

10 years

Clinical needs

What will CASyM achieve? Stakeholders

Clinicians, Patients Biomedcial researchers

Health care organisations Industry

Technology base -omics data

Data management Computational modelling

Molecular pathology

Beneficiaries Participatory medicine Stakeholder meetings Workshops Conferences

Technology needs Advanced data analysis Deep data mining Data integration

Application of Systems Medicine Where will be the biggest impact?

What are the best applications? How can we fully exploit the potential?

Prevention and early intervention

Training Postgenome generation

Complexity of diseases Use of novel technologies

Clinical needs Better diagnostics Better treatments Better clinical trials Faster drug approvals Cheaper healthcare

New generation of clinician-scientists Interdisciplinary training programmes Integration between basic research and clinical practice

Innovation Systems approaches in industry

Best practice

Exploitation Success stories Enhancing European competitiveness

What will CASyM achieve?

Stakeholders Clinicians, Patients

Biomedcial researchers Health care organisations

Industry

Technology base -omics data

Data management Computational modelling

Molecular pathology

Beneficiaries Participatory medicine Stakeholder meetings Workshops Conferences

Technology needs Advanced data analysis Deep data mining Data integration

Application of Systems Medicine Where will be the biggest impact?

What are the best applications? How can we fully exploit the potential?



Complexity of diseases Use of novel technologies

Clinical needs Better diagnostics Better treatments Better clinical trials Faster drug approvals Cheaper healthcare

New generation of clinician-scientists Interdisciplinary training programmes Integration between basic research and clinical practice

Innovation Systems approaches in industry

Best practice

Exploitation Success stories Enhancing European competitiveness

ROADMAP

Networking and disseminating the CASyM concept and its achieved results

Integration of national efforts in Systems Medicine

StakeholdersClinicians, Patients

Biomedcial researchersHealth care organisations

Industry

Technology base-omics data

Data managementComputational modelling

Molecular pathology

BeneficiariesParticipatory medicineStakeholder meetingsWorkshops Conferences

Technology needsAdvanced data analysisDeep data miningData integration

Application of Systems MedicineWhere will be the biggest impact?

What are the best applications?How can we fully exploit the potential?



Complexity of diseasesUse of novel technologies

Clinical needsBetter diagnosticsBetter treatmentsBetter clinical trialsFaster drug approvalsCheaper healthcare

New generation of clinician-scientistsInterdisciplinary training programmesIntegration between basic research and clinical practice

InnovationSystems approaches in industry

Best practice

ExploitationSuccess storiesEnhancing European competitiveness

ROADMAP

What will CASyM achieve?

What is CASyM?

The big picture: Relevance to P4 medicine, health

and wealth

Inclusive – a concept, not a

club: Partnerships, open network and concerted actions

Representative: Political, public,

Academic, healthcare,

Industry/SMEs

Real life examples - Science, drug

discovery, patho-physiology,

patient´s benefit and public health Translational:

Across disciplines

Adaptable: Addresses real problems and

evolves over time.

Awareness - Education and

training

Join CASyM and work with us on the future of healthcare & medicine!

www.casym.eu

Organization and support

The CASyM Steering Committee David Harrison (speaker) – The University Court of the University of St. Andrews, United Kingdom Damjana Rozman (deputy speaker) –University of Ljubljana, Faculty of Medicine, Slovenia Mikael Benson (deputy speaker) –The Center for Individualized Medication Linköping University Hospital, Sweden Charles Auffray – European Institute for Systems Biology & Medicine/HLA & Médecine, France Rob Diemel – The Netherlands Organisation for Health Research and Development Walter Kolch – University College Dublin, Ireland Frank Laplace – Federal Ministry of Education and Research, Germany Francis Lévi – Institut National de la Sante et de la Recherche Medicale, France Johannes Schuchhardt – MicroDiscovery GmbH, Germany Olaf Wolkenhauer – University of Rostock, Germany

Coordination Marc Kirschner – Forschungszentrum Jülich, Project Management Jülich (PtJ), Gemany

Round table1 - What are the big questions in non-cancer lung disease (particularly chronic obstructive lung disease) and how might Systems Medicine address them? Leader: Alfredo Cesario

State of the Art (1: background concepts)

► COPD AND Systems Medicine / Systems Biology (and vice-versa) medline (pubmed) search 12th May: no “big questions” answered…

However, some concepts well accepted: Integration of an ever-increasing variety and quantity of biological, clinical, epidemiological,

environmental, functional, genetic, genomic, pathological, physiological (and imaging?) data through systems approaches is the cornerstone for the personalized treatment (P4 / SM) of individuals.

Auffray C, et al. Systems medicine: the future of medical genomics and healthcare, Genome Med 2009 Bousquet et al. Systems medicine and integrated care to combat chronic noncommunicable Disease, Genome Med 2011 Auffray C, et al. Systems biology and personalized medicine - the future is now. Biotechnol J 2012 Hood L, et al. Revolutionizing medicine in the 21st century through systems approaches. Biotechnol J 2012 Chen R et al. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell 2012 Smarr L: Quantifying your body: a how-to guide from a systems biology perspective. Biotechnol J 2012

Focus on the development of panels of indicators for disease control as part of decision- support systems for the monitoring of prominent complex diseases, such as Chronic Obstructive Pulmonary disease, by patients and their physicians (P4 in practice)

Agusti A, et al. The COPD control panel: towards personalised medicine in COPD. Thorax 2012

State of the Art (2: ongoing research activities) Respiratory Diseases (COPD) SB/SM EU projects: U-Biopred (FP7, IMI, asthma focused fingerprint / handprint) Medall (FP7, Cooperation Health, Allergy) AirProm (FP7, Cooperation Health, Patient Specific Computational Modelling) Synergy COPD (FP7, ICT, SM Simulation Environment – COPD as use case) SysClad (FP7, Cooperation Health, Chronic Lung Allograft Dysfunction) Biobridge (FP6, Cooperation Health, systemic effects of COPD/HF/DMII – focus on nitroso/redox unbalance CVS, skeletal muscle wasting/dysfunction). “…the complexities of the interactions between susceptibility (i.e. genetic determinants) and life style factors (i.e. low physical activity, tobacco smoking, nutrition, etc...) put on display the insufficiencies of the classical hypothesis-based research approach to effectively explore the underlying mechanisms determining the clinical problem. It prompts the need for complementary novel strategies based on integrative translational research using Systems Biology methodologies aligning two well differentiated dimensions, biomedical and bioinformatics” (2006...)

OUTPUT: Biological knowledge through the simulation environment AND contributions in several bio-informatic dimensions: - multilevel data integration; - development of SBML standards ensuring interoperability among different ICT tools; - development of deterministic modelling of oxygen transport-central metabolism and mitochondrial ROS generation; - preparing tools for inference analysis and probabilistic modelling; - integration of simulation environment into a workable portal

State of the Art (3: biomedical dimensions) Challenges / Priorities COPD not an homogeneous disease heterogeneity lies at the pulmonary and extra-pulmonary level (systemic) and beyond (genetics, lifestyle,…) COPD complex phenotype is a summative entity (of phenotypic traits / comorbidities ?) with emerging

properties that cannot be attributed to each of the elements considered separately hence redefinition of (COPD) taxonomy (multidimensional) as THE challenge for a SB/SM modelling

exercise ? therefore validation of actionable interventions new-taxonomy driven through solid(ly) clinical benchmarks (severity / activity / impact)? Severity (degree of functional reserve): FEV1; IC/TLC; Arterial Oxygenation; exercise capacity Activity (doesn’t go in parallel with severity): rate of change of FEV1, continued smoking, frequency of exacerbations; persistence of systemic inflammation (circulating leukocytes; C-reactive protein; IL-6; fibrinogen and selected biomarkers (!); Impact (degree of perception) : COPD Assessment Test; mMRC

Implementation / Actions ( redefinition of taxonomy) Methodology (1): General Framework 1) From CASyM 1 (Lyon) – RT 3/9: The distribution and co-existence of chronic diseases is studied via

hypothesis-driven approaches based on existing disease ontologies, i.e. “classical phenotypes” (Coronary Heart Disease / HF, COPD, Diabetes).

COPD centered: COPD + related diseases via systems approaches Top down, ontology driven, classical diagnostic (eligibility) criteria Classical Phenotypes 2) From CASyM 1 (Lyon) – RT 3/9: Bottom up, via the modelling of novel “complex phenotypes” including co-

morbidities, risk factors, drug response and socio-economic determinants using hypothesis-free statistical models and data from patients.

Co-morbidity centered: applying SB/SM approaches to overlapping co-morbidities 1 & 2) Reshape (research ?) exercise to allow full deployment and (hopefully) validation of systems medicine

approaches. This includes, as well, addressing inequality and literacy (patients & operators) correlated with highly technological approaches. Health technology assessment further considered as a tool for accountability and sustainability matters.

Methodology (2): Recruitment From CASyM 1 (Lyon) – RT 3/9 New paradigms of recruitment of Systems Medicine based clinical trials and SMknowledge / understanding studies. 1) Existing Cohorts (SOPs? Data completeness and Quality?) discovery 2) New Cohorts (CT, Obs,…) specific interventions 1& 2) Investigation regarding the changing paradigms of recruitment (SM based) : - Patients / physicians - Industry / regulatory agencies Methodology (3): Data From CASyM 1 (Lyon) – RT 3/9 Which data ? What depth? standardization & harmonization – Exchange & Sharing Validation of standardisation / harmonisation strategies – Exchange & Sharing (Systems Medicine oriented) in the data handling.

Implementation / Actions ( recruitment & data)

Round table 2: What are the big questions in infection and how might Systems Medicine address them? Leader: François Gueyffier

Conflicts of interest F. Gueyffier ► From 2001 to 2011, head of the Clinical Investigation Center in

Lyon, France (about 100 clinical research contracts with pharmaceutical industry)

► Since 2009, shareholder of NovaDiscovery (http://www.novadiscovery.com/)

► PI of clinical trials using blood pressure lowering drugs, in a rare disease or in arterial hypertension

► Head of a team including the coordinator of CRESIM project ► Member of the steering committee of the French EcoFect LabEx

(http://ecofect.universite-lyon.fr/)

http://www.novadiscovery.com/

http://ecofect.universite-lyon.fr/

Objective of St Andrews Round Tables

► To specifically investigate examples of real medical problems and to determine what questions are tractable using Systems Medicine approaches

► Focus of our RT : “What are the big questions in infection and how might Systems Medicine address them? “

Application of Systems Medicine ► Where will be the biggest impact?

− Frequent and severe diseases − With unmet medical needs − Or with special research expectations

− Understanding mysteries in pathophysiology of immune system more or less related to infection (cancer, CV diseases, auto-immunity)

► What are the best applications? − Easy-to-use & efficient, with feasible implementation

► How can we fully exploit the potential?

► Prevention and early intervention − Eradication of infectious agent : out of scope of e:Med − Understanding the key factors for infectious diseases control, implementing

preventive efficient measures

Reasons to choose big questions topics ► High prevalence ► High lethality / disability rates ► Room for optimization of treatment ► Big research challenges ► Deciphering the potential of zoonoses, which

represent 60% of the emerging diseases at the world wide scale (Jones et al. 2008).

► Interactions with other diseases − Cancer − Cardiovascular diseases − Auto-immune diseases

6 diseases cause 90% of infectious deaths ► Infectious diseases are now the world's biggest killer

of children and young adults (half of premature deaths)

► More than 13 million deaths a year - one in two deaths in developing countries

6 diseases cause 90% of infectious deaths ► Pneumonia

− Kills more children than any other infectious disease − 10 to 40 000 deaths in an average influenza season in US

► Tuberculosis − Kills 1.5 million people per year, 1st in ado and adults − Nearly 1/3 of the world population has latent TB infection; causes 1/3 or

HIV related deaths. ► Diarrhoeal diseases (cholera, dysentery, typhoid, rotavirus, etc.)

− Two million lives a year among children under five ► Malaria

− Incidence of 275 million per year − Kills over one million people a year

► Measles − Most contagious disease, about 900 000 deaths a year

► HIV/AIDS − 33 million people living with HIV

Malaria ► Globally, an estimated 3.3 billion people were at risk of malaria in

2011, with populations living in sub-Saharan Africa having the highest risk of malaria infection. Approximately half of countries with ongoing malaria transmission are on track to meet the World Health Assembly target to achieve a 75% reduction in malaria case incidence rates by 2015, compared to levels in 2000.

► Number of malaria cases − 219 million estimated malaria cases in 2010 (range: 154–289 million).

► Number of malaria deaths − 660 000 estimated malaria deaths in 2010 (range: 490 000–836 000).

► Elimination − 10 of the 99 countries with ongoing malaria transmission are classified as being

in malaria elimination phase.

Tuberculosis ► One of the leading causes of death by infection

worldwide ► Efficient treatments but prolonged and multi-drugs ► Challenges :

− Shortening of the treatment − Defining the best drugs associations on bacterial multiplication and

resistance occurrence

AIDS ► … ► New expectations from patients to make the disease

more acceptable in daily life − Mastering virus transmission − Focus on prevention, adapted to individual behaviors − Pre-contamination Treatment

Septic shock ► 15 to 19 million cases of sepsis occur worldwide each

year. In the USA, about 750,000 cases of severe sepsis represent an estimated mortality of 200,000 per year.

► The annual cost of hospital care for patients with severe sepsis in the USA has been estimated at 16.7 billion dollars.

► Complex interplay between regulation systems, leading to explosive behaviors − Stimulated by pathogen and its derivatives as endotoxins − Hyper-response pro-inflammation, violent and visible − Vasodilation, ischemia and organ failure − Hyper response anti-inflammation, less visible but responsible of late

deaths, e.g. secondary hospital acquired infections

Various types of stakeholders ► Patients ► Clinicians ► Researchers ► Pharmaceutical and medical device industry ► Regulators ► Health care payers ► Research payers ► …

RT2: What are the big questions in infection and how might Systems Medicine address them?

IMPA

CT



Molecular microbiolog\ (genomics) >diagnose (genome) by MS signatures &species >diagnose by genome > species plus drug resistance (epidemiology built in for public health)

Sepsis&critical care phenotype

Antibiotic resistance

Better patients phenotyping >prior to disease >real time in market >changes plus ring alarm bells >post analysis to (analytics) to improve algorithms.

Nosokomial infections > susceptibility plus infestation

Clinical endpoints are unclear > how do we measure cure oin e.g. TB (relapse\reinfection being a problem)?

Patient data >electronic health records

Humanized animal models

How do we challenge current regimens? (model development raises questions)

New antibiotics > needs new bacterial focused compound libraries

Infection and chronic health

Pandemic outbreaks > early warning systems (e.g. WHO; when there is an outbreak, is the proper scientific structure established?) Computational systems

chemistry >Antibiotic discovery

Symbiosis \ Dysbiosis > what is health!

Envisaged priorities ► Tackling anti-infective resistance ► Pathogen agents

− Rapid and deep diagnosis / antibiotic resistance – molecular microbiology (genomics)

► Patients − Better patient phenotyping – Analytics / Bioinformatics − Early diagnosis – Infestation – susceptibility to infection – nosocomial infections (ST/MT) − Infection diagnostic / Sepsis phenotyping / real time patients health record − Identification of clinical endpoints – How do we measure cure / relapse − Infection chronic disease access

► Treatments − New antibiotics / computational systems / more bacteria-focused − Humanized animal models − How to challenge accepted therapeutic regimens

► Pandemic outbreaks – Alert systems ► Infection & chronic health : Immunity and inflammation – CV, Kc and

auto-immunity

Priority 1 : Tackling anti-infective resistance Actions

− Networking of databases, policies of databases exchanges across countries − Guidelines to support shared clinical data bases − Exploit high throughput molecular diagnostic, genomic type… − Integration of omics and clinical relevant data… Use of European clinical data

infrastructures − Data handling of huge amount of data; physically centralized data base (shared

need with other diseases domains; thousand genomes – infection…) − Gut microbes taxonomy − Complex interactions between microbiomal environment and the drugs safety

and efficacy − Innovative computational / data handling approaches − Visualization of data – rapid access to relevant results − Develop an infection control system − New drugs / molecular engineering / reverse engineering / small molecular

library

Priority 1 : Tackling anti-infective resistance

Expected results − Bedside rapid screening tool which could guide therapy within 24 hours… − New drug targets… less redundant therapy – appropriate redundancy − Use of the environment… ecological regimens (e.g. fecal transplants…) − Making diagnosis approach more closely related to the therapeutic

choices – − Theranostics – predictive biomarkers to stratify patients

RT2: What are the big questions in infection and how might Systems Medicine address them?



− Rapid\early gains (if successful can go far beyond actual status quo, has potential for great impact, diagnostic fingerprinting\epidemiology already established)

− Instant public understanding − Reduce inappropriate prescribing

Data challenge Lowering mortality

Health system inertia

Problem specification

Missing standards

Systems complexity (clinical system\clinical practice and complexity of whole biological systems)

Money (attractive for SMEs)

Priority 1 : Tackling anti-infective resistance

► Strengths − Rapid early gains − Public understanding − Worldwide global issue

► Weaknesses − Health system inertia − System complexity; requires systems biology / medicine approaches

► Opportunities − Patients engagements − Likely mortality gains, but also social organization gains − Vast market, opportunities for SMEs

► Threats − Data challenges − Problem specification − Missing standards − Validation issues

Priority 2 : Infection & chronic health : Immunity and inflammation – CV, Kc and auto-immunity

► Actions − Defining the patient phenotype − Problem specifications… − Inflammasome − Which models ?

− Understanding the expression level regulation of immune system… − Antibodies specification…

► Expected results

This priority issue was regarded as too complex. Chronic health cannot be explained without better patient phenotyping.

Clinical questions to be addressed

► Clinical trials (short term)- systems biology approaches could guide clinical trial design shortening times and costs

► Re-definition of clinical phenotypes based on molecular and dynamic parameters

► Discovery of effective biomarkers of multiple nature for disease progression (clinically useful: risk, prognosis, diagnosis); several biomarkers are often needed to make appropriate medical decisions.

► Combinatorial therapy for reducing toxicity (mid-term?); this approach would be useful to find out a combination and lower doses of effective drugs; in particular in the case of co-morbidity, in the frequent cases where more than one disease is affecting the patient

► Improvement of drug development, optimized drug efficacy and delivery, drug safety (via the of study drug-metabolizing enzymes pathways), timing and dosage of therapy

► It is important also to address the healthy individual (long term?)

FP7 RECOIN project : Studying the Mechanisms of Enhanced Pathogenesis in Polymicrobial Respiratory Co-Infection Objective: Illness caused by respiratory infection with Influenza viruses represents a vast healthcare and economic burden in the modern world. It is well established that respiratory viral infections are often complicated by secondary bacterial infections, however co-infection often causes a much more severe disease than either microorganism would individually. The mechanisms behind this synergy are not fully understood, however adhesion; the first step in bacterial colonisation, has been shown to be enhanced in virus-infected cells. We hypothesise that early events following Influenza infection of lung epithelium promote bacterial adhesion by regulating primary receptor trafficking and may offer new targets for anti-bacterial intervention. The aims of this project are to dynamically characterise the adhesion of individual bacteria to airway epithelial cells with high-temporal and spatial resolution and to study the effects of Influenza A co-infection on this phenomenon. We will develop new protocols to track bacteria in three dimensions in order to study individual adhesion events and will calculate diffusion modes during and after bacterial contact with the host cells. These studies will provide novel insights into the processes underlying bacterial adhesion and will explore the mechanism of viral-bacterial synergy to discover new targets for the prevention and treatment of serious respiratory infections.

FP7 INTRICATE project : Infectious triggers of chronic autoimmunity

Objective: This proposal builds on existing expertise and collaborations of a multidisciplinary Consortium of basic scientists and clinical investigators each of whom has made a substantial individual contribution to understanding the links between infection and autoimmunity. The aim of the INTRICATE Consortium is to prosecute a programme of Translational Research that deliniates the role of infection in the induction and perpetuation of severe systemic autoimmune disease with the ultimate object of identifying new therapeutic strategies based on knowledge of pathogenesis. Our strategy will systematically analyse the complex and diverse processes involved in a ?model? human disease: - Anti-neutrophil cytoplasmic antibody (ANCA) associated systemic vasculitis (AASV). AASV is ideally suited because it is known to be caused by autoantibodies of defined specificity and second because it is strongly linked to infection to infection. INTRICATE will use mouse models to answer the specific question whether infection with clinically relevant bacteria induces autoimmune disease in transgenic mice that express the human autoantigen. The use of novel high-throughput antigen array technology in well-characterized patient cohorts and analysis of microbial and host specific mechanisms combined with genome wide association study (GWAS) will determine whether dysbiosis or infection with specific microorganisms triggers the induction or re-activation of AASV. Unraveling the pathogenic processes that are responsible for this chronic autoimmune disease and the knowledge gained will lead to the development of novel preventive and therapeutic strategies.

Round table 3: What are the big questions in public health (obesity and exercise) and how might Systems Medicine address them? Leader: Natal van Riel

State of the art ► Public health is population based, not individualized ► Increase of public awareness in many areas, but

limited impact ► Lacking in primary prevention, focus on secondary

and tertiary prevention ► A deficit perspective ► Reductionist approach

physical activity, diet, smoking, alcohol, drugs, sexual health, violence and injury, mental health, air pollution (outdoor and indoor)

Apply a systems approach in public health

RT3: What are the big questions in public health (obesity and exercise) and how might Systems Medicine address them?

Primary prevention: the goal is to protect healthy people from developing a disease Secondary prevention: goal is to halt or slow the progress of disease in its earliest stages Tertiary prevention: goals include preventing further physical deterioration and maximizing quality of life

Priority issues Participatory Prevention in Public Health 1. Prevention

► Focus on primary prevention ► Target all levels in policy ‘rainbow’ (from individual to

socio-economic, cultural and environmental context) ► Education and health literacy

2. Citizen participation ► Empowerment of patient and public

3. Systems oriented methods ► Longitudinal data, modelling ► How to measure effectiveness?, Health Technology Assessment

4. Assets perspective ► Healthy ageing, health equality ► Integrative approach of health factors and comorbidities

5. Context ► Political will ► Ethical questions


IMPA

CT

LOW

M

IDD

LE


HIG

H


validation of the approach

RT3: What are the big questions in non-cancer lung disease (particularly chronic obstructive lung disease) and how might Systems Medicine address them?

Conceptualization of a systems approach in -Public Health -in primary prevention

Participatory actions to identify pilot projects

Pilot project Community level

Participatory model at community level

Building assets Change paradigm from reductionist to asset benefits

Health Change Behaviour change

Tools methodology

Systems medicine Personalized approach to public health in a cohort model


PRIORITY ISSUES

ACTIONS

EXPECTED RESULTS

► Participatory Prevention in Public Health ► Targeting all levels in policy rainbow and primary, secondary and tertiary prevention

► Develop collaborations and obtain funding to conceptualize a systems approach for

PH, and new methods and tools ► Pilot project ► Implementation of policy in different countries and EU

► A framework for Systems Medicine based PH ► Change paradigm for PH ► Socio-economic and health benefits for society and individual citizen

RT3: What are the big questions in non-cancer lung disease (particularly chronic obstructive lung disease) and how might Systems Medicine address them?



Participatory Comprehensive – not reductionist Based on established theory Multidisciplinary Benefit for the individual

Low fit with systems biology Ethical issues unclear

Novelty Socio-economic impact Change in public health practice Health impact Horizon 2020

Complexity of public health issues Data availability Costs Lack of engagement of stakeholders

Round table 4: What are the big questions in drug development and how might Systems Medicine address them? Leader: Alex McDonald

Paul et al

Phase II/III Attrition Key to R&D Productivity

However: Phase II/III attrition appears to be increasing • novel targets • new diseases/populations • higher safety hurdles • risk/benefit • cost effectiveness

Inflammation

Kidney Lung

Coagulation

Heart and Circulation

Developmental Treatments

INPUTS Individual Patient

Characteristics:

Vital signs

Comorbidities

Genetics

A“Virtual Clinician” applies interventions (fluids, etc.)

Lymphatics

Immunetrics builds models that make quantitative, clinically applicable predictions.

OUTPUTS Mortality

Treatment effect

Organ function time courses

Biomarker time courses

State of the Art in Sepsis and Critical Care

IMPA

CT

LOW

M

IDD

LE


HIG

H


RT4: What are the big questions in Drug Development and how might Systems Medicine address them?

Dose, regimen and timing Population (stratification, prognosis and prediction)

RT4: What are the big questions in drug development and how might Systems Medicine address them?

PRIORITY ISSUES

ACTIONS

EXPECTED RESULTS

Population (stratification, prognosis and prediction)

Dose, regimen and timing

Action 2: Develop exemplar systems dynamic models that are both descriptive and predictive, models that are open to new inputs, able to encompass experimental and clinical heterogeneity, using data from other/different sources.

Results 1: Summary of systematic review

Action 1: Systematic Review of systems dynamic models in above areas

Results 2: One or more exemplar models to showcase the systems medicine approach

Action: Disease prioritisation – respiratory and oncology

RT4: What are the big questions in drug development and how might Systems Medicine address them?



The SWOT analysis will be presented in the follwing meeting report.

st andrews, may 2013 · 2019-04-09 · clinical laboratory genomics & transcriptomics cell...

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