ICT for a Global

Infrastructure for Health

Research

Dr. Fernando Martin-Sanchez

Director, Medical NanoBioInformatics Dept.

Institute of Health “Carlos III”

Madrid, Spain

Objectives of the session

• Background

- Biomedical research is an information intensive activity

- There exist new avenues in biomedical research

- New data types (extremely complex and heterogeneous)are being

generated at an unprecedented pace

• Main issues

- How can we collect, store, integrate and process this information -

high throughput - distributed computing?

- How can we use research data to model and simulate human

physiology and pathology?

- How can we promote the use of the EHR for research?

Participants

Dr. Fernando Martin-Sanchez.

Instituto de Salud Carlos III.

Prof. Vicente Hernandez Universitat

Politécnica de Valencia

Prof. Alex Frangi, University Pompeu

Fabra, Barcelona

Dr. Octavian Purcarea, Chief

Research and Strategy Officer.

Microsoft

Background

• New trends in medicine

• Data collection

- The “Nanoscope”

- High-throughput sequencing

- High-throughput phenotyping

• Data integration

• Data analysis and decision support

Genomic medicine

Why personalised medicine?

• To develope individualized

treatment regimes to avoid failures,

inefficiency and adverse reactions

related to drug therapy

• To facilitate early diagnosis and

advance in risk profiling, disease

prediction and prevention

• To improve disease classification

systems

• Growing health system costs

Why now?

• Advances in Information

Technologies

• Results from the Human Genome

Project and the Human Genetic

Variation Map (Hapmap)

• Laboratory technologies for

personal genome sequencing

• Growing knowledge about

molecular causes of disease

EC support to personalised

medicine (2001-)

New trends in medicine

• Genomic (molecular, personalised) medicine

• Regenerative medicine/tissue engineering

seeks to develop functional cell, tissue, and

organ substitutes to repair, replace or enhance

biological function that has been lost due to

congenital abnormalities, injury, disease, or

aging (NIH Definition, NIBIB, June 2004)

• NanoMedicine – Use of nanoscale tools and

components for the diagnosis, prevention and

treatment of diseases and for understanding

their pathophysiology (European Science

Foundation, Nov. 2005)

Why nano and regenerative

medicine?

• Cellular function takes place at the Nano

level: molecular nano-machines

• There are several nano-objects that can

produce disease (LDL, viruses, pollutans)

• The cause of the disease can be “nano”

but treatment is now “micro” or “macro”

• Advances in tissue engineering, cell and

gene therapy

ActionGrid - EC project

• ACTION-Grid is an international cooperative

support action on

- Medical Informatics

- Bioinformatics

- Grid Computing

- Nanoinformatics

• from Jun 08 to Jun 10

• Coordination. Prof. Victor Maojo - UPM

Data collection

F. Martin-Sanchez. “New Technologies and Applications Towards

Genomic Medicine”. En XIX Image Analysis Course of the Univ. La

Laguna, Personalized virtual medicine (p-Health) 6th-19th March 2006.

CATAI: 2006, 68-73 pp.

Data collection: The “Nanoscope”

i.e.:

DNA

ultrasequencers

i.e.:

Transdermal

glucose monitoring

i.e.:

Nanosensors for

Radiation, contamination,

Toxicity)Martín-Sanchez et al. “A primer in knowledge management for

Nanoinformatics in Medicine”. IOS-Press Proceedings 12th

International Conference on Knowledge-Based Intelligent

Information & Engineering Systems KES2008.

Information processing in

Nanomedicine - Nanoinformaticshttp://www.nanotech.neu.edu/medicine/

Maojo, Martín-Sanchez et al. “”Nanoinformatics and DNA computing:

catalizing nanomedicine”. (2010) Pediatric Research. Special issue on

Nanomedicine.

15 September 2005

Volume 437 Number

7057 pp376-380

High-throughput sequencing

Fred Sanger

Human genomes sequenced

up to now

• James Watson, 454. $70 mill

• Craig Venter, Sanger, - $1 mill.

• African - HapMap – Illumina & Solid, $100.000

• Five african – Penn State Univ.

• Chinese, Illumina

• Two koreans

• Prof. Quake - Stanford - - Nature genetics paper -

$50.000, 1 week, Helicos SMS . Stanford team -

Clinical annotation of genome from “patient Zero”

• Drug metabolism

• Rare genetic variants - rare diseases

• Common genetic variants - Risk of complex

diseases

High throughput phenotyping

• Disease specific algorithms scanning across

electronic medical records - generate structured

,standardized, anonymized, clinical data sets

for research

• Important issues:

• NLP on administrative, laboratory and medical data

• Reproducibility and standardisation

• Privacy and confidenciality

Data integration

• Ontologies

• NCBO Bioportal

• 168 ontologies: from

Nanomedicine to

public health

• Browser, mappings,

visualization features

• Useful for annotation

of data resources

Data analysis: GWAS (Genome

Wide Association Studies)

• >500.000 SNPs, >2000

individuals

• Connecting molecular data

with clinical phenotypes

through system biology

approaches:

- genetic networks

- pathway analysis

- interaction maps

• Analysis methods

- Bayesian networks,Markov

graphs, Petri nets...

The central role of EHR

From data collection to medical

decision making

Final remark: from particle to

population

Altman RB, Balling R, Brinkley JF, Coiera E, Consorti F, Dhansay MA, Geissbuhler A, Hersh W,

Kwankam SY, Lorenzi NM, Martin-Sanchez F, Mihalas GI, Shahar Y, Takabayashi K,

Wiederhold G. "Commentaries on Informatics and medicine: from molecules to populations".

Methods Inf Med. 2008;47(4):296-317. PMID: 18690363