hisa 29 feb 2012 - bioinformatics

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Presentation given by Prof Fernando J Martin-Sanchez at the HISA (Health Informatics Society Australia) event "A Leap into E-Health" - see http://www.hisa.org.au/events/event_details.asp?id=211738 for further details - on 29th February 2012.

TRANSCRIPT

“(Health) (Clinical) (Medical) (Translational),…

Bioinformatics”

HISA Victoria – A leap into eHealth 29 Feb 2012

Fernando J. Martin-Sanchez

Professor and Chair of Health Informatics Melbourne Medical School

& Director, Health and Biomedical Informatics Research (HBIR) Unit

Faculty of Medicine, Dentistry & Health Sciences

Objectives

•  Terminology (What is xBioinformatics?) •  Importance (Why should we care?) •  Role of Informatics in Personalised medicine (How?)

Terminology and

Definitions (What?)

What is “Health and Biomedical Informatics”

Different “flavours” of Health Informatics

•  Medical informatics •  Nursing informatics •  Pharma informatics •  Dental informatics •  Pathology informatics •  ...

•  Cancer informatics •  Cardio informatics •  Neuro informatics •  Pain informatics •  …

•  Public health informatics •  Clinical informatics •  Research informatics •  Consumer informatics •  ...

•  e-health •  m-health •  i-health •  u-health • …

User

Specialty

Tech

Profession

AMIA endorsed framework – Based on T. Shortliffe’s idea

Different scope, different methods

Biomedical Informatics: Biomedical Information processing 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.

Multilevel modeling, ontologies, data integration, data mining, …

Importance (Why?)

Current challenges in Medicine

• Need  of  earlier  diagnosis      • More  personalized  therapies  • Risk  profiling,  disease  predic8on  and  preven8on      

•  Improve  disease  classifica8on  systems      • Control  health  system  costs    • Clinical  trials  and  the  development  of  new  drugs  need  to  be  more  agile  and  effec8ve.  

• Ci8zens  could  take  more  responsibility  for  the  maintenance  of  their  own  health.  

Why personalised medicine?

•  To develop 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

•  DNA  Sequencer  –  designed  to  sequence  the  en4re  human  genome  in  a  day  for  $1,000  

Advances in genomic technology

Benchtop  Ion  Proton™  

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Clinical applications of genomic information

• Pharmacogenetics - PMC • Molecular autopsy • Fetal DNA sequencing to preempt amniocentesis

• Cystic fibrosis – successful clinical trial for a specific mutation

• Identification of metabolic diseases

Role of Informatics in personalised

medicine (How?)

Genomic sensors Environmental sensors

Phenomic sensors

Biomarkers (DNA sequence, proteins, gene expression, epigenetics

Environmental risk factors (pollution, radiation, toxic agents, …)

Physiological, biochemical parameters (cholesterol, temperature, glucose, heart rate…)

Integrated personal health record

Patient data collection

Adapted from: Stead et al. 2011, Acad. Med.

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The role of Biomedical Informatics to facilitate Genomic Medicine

•  Data acquisition at the point of care, including the use of new nanodevices for diagnosis and ultra DNA sequencing

•  Data integration (putting into context molecular information from the patient with existing biomedical knowledge on the web and integrating it with the health record)

•  Supporting decision making through new clinical guidelines, alerting systems which take into account the results of genetic testing and pharmacogenetics approaches

•  Education of patients and health professionals in genomics and informatics

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AMIA definition

• Translational Bioinformatics is the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data, and genomic data, into proactive, predictive, preventive, and participatory health.

© Copyright The University of Melbourne 2011

Thank you for your attention!

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