Call Girls Varanasi Just Call 9907093804 Top Class Call Girl Service Available
Â
Lecture fjms ballarat 2012
1. Health and Biomedical informatics:
information processing for
preventative Medicine
Colloquia Series at University of Ballarat
June 13, 2012
Fernando J. Martin-Sanchez
Professor and Chair of Health Informatics
Melbourne Medical School
Faculty of Medicine, Dentistry & Health Sciences
&
Adjunct Professor, School of Engineering
Director, IBES Health and Biomedical Informatics Research Lab.
2. Outline
â˘âŻ Current challenges in Medicine
â˘âŻ The Vision: HebyEq
â˘âŻ Opportunities from Health Informatics and
Technology
â˘âŻ Personalised Medicine
â˘âŻ Participatory Health
â˘âŻ Self-omics
â˘âŻ The central role of Informatics
â˘âŻ HBIR @ UoM
4. Main problems
â˘âŻ Demographic change â Aging
population.
â˘âŻ Increasing number of patients with
chronic diseases
â˘âŻ Unhealthy life habits (sedentary,
fast food, alcohol, tobacco)
â˘âŻ Rapidly increasing cost of medical
technology
â˘âŻ Climate change â rise of infectious
disease
â˘âŻ Workforce shortage
Ă ď Unsustainability of the US National Center for Disease Control
Healthcare system?
5. Current challenges in Medicine
â˘âŻ Need of earlier diagnosis
â˘âŻ More personalized therapies Personalised
â˘âŻ Clinical trials and the development of new medicine
drugs need to be faster and more effective
â˘âŻ Improve disease classification systems Preventative
â˘âŻ Risk profiling, disease prediction and medicine
prevention
â˘âŻ Control health system costs
Participatory
â˘âŻ Citizens should take more responsibility for medicine
the maintenance of their own health.
Ă ď Emphasis on prevention, not cure
6. The Vision:
Health
by
equation
verse in which Prospero calls Caliban:
A devil, a born devil, on whose nature
Nurture can never stick; on whom my pains,
Humanely taken, all, all lost, quite lost;
William Shakespeare, The Tempest, 1610
7. G*E=P
â˘âŻ Disease phenotypes arise from complex
interactions among individual genetic
information and environment (way of life,
risk factors, external agents)
8. Activation factors
Way of life
Environmental Environmental
exposure risk
Mutagen agents Disease risk Disease
Mutations and Genetic
Inheritance polymorphisms risk
9. Visions of the future for the field of BMI
â˘âŻ Integrated environments for assessing and
modeling the relative contribution of factors
(genetic, environmental, phenotypic) that
confer an individual a relative risk of
developing a disease
â˘âŻ Models coupled to information systems to
contextualize the patient molecular
information and clinical decision making
support systems at the Point of Care for
personalized care
10. â˘âŻ Prevention is better than a cure; how to
prevent is the question.
â˘âŻ What if it was possible to calculate
accurately a person s medical strengths
and weaknesses as a combination of
genetic and environmental factors?
â˘âŻ This will illustrate how informatics and
technology will play a major role in a
new wave of preventative medicine, by
estimating risk factors as a personalised
profile and supporting personalized
clinical decision making.
11. Health by Equation - Rationale
â˘âŻ Research and Technology development in genetic
analysis, informatics, clinical devices
â˘âŻ New data and knowledge:
ĂźďźâŻAvailability of genomic personal information â
Characterising individual genetic variation â Human
Genome
ĂźďźâŻCharacterising human phenotypes, including disease â
Human Phenome
ĂźďźâŻKnowledge about action mechanisms of environmental
factors (toxic agents, drugs, food, âŚ) â Envirome or
Exposome
12. Background
â˘âŻ Well-being is not only the absence of disease. It is also related with
the risk of future problems.
â˘âŻ Future emphasis on understanding health protecting factors
(Healthome) instead of only causes of disease (Diseasome).
13. The Equation
Health
Profile
â˘âŻ The different genetic and environmental factors, will be weighted in terms of their contribution to
health maintenance or loss.
â˘âŻ The ratio between positive and negative factors yields a Health Profile that could be informative
of the current health status of an individual and even predictive of future health problems.
15. HeByEq
â˘âŻ Health by Equation is an informatics system
for the prevention of diseases and the
maintenance of health.
â˘âŻ It can be readily accessed and used by
professionals around the world.
â˘âŻ By using its tables, decision matrices and
protocols, doctors can evaluate genetic,
clinical, and environmental data for a patient.
â˘âŻ They can then offer the patient
recommendations for treatment and disease
prevention.
â˘âŻ These recommendations are comprehensive,
individualised and safe, and are based on the
patient s health status and risk profile.
16.
17. Opportunities
from
Health
Informatics
and
technology
18. The Digitalization of Medicine
â˘âŻ Digital
 revolu-on
 in
 other
 domains
 (banking,
 insurance,
Â
leisure,
 government,âŚ)
Â
â˘âŻ The
 incorpora-on
 of
 digital
 systems
 in
 healthcare
 is
 lagging
Â
behind
 other
 sectors:
Â
â⯠Reasons:
 complexity,
 privacy,
 volume
 of
 data,
 lack
 of
 demand
Â
â⯠It
 has
 greatly
 aďŹected
 healthcare
 at
 the
 hospital
 or
 research
Â
centre
 level.
Â
Â
â⯠The
 digital
 revolu-on
 has
 not
 yet
 reached
 medicine,
 at
 the
Â
pa-ent/ci-zen
 level
Â
Â
â˘âŻBUT
 THIS
 IS
 STARTING
 TO
 HAPPEN
 NOW
 !!!
Â
19. Enabling science and technology
â˘âŻ Broadband
 technologies
 and
 networks
Â
â˘âŻ High
 performance
 compu-ng
 (and
 A.I.
 systems)
Â
â˘âŻ Ubiquity
 of
 smartphones,
 tablets,
 and
 apps
Â
â˘âŻ Sensors,
 imaging
 and
 wearables
Â
â˘âŻ Personal
 genome
 sequencing,
 gene-c
 tes-ng
 and
Â
epigene-cs
Â
â˘âŻ Metagenomics
 and
 the
 Human
 Microbiome
 Project
â˘âŻ Social
 networks,
 games
 and
 the
 Quan-ďŹed
 Self
Â
â˘âŻ Knowledge
 on
 gene-c
 diseases
 and
Â
 gene-c
Â
varia-on
Â
â˘âŻ Systems
 biology
 modelling
Â
20. Measuring the genome
â˘âŻ Human Genome Project
Maps of genetic
variation (Human
Variome)
DNA Sequencer â
designed to sequence
the entire human
genome in a day for
$1,000 Benchtop
 Ion
 Protonâ˘
Â
25. High-Ââcapacity
 Broadband
 technologies
 and
 networks
Â
â˘âŻ The
 availability
 of
 ultra-Ââhigh-Ââspeed,
Â
high-Ââcapacity,
 ubiquitous,
 âalways-Ââonâ
Â
broadband
 connec-vity
 will
 contribute
Â
to
 the
 development
 of
 an
 integrated
Â
digital
 infrastructure
 for
 medicine,
Â
reaching
 the
 ci-zen,
 that
 will
 make
Â
feasible
 the
 concepts
 of
 personalized
Â
medicine
 and
 par-cipatory
 health.
Â
27. Definition
â˘âŻ Personalized medicine uses an
individual's genetic (and molecular)
profile and individual information
about environmental exposures to
guide decisions made in regard to
(risk profiling) and the prevention,
diagnosis, and treatment of
disease.
(Adapted from F. Collins, Director NIH)
28. Clinical applications of genomic information
â˘âŻPharmacogenetics â
Personalized Medicine
Coalition - 72 drugs in 2011
â˘âŻCystic fibrosis â successful
clinical trial for a specific
mutation
â˘âŻIdentification of metabolic
diseases
31. Participatory Health
â˘âŻ
â˘âŻ From Web 1.0 â Use of internet to find health information to Web 2.0 â web-
based communities and services. NHS Social Care Model (NHS)
â˘âŻ A survey of 1,060 U.S. adults by the PwC Health Research Institute found
that a third of respondents are gravitating toward social media as a place for
discussions of health care.
â˘âŻ Pew Internet study â 27% of US internet users had tracked health data online
â˘âŻ Care management, disease management, supported self-care, promoting
better health Ă ď Patients empowered, informed and involved in decision
making, prevention and learning
33. Social media & PCEHR
â˘âŻ Quality = patients reviewing their own records - Shared
Medical Records
â˘âŻ MyHealth@Vanderbilt â information on prescriptions is
shared. Knowledge management team â consumers will have
convenient e-access to their medical records and genetic
profiles to social media & games
â˘âŻ Facebook
â˘âŻLifeline â support line for suicide
â˘âŻOrgan donor status
â˘âŻBlood type â app will contact the user
34. Social
 media
 as
 a
 research
 tool
Â
â˘âŻ We
 are
 witnessing
 a
 transi-on
 from
 research
 informa-on
 systems
 centralized
Â
at
 hospitals
 and
 clinical
 research
 centres
 to
 distributed
 systems
 that
 reach
 out
Â
to
 the
 residence
 of
 any
 ci-zen
 /
 pa-ent
 who
 opts
 in.
Â
Â
â˘âŻ Clinical
 Research
 with
 the
 pa-ents,
 not
 on
 the
 pa-ents
Â
â˘âŻ Examples
Â
â⯠23andMe
 â
 Parkinsonâs
 Disease
 â
 PLoS
 Gene-cs,
 2
 new
 gene-c
Â
associa-ons
Â
â⯠Pa-entsLikeMe
 â
 Nature
 Biotech.
 Self-Ââreported
 data
 from
 600
 pa-ents
Â
on
 the
 use
 of
 lithium
 for
 Amyotrophic
 Lateral
 Sclerosis
 (ALS)
Â
35. Crowdsourced clinical trials
â˘âŻ DIY science, Crowdsourced Health Research Studies, Citizen
science, Amateur Scientist, Self-Experimentation
â˘âŻ Patients Like Me â 125.000 members. 1000 condition-based
communities â25 Papers published in PNAS, Nat Biotech, JMIR, âŚ
â˘âŻ 23andme â 23 and we â
â˘âŻ Acor, RevolutionHealth, Curetogether, Genomera, Althea Health
self tracking devices
Social web
games
Participatory Health
mobile Internet of things
sensors PCEHR
36. NBN and patient empowerment
Current NBN-enabled Driving forces: patient empowerment,
networks personalized medicine, social networks
EHR Personally Citizens are able to maintain and control
Controlled EHR their own health information
Gene-disease Personal Citizens ask for genetic analysis of their
association genomics DNA through the Internet and receive
studies reports on various aspects of their health
Clinical trials Crowdsourced The patient voluntarily shares information
clinical trials on treatments and evolution of his/her
illness with other patients
37. Social media strategy
â˘âŻ âThe democratization of information through social media is shaping
clinical encounters and the patient-provider relationship (Wen-ying
Sylvia Chou, NCI)
â˘âŻ Many health care organizations are reshaping their social media strategy
from marketing to engage patients, interact with them and even provide
services at lower cost.
â˘âŻ âParticipatory Health Research is helping to expand the conceptual
scope of medicine from the traditional focus on disease cure to the
personalised preventative medicine of the futureâ (Melanie Swan)
â˘âŻ Be careful! â terms for use of social media.
39. â˘âŻ Self tracking / self quantifying / self monitoring
â˘âŻ The belief that gathering and analysing data can help them
improve their lives!
â˘âŻ QSâers doubling every year.â 5524 members, 42 meetup groups
â˘âŻ Larry Smarrâ 10years quantifying his body
â⯠Weight â physical activity: calories burnt (body media) â
Food intake â Sleep (Zeo) â blood chemicals (60 Markers) â
cholesterol/triglycerides / Apo B / Ί â 6, Ί â 3/ C-reactive
protein - Ultrasound â (plaque in arteries) â stool test â
colonoscopy â DNA â Microbiome
â˘âŻ Fitbit â Sleep â Movement
â˘âŻ +9000 health apps, each person connected to 140 devices, 9
billion of connected devices now, 24 billion by 2020
â˘âŻ NODE Sensor Environment
40. Self-genomics - Clinical annotation of
individual genomes
â˘âŻ Prof. Quake - Stanford - - Nature
genetics paper - $50.000, 1 week,
Helicos. Stanford team -
â˘âŻ Clinical annotation of genome from
âpatient Zeroâ
â⯠Drug metabolism
â⯠Rare genetic variants - rare diseases
â⯠Common genetic variants - Risk of
complex diseases
Ashley et al. The Lancet, Volume 375, Issue 9725, Pages 1525 - 1535, 1 May 2010
41. First personal longitudinal OMICS profiling exercise
â˘âŻ Combined analysis of genomic, transcriptomic, proteomic,
metabolomic and immunological profiles from a single
individual (one of the authors- Prof. Michael Snyder), over a
14 month period. More than 3 billion measurements.
â˘âŻ He contracted two mild viral infections in the data-gathering
period, which left their molecular signature in the analyses.
â˘âŻ During one of these infections, his blood glucose levels began
to approach those of a diabetes sufferer. After changing his
diet and exercise habits, glucose level returned to normal.
â˘âŻ This study shows that diseases are a product of an
individualâs genetic profile as well as interaction with the
environment and that disease can be treated based on
molecular information.
(Chen et al, Cell 148, 1293-1307 March 16 2012 )
42. Personal Quantified Smartphones
Sensors
omics Self & apps
Selfomics
(Personal molecular profiles, life
habits, physiological measures,
environmental exposure)
Social media &
networks
Big data (Cloud)
Personalized Preventative Participatory
Medicine Medicine Health
44. Health and Biomedical Informatics
â˘âŻ Informatics is the science of information
â˘âŻ Information is data plus meaning
â˘âŻ Biomedical informatics is the science of
information in the context of biomedicine.
â˘âŻ Informaticians study information (data + meaning).
â˘âŻ Thus, HBI practitioners must understand the
context or domain (biomedicine).
â˘âŻ Health Informatics â use of information, often aided
by technology, to improve individual health,
healthcare, public health and biomedical research
4
47. âA man in his late
80s with congestive
heart failure, failing
kidneys, weight and
appetite loss,
declining cognitive
ability and the need
for extensive
assistance has a 69
percent chance of
Hierarchical Association dying within six
Rule Model monthsâ.
48. Role of informatics - New taxonomy of diseases
Stratification of disease â ICD 11 â US Nat Academy â Towards Precision Medicine
New taxonomy based on human molecular biology
skin, colon, parathyroid â BRAF Mutation
MD Anderson CC â Breast, Ovarian, Uterine, Cervical â PIK3CA Mutation trial
50. Role of informatics - Measuring the exposome
Environment-Wide
Association Study
on Type 2
Diabetes Mellitus
266 environmental
Factors
Future: combined
GWAS-EWAS?
(Patel et al. 2010 PloS One)
53. Conclusions
â˘âŻ The routine application of personalised medicine is still a long
way ahead, however we have now all the ingredients to
make it happen.
â˘âŻ The convergence of medicine and the digital revolution will
produce an information ecosystem that will facilitate the
advent of safer and more efficient preventive, diagnostic and
therapeutic solutions.
â˘âŻ The citizen will have access to her genetic profile and clinical
record, and will monitor and adjust her health using next
generation sensors and social networks to share this
information with peers, clinicians and researchers.
â˘âŻ But
 all
 of
 this
 will
 only
 be
 possible
 if
 we
 realise
 that
 it
 is
 9me
 for
 us
Â
to
 take
 responsibility
 for
 our
 own
 health.
Â
Â
54. Thank you for your attention!
Š Copyright The University of Melbourne 2011