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 EngineeringDirector, IBES Health and Biomedical Informatics Research Lab.
Outline• Current challenges in Medicine• The Vision: HebyEq• Opportunities from Health Informatics and Technology• Personalised Medicine• Participatory Health• Self-omics• The central role of Informatics• HBIR @ UoM
Main problems• Demographic change – Aging population.• Increasing number of patients with chronic diseases• Unhealthy life habits (sedentary, fast food, alcohol, tobacco)• Rapidly increasing cost of medical technology• Climate change – rise of infectious disease• Workforce shortage àUnsustainability of the US National Center for Disease Control Healthcare system?
Current challenges in Medicine• Need of earlier diagnosis• More personalized therapies Personalised• Clinical trials and the development of new medicine drugs need to be faster and more effective• Improve disease classification systems Preventative• Risk profiling, disease prediction and medicine prevention• Control health system costs Participatory• Citizens should take more responsibility for medicine the maintenance of their own health.àEmphasis on prevention, not cure
The Vision: Health by equation verse in which Prospero calls Caliban: A devil, a born devil, on whose natureNurture can never stick; on whom my pains, Humanely taken, all, all lost, quite lost; William Shakespeare, The Tempest, 1610
G*E=P• Disease phenotypes arise from complex interactions among individual genetic information and environment (way of life, risk factors, external agents)
Activation factors Way of life Environmental Environmental exposure risk Mutagen agents Disease risk Disease Mutations and GeneticInheritance polymorphisms risk
Visions of the future for the field of BMI• 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• 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
• Prevention is better than a cure; how to prevent is the question.• What if it was possible to calculate accurately a person s medical strengths and weaknesses as a combination of genetic and environmental factors?• 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.
Health by Equation - Rationale• Research and Technology development in genetic analysis, informatics, clinical devices• New data and knowledge: ü Availability of genomic personal information – Characterising individual genetic variation – Human Genome ü Characterising human phenotypes, including disease – Human Phenome ü Knowledge about action mechanisms of environmental factors (toxic agents, drugs, food, …) – Envirome or Exposome
Background• Well-being is not only the absence of disease. It is also related with the risk of future problems.• Future emphasis on understanding health protecting factors (Healthome) instead of only causes of disease (Diseasome).
The Equation Health Profile• The different genetic and environmental factors, will be weighted in terms of their contribution to health maintenance or loss.• 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.
Life-long (longitudinal) records Health = Profile f( Healthome Diseasome )HealthProfile
HeByEq• Health by Equation is an informatics system for the prevention of diseases and the maintenance of health.• It can be readily accessed and used by professionals around the world.• By using its tables, decision matrices and protocols, doctors can evaluate genetic, clinical, and environmental data for a patient.• They can then offer the patient recommendations for treatment and disease prevention.• These recommendations are comprehensive, individualised and safe, and are based on the patient s health status and risk profile.
Opportunities from Health Informatics and technology
The Digitalization of Medicine• Digital revolu-on in other domains (banking, insurance, leisure, government,…) • The incorpora-on of digital systems in healthcare is lagging behind other sectors: – Reasons: complexity, privacy, volume of data, lack of demand – It has greatly aﬀected healthcare at the hospital or research centre level. – The digital revolu-on has not yet reached medicine, at the pa-ent/ci-zen level • BUT THIS IS STARTING TO HAPPEN NOW !!!
Enabling science and technology• Broadband technologies and networks • High performance compu-ng (and A.I. systems) • Ubiquity of smartphones, tablets, and apps • Sensors, imaging and wearables • Personal genome sequencing, gene-c tes-ng and epigene-cs • Metagenomics and the Human Microbiome Project• Social networks, games and the Quan-ﬁed Self • Knowledge on gene-c diseases and gene-c varia-on • Systems biology modelling
Measuring the genome• Human Genome Project Maps of genetic variation (Human Variome) DNA Sequencer – designed to sequence the entire human genome in a day for $1,000 Benchtop Ion Proton™
High-‐capacity Broadband technologies and networks • The availability of ultra-‐high-‐speed, high-‐capacity, ubiquitous, ‘always-‐on’ broadband connec-vity will contribute to the development of an integrated digital infrastructure for medicine, reaching the ci-zen, that will make feasible the concepts of personalized medicine and par-cipatory health.
Definition• Personalized medicine uses an individuals 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)
Clinical applications of genomic information• Pharmacogenetics – Personalized Medicine Coalition - 72 drugs in 2011• Cystic fibrosis – successful clinical trial for a specific mutation• Identification of metabolic diseases
Participatory Health• • From Web 1.0 – Use of internet to find health information to Web 2.0 – web- based communities and services. NHS Social Care Model (NHS)• 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.• Pew Internet study – 27% of US internet users had tracked health data online• Care management, disease management, supported self-care, promoting better health à Patients empowered, informed and involved in decision making, prevention and learning
Social media & PCEHR• Quality = patients reviewing their own records - Shared Medical Records• MyHealth@Vanderbilt – information on prescriptions is shared. Knowledge management team – consumers will have convenient e-access to their medical records and genetic profiles to social media & games• Facebook • Lifeline – support line for suicide • Organ donor status • Blood type – app will contact the user
Social media as a research tool • We are witnessing a transi-on from research informa-on systems centralized at hospitals and clinical research centres to distributed systems that reach out to the residence of any ci-zen / pa-ent who opts in. • Clinical Research with the pa-ents, not on the pa-ents • Examples – 23andMe – Parkinson’s Disease – PLoS Gene-cs, 2 new gene-c associa-ons – Pa-entsLikeMe – Nature Biotech. Self-‐reported data from 600 pa-ents on the use of lithium for Amyotrophic Lateral Sclerosis (ALS)
Crowdsourced clinical trials• DIY science, Crowdsourced Health Research Studies, Citizen science, Amateur Scientist, Self-Experimentation• Patients Like Me – 125.000 members. 1000 condition-based communities –25 Papers published in PNAS, Nat Biotech, JMIR, …• 23andme – 23 and we –• Acor, RevolutionHealth, Curetogether, Genomera, Althea Health self tracking devices Social web games Participatory Health mobile Internet of things sensors PCEHR
NBN and patient empowermentCurrent NBN-enabled Driving forces: patient empowerment,networks personalized medicine, social networksEHR Personally Citizens are able to maintain and control Controlled EHR their own health informationGene-disease Personal Citizens ask for genetic analysis of theirassociation genomics DNA through the Internet and receivestudies reports on various aspects of their healthClinical trials Crowdsourced The patient voluntarily shares information clinical trials on treatments and evolution of his/her illness with other patients
Social media strategy• “The democratization of information through social media is shaping clinical encounters and the patient-provider relationship (Wen-ying Sylvia Chou, NCI)• 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.• “Participatory 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 future” (Melanie Swan)• Be careful! – terms for use of social media.
• Self tracking / self quantifying / self monitoring• The belief that gathering and analysing data can help them improve their lives!• QS’ers doubling every year.– 5524 members, 42 meetup groups• Larry Smarr– 10years quantifying his body – Weight – physical activity: calories burnt (body media) – Food intake – Sleep (Zeo) – blood chemicals (60 Markers) – cholesterol/triglycerides / Apo B / Ω – 6, Ω – 3/ C-reactive protein - Ultrasound – (plaque in arteries) – stool test – colonoscopy – DNA – Microbiome• Fitbit – Sleep – Movement• +9000 health apps, each person connected to 140 devices, 9 billion of connected devices now, 24 billion by 2020• NODE Sensor Environment
Self-genomics - Clinical annotation of individual genomes • Prof. Quake - Stanford - - Nature genetics paper - $50.000, 1 week, Helicos. Stanford team - • Clinical annotation of genome from “patient Zero” – Drug metabolism – Rare genetic variants - rare diseases – Common genetic variants - Risk of complex diseasesAshley et al. The Lancet, Volume 375, Issue 9725, Pages 1525 - 1535, 1 May 2010
First personal longitudinal OMICS profiling exercise• 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.• He contracted two mild viral infections in the data-gathering period, which left their molecular signature in the analyses.• 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.• This study shows that diseases are a product of an individual’s 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 )
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
Health and Biomedical Informatics• Informatics is the science of information• Information is data plus meaning• Biomedical informatics is the science of information in the context of biomedicine.• Informaticians study information (data + meaning).• Thus, HBI practitioners must understand the context or domain (biomedicine).• Health Informatics – use of information, often aided by technology, to improve individual health, healthcare, public health and biomedical research 4
“A 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 ofHierarchical Association dying within sixRule Model months”.
Role of informatics - New taxonomy of diseasesStratification of disease – ICD 11 – US Nat Academy – Towards Precision MedicineNew taxonomy based on human molecular biologyskin, colon, parathyroid – BRAF MutationMD Anderson CC – Breast, Ovarian, Uterine, Cervical – PIK3CA Mutation trial
Role of informatics - Network and systemsmedicine
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)
Conclusions• The routine application of personalised medicine is still a long way ahead, however we have now all the ingredients to make it happen.• 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.• 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.• But all of this will only be possible if we realise that it is 9me for us to take responsibility for our own health.