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Joined up Health and Bio Informatics: Alan Rector Bio and Health Informatics Forum/ Medical Informatics Group Department of Computer Science University of Manchester [email protected] www.cs.man.ac.uk/mig img.man.ac.uk www.clinical-escience.org mygrid.man.ac.uk O p e n G A LE N 1 The Problem • The next steps in exploiting our exploding knowledge of basic biology depends on understanding its relation with health and disease. • Health care is – Deluged with information • about generalities, policies, and theory – Information and Knowledge Poor • about specifics of patient care and outcomes O p e n G A LE N 2 A Convergence of Need • Post genomic research • Safe, high quality, evidence based health care Need more and better clinical information • Which scales – In Size – In Complexity Knowledge is Fractal O p e n G A LE N 3 A convergence of Technologies • Post genomic research • Safe, high quality, evidence based health care • Web/Grid/Semantic Web • Ontologies & Information fusion • Language technology • Data mining and case based reasoning • Healthcare records & standards • Mobile devices Open Collaborative Research O p e n G A LE N 4 A Unique Time • E-Science • The Grid • The Semantic Web / Grid • BioInformatics Genomics/Proteomics… • Massive investment in population medicine • Massive investment in NHS computing • Maturing Electronic Health Records • … Ride the Whirlwind! O p e n G A LE N 5 Protocol/Collection-based research Research idea Results in vivo Plausibility in Silico/Collecto Data Analysis Tools Shared Collections Models & Standards Data Collection Tools Protocol Approval Tools Automatic Patient Screening O p e n G A LE N Protocol Authoring Tools 6 “Stones in the Road” • Confidentiality, Privacy and Consent – How to keep public confidence while enabling research • Information capture – Speed and ease of use require language technology • doctors dictate! • Information integration – Need common ontologies which bridge bio and health information O p e n G A LE N 7 One Response: CLEF Joining up Health Care & Bioscience in Cancer • Clinical e-Science Framework – Clinical care – Clinical research – Clinical bioscience • Genotype meets Phenotype • New technologies for healthcare – A focus to adapt new technologies to healthcare • New ways to do clinical research – Faster, safer, easier, better • Trial design, execution, archiving, reporting O p e n G A LE N 8 CLEF Towards and “end-to-end” solution in an ethical framework • Patient care • Formulation of clinical studies • Information capture • Information representation • Information analysis and integration • Knowledge & hypothesis generation • Clinical support O p e n G A LE N 9 CLEF: A meeting of open technologies • Organisational issues & Information governance – Consent, Models of access, balance of research and privacy • Information capture & quality – Language technology + Ontologies (OpenGALEN & OWL) + E Health Record (OpenEHR) • Information use for Care – E Health Record + Decision support + Ontologies + Language generation • Information Re-use for Research – Pseudonymised E Health Record + Ontologies + Metadata/repositories O p e n G A LE N 10 CLEF: Language Technology • Extraction of simple information from clinical records – Measures of reliability • Pseudonomysation aids • Language generation – Validation • “What you see is what you meant” – Presentation O p e n G A LE N 11 CLEF Logic-based Ontologies: Conceptual Lego “SNPolymorphism of CFTRGene causing Defect in MembraneTransport of ChlorideIon causing Increase in Viscosity of Mucus in CysticFibrosis…” “Hand which is anatomically normal” OpenGALEN & OWL O p e n G A LE N 12 Species Bridging Scales with Ontologies Genes Protein Function CFTRGene in humans Disease Protein coded by (CFTRgene & in humans) Membrane transport mediated by (Protein coded by (CFTRgene in humans)) Disease caused by (abnormality in (Membrane transport mediated by (Protein coded by (CTFR gene & in humans)))) O p e n G A LE N 13 Avoiding combinatorial explosions • The “Exploding Bicycle” From “phrase book” to “dictionary + grammar” – 1980 - ICD-9 (E826) 8 – 1990 - READ-2 (T30..) 81 – 1995 - READ-3 87 – 1996 - ICD-10 (V10-19 Australian) 587 • V31.22 Occupant of three-wheeled motor vehicle injured in collision with pedal cycle, person on outside of vehicle, nontraffic accident, while working for income – and meanwhile elsewhere in ICD-10 • W65.40 Drowning and submersion while in bath-tub, street and highway, while engaged in sports activity O p e n G A LE N • X35.44 Victim of volcanic eruption, street and highway, while resting, sleeping, eating or engaging in other vital activities 14 Making it simple: Tools • Logic based ontology (OWL) is the assembler – Write real ontologies in “high level languages” • “Intermediate representations” – Present real ontologies to be relevant to needs • “Views” • Scalable simplicity for end-users requires sophisticated architecture – “Swans paddle furiously under water” • Decoupled distributed environment – “Owned” by the domain experts O p e n G A LE N 15 Summary • Convergence of need in healthcare & post genomic research – Matched by convergence of technologies • E-Science – an opportunity for collaboration – Faster, less costly, more effective translation from bioscience to health care • Barriers to be overcome – Information capture – Privacy, confidentiality, & consent – Information integration – sharing of meaning • Common “Ontologies” are a key resource O p e n G A LE N 16 CLEF Consortium www.clinical-escience.org • Bio Health Informatics Forum, Department of Computer Science, University of Manchester • Centre for Health Informatics and Multiprofessional Education, University College London • Natural Langauge Group, Department of Computer Science, University of Sheffield • Judge Institute for Management Studies, University of Cambridge • Information Technology Research Institute, University of Brighton • Royal Marsden Hospital Trust • North and North Central London Cancer Networks 17 O p e n G A LE N