Transcript here - HL7 UK

EuResist
From Data to Knowledge
Integration of viral genomics with clinical data
to predict response to anti-HIV treatment
IBM Haifa Research Lab
© 2007 IBM Corporation
Outline
• The Problem
• Present solutions
• The project
– Vision, objectives, and value
– Partners
– Preliminary results
• Alignment with standards
• Collaborations
• Links
© 2007 IBM Corporation
The problem
© 2007 IBM Corporation
The problem
• HIV is a deadly virus
• Effective treatment available
since 1996
– HAART = “Highly Active Antiretroviral Therapy”
• (combined use of 3 – 4 anti-HIV drugs)
• Anti-HIV drugs work, but the virus is not eradicated
• The virus replicates itself and generates variants
with reduced suceptibility to anti-HIV drugs
– Drug resistance
• Testing for drug resistance has been recommended
in clinical practice since 2001
© 2007 IBM Corporation
Present solutions
• How do we measure antiretroviral resistance?
– Phenotypic test
• The virus “behavior” towards the drugs is observed “in vitro”
– Pick the virus from the patient blood and replicate it in the
lab in the presence of any single antiretroviral drug
• Costly, lengthy, complex – some drugs work “in vitro” and develop
resistance “in vivo”
• Important for the formal characterization of drug resistance
mutations, but not suitable for routine application
© 2007 IBM Corporation
Present solutions
• How do we measure antiretroviral resistance?
– Genotypic test
• The virus genetic make-up is investigated; its “behavior” is
inferred
– Pick the virus from the patient blood and read the virus’
genetic code, then infer its drug susceptibility profile based
on our knowledge of the relationship between mutations and
drug resistance
• Easier than phenotypic tests, but
– We still have limited knowledge about the newest drugs
– Some important mutations and interactions among mutations
have not yet been identified
• Imperfect tool, but definitely the reference test for routine
application
© 2007 IBM Corporation
EuResist vision
• To predict the in-vivo efficacy of anti-retroviral
drug regimens against a given HIV, based on the
use of viral genotype data integrated with
treatment response data derived from clinical
practice
© 2007 IBM Corporation
EuResist objectives
• Integrate biomedical information from three
large genotype-response correlation databases
–
Karolinska
–
ARCA
–
Arevir
• Develop an array of engines for effective prediction of the
response to treatment
–
Case-based reasoning
–
Machine learning (Bayesian networks, support vector machines)
–
Graph theory
–
Evolutionary models
–
Fuzzy logic
• Combine the engines into a predictive system
publicly available on the web
© 2007 IBM Corporation
EuResist value
• Largest resistance database in the
world
• Innovative prediction system, based on state-of-the-art
methods
– Some of the methods were not applicable before due to
insufficient amounts of data
• More effective care for patients
– Harness the power of information technology
• Significant decrease in global therapy management costs
• A pilot for hepatitis (HCV and HBV) where development
of drug resistance can be foreseen
© 2007 IBM Corporation
EuResist partners
• Informa S.r.l., Italy, Rome
• Università degli Studi di Siena, Italy, Siena (ARCA database)
• Karolinska Institutet, Sweden, Stockholm (Karolinska database)
• University of Cologne – University hospital, Germany,
Cologne (Arevir database)
• Max-Planck-Society for Advancement of Science, Germany
Saarbrucken
• Research Institute for Particle and Nuclear Physics of the
Hungarian Academy of Sciences, Hungary, Budapest
• European Federation of Pharmaceutical Industries and
Associations (EFPIA)
• Kingston University, United Kingdom, Kingston upon Thames
• University of Roma TRE, Italy
• IBM Haifa Research Lab
© 2007 IBM Corporation
EuResist at a glance
Prediction
System
Training
EuResist database
DB2 V9
Integrating
ARCA
Arevir
Karolinska
© 2007 IBM Corporation
Preliminary results
• Very encouraging preliminary results
• Integrating clinical, demographic and viral genomic data, and applying ML
techniques improves the quality of treatment while significantly reducing
costs
– “The whole is more than its parts”
• Success rate of individual prediction engines varies between 75%78%
• Their combination gives a success rate of 80%
– Clinical and demographic data significantly improves prediction
• Prediction based on clinical, demographic and viral genomic data
outperforms predictions based solely on viral genomic data
© 2007 IBM Corporation
Alignment with standards
• EuResist defines an HIV specific data-mart
– Researchers run their analytical tools on this datamart
• HL7 RIM based repository (e.g., IBM CG v3)
– Provides a standard way of storing healthcare
information
– Supports HL7 v3 messages (e.g., CDA)
• Specialization vs. Generalization => Tension!
© 2007 IBM Corporation
Alignment with standards
• EuResist infrastructure should be open and
interoperable, supporting standard
interfaces
– EuResist HIV specific data-mart can be
derived from HL7 RIM
– EuResist defines a CDA template for HIV
treatment
© 2007 IBM Corporation
Alignment with standards
• CDA template for HIV treatment
– Holds demographical and clinical data for a
patient, as well as viral genomic data through
links to the HL7 Clinical Genomics models
– Provides a much-needed standard way for
HIV scientists/caregivers to exchange
information.
© 2007 IBM Corporation
Alignment with standards
• What are the recommended tools for CDA
template definition?
– Authoring tools
– Validation mechanism
• What is the recommended mechanism to
disseminate a CDA template?
– Implementation guides?
– Balloting?
– NIST/HL7 Registry?
© 2007 IBM Corporation
Alignment with standards
HL7 V3.0
Certified
HL7 3.0 Msg
Mapping
HL7 RIM
Repository
EuResist
Integrated
database
HL7 3.0 Msg
CG v3
HL7 v3
Export/Import
© 2007 IBM Corporation
Collaborations
•
Retrovirology Laboratory Luxembourg
–
•
Stanford University
–
•
http://hidb.stanford.edu
The Rega Institute, Katholieke Universiteit Leuven
–
•
http://www.retrovirology.lu/
http://www.kuleuven.be/rega/
Carlos III HIV resistance center
–
Reference national coordinating center for HIV resistance in
Spain
–
http://www.fundacionies.com/
© 2007 IBM Corporation
Links
• Official EuResist site
– http://www.euresist.org/
• IBM Haifa Research Lab
– http://www.haifa.ibm.com/projects/software/euresist
– http://www.haifa.ibm.com/projects/verification/ml_euresist
© 2007 IBM Corporation
Obrigado
Brazilian Portuguese
Gracias
‫תודה‬
Hebrew (Toda)
Spanish
Thank You!
Danke
German
Grazie
Merci
Italian
French
Tack
Swedish
Köszö
nöm
Hungarian
© 2007 IBM Corporation