Transcript How will WWARN function?

WWARN
Perspective and Progress
RBM Case Management Working Group
Philippe Guerin
Geneva
8 July 2009
WWARN History
• Planning for over 4 years
– Core group of > 50 individuals
– 28 malaria endemic countries
• Support from the Bill and Melinda Gates
Foundation
- Starting 30 January 2009
• Collaboration between WHO and
WWARN / Oxford University
- MOU signed June 2009
WWARN objectives
• Develop a global network of scientists
involved in antimalarial drug resistance work
• Central database of information from malariaendemic countries on drug resistance
• Shared efforts with WHO
– Surveillance data by NMCPs on global
antimalarial therapeutic efficacy
• Collate data from additional sources
WWARN Scientific Aims
• Support standardisation of antimalarial
resistance indicators
– Standard data formats allow analysis of data
from diverse studies
• Test utility of proxy markers
• Provide spatio temporal evidence on drug
efficacy
– Early WWARNing System
 Provide evidence base for policy markers
Where do we stand with
resistance data globally?
• Absence of data
– Geographical gap
• Poor quality
• Absence of standardisation
– Data collection, analyze
• Good quality but delay accessing data
– Publication years after data collection
– Unpublished data
• Used “only” for surveillance or registration purposes
• Not see as a priority, lack of resources
Historical data on resistance
Drugs
Introduction
Reported
resistance
Difference
(Years)
Quinine
XVIII cent.
1910
100?
Chloroquine
1945
1957
12
Proguanil
1948
1949
1
Sulfadoxinepyrimethamine
1967
1967
0
Mefloquine
1977
1982
5
Atovaquone
1996
1996
0
Artemisinin
1973
2005?
32?
Adapted from Wongsrichanalai et al. LID 2002
Resistance spread: chloroquine and SP
Resistance spread: chloroquine and SP
Drug quality
• Counterfeit drugs
– Investigation South East Asia in 2007
• 195 counterfeit drugs out of 391 samples
• Little or no artesunate
– Lots of potentially dangerous products
(metamizole, safrole, ecstasy)
• Suboptimal concentration of drugs
– Very limited information on Africa
• “Pre-qualified” drugs and others
• Drug used
– Storage
– “Fixed dose versus blister combination”
Newton et al.
PlosMed 2008;5(2):e32
Resistance data format
• Four angles to look at resistance
– Clinical efficacy
– Clinical pharmacology
– In Vitro susceptibility
– Molecular markers
4 core modules
of WWARN
WHO in vivo study protocol
http://www.wwarn.org
Clinical Efficacy
Optimise analytical methodologies
Facilitate the conduct and analysis of clinical trials
• Technical support, tools, CRFs, syntax or Do files
• Process own data online:
• Cleaning and standard report
Collate current knowledge of antimalarial efficacy
Correlate with in vitro, molecular, and pharmacokinetic data
Clinical Pharmacology
Measuring drug concentrations essential to define resistance
accurately and inform optimal dosing regimens
Clinical pharmacology module activities include:
Guidelines & Technical support
• Study design, sample assay and PK-PD analysis
QA programme
• Greater assay accuracy/comparability
Tools for data cleaning and PK analysis
Analysing pooled data
• Define therapeutic drug concentrations
• Inform optimal dosing regimens
–
most important / vulnerable target populations
In-Vitro Susceptibility
Clinical failure may be the result of factors other than resistance
and even resistant parasites may be cleared with drug therapy
Pilot protocols will be developed on website
• Fresh patient isolates
• Culture time, media, parasitemia, hematocrit
Standardized quality control measures
• Positive & negative controls
• Standard reference clones
• Standard drugs
Molecular Markers
Molecular information in the WWARN database linked to
clinical outcomes and in vitro susceptibility results
Surveillance with defined molecular markers of drug
resistance
• Single nucleotide polymorphisms (SNPs)
• Copy number variation
Regional and global patterns of emergence and spread
• Track trends
• Detect new patterns of rising or falling resistance
Identification and validation of markers to ACT resistance
• Critical mass of data
Informatics
We aim to create a web platform which provides
• Secure environment
• Easy-to-use tools to manage and analyse their data
• Statistical algorithms for analysis of complex patterns
and trends
• Accessible data summaries for different user groups
WWARN Stakeholders
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Patients
Policy makers
National Malaria Control Programmes
WHO
RBM
NGOs
Scientific community
Drug developers
Funding agencies
…
Stakeholder Groups
 Field Researchers
 National Policy Makers
 Regional / Global analysis
Stakeholder Groups
- Library of Protocols
- SOPs for Data Formats
- Analytical Tools
 Field
Researchers
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•Online protocols
 WHO/WWARN
• Detailed procedures
 SOPs
 Quality Control Standards
• Standardised Analysis
 Acceptable methodology
• Follow up trends
Stakeholder Groups
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 Field Researchers
- Spatio-temporal Description of Drug Efficacy
- Evidence to Inform Policy Makers
 National Policy Makers
• Updated Geographic Data
• Drug Quality Information
 Data on Available supply
• Accessible to Public Health
Professionals
Stakeholder Groups
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• Provide Early Warning
• Inform Global Policy Makers
 Global Fund, PMI,
World Bank, UNITAID...
• Guide Drug Development
 Field Researchers
 National Policy Makers
- Regional Analysis of Drug Resistance Trends
- Evidence to Inform International Policy: Proactive Strategy
- Evidence to Inform Drug Developers
 Regional / Global analysis
WWARN Targets
 Field
Researchers

• NMCP
• NGOs
• Scientific community
• NMCP
 National Policy Makers
• MoH
• WHO
• WHO
 Regional / Global analysis
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• MoH
• Policy Makers
• Drug developers
• Patients
Process and Data Access
• Individual data collection
– Limitation of aggregated data
• Secured process
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Data upload
Data consistency
Data analysis
Data output
Web based access
• Improve access of data
– Data sharing should not undermine publication
– Speed up publication
Comprehensive, up to date, quality-assured information
Scientific Advisory
Committee
Board
Structure
Executive Team
DATA PLATFORM
Integrating Database U. Oxford Dominic Kwiatkowski
Stakeholders
Clinical Efficacy
U. Oxford / Darwin
Ric Price
Molecular Markers
Maryland U.
Chris Plowe
Phenotyping
IMEA – CNR palu
J. Le Bras
Pharmacology
Cape Town U.
Mahidol U.
Karen Barnes
Regional sites
East Africa
Leader & Team
West Africa
Leader & Team
Asia
Leader & Team
Latin America
Leader & Team
Country View
Clinical: single study detail
• Implements standard
analysis methods
• Tools available for
anyone who’d like to
use them
• Storing raw data gives
flexibility to analyse
data in numerous ways
Clinical study: risk of failure
Thai-Burmese Border
Nosten et al.
Clinical study: risk of failure
Thai-Burmese Border
Molecular: frequency of
resistance markers
Data courtesy of Cally Roper
Geomaps – historical
summaries
Pharmacology: drug
concentration