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 malaria-endemic 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• Good quality but delay accessing data– Publication years after data collection– Unpublished data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

Sulfadoxine-pyrimethamine

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

• Patients• Policy makers• National Malaria Control Programmes• WHO• RBM• NGOs• Scientific community• Drug developers• Funding agencies• …

Regional / Global analysis

Stakeholder Groups

National Policy Makers

Field Researchers

Field Researchers

- Library of Protocols- SOPs for Data Formats- Analytical Tools

•Online protocols WHO/WWARN

• Detailed procedures SOPs Quality Control Standards

• Standardised Analysis Acceptable methodology

• Follow up trends

Stakeholder Groups

National Policy Makers

Field Researchers

- Spatio-temporal Description of Drug Efficacy- Evidence to Inform Policy Makers

• Updated Geographic Data• Drug Quality Information

Data on Available supply• Accessible to Public Health Professionals

Stakeholder Groups

Regional / Global analysis

National Policy Makers

Field Researchers

- Regional Analysis of Drug Resistance Trends- Evidence to Inform International Policy: Proactive Strategy- Evidence to Inform Drug Developers

• Provide Early Warning• Inform Global Policy Makers

Global Fund, PMI, World Bank, UNITAID...

• Guide Drug Development

Stakeholder Groups

Regional / Global analysis

WWARN Targets

National Policy Makers

Field Researchers

• NMCP• NGOs• Scientific community

• NMCP• MoH• WHO

• WHO• MoH• Policy Makers• Drug developers• Patients

Process and Data Access• Individual data collection

– Limitation of aggregated data

• Secured process– Data upload– Data consistency– Data analysis– Data output

• Improve access of data – Data sharing should not undermine publication– Speed up publication

Web based access

Comprehensive, up to date, quality-assured information

StructureBoardBoard

Executive TeamExecutive Team

DATA PLATFORMDATA PLATFORM

Clinical EfficacyU. Oxford / Darwin

Ric Price

Molecular MarkersMaryland U.Chris Plowe

PhenotypingIMEA – CNR palu

J. Le Bras

PharmacologyCape Town U.

Mahidol U.Karen Barnes

Integrating Database U. Oxford Dominic Kwiatkowski

Scientific Advisory Committee

Scientific Advisory Committee

Stakeholders

Regional sitesRegional sites

East AfricaLeader & Team

West AfricaLeader & Team

AsiaLeader & Team

Latin AmericaLeader & 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 failureThai-Burmese Border

Nosten et al.

Clinical study: risk of failureThai-Burmese Border

Molecular: frequency of resistance markers

Data courtesy of Cally Roper

Geomaps – historical summaries

Pharmacology: drug concentration