1. www.wwarn.org Twitter: @WWARN DEVELOPING A DATA STANDARD FOR MALARIA Clinical Data Interchange Standards Consortium (CDISC) WorldWide Antimalarial Resistance Network (WWARN) Lesley Workman CRC, 16 February, 2016

2. Why do we need data standards for malaria? Data Sharing has shifted from an “add on” to an essential part of the data cycle continuum – required by more and more journals and medicines regulatory authorities. Meaningful data sharing requires its standardization Data standards also enable Data exchange / sharing for: – Comparing data – Pooling data – Data re-use

3. “In short, establishing common standards for data reporting will provide new opportunities to transform the massive amount of data from drug studies on specific diseases into useful information to potentially speed the delivery of new therapies to patients.” Janet Woodcock, M.D. FDA Works with Partners to Establish Important Therapeutic Area Data Standards, October 24, 2012. FDA_Voice

4. Why CDISC? CDISC has established worldwide industry standards to support the electronic acquisition, exchange, submission and archiving of clinical research data and metadata that are platform independent CDISC has been adopted by FDA as the mandatory standard for data submissions after December 2016 EMA and Japan are currently reviewing the adoption of CDISC NIH and CDISC have recently started discussing the need for similar standards for epidemiology studies

5. WWARN’s Experience Over 5 years developing tools and platforms for curating, pooling and archiving data: using data dictionaries, study protocols and data sets relating to antimalarial efficacy contributed from a broad group of researchers from over 230 institutions in > 50 countries on >110,000 individual patient and ~10 000 healthy volunteer records Difficulties encountered: Lost/unavailable data No common standards Data not anonymized Poorly structured data Gaps: Data only on licensed antimalarials Phase III-IV only

6. Draft Project Mission: To support efficient, scientifically valid generation and reporting of clinical malaria data to streamline antimalarial development, regulatory submission and post-marketing research, as well as enable data sharing, comparison and aggregation. Draft Aim: Consensus-based development of a single, freely available data standard to ensure the consistent use of existing CDISC standards, and to facilitate alignment and development of new standards for the electronic acquisition, exchange, submission and archiving of clinical malaria data collection, analysis and reporting Draft Scope (Year 1): – Uncomplicated falciparum malaria – Uncomplicated vivax malaria Preventive treatment (e.g SMC, IPT, MDA), severe malaria to follow, as needed

7. Status CDISC Malaria Project Snapshot Focus: Uncomplicated Malaria Diagnosis Clinical and laboratory findings (baseline and follow-up) to assess therapeutic efficacy 7 Project Scope Essential core clinical data items, with definitions, data types and SDTM mappings Concept maps of malaria research concepts CDASH metadata for selected research concepts Annotated CRFs (with CDASH and SDTM-based annotations) ADaM: Analysis Data Model TAUG: Therapeutic Area User Guide Review : to ensure existing CDISC standards for the following are complete Medical history Antimalarial Drug administration Pharmacokinetic sampling Adverse Events of special interest.

8. DATA versus METADATA When standardising data it is critical to have the metadata Data is a single term of factual information – EG. If the CRF section is vital signs and the measurement required is “Temperature” – The data is the actual recorded Result of temperature for that person at that time Metadata describes the characteristics of the data – Metadata for “Temperature” includes method of recording and units of measurement

9. DATA ELEMENTS Data Elements are attributes about the data – Stored in metadata repositories (for reuse) Used to be referred to as “data dictionaries” A simple data element will contain: – Description (EG CRF FIELD name “What is your age?”) – VARIABLE name (EG. CDISC name Age) – Data type (character, numeric (also needs to include decimal places/integer), date, binary – Allowed values for the data item (EG. Controlled terminology for SEX Male/Female)

10. CONTROLLED TERMINOLOGY and DOMAINS When many different terms are used to describe similar data concepts it becomes difficult to reuse and prevents data interchange without curation/mapping Controlled Terminology – Defines allowed values for each SDTM Dates – YYYY-MM-DD/DD-MMM-YYYY Unique study identifier: USUBJID [PATNO; SCR NUM; ENROLNUM; PID; STUDY NUMBER] etc. etc. etc.…. DOMAINS: Collection of observations that relate to a particular topic – EG: Demographics, Adverse Events, Vital signs, Medical History, Laboratory Standard variables in each domain EG. Laboratory Test Results

11. Chains of Connected Concepts Slide courtesy of Diane Wold (GSK) 11 Study Subject Specimen Collection SpecimenLab Test Lab Test Result Clinical Significance Assessment Clinical Significance Result Subject Result / Subject Result / Subject Result

12. Draft Concept Map

13. NEXT STEPS..CDASH The standardization effort is planning to 1.Define each data element relevant to uncomplicated malaria 2.Create a concept map (defines how data elements are related) 3.Develop the meta data 4.Define and describe the controlled terminology

14. FINAL OUTPUT THERAPEUTIC AREA USER GUIDE: UNCOMPLICATED MALARIA FOR P FALCIPARUM 1.Annotated CRF template (CDASH) 2.Examples of SDTM 3.All metadata with descriptions 4.Concept maps STUDYIDDOMAINUSUBJIDLBSEQLBCATLBSCATLBTESTLBORRESLBORRESUVSDY WWARN01LBW0011MALDIAGP falciparumSEXUAL0µL0 WWARN01LBW0012MALDIAGP falciparumASEXUAL4840µL0 WWARN02LBW0013MALDIAGP falciparumSEXUAL0µL1 WWARN02LBW0014MALDIAGP falciparumASEXUAL160µL1 WWARN03LBW0021MALDIAGP falciparumSEXUAL120µL0 WWARN03LBW0022MALDIAGP falciparumASEXUAL34688µL0 WWARN04LBW0023MALDIAGP falciparumSEXUAL24µL1 WWARN04LBW0024MALDIAGP falciparumASEXUAL3240µL1

15. CDISC Standards specify how to structure the data to support efficient data sharing for regulated clinical trials. CFAST is an initiative of CDISC and the Critical Path Institute to accelerate clinical research and medical product development by facilitating the creation and maintenance of data standards, tools, and methods for conducting research in therapeutic areas important to public health.

16. The role of stakeholders Review draft data standards Share relevant experience: Recent CRF templates (~CDASH) Data Specifications (~SDTM) Statistical Analysis Plans (~ADaM) Identification of critical issues in regulatory submissions. Pilot test CDASH Current Stakeholders include: CDISC, CPATH WWARN members WHO GMP / TDR Pharmaceutical Manufacturers: o GlaxoSmithKline o Medicines for Malaria Venture o Merck o Novartis o Sanofi o Shin Poon o Sigma Tau o Takeda o UCB Others interested, please contact Lesley.Workman@wwarn.org Current Stakeholders include: CDISC, CPATH WWARN members WHO GMP / TDR Pharmaceutical Manufacturers: o GlaxoSmithKline o Medicines for Malaria Venture o Merck o Novartis o Sanofi o Shin Poon o Sigma Tau o Takeda o UCB Others interested, please contact Lesley.Workman@wwarn.org

17. Critical regulatory issues for consensus building, e.g.: 1. Antimalarial efficacy Study population definition (PP vs. mITT vs. ITT) Parasite / Fever Clearance Time, its measurement and analysis Duration of follow up and the time points for assessment (and relationship to half-life of the antimalarial/s tested). Role of PCR (recrudescence / reinfection / ) Contribution of each partner drug to efficacy of a FDC Measurement of gametocyte carriage 2. Clinical data support other comparative advantages Improved compliance / adherence Transmission blocking Less vulnerable to resistance 3. Antimalarial safety Differentiating malaria disease effects from drug induced liver injury, ECG (particularly QTc interval) changes, anaemia, haemolysis.

18. Sharing and Archiving Clinical Data to Strengthen EBM We need to share data We need to archive in order to share We need an archival format that is standardised and human readable in order to share meaningfully Organisations to take long term responsibility for: – Maintaining the standard archival format e.g. CDISC – Curating and approving data submissions – Providing the storage infrastructure and maintaining the platform Archiving the Phenome: Clinical Records Deserve Long- term Preservation – JAMIA paper http://www.ncbi.nlm.nih.gov/pmc/articles/PMC260559 2/ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC260559 2/

19. RECOMMENDATION 1: Stakeholders in clinical trials should foster a culture in which data sharing is the expected norm, and should commit to responsible strategies aimed at maximizing the benefits, minimizing the risks, and overcoming the challenges of sharing clinical trial data for all parties. RECOMMENDATION 2: - Timelines for sharing data RECOMMENDATION 3: - Data sharing agreements RECOMMENDATION 4: The sponsors of this study should take the lead, together with or via a trusted impartial organization(s), to convene a multi-stakeholder body with global reach and broad representation to address, in an ongoing process, the key infrastructure, technological, sustainability, and workforce challenges associated with the sharing of clinical trial data.

20. WHAT DOES CDISC DATA LOOK LIKE?

21. USEFUL LINKS http://www.cdisc.org/ http://www.cdisc.org/Video-Library http://www.wwarn.org/tools-resources/clinical-data- management-and-analysis-plan http://califesciences.org/live-webinar-cdisc-sdtm- conversion-made-easy-with-cdisc-express/