Objectives 1 2 3 4 5 Opportunities Data: w here RW E can strengths, W hich Data? Exam ples Conclusions support the AP lim itations approach and challenges 1
2 Objectives W hich Data? 1
Which Data? W hich Data? Epigenetics Transcriptomics Genomics Proteomics Functional RCTs Phenotypes Metabolomics Pharmaco Lipidomics In silico genomics Social modelling Media Structural M ‐ Health Electronics biology Surveys health records RWE Real w orld data Environmental is defined as data that are collected Claims Registries data databases outside the constraints of conventional randomised clinical trials. 3
Which Data? Electronic health records Primary care data, hospital records Patient and Claim s data caregiver surveys Registries Existing disease The Future Registries / new Social media product registries data Datasources Datasources Prescription databases Patient derived data Drug utilisation (via smart phone or web based technologies) 4
5 Julian I sla Patient Driven Platform for RWE – the future
Objectives 1 2 W hich Data? Exam ples 6
RWE is already in routine use in the EU Particularly true for marketed products - safety monitoring and drug utilisation. 7
Post-authorisation safety Exam ples • RCT suggested increased fracture risk in w om en at arm , w rist, hand & foot. • Electronic health records – GPRD • 1 8 1 9 patients w ere included w ith w ell defined exposure and a fracture. • I ncreased fracture risk w ith exposure to rosiglitazone and pioglitazone, in both m en and w om en and at a range of fracture sites. 8
9 im m unisation records registers linked to needs/ disability Special Post-authorisation safety
Observational studies supporting withdrawals/ restrictions 10
Increasing use of RWE for understanding the prescribing landscape, effectiveness studies, delivering outcomes for HTA, and rapid cycle evaluation of medicines. Sw edish Biologics Sw edish Biologics Registry ( Artis) Registry ( Artis) Medicare Claim s Data Medicare Claim s Data Directly com pared risk of stroke, Directly com pared risk of stroke, bleeding or death in patients w ith bleeding or death in patients w ith nonvalvular AF nonvalvular AF 11
Understanding the Landscape Depression Observational Health Data Science and I nform atics ( OHDSI ) UK USA Substantial variation in treatment practice for depression across data sources, health systems, geographies, and over time USA Consistent heterogeneity in treatment choice as no source showed one preferred first-line treatment 11% of depressed patients followed a treatment pathway that was shared with no one else in any of the databases USA Japan Use of RWE can help identify the most appropriate comparator group Hripcsak et al, PNAS, 2 0 1 6 12
Use of Registry Data to support an extension of an Indication • Soliris (eculizumab), a C5 inhibitor was approved in June 2007 for paroxysomal nocturnal haemoglobinuria (PNH) in a restricted patient population with a prior history of transfusions • At authorisation a PNH disease registry was agreed which ultimately recruited approximately 2000 patients and included PNH patients treated and not treated with eculizumab across all stages of disease severity How ever these exam ples w ere not prospectively planned studies…………. • The use of registry data to extend the indication to patients without a prior history of infusions was discussed with CHMP via the Scientific Advice process. It was agreed that depending on patient numbers, the registry may allow for some assessment of the benefit of treatment in this patient population. • Given the challenges of the disease and the efficacy of eculizumab, a prospective randomised study requiring a non treatment group was not possible • A comparison of outcome recorded by the registry in patients with no transfusion history treated or not with eculizumab enabled a extension of the indication to patients w ith haem olysis w ith clinical sym ptom ( s) indicative of high disease activity, regardless of transfusion history. 13
Adaptive pathways • A prospectively designed iterative, developmental plan • Incorporation of real world evidence to complement RCTs in the post authorisation phase • Early involvement of HTA and other downstream decision makers 14
Objectives 1 2 3 Opportunities W hich Data? Exam ples w here RW E can Conclusions support the AP approach 15
16 authorisation Post - Opportunities of Real World Data Authorisation Developm ent
Developm ent • Characterisation of disease progression and unmet need • Identification of the target population • Understanding current clinical care practices (resource utilisation) • Drug utilisation • Registry data for historical controls in rare / orphan diseases • Validation of surrogate endpoints 17
Authorisation • Open label extension studies in a registry • Drug utilisation studies to monitor use • Confirming long term safety • Risk management activities to address uncertainties • Comparative effectiveness studies 18
Post - authorisation • Quality of life metrics • Pragmatic clinical trials / registry studies • Understanding subgroups • Assessing long term safety • Collecting patient reported outcomes 19
Objectives 1 2 3 4 Opportunities Data: w here RW E can strengths, W hich Data? Exam ples Conclusions support the AP lim itations approach and challenges 20
Claims Data Electronic Health Records Patient Registries 21
Claims Data Strengths Lim itations • Quality of recording may be better • Structural limitations as link to payment • Bias due to reporting and coding • Auditable • Bias due to differential follow up • More consistent terminology • Often short term follow up • Large data sets • May not have full medical history • Relatively low cost • Inability to assess appropriateness • Good for resource utilisation studies of care • Benefits of treatment may be missing • Absence of diagnosis, data on life time factors and PROS • Medical records needed for in depth analysis • Mother/ child linkage difficult • Non-reimbursed products/ services missing 22
Electronic Health Records Strengths Lim itations • Longitudinal record – cradle to • Variable quality grave (with unique patient • Hospital prescribing not recorded identifier) • Variability in care delivery impacts on • Full patient history datasets • Linkage may be possible • Variation in diagnosis/ coding across GPs • No over the counter information • Large data sets • Frequently missing data • Relatively low cost • Limited PROs • Challenge to monitor drug use in children • Good for resource utilisation studies as the number of drugs with sufficient • Possibility of capturing off label use exposure to detect rare adverse events in children and adolescents is limited. 23
Patient Registries Strengths Lim itations • Systematic assessment of investigator • Substantial set up and running costs designed measurements of relevant (sustainability) clinical parameters • Time consuming to initiate • Natural history of disease • Medications commonly missing • Disease burden • ADRS not routinely recorded • Standard of care • Co-morbidities missing • Patient stratification • Data ownership/ governance • RCTs challenges • Open label studies possible • Data Quality - absence of clear • Capture off label use benefit for clinical practice limits HCP • Captures information on high risk commitment groups and rare diseases • If no comparator will limit utility • Patient reported outcomes 24
Objectives 1 2 3 4 Data: Opportunities strengths, W hich Data? Exam ples w here RW E can Conclusions lim itations support the AP and challenges approach 25
What is the current European landscape? ….fragm entation, ……lack of interoperability, ……..increased cross border collaborations are required to leverage existing data and know ledge 26
Analysis of EU Wide Datasets Potential data sets were identified I dentified potential data sets 1 5 6 • ENCePP Resource Database • PROTECT • ADVANCE • EU-ADR • FRAMEWORK CONTRACTS 27
Analysis of EU Wide Datasets Potential data sets were identified I dentified potential data sets 1 5 6 Useful RW E Data sets were screened to data sets select those with: 6 6 • Longitudinal data • National representation • Linked exposure to outcome data • Quality/ validity/ scientific publications 28
Analysis of EU Wide Datasets 3 12 6 Data source verification: 5 66 in total 6 1 1 5 4 1 2 2 1 Multi-national 1 3 8 4 29
30 Analysis of EU Wide Datasets
Objectives 1 2 3 4 5 Data: Opportunities strengths, W hich Data? Exam ples w here RW E can Conclusions lim itations support the AP and challenges approach 31
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