W hat are the real-w orld evidence tools and how can they support - PowerPoint PPT Presentation

W hat are the real-w orld evidence tools and how can they support decision m aking? EMA-EuropaBio I nfo Day – 2 2 nd Novem ber 2 0 1 6 Dr Alison Cave, Principal Scientific Administrator, Pharmacovigilance and Epidemiology Department An agency of the European Union

Disclaim er The views expressed in this presentation are my personal views and may not be understood or quoted as being made on behalf of or reflecting the position of the European Medicines Agency or one of its committees or working parties. 1

Objectives • W hich data and W hen? • Opportunities for real w orld data • Patient Registries I nitiative Conclusions • 2

Data – W hich data and w hen? Epigenetics Transcriptomics Genomics Proteomics Functional RCTs Phenotypes Metabolomics Pharmaco Lipodomics In silico genomics modelling Real world evidence is defined as Social Media data that are collected outside the Structural M-Health RWE biology Electronics health Surveys records constraints of conventional randomised clinical trials . Environmental Claims data Registries databases 3

RW E - W hat are the Opportunities across the product life cycle? Developm ent Grow th phase Mature phase Post m arketing PROs Budget com m itm ents im pact Head to head ( safety etc.) Evidence required Usage com parative Effects of Unm et need Adherence Differ- effectiveness sw itching on / disease ence Differentiation outcom es burden in sub- Utilization Patient Effectiveness Differentiate / prescribing populations recruitm ent w ith or vs. patterns protected Target galenics populations Understand standard of Now care and NHD Trial Past design Com petitor Conditional New New form ulation/ Launch goes generic pricing review com petition indication 4 Source: I MI GetReal

Medicines Developm ent • Population-based databases to characterize frequency and distribution of disease • Identify the population to be treated • Identify whether the disease effects high risk populations e.g. paediatrics • Identify unmet medical need • Identifying prevalence of disease (orphan medicines) • Current standard of care • Clinical trial recruitment • Real World clinical trials 5

At and Follow ing Authorisation • The EU Risk Management Plan is key to driving proactivity and promoting better targetted studies • Safety Specification – important known and potential risks + missing information • Pharmacovigilance Plan – routine PhV + additional studies • + / - Risk Minimisation Plan – including effectiveness measures • Future – Benefit risk management plans 6

Post-authorisation safety • The entire evidence hierarchy • Detecting signals (new or changing safety issues) • Confirming signals e.g: observed vs. expected; impact / burden • Continuous safety monitoring in real world • Formal association studies in case control, cohort, etc • Assessing rare, delayed or chronic exposure adverse reactions • Effectiveness studies • Health outcome and HTA studies 7

Data – W hich data and w hen? Epigenetics Transcriptomics Genomics Proteomics Functional RCTs Phenotypes Metabolomics Pharmaco Lipodomics In silico genomics modelling Social Media Structural M-Health RWE biology Electronics health Surveys records Environmental Claims data Registries databases 8

Registry roles Multiple: • Describe natural history of a disease • Determ ine clinical effectiveness of healthcare products / services • Measure / m onitor safety / harm • Measure quality of care All m ay inform research and m edicines approval & m onitoring 9

EMA Activities: Registry analysis 2 0 0 5 -2 0 1 3 Registry Analysis Determ ined num ber of registries im posed as an obligation at the tim e of authorisation from 2 0 0 5 -2 0 1 3 2 0 0 5 -2 0 1 3 : 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% exceptional orphan non-orphan conditional all ( n= 335 ) circum stances ( n= 70) ( n= 265 ) ( n= 17) ( n= 21) no registry 30 4 50 25 4 15 7 registies 31 20 11 2 14 10

Registry analysis 2 0 0 5 -2 0 1 3 Results Registries characteristics Registries characteristics N % Disease registry 1 1 3 5 % Product registry 2 0 6 5 % New registry 2 4 7 7 % Existing registry 6 1 9 % Both ( com bination of new and existing) 1 3 % 11

Registry analysis 2 0 0 5 -2 0 1 3 Results Registry objectives Prim ary objectives N % Safety 2 2 7 1 % Effectiveness/ efficacy 3 1 0 % Safety in pregnancy 3 1 0 % Other 3 1 0 % Secondary objective effectiveness/ efficacy 1 2 3 9 % 12

Registry analysis 2 0 0 5 -2 0 1 3 Collection of HTA-related variables Results in registry 13

Registry analysis 2 0 0 5 -2 0 1 3 Results Problem s reported w ith registries  Percentages are based on a total of 24 registries that initiated patient inclusion. 1 4

Registry analysis 2 0 0 5 -2 0 1 3 Difference betw een planned num bers of patients and actual num bers of patients included Accrual of patients to registries 600 500 Actual = Planned Actual annual accrual 400 300 200 100 Actual is less than half planned rate 0 0 100 200 300 400 500 600 700 Planned annual accrual (Only 14 of 31 registries give data) 15

Current Challenges w ith Registries • Majority of imposed registries are for orphan products and/ or products approved under exceptional circumstances and imposed for safety reasons. • Registries face challenges around:  Recruitment: lack of physician engagement due to administrative burdens, patient consent, low product usage and competing registries  Data Quality: compliance, study design, representativeness of registry population  Companies predominantly choose to establish individual product registries rather than utilise existing disease registries. • This often results in duplication of effort, a likely slower resolution of the initial concern and multiple, relatively inflexible registries with limited application in the future • Lack of sustainability of current disease registries 16

EMA Strategy on Registries MAA = Marketing Authorisation Applicant MAH = Marketing Authorisation Holder NCA = National Competent Authority 17

Status of Pilot Phase • Creation of a taskforce composed of representatives of EMA Scientific committees and working parties, the European Commission, experts from national competent authorities and EMA staff • Currently > 12 expressions of interest received (pharmaceutical companies and registry managers) • Suitability of candidates discussed within the Cross-Committee Task Force • Four case studies have been identified which together represent the need to • Establish a new registry • Use of an existing disease registry • Switching from product registry to disease registry 18

Learnings to date Collaborations would be facilitated by: • Early dialogue between the MAHs and registry owners • Clear lines of communication between the stakeholders • Definition of a clear protocol at an early stage in order that the registry can establish the feasibility of any collaboration • Clear governance models to address issues such as consent and data ownership • Clear information from the registry on the model of collaboration, structure, governance, data collection mechanisms and points of contact. 19

Patient Registries W orkshop Brought together registry owners, industry, HTA representatives, regulators to discuss solutions to better use existing patient registries that collect high-quality data from the use of medicines in clinical practice Aim s • Identify the challenges faced by registries and industry when collaborating; • Understand the technical challenges presented by disparate datasets; • Identify solutions to best facilitate collaborations & avoid duplication. Output Recommendations for tools and standards to support a systematic and standardised approach to best use of registries, especially for post-marketing evaluation of safety & effectiveness - 2017 http:/ / w w w .em a.europa.eu/ em a/ index.jsp?curl= pages/ ne w s_ and_ events/ new s/ 2 0 1 6 / 1 0 / new s_ detail_ 0 0 2 6 2 7 .jsp&m id= W C0 b0 1 ac0 5 8 0 0 4 d5 c1 20

Session 1 : Setting the scene Challenges and Opportunities for Collaboration 21

Sum m ary of the challenges • Financial stability and sustainability of the registry • Clarity of data ownership including linked data • Data access • Mismatch between the required standards for industry and registry • Regulatory guidance to increase understanding among registries around MAH obligations and required data standards 22

Session 2 : Success factors for international collaborations 23

Sum m ary of the key success factors • Need for guidance on standardised data collection and coding • Recoding of medicines information, response to treatment, changes in disease state etc • Flexibility and capacity to accommodate methodological differences across multiple studies • Defined contact points to facilitate communication • Appropriate approvals/ established governance to allow data access and sharing • Feedback to healthcare professionals and participating families 24

Session 3 : Possible solutions 25