Using local RWD to drive global therapeutic advancements.

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Joanna Nicholson
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1 Using local RWD to drive global therapeutic advancements. Helsinki, 30 th Nov 2016 Mike Spencer, Head of Real World Evidence, EMEA, Janssen

2 The following represent my own views and not necessarily those of my organisation

3 The Shattered Mirror

4 3 (connected) Trends Adaptive Pathways RWD Research efficiency Value based healthcare

5 Drivers Patient demands for innovative medicines Constrained budgets Rising demand Spiralling costs of R&D Precision medicine 5

6 Research efficiency

7 Big challenges in clinical development

8 How can RWD contribute to efficiency Obviate need for large (some) PIIIs Assess (optimize) trial feasibility Subject identification (and recruitment) Reduce (remove) need for data entry

9 Trial recruitment example Aim to intervene early in prodromal disease Patients enrolled based on out of range test values How to efficiently recruit? GP GP GP Subject Hospital / GP hub Subject Subject Subject Subject 9

EHR / Registry studies "Many of us within the FDA believe the most useful source of

"In general, it's time to take advantage of the change in our clinical data

product development without sacrificing established standards of evidence, FDA

10 EHR / Registry studies "Many of us within the FDA believe the most useful source of knowledge will come from randomization in the context of clinical practice,". "In general, it's time to take advantage of the change in our clinical data environment to create efficiencies by streamlining and reducing the costs of medical product development without sacrificing established standards of evidence, FDA Commissioner Robert Califf "The study is a first, an example, and I think it will trigger a lot of discussion. I think we will see more effectiveness studies coming along in different forms David Leather, Global Medical Affairs Leader in the Respiratory Franchise at GSK 10

11 Adaptive Pathways Pathways

12 12/ 6) Adaptive Pathways Source:

13 What about the payers? Required? Scope? Patient risk? Data collection who funds? Evaluation and HTA? Complexity of resource allocation? Control of usage (to relevant pop)? Exit strategies? 13

14 Value based healthcare Managed Entry Agreements Pay for performance Coverage with Evidence Development

15 Managed Entry Agreements 15

Mike s dream Integrated Evidence Generation Planning Assess unmet needs, patient pathways, value propositions Agreement between regulators, HTA and company on lifecycle

questions Exploratory clinical development Full clinical development Launch planning Early to mid lifecycle Trial feasibility, optimised entry criteria Patient

16 Mike s dream Integrated Evidence Generation Planning Assess unmet needs, patient pathways, value propositions Agreement between regulators, HTA and company on lifecycle evidence package Managed entry agreements allow rapid access and address payer uncertainty RWE to expand indications and broaden the value proposition Address in market questions Exploratory clinical development Full clinical development Launch planning Early to mid lifecycle Trial feasibility, optimised entry criteria Patient identification and recruitment facilitated by RWD Data extracted directly to trial DB Registries and routine data in data platforms to support MEAs, Safety and risk management MA

17 What the competition are saying The UK government will invest an extra 2 billion pounds (2.3 billion euros) a year in research and development, prime minister Theresa May said at a conference on Monday. ABPI chief executive Mike Thompson said: "Given the right support, the NHS has the infrastructure to become the go-to place for companies to research, develop and use new medicines. Working with the pharmaceutical industry and other partners the NHS can capitalise on its unique ability to access clinical data. By using anonymous patient data safely and effectively we can help make the UK the best place in the world to support the clinical development and use of innovative medicines."

18 EMIF project overview ACADEMIC PARTNERS 57 partners from 14 European countries 56 million worth of resources Three projects in one Five year project ( ) SME PARTNERS EFPIA PARTNERS PATIENT ORGANISATION

Data available through consortium Primary

specific) Data is available from more than

19 Data available through consortium Primary care data sets Hospital data Administrative data Regional record-linkage systems Registries and cohorts (broad and disease specific) Data is available from more than 40 million subjects from seven EU countries Biobanks

20 Big Data for Better Outcomes (BD4BO)

21 OHDSI is an international community Voluntary participation Industry and academia Partners with data and partners with methods skills 21

22 Treatment pathways study 250 million subjects Focus on people with type 2 diabetes, hypertension, and depression What sequence of drugs did they use? 22

24 In my ideal world Data infrastructure Interoperability and routine aggregation across large populations Infrastructure and regulator valid models for randomisation in clinical practice Application of standards i.e. OMOP common data model Mechanisms and incentives for sharing Public / professional understanding of the value of data access Ethical and legal harmonisation across region New ways of working with industry that go beyond give us the cash, and we ll do the science Mobile tech as an enabler of increased patient centricity RWD driven commercial models to mitigate uncertainty 24

Case study: Challenges faced by EMIF in utilising the OMOP CDM. Johan van der Lei Erasmus Medical Center Rotterdam

Case study: Challenges faced by EMIF in utilising the OMOP CDM Johan van der Lei Erasmus Medical Center Rotterdam Outline Scaffolding EMIF and a CDM EMIF and the OMOP CDM Ongoing activities/challenges