Date: Thursday 7th December 2023
Time: 13:00-14:30 GMT | 14:00-15:30 CET
Speakers: Robert Hemmings (Consilium Salmonson & Hemmings), Antonio Remiro-Azócar (Bayer) and Nicholas Latimer (University of Sheffield).
Who is this event intended for? Regulatory and HTA statisticians. Anybody interested in the new EU HTA regulation.
What is the benefit of attending? Learn about the multiple frameworks used to define a research question and the context in which they are used. Discuss how they may complement each other in light of the new EU HTA regulation.
Over the past years, areas of clinical development and patient access / health technology assessment (HTA) have moved closer together. However, both areas differ in how they approach their respective research or policy questions. While the estimand framework is being the focus in clinical development, HTA is being viewed through the lens of the PICO framework. This might lead to mutual misunderstandings and ultimately prevent timely patient access due to evidence gaps. Additionally, the Target Trial Emulation framework has become popular in the Real-World Data setting to translate research questions into a meaningful design, and share some commonalities with the estimand and PICO frameworks.
For randomized controlled trials (RCTs) in the regulatory setting, the estimand framework has been introduced and stimulated by the publication of the International Council of Harmonisation (ICH) E9 (R1) Addendum [1]. It is recognized by regulatory agencies such as EMA and the Food and Drug Administration (FDA). According to ICH guidance, an estimand is defined on the basis of five attributes: (1) treatment(s); (2) target population; (3) clinical outcome of interest; (4) population-level summary effect measure; and (5) strategy for intercurrent (post-randomization) events.
In HTA, the PICO framework is typically used to translate policy questions into research questions. PICOs consist of five components: (1) population; (2) intervention; (3) comparator(s); and (4) outcome. During the reimbursement process, the manufacturer typically submits an evidence dossier that addresses the research questions(s) included in the scope. Best-practice guidelines recommend specifying relevant PICO question(s) in the HTA scoping process [2]. In evidence synthesis, PICO questions are often formulated prior to the analysis in order to guide the data extraction required for systematic literature reviews [3].
The Target Trial Emulation (TTE), developed by Hernan et al. (2016) [3], is a framework proposed for Real-World Data studies to minimize common biases due to selection or confounding. TTE is a two-step process, whereby a protocol for an hypothetical RCT that would answer the question of interest is developed; This protocol is applied to the Real-World Data so that it mimics the data that would have been gathered for the RCT [5]. In this framework, eligibility criteria, treatment strategies, assignment procedures, follow-up period, outcome, causal contrasts of interest and analysis plan should be specified. Gomes, Latimer, Soares et al., in [4], discusses opportunities and challenges of using TTE with Real-World-Data in the HTA context.
In this webinar series, we will compare and contrast all three frameworks and discuss how they may complement each other, also in light of the new EU HTA regulation.
This webinar brings together Antonio Remiro-Azocar, Robert Hemmings and Nicholas Latimer, who are renowned experts in the respective fields. They will provide an introduction to these three concepts, illustrated with examples, thus enabling a solid understanding of these frameworks as well as their communalities and differences. A Q&A session will provide opportunities for the audience to engage with the speakers and clarify any questions.
[1] https://pubmed.ncbi.nlm.nih.gov/26908545/
[3] https://pubmed.ncbi.nlm.nih.gov/17573961/
[4] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832051/
[5] https://link.springer.com/article/10.1007/s40273-022-01141-x
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Speaker |
Biography |
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Robert Hemmings is currently partner at Consilium Salmonson & Hemmings and has deep expertise in global clinical trial design, critical appraisal of clinical trial data and regulatory affairs. He was head of the group of statisticians and pharmacokineticists at the Medicines and Healthcare Products Regulatory Agency (MHRA) in the UK for nearly 20 years. He has been a member of the Committee for Medicinal Products for Human Use (CHMP) at the EMA for 11 years, has chaired EMA’s Scientific Advice Working Party 8 years, and chaired and served on EMA’s groups for biostatistics, modelling and simulation and extrapolation. Hemmings also represented the EU and was the Rapporteur for the revision of the ICH guideline E9 (R)1 addendum on estimands and sensitivity analysis in clinical trials, to the guideline on statistical principles for clinical trials. Additionally, he has involvement in multiple initiatives related to innovation in clinical trial design and regulatory strategy including, EMA’s Priority Medicines (PRIME) scheme for unmet medical needs, adaptable pathways, and accelerated access pathways in the UK. |
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Nicholas Latimer is professor of Health Economics at the School of Medicine and Population Health of the University of Sheffield, UK. His research interests focus on economic evaluation methodology, with a particular emphasis on the incorporation of survival analysis within economic models. Professor Latimer is especially interested in the use of causal inference methods to estimate comparative effectiveness in clinical trials confounded by treatment switching, and in observational (or “Big”, or “Real World”) data. Professor Latimer is currently undertaking a Senior Research Fellowship funded by Yorkshire Cancer Research. During this Fellowship, his focus is on investigating the use of cancer registry datasets to estimate the comparative effectiveness of cancer treatments used in the NHS. |
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Antonio is Lead Medical Affairs Statistician at Bayer, specializing in health technology assessment (HTA), health economics and outcomes research (HEOR), and observational studies. At Bayer, Antonio leads cross-functional teams in providing inputs to life-cycle management strategies, publication plans, reimbursement requirements, HTA studies and analyses for payers, across a number of therapeutic areas. Prior to his current role, Antonio provided support on the statistical aspects of evidence synthesis, HTA and HEOR to contract research organizations such as IQVIA and ICON plc, and public bodies such as SickKids. Antonio holds a PhD in Statistical Science and an MSc in Machine Learning from University College London. |
