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
|
Speaker |
Biography |
|
|
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. |
|
|
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. |
|
|
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. |
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
|
Speaker |
Biography |
|
|
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. |
|
|
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. |
|
|
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. |
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
|
Speaker |
Biography |
|
|
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. |
|
|
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. |
|
|
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. |
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
|
Speaker |
Biography |
|
|
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. |
|
|
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. |
|
|
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. |
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
|
Speaker |
Biography |
|
|
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. |
|
|
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. |
|
|
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. |
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. |
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
The book club’s usual focus is to read and discuss professional development books. In this short format event you can more easily develop you career without the commitment of reading the whole book - simply listen to the 1-hour long podcast before joining the interactive session on 21 May.
This webinar is organised by the RWD SIG and the Historical Data SIG. We will review recent methods, applications, and tools of integrating subject-level-data from clinical trial with external data using Bayesian methods and/or causal inference methods.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This will be a 45 minute webinar which will explain the topic presented in the published paper, ‘Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance’. There will be 15 minutes for a panel Q&A with some of the authors following the presentation.
This 1-hour webinar will be an opportunity to hear about the methodology and first results of the iRISE consortium. iRISE is working towards a better understanding of reproducibility and the interventions that work to improve it. At the end of the presentation there will also be the opportunity to ask questions.
This one-day event focuses on the comprehensive management of transitioning to R/Open-Source, addressing the challenges and providing actionable insights. Attendees will participate in sessions covering essential topics such as training best practices, creating strategic plans, making the case to senior management, and managing both statistical and programming aspects of the transition.
Develop your non-technical skills by reading The Art of Explanation by Ros Atkins and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply skills from the book in-between sessions.
This course is aimed at biostatisticians with no or some pediatric drug development experience who are interested to further their understanding. We will give you an introduction to the pediatric drug development landscape. This will include identifying the key regulations and processes governing pediatric development, a discussion on the needs and challenges when conducting pediatric research and a focus on the ways to overcome these challenges from a statistical perspective.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
The program will feature insightful sessions led by distinguished invited speakers, alongside a poster session showcasing the latest advancements in the field. Further details will be provided.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This is an exciting, new opportunity for an experienced Statistician looking to take the next step in their career. Offered as a remote or hybrid position aligned with our site in Harrogate, North Yorkshire.
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