Hans-Joachim Helms
(Roche)

Hans-Joachim Helms is a Principal Statistical Scientist at F. Hoffmann-La Roche (Basel) having joined in 2014. He is currently working in oncology early development (pRED) and is supporting the platform trials in the Morpheus program.

He started as a study statistician in oncology, late stage breast cancer supporting multiple Phase 3 trials as well as several initiatives around event tracking to predict trail readouts.

Before joining Roche, he did his Master degree in mathematics (Dipl. Math.) at the Georg-August-University Göttingen and his PhD in Biostatistics at the Medical Center Göttingen (Germany). During his PhD he did two internships at the German Federal Institute for Drugs and Medical Devices (BfArM).

An introduction into the Morpheus program

This Presentation will introduce the general idea and framework of the platform trials in the Roche Morpheus program. These platform trials include several Phase 1b signal detection studies in various cancer indications to detect promising new anti-cancer drug combinations. The presentation will focus on the Morpheus Lung study in metastatic NSCLC to describe the study set-up and statistical properties including gating considerations. In addition operational and logistical challenges including interactions with health authorities will be discussed.

Andrew Thomson 
(EMA)

Andrew Thomson is a statistician at the EMA Taskforce dedicated to Data, Analytics and Methodology, joining the Agency in 2014. He supports the methodological aspects of the assessments of Marketing Authorisation Applications, as well as Scientific Advice, and methodological aspects of Paediatric Investigational Plans. Additionally he is the EC lead for ICH E11A where he leads the statistical workstream. Prior to the EMA, he worked at the UK regulator, the Medicines and Healthcare product Regulatory Agency. Here he worked initially as a statistical assessor in the Licensing Division, assessing Marketing Application Authorisations and providing Scientific Advice to companies. After rising to Senior Statistical Assessor, he moved to the Vigilance and Risk Management of Medicines Division, to be Head of Epidemiology. Here he managed a team of statisticians, epidemiologists and data analysts providing support to the assessment of post-licensing observational studies and meta-analyses. He also managed the team’s design, conduct and analysis of epidemiology studies, using the UK Clinical Practice Research Datalink.

A regulatory view on platform trials – errors, decisions, and information leakage

One of the increasingly common master protocol proposals - platform trials - has raised a number of challenging questions and debates, especially as regards trial methodology and clinical interpretation of the results. The methodological challenges cover a broad spectrum of experimental design aspects, ranging from randomization and stratification, level of replication, ways of blinding different treatment modalities, and advantages/disadvantages to include different treatments in the same trial. From a statistical and regulatory perspective, one of the most important considerations that has emerged from these discussions is the control of the Type 1 Error. The potentially large number of substudies and treatments constituting a master protocol, and some proposed uses of Bayesian decision criteria especially with frequent interim analyses, raises the question as to whether this necessitates a more critical assessment of the types of errors that we are making, which is of utmost importance for regulators in confirmatory trials.

Martin Posch
(Medical University of Vienna)

Martin Posch is professor of Medical Statistics at the Medical University of Vienna and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-202 he worked as statistical expert at the European Medicines Agency (London, UK) in the Human Medicines Development and Evaluation sector, where he contributed to guideline development and the assessment of study designs. He has a PhD in Mathematics from the University of Vienna and was scientific assistant and associate professor at the Medical University of Vienna. His research interests are group sequential trials, adaptive designs and multiple testing, focusing on applications in clinical trials and Bioinformatics. Martin Posch serves as Associate Editor of Biometrics and Biometrical Journal and contributes to the Biostatistics Working Party of the European Medicines Agency.

Current statistical issues in platform trials for the evaluation of multiple treatments

Adaptive platform trials provide a framework to simultaneously study multiple treatments in a disease. They are multi-armed trials where interventions can enter and leave the platform based on interim analysis as well as external events, for example if new treatments become available. The attractiveness of platform trials compared to separate parallel group trials is not only due to operational aspects as a joint trial infrastructure and more efficient patient recruitment, but results also from the possibility to share control groups, to efficiently prune non-efficacious treatments, and to allow for direct comparisons between experimental treatment arms. However, the flexibility of the framework also comes with challenges for statistical inference and interpretation of trial results as the adaptivity of platform trials (decisions on the addition or dropping of arms cannot be fully pre-specified but may have an impact on current trial arms), multiplicity issues (due to multiple interventions, subgroups and interim analysis) and the use of shared controls (non-concurrent controls and blinding for interventions that have different routes of administration, change in standard of care). We will highlight some statistical approaches to address these issues. Furthermore, we give an overview of the IMI project EU-PEARL (Grant Agreement no. 853966) that aims to establish a general framework for platform trials, including the necessary statistical and methodological tools.

Hans-Joachim Helms
(Roche)

Hans-Joachim Helms is a Principal Statistical Scientist at F. Hoffmann-La Roche (Basel) having joined in 2014. He is currently working in oncology early development (pRED) and is supporting the platform trials in the Morpheus program.

He started as a study statistician in oncology, late stage breast cancer supporting multiple Phase 3 trials as well as several initiatives around event tracking to predict trail readouts.

Before joining Roche, he did his Master degree in mathematics (Dipl. Math.) at the Georg-August-University Göttingen and his PhD in Biostatistics at the Medical Center Göttingen (Germany). During his PhD he did two internships at the German Federal Institute for Drugs and Medical Devices (BfArM).

An introduction into the Morpheus program

This Presentation will introduce the general idea and framework of the platform trials in the Roche Morpheus program. These platform trials include several Phase 1b signal detection studies in various cancer indications to detect promising new anti-cancer drug combinations. The presentation will focus on the Morpheus Lung study in metastatic NSCLC to describe the study set-up and statistical properties including gating considerations. In addition operational and logistical challenges including interactions with health authorities will be discussed.

Andrew Thomson 
(EMA)

Andrew Thomson is a statistician at the EMA Taskforce dedicated to Data, Analytics and Methodology, joining the Agency in 2014. He supports the methodological aspects of the assessments of Marketing Authorisation Applications, as well as Scientific Advice, and methodological aspects of Paediatric Investigational Plans. Additionally he is the EC lead for ICH E11A where he leads the statistical workstream. Prior to the EMA, he worked at the UK regulator, the Medicines and Healthcare product Regulatory Agency. Here he worked initially as a statistical assessor in the Licensing Division, assessing Marketing Application Authorisations and providing Scientific Advice to companies. After rising to Senior Statistical Assessor, he moved to the Vigilance and Risk Management of Medicines Division, to be Head of Epidemiology. Here he managed a team of statisticians, epidemiologists and data analysts providing support to the assessment of post-licensing observational studies and meta-analyses. He also managed the team’s design, conduct and analysis of epidemiology studies, using the UK Clinical Practice Research Datalink.

A regulatory view on platform trials – errors, decisions, and information leakage

One of the increasingly common master protocol proposals - platform trials - has raised a number of challenging questions and debates, especially as regards trial methodology and clinical interpretation of the results. The methodological challenges cover a broad spectrum of experimental design aspects, ranging from randomization and stratification, level of replication, ways of blinding different treatment modalities, and advantages/disadvantages to include different treatments in the same trial. From a statistical and regulatory perspective, one of the most important considerations that has emerged from these discussions is the control of the Type 1 Error. The potentially large number of substudies and treatments constituting a master protocol, and some proposed uses of Bayesian decision criteria especially with frequent interim analyses, raises the question as to whether this necessitates a more critical assessment of the types of errors that we are making, which is of utmost importance for regulators in confirmatory trials.

Martin Posch
(Medical University of Vienna)

Martin Posch is professor of Medical Statistics at the Medical University of Vienna and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-202 he worked as statistical expert at the European Medicines Agency (London, UK) in the Human Medicines Development and Evaluation sector, where he contributed to guideline development and the assessment of study designs. He has a PhD in Mathematics from the University of Vienna and was scientific assistant and associate professor at the Medical University of Vienna. His research interests are group sequential trials, adaptive designs and multiple testing, focusing on applications in clinical trials and Bioinformatics. Martin Posch serves as Associate Editor of Biometrics and Biometrical Journal and contributes to the Biostatistics Working Party of the European Medicines Agency.

Current statistical issues in platform trials for the evaluation of multiple treatments

Adaptive platform trials provide a framework to simultaneously study multiple treatments in a disease. They are multi-armed trials where interventions can enter and leave the platform based on interim analysis as well as external events, for example if new treatments become available. The attractiveness of platform trials compared to separate parallel group trials is not only due to operational aspects as a joint trial infrastructure and more efficient patient recruitment, but results also from the possibility to share control groups, to efficiently prune non-efficacious treatments, and to allow for direct comparisons between experimental treatment arms. However, the flexibility of the framework also comes with challenges for statistical inference and interpretation of trial results as the adaptivity of platform trials (decisions on the addition or dropping of arms cannot be fully pre-specified but may have an impact on current trial arms), multiplicity issues (due to multiple interventions, subgroups and interim analysis) and the use of shared controls (non-concurrent controls and blinding for interventions that have different routes of administration, change in standard of care). We will highlight some statistical approaches to address these issues. Furthermore, we give an overview of the IMI project EU-PEARL (Grant Agreement no. 853966) that aims to establish a general framework for platform trials, including the necessary statistical and methodological tools.

Hans-Joachim Helms
(Roche)

Hans-Joachim Helms is a Principal Statistical Scientist at F. Hoffmann-La Roche (Basel) having joined in 2014. He is currently working in oncology early development (pRED) and is supporting the platform trials in the Morpheus program.

He started as a study statistician in oncology, late stage breast cancer supporting multiple Phase 3 trials as well as several initiatives around event tracking to predict trail readouts.

Before joining Roche, he did his Master degree in mathematics (Dipl. Math.) at the Georg-August-University Göttingen and his PhD in Biostatistics at the Medical Center Göttingen (Germany). During his PhD he did two internships at the German Federal Institute for Drugs and Medical Devices (BfArM).

An introduction into the Morpheus program

This Presentation will introduce the general idea and framework of the platform trials in the Roche Morpheus program. These platform trials include several Phase 1b signal detection studies in various cancer indications to detect promising new anti-cancer drug combinations. The presentation will focus on the Morpheus Lung study in metastatic NSCLC to describe the study set-up and statistical properties including gating considerations. In addition operational and logistical challenges including interactions with health authorities will be discussed.

Andrew Thomson 
(EMA)

Andrew Thomson is a statistician at the EMA Taskforce dedicated to Data, Analytics and Methodology, joining the Agency in 2014. He supports the methodological aspects of the assessments of Marketing Authorisation Applications, as well as Scientific Advice, and methodological aspects of Paediatric Investigational Plans. Additionally he is the EC lead for ICH E11A where he leads the statistical workstream. Prior to the EMA, he worked at the UK regulator, the Medicines and Healthcare product Regulatory Agency. Here he worked initially as a statistical assessor in the Licensing Division, assessing Marketing Application Authorisations and providing Scientific Advice to companies. After rising to Senior Statistical Assessor, he moved to the Vigilance and Risk Management of Medicines Division, to be Head of Epidemiology. Here he managed a team of statisticians, epidemiologists and data analysts providing support to the assessment of post-licensing observational studies and meta-analyses. He also managed the team’s design, conduct and analysis of epidemiology studies, using the UK Clinical Practice Research Datalink.

A regulatory view on platform trials – errors, decisions, and information leakage

One of the increasingly common master protocol proposals - platform trials - has raised a number of challenging questions and debates, especially as regards trial methodology and clinical interpretation of the results. The methodological challenges cover a broad spectrum of experimental design aspects, ranging from randomization and stratification, level of replication, ways of blinding different treatment modalities, and advantages/disadvantages to include different treatments in the same trial. From a statistical and regulatory perspective, one of the most important considerations that has emerged from these discussions is the control of the Type 1 Error. The potentially large number of substudies and treatments constituting a master protocol, and some proposed uses of Bayesian decision criteria especially with frequent interim analyses, raises the question as to whether this necessitates a more critical assessment of the types of errors that we are making, which is of utmost importance for regulators in confirmatory trials.

Martin Posch
(Medical University of Vienna)

Martin Posch is professor of Medical Statistics at the Medical University of Vienna and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-202 he worked as statistical expert at the European Medicines Agency (London, UK) in the Human Medicines Development and Evaluation sector, where he contributed to guideline development and the assessment of study designs. He has a PhD in Mathematics from the University of Vienna and was scientific assistant and associate professor at the Medical University of Vienna. His research interests are group sequential trials, adaptive designs and multiple testing, focusing on applications in clinical trials and Bioinformatics. Martin Posch serves as Associate Editor of Biometrics and Biometrical Journal and contributes to the Biostatistics Working Party of the European Medicines Agency.

Current statistical issues in platform trials for the evaluation of multiple treatments

Adaptive platform trials provide a framework to simultaneously study multiple treatments in a disease. They are multi-armed trials where interventions can enter and leave the platform based on interim analysis as well as external events, for example if new treatments become available. The attractiveness of platform trials compared to separate parallel group trials is not only due to operational aspects as a joint trial infrastructure and more efficient patient recruitment, but results also from the possibility to share control groups, to efficiently prune non-efficacious treatments, and to allow for direct comparisons between experimental treatment arms. However, the flexibility of the framework also comes with challenges for statistical inference and interpretation of trial results as the adaptivity of platform trials (decisions on the addition or dropping of arms cannot be fully pre-specified but may have an impact on current trial arms), multiplicity issues (due to multiple interventions, subgroups and interim analysis) and the use of shared controls (non-concurrent controls and blinding for interventions that have different routes of administration, change in standard of care). We will highlight some statistical approaches to address these issues. Furthermore, we give an overview of the IMI project EU-PEARL (Grant Agreement no. 853966) that aims to establish a general framework for platform trials, including the necessary statistical and methodological tools.

Hans-Joachim Helms
(Roche)

Hans-Joachim Helms is a Principal Statistical Scientist at F. Hoffmann-La Roche (Basel) having joined in 2014. He is currently working in oncology early development (pRED) and is supporting the platform trials in the Morpheus program.

He started as a study statistician in oncology, late stage breast cancer supporting multiple Phase 3 trials as well as several initiatives around event tracking to predict trail readouts.

Before joining Roche, he did his Master degree in mathematics (Dipl. Math.) at the Georg-August-University Göttingen and his PhD in Biostatistics at the Medical Center Göttingen (Germany). During his PhD he did two internships at the German Federal Institute for Drugs and Medical Devices (BfArM).

An introduction into the Morpheus program

This Presentation will introduce the general idea and framework of the platform trials in the Roche Morpheus program. These platform trials include several Phase 1b signal detection studies in various cancer indications to detect promising new anti-cancer drug combinations. The presentation will focus on the Morpheus Lung study in metastatic NSCLC to describe the study set-up and statistical properties including gating considerations. In addition operational and logistical challenges including interactions with health authorities will be discussed.

Andrew Thomson 
(EMA)

Andrew Thomson is a statistician at the EMA Taskforce dedicated to Data, Analytics and Methodology, joining the Agency in 2014. He supports the methodological aspects of the assessments of Marketing Authorisation Applications, as well as Scientific Advice, and methodological aspects of Paediatric Investigational Plans. Additionally he is the EC lead for ICH E11A where he leads the statistical workstream. Prior to the EMA, he worked at the UK regulator, the Medicines and Healthcare product Regulatory Agency. Here he worked initially as a statistical assessor in the Licensing Division, assessing Marketing Application Authorisations and providing Scientific Advice to companies. After rising to Senior Statistical Assessor, he moved to the Vigilance and Risk Management of Medicines Division, to be Head of Epidemiology. Here he managed a team of statisticians, epidemiologists and data analysts providing support to the assessment of post-licensing observational studies and meta-analyses. He also managed the team’s design, conduct and analysis of epidemiology studies, using the UK Clinical Practice Research Datalink.

A regulatory view on platform trials – errors, decisions, and information leakage

One of the increasingly common master protocol proposals - platform trials - has raised a number of challenging questions and debates, especially as regards trial methodology and clinical interpretation of the results. The methodological challenges cover a broad spectrum of experimental design aspects, ranging from randomization and stratification, level of replication, ways of blinding different treatment modalities, and advantages/disadvantages to include different treatments in the same trial. From a statistical and regulatory perspective, one of the most important considerations that has emerged from these discussions is the control of the Type 1 Error. The potentially large number of substudies and treatments constituting a master protocol, and some proposed uses of Bayesian decision criteria especially with frequent interim analyses, raises the question as to whether this necessitates a more critical assessment of the types of errors that we are making, which is of utmost importance for regulators in confirmatory trials.

Martin Posch
(Medical University of Vienna)

Martin Posch is professor of Medical Statistics at the Medical University of Vienna and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-202 he worked as statistical expert at the European Medicines Agency (London, UK) in the Human Medicines Development and Evaluation sector, where he contributed to guideline development and the assessment of study designs. He has a PhD in Mathematics from the University of Vienna and was scientific assistant and associate professor at the Medical University of Vienna. His research interests are group sequential trials, adaptive designs and multiple testing, focusing on applications in clinical trials and Bioinformatics. Martin Posch serves as Associate Editor of Biometrics and Biometrical Journal and contributes to the Biostatistics Working Party of the European Medicines Agency.

Current statistical issues in platform trials for the evaluation of multiple treatments

Adaptive platform trials provide a framework to simultaneously study multiple treatments in a disease. They are multi-armed trials where interventions can enter and leave the platform based on interim analysis as well as external events, for example if new treatments become available. The attractiveness of platform trials compared to separate parallel group trials is not only due to operational aspects as a joint trial infrastructure and more efficient patient recruitment, but results also from the possibility to share control groups, to efficiently prune non-efficacious treatments, and to allow for direct comparisons between experimental treatment arms. However, the flexibility of the framework also comes with challenges for statistical inference and interpretation of trial results as the adaptivity of platform trials (decisions on the addition or dropping of arms cannot be fully pre-specified but may have an impact on current trial arms), multiplicity issues (due to multiple interventions, subgroups and interim analysis) and the use of shared controls (non-concurrent controls and blinding for interventions that have different routes of administration, change in standard of care). We will highlight some statistical approaches to address these issues. Furthermore, we give an overview of the IMI project EU-PEARL (Grant Agreement no. 853966) that aims to establish a general framework for platform trials, including the necessary statistical and methodological tools.

Hans-Joachim Helms
(Roche)

Hans-Joachim Helms is a Principal Statistical Scientist at F. Hoffmann-La Roche (Basel) having joined in 2014. He is currently working in oncology early development (pRED) and is supporting the platform trials in the Morpheus program.

He started as a study statistician in oncology, late stage breast cancer supporting multiple Phase 3 trials as well as several initiatives around event tracking to predict trail readouts.

Before joining Roche, he did his Master degree in mathematics (Dipl. Math.) at the Georg-August-University Göttingen and his PhD in Biostatistics at the Medical Center Göttingen (Germany). During his PhD he did two internships at the German Federal Institute for Drugs and Medical Devices (BfArM).

An introduction into the Morpheus program

This Presentation will introduce the general idea and framework of the platform trials in the Roche Morpheus program. These platform trials include several Phase 1b signal detection studies in various cancer indications to detect promising new anti-cancer drug combinations. The presentation will focus on the Morpheus Lung study in metastatic NSCLC to describe the study set-up and statistical properties including gating considerations. In addition operational and logistical challenges including interactions with health authorities will be discussed.

Andrew Thomson 
(EMA)

Andrew Thomson is a statistician at the EMA Taskforce dedicated to Data, Analytics and Methodology, joining the Agency in 2014. He supports the methodological aspects of the assessments of Marketing Authorisation Applications, as well as Scientific Advice, and methodological aspects of Paediatric Investigational Plans. Additionally he is the EC lead for ICH E11A where he leads the statistical workstream. Prior to the EMA, he worked at the UK regulator, the Medicines and Healthcare product Regulatory Agency. Here he worked initially as a statistical assessor in the Licensing Division, assessing Marketing Application Authorisations and providing Scientific Advice to companies. After rising to Senior Statistical Assessor, he moved to the Vigilance and Risk Management of Medicines Division, to be Head of Epidemiology. Here he managed a team of statisticians, epidemiologists and data analysts providing support to the assessment of post-licensing observational studies and meta-analyses. He also managed the team’s design, conduct and analysis of epidemiology studies, using the UK Clinical Practice Research Datalink.

A regulatory view on platform trials – errors, decisions, and information leakage

One of the increasingly common master protocol proposals - platform trials - has raised a number of challenging questions and debates, especially as regards trial methodology and clinical interpretation of the results. The methodological challenges cover a broad spectrum of experimental design aspects, ranging from randomization and stratification, level of replication, ways of blinding different treatment modalities, and advantages/disadvantages to include different treatments in the same trial. From a statistical and regulatory perspective, one of the most important considerations that has emerged from these discussions is the control of the Type 1 Error. The potentially large number of substudies and treatments constituting a master protocol, and some proposed uses of Bayesian decision criteria especially with frequent interim analyses, raises the question as to whether this necessitates a more critical assessment of the types of errors that we are making, which is of utmost importance for regulators in confirmatory trials.

Martin Posch
(Medical University of Vienna)

Martin Posch is professor of Medical Statistics at the Medical University of Vienna and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-202 he worked as statistical expert at the European Medicines Agency (London, UK) in the Human Medicines Development and Evaluation sector, where he contributed to guideline development and the assessment of study designs. He has a PhD in Mathematics from the University of Vienna and was scientific assistant and associate professor at the Medical University of Vienna. His research interests are group sequential trials, adaptive designs and multiple testing, focusing on applications in clinical trials and Bioinformatics. Martin Posch serves as Associate Editor of Biometrics and Biometrical Journal and contributes to the Biostatistics Working Party of the European Medicines Agency.

Current statistical issues in platform trials for the evaluation of multiple treatments

Adaptive platform trials provide a framework to simultaneously study multiple treatments in a disease. They are multi-armed trials where interventions can enter and leave the platform based on interim analysis as well as external events, for example if new treatments become available. The attractiveness of platform trials compared to separate parallel group trials is not only due to operational aspects as a joint trial infrastructure and more efficient patient recruitment, but results also from the possibility to share control groups, to efficiently prune non-efficacious treatments, and to allow for direct comparisons between experimental treatment arms. However, the flexibility of the framework also comes with challenges for statistical inference and interpretation of trial results as the adaptivity of platform trials (decisions on the addition or dropping of arms cannot be fully pre-specified but may have an impact on current trial arms), multiplicity issues (due to multiple interventions, subgroups and interim analysis) and the use of shared controls (non-concurrent controls and blinding for interventions that have different routes of administration, change in standard of care). We will highlight some statistical approaches to address these issues. Furthermore, we give an overview of the IMI project EU-PEARL (Grant Agreement no. 853966) that aims to establish a general framework for platform trials, including the necessary statistical and methodological tools.

Hans-Joachim Helms
(Roche)

Hans-Joachim Helms is a Principal Statistical Scientist at F. Hoffmann-La Roche (Basel) having joined in 2014. He is currently working in oncology early development (pRED) and is supporting the platform trials in the Morpheus program.

He started as a study statistician in oncology, late stage breast cancer supporting multiple Phase 3 trials as well as several initiatives around event tracking to predict trail readouts.

Before joining Roche, he did his Master degree in mathematics (Dipl. Math.) at the Georg-August-University Göttingen and his PhD in Biostatistics at the Medical Center Göttingen (Germany). During his PhD he did two internships at the German Federal Institute for Drugs and Medical Devices (BfArM).

An introduction into the Morpheus program

This Presentation will introduce the general idea and framework of the platform trials in the Roche Morpheus program. These platform trials include several Phase 1b signal detection studies in various cancer indications to detect promising new anti-cancer drug combinations. The presentation will focus on the Morpheus Lung study in metastatic NSCLC to describe the study set-up and statistical properties including gating considerations. In addition operational and logistical challenges including interactions with health authorities will be discussed.

Andrew Thomson 
(EMA)

Andrew Thomson is a statistician at the EMA Taskforce dedicated to Data, Analytics and Methodology, joining the Agency in 2014. He supports the methodological aspects of the assessments of Marketing Authorisation Applications, as well as Scientific Advice, and methodological aspects of Paediatric Investigational Plans. Additionally he is the EC lead for ICH E11A where he leads the statistical workstream. Prior to the EMA, he worked at the UK regulator, the Medicines and Healthcare product Regulatory Agency. Here he worked initially as a statistical assessor in the Licensing Division, assessing Marketing Application Authorisations and providing Scientific Advice to companies. After rising to Senior Statistical Assessor, he moved to the Vigilance and Risk Management of Medicines Division, to be Head of Epidemiology. Here he managed a team of statisticians, epidemiologists and data analysts providing support to the assessment of post-licensing observational studies and meta-analyses. He also managed the team’s design, conduct and analysis of epidemiology studies, using the UK Clinical Practice Research Datalink.

A regulatory view on platform trials – errors, decisions, and information leakage

One of the increasingly common master protocol proposals - platform trials - has raised a number of challenging questions and debates, especially as regards trial methodology and clinical interpretation of the results. The methodological challenges cover a broad spectrum of experimental design aspects, ranging from randomization and stratification, level of replication, ways of blinding different treatment modalities, and advantages/disadvantages to include different treatments in the same trial. From a statistical and regulatory perspective, one of the most important considerations that has emerged from these discussions is the control of the Type 1 Error. The potentially large number of substudies and treatments constituting a master protocol, and some proposed uses of Bayesian decision criteria especially with frequent interim analyses, raises the question as to whether this necessitates a more critical assessment of the types of errors that we are making, which is of utmost importance for regulators in confirmatory trials.

Martin Posch
(Medical University of Vienna)

Martin Posch is professor of Medical Statistics at the Medical University of Vienna and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-202 he worked as statistical expert at the European Medicines Agency (London, UK) in the Human Medicines Development and Evaluation sector, where he contributed to guideline development and the assessment of study designs. He has a PhD in Mathematics from the University of Vienna and was scientific assistant and associate professor at the Medical University of Vienna. His research interests are group sequential trials, adaptive designs and multiple testing, focusing on applications in clinical trials and Bioinformatics. Martin Posch serves as Associate Editor of Biometrics and Biometrical Journal and contributes to the Biostatistics Working Party of the European Medicines Agency.

Current statistical issues in platform trials for the evaluation of multiple treatments

Adaptive platform trials provide a framework to simultaneously study multiple treatments in a disease. They are multi-armed trials where interventions can enter and leave the platform based on interim analysis as well as external events, for example if new treatments become available. The attractiveness of platform trials compared to separate parallel group trials is not only due to operational aspects as a joint trial infrastructure and more efficient patient recruitment, but results also from the possibility to share control groups, to efficiently prune non-efficacious treatments, and to allow for direct comparisons between experimental treatment arms. However, the flexibility of the framework also comes with challenges for statistical inference and interpretation of trial results as the adaptivity of platform trials (decisions on the addition or dropping of arms cannot be fully pre-specified but may have an impact on current trial arms), multiplicity issues (due to multiple interventions, subgroups and interim analysis) and the use of shared controls (non-concurrent controls and blinding for interventions that have different routes of administration, change in standard of care). We will highlight some statistical approaches to address these issues. Furthermore, we give an overview of the IMI project EU-PEARL (Grant Agreement no. 853966) that aims to establish a general framework for platform trials, including the necessary statistical and methodological tools.