Speaker

Biography

Abstract

Rachel Hodge
Astrazeneca

Session chair: Fabio Rigat, Janssen. 

Rachel Hodge is Director and Biometric Team Leader at AstraZeneca which she joined 6 years ago. Rachel led the development of Tagrisso in NSCLC through its multiple filings and designed several studies. Rachel is also the statistical lead for the ctDNA workstream at AstraZeneca. Previously, Rachel worked at GSK where she designed and reported several phase 2 and phase 3 oncology trials. Rachel holds an MSc in Statistics from the University of Sheffield.

Expanding Uses for ctDNA in Clinical Trial Design

In this introduction, two main uses of ctDNA will be presented and discussed. Firstly, ctDNA as a measure of minimal residual disease (MRD) allows to detect patients at higher of disease relapse. Multiple ctDNA assay may be required and personalised assay can be developed. This has various implications for study designs focusing on patients with MRD. Secondary, ctDNA can serve as response evaluation criteria. Many examples exist in leukemia. The challenges to use ctDNA as surrogate endpoint in solid tumors will be discussed. 

Thomas Jaki
MRC Biostatistics Unit

Session chair: Rhiannon Maudsley, AstraZeneca.

Professor Thomas Jaki is Programme Leader in the DART theme at the MRC Biostatistics clinical trial unit in Cambridge. Thomas has been Professor of Statistics at University of Lancaster, where he has led several substantial research projects and is head of Medical Statistics. His work has focused on developing and evaluating novel statistical methods for clinical and pre-clinical studies. These methods are adapted for specific applications to ensure they can be used in the pharmaceutical industry and in public sector research institutions. Thomas will lead this evolving research theme into a new era, developing new streams of clinical trials tackling current public health challenges, including COVID-19.

Thoughts on Late-Onset Toxicities in dose-finding studies

Phase I dose-finding trials often seek to identify the maximum tolerated dose; the dosewith a particular risk of toxicity and only toxicities during the first cycle of therapy are used for this purpose.A course of treatment frequently consists of multiple cycles of therapy, however, so that theoverall risk of toxicity for a given treatment is not fully encapsulated by observations from the first cycle. This talk will discuss the challenges that arise when the toxicity period is extended and discuss different methods to account for such late onset toxicities

Archan Bhattacharya
Janssen

Session chair: Thomas Jaki, MRC Biostatistics clinical trial unit.

Archan Bhattacharya is a clinical statistician at Janssen, working on design and analysis of lung cancer trials. Prior to joining Janssen, Archan worked at PAREXEL where he supported oncology development programs targeting solid tumours and multiple myeloma with small molecules, drug-antibody conjugates and T-cell therapy. Prior to working in oncology, Archan was a CRO statistician on phase III/IV rheumatoid arthritis trials. He received his PhD in Statistics from the University of Georgia focusing in on Bayesian inference and computation. He has been a research fellow at the University of Nottingham, working on the identification of contributing factors in osteoarthritis to reduce disease burden through life-style changes and social awareness. He taught Statistics at different levels in universities in India.

Integration of real world data in oncology early development studies

Single arm phase 1 trials are important in early clinical development process across all therapeutic area and in oncology as well. Lack of control arms always raise the question of ability to generalise its findings as well. Health authorities are more keen to know about performance of novel treatment as compared to what has been available. Not to mention, it has become an integral part of health economics modelling and market access applications. I am going to go through my recent experience about an external control arm study starting from real world data acquisition, data quality, protocol development, covariate balancing, process development and dissemination.

Nigel Stallard
University of Warwick

Session chair: Emma Clark, Roche.

Nigel Stallard is Professor of Medical Statistics, Head of the Statistics and Epidemiology Group and Deputy Head of the Division of Health Sciences at Warwick Medical School. Professor Stallard's primary research interests are in the statistical design and analysis of clinical trials. In particular, he has worked on optimal trial design and on methodology for clinical trials with interim analyses and adaptations such as treatment selection. His most recent work involves the use of short-term endpoint data for decision-making during the course of a clinical trial and the development of innovative methods for clinical trials in small populations.

Multiplicity in confirmatory clinical trials with master protocol designs

Recent advances in tumour biology and targeted therapies have led to clinical trials considering treatment effects in multiple subgroups of the patient population. These can lead to efficiency gains by testing several statistical hypotheses in the same clinical trial. Recently proposed approaches include adaptive enrichment, umbrella and basket trial designs. Although much of the development of novel designs has been in exploratory phase II trials, there is growing interest in such methods in confirmatory randomized controlled trials. These might be phase III trials with subgroup analyses or phase II/III trials combining exploratory and confirmatory elements. In such a setting, the multiple hypothesis tests can lead to statistical error rate inflation and hence to the question of when statistical correction for multiplicity should be implemented. This talk will survey the novel design approaches for clinical trials with subgroups and explore the multiplicity issues that arise. Based on this, a proposal will be made for when multiplicity corrections are needed for confirmatory trials employing such innovative designs.

Emma Clark
Roche

Session chair: Kirsty Hicks, GSK.

FDA Complex Innovative Design Pilot: experience of using external control data to analyse secondary endpoints

Randomized phase 3 studies are considered the gold standard for registrational purposes. On the other hand, inclusion of external controls has perceived benefits in terms of costs, timelines, and sparing new patients from control arm treatment but also comes with potential risks such as Type 1 error inflation. Health Authorities are understandably cautious of approving such designs. This talk will focus on our experience of collaborating with the FDA on the design of a phase 3 study in 1L Diffuse Large B-Cell Lymphoma (DLBCL), incorporating a hybrid external control arm using Bayesian dynamic borrowing with propensity score matching for the analysis of overall survival, a key secondary endpoint, through the FDA’s Complex Innovation Trial Designs (CID) Pilot Meeting Program. The proposed design brings in the key secondary analysis with increased power and a label-enabling potential at the same time as the primary endpoint.