PSI Events

PSI One Day Meeting: Bayesian Methods for Dose Finding and Biomarkers

  • Dates: 28 – 28 Feb, 2018
Timings: 09:30 - 17:00 UK Time
Location: Royal Statistical Society
Address: 12 Errol Street, London

Bayesian methods are being increasingly used in the design and analysis of trials through all stages of clinical drug development. This meeting will include talks on two areas of application commonly used in early phase trials – dose selection and biomarkers. The meeting will include a range of case studies presented from different therapeutic areas. More details to follow. 

Click here to register.

Agenda

Time

Agenda

09.30 - 09.55 Registration

09.55 - 10.00

Welcome and Introduction

10.00 - 10.40

Title to be confirmed
Andy Grieve, UCB Pharma

10.40 - 11.20

Model based dose escalation: in practice
Phil Overend, AstraZeneca

11.20 - 11.40

Break

11.40 - 12.20

A Bayesian information theoretic design for phase I dose finding trials without monotonicity assumption
Pavel Mozganov, University of Lancaster

12.20 - 13.00

Bayesian hierarchical model for dose escalation
Alessandro Matano, Novartis

13.00 - 13.50

Lunch

13.50 - 14.30

The use of formally elicited priors to aid the design of a phase 2B dose ranging study
Doug Thompson, GlaxoSmithKline

14.30 -15.10

Bayesian methods for design and analysis of clinical trials assessing multiple treatments and biomarkers
Prof James Wason, MRC Biostatistics Unit

15.10 - 15.30

Break

15.30 - 16.10

Error rates control via shrinkage priors in multivariate error-in-variable dose-response models
Fabio Rigat, GlaxoSmithKline

16.10 - 16.50

Prior elicitation and translation of biomarkers to aid clinical development plans and compound selection
Trevor Smart, Lilly

16.50 - 17.00

Close


Abstracts

Andy Grieve, UCB Details to be confirmed
Phil Overend, AstraZeneca

Title: Model based dose escalation: in practice

Abstract: At AstraZeneca, the implementation of a model based Bayesian dose escalation design in Oncology phase 1 studies has been facilitated by putting practical considerations in place that address the operational challenges that arise due to increased statistical complexity that accompanies the methodology. We will discuss a practical case study, describing the first time that this approach was implemented at AstraZeneca, including the options explored for specifying the prior, the advantages of the approach together with practical and methodological learnings for future studies.  The extension to 2-drug combination dose escalation studies will be introduced.

Pavel Mozgunov

Pavel Mozgunov, University of Lancaster
Title: A Bayesian information theoretic design for phase I dose finding trials without monotonicity assumption

Abstract: Methods for finding the highest dose that has an acceptable risk of toxicity in Phase I dose-escalation clinical trials assuming a monotonic dose-response relationship have been studied extensively in recent decades. The assumption of monotonicity is fundamental in these methods. As a result, such designs fail to identify the correct dose when the dose-response relationship is non-monotonic, for example, in dose-schedules and dose-combinations trials. We propose a dose-escalation method that does not require monotonicity or any pre-specified relationship between dose levels. The design is based on the Bayesian model incorporating an information-theoretic criterion for dose selections. We will discuss the practical aspects of the design such as prior and safety stopping. For small sample size typical for dose-escalation studies we will show in simulations that the proposed method is comparable to well-studied and used methods under the assumption of monotonicity and outperforms them when this assumption is violated. We conclude with an extension of the design which allows to include an efficacy endpoint.

Alessandro Matano

Alessandro Matano, Novartis
Title: Bayesian hierarchical model for dose escalation

Abstract: Clinical trials with multiple strata (e.g. indication, dose regimen, mutation status) are increasingly used in drug development. In dose escalation trials, where data are often sparse and a multiple strata analysis may be the only option to study a new treatment, good statistical inference and decision-making can be challenging. Inferences from simple pooling or stratification are known to be inferior to hierarchical modeling methods, which build on exchangeable strata parameters to allow borrowing information across strata. However, the standard exchangeability (EX) assumption bears the risk of too much shrinkage and excessive borrowing for extreme strata. This talk will present the exchangeability-nonexchangeability (EXNEX) approach in dose finding studies, as a robust extension of the standard EX approach. It allows each stratum-specific parameter to be exchangeable with other similar strata parameters or nonexchangeable with any of them. A case study from a Phase I trial will also be shown.

Doug Thompson

Doug Thompson, GSK
Title: The use of formally elicited priors to aid the design of a phase 2B dose ranging study

Abstract: Prior distributions formally elicited about the mean response at certain dose levels can be used to set certain constraints such that a spread of plausible three parameter E-max curves may be generated. In this presentation we will discuss our recent experiences in the development of a dose response trial simulator. We will illustrate how we have used our simulator to help characterise interim futility rules, dose adaptation rules and assurance calculations.

James Wason

Prof James Wason, MRC Biostatistics Unit
Title: Bayesian methods for design and analysis of clinical trials assessing multiple treatments and biomarkers

Abstract: Response to treatments is often highly heterogeneous, especially ones that are targeted at specific biological pathways. The increasing availability of biomarkers and targeted treatments has led to the need for trial designs that efficiently test new treatments in biomarker-stratified patient subgroups. Often new treatments are targeted at a specific biomarker subgroup, but may in fact work in a narrower or broader set of patients.

I will discuss Bayesian adaptive methodology for trials that have multiple treatments and biomarkers. The proposed design incorporates biological hypotheses about the links between treatments and biomarker subgroups, but allows alternative links to be formed during the trial. The statistical properties of the method compare well to alternative designs available.  This design has been developed for trials in ovarian cancer and breast cancer and some methodology issues specific to each application will be discussed. These include the use of continuous biomarker information to allocate patients and adding in new treatments and biomarkers during the trial.

Fabio Rigat, GSK Title: Error rates control via shrinkage priors in multivariate error-in-variable dose-response models

Abstract: When planning & analysing limited numbers of dose-response data, the risk of false positive results may be considerable. In this case, priors can be used to penalise inferences for dose-response parameters so as to reduce this risk. We demonstrate a simple example of such priors for analysing the multivariate relation between the dose of an investigational asset administered to a cohort of cancer patients and the associated average change in the expression of several target genes. This analysis is further robustified by identifying error terms capturing the technical variability of these biomarker data from those representing sampling variation. 
Trevor Smart, Lilly Title: Prior elicitation and translation of biomarkers to aid clinical development plans and compound selection

Abstract: The talk will show how prior elicitation of a pharmacodynamic (PD) biomarker can be used to estimate a design prior to be used in designing clinical trials.  In addition, if the translation of the biomarker to efficacy or safety is elicited, then this can help evaluate the benefits of the biomarker and how decisions may be made based on the biomarker.  An example will be given where efficacy and safety biomarkers are used to compare several compounds being considered for the same indication.  The elicitation of the translation allows us to weigh up which biomarker is most relevant in making the decision over which compound to progress first.  When this decision can be made, pre-clinical, Phase 1 or Phase 2, can be compared.


Click here to register. 


 

Registration Fees

PSI Member

£40 + VAT

Non-Member

£135 + VAT
(This includes PSI membership for the remainder of 2018)



Please register before Wednesday 21st February 2018. 

Please contact the PSI secretariat on psi@mci-group.com if you have any dietary requirements or queries about the event.

Andy Grieve, UCB Pharma

Andy Grieve, UCB Pharma

Andy Grieve, UCB Pharma

Bayesian methods in a seamless Phase 2/3 diabetes trial
Tom Parke, Berry Consultants

Error rates control via shrinkage priors in multivariate error-in-variable dose-response models
Fabio Rigat, GSK

Error rates control via shrinkage priors in multivariate error-in-variable dose-response models
Fabio Rigat, GSK

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