• Decision-making in drug development

    Dates: 12 Dec, 2018
    Taking decisions during the development of a new drug requires combining many and varying pieces of information. The interconnections between them are often only partially known, reflecting the complexity of the context in which drugs are evaluated and the cognitive load required for health care decisions. Decision-makers need quantitative tools to support informed decisions, with transparent processes that synthesize the whole available information in order to evaluate the success associated to different options.

    This meeting aims to bring together statisticians from the pharmaceutical industry and academia to hear about recent advances in statistical methods for quantitative decision-making in drug development.

    Confirmed speakers include:

    Anthony O'Hagan
    University of Sheffield 
    Introduction to decision-making
    Juan Abellan
    Prior elicitation to support quantitative decision-making
    Paul Frewer
    Astra Zeneca
    Decision Making in Early Clinical Development: The framework used within AstraZeneca
    Maria Costa
    Benefit-Risk Assessment in Drug Development
    Nigel Stallard
    University of Warwick
    Decision-making in phase II/III trials using early endpoint data
    Tom Parke
    Berry Consultants
    Using simulations to optimize drug development decision-making

    Poster Session - Call for Abstracts:

    If you wish to present a poster, please send an abstract to Gaëlle Saint-Hilary (gsainthilary@gmail.com) by October 31st 2018. The notification of acceptance will be provided by November 9th 2018.

    For more details and to view the flyer, please click here.
  • PSI Webinar: How to use prior knowledge and still give new data a chance?

    Dates: 19 – 19 Dec, 2018

    Time: 15:00 - 17:00 UK time

    The paper to be presented appeared earlier this year in Pharmaceutical Statistics (Weber, Hemmings, Koch, 17, 329-341) and is motivated by the opportunities and challenges for using Bayesian methods with informative priors to support drug development and licencing when only a small pool of patients is available, as in the case of rare diseases and paediatric population. With a small study population, meeting the expected level of evidence required for regulatory approval can be challenging. The specific focus of the paper is on the use of data‐based priors in the decision-making process of paediatric extrapolation, and results are presented comparing different frequentist and Bayesian meta-analytic methods for combining adult and paediatric data.

    In this webinar, the authors will present their paper, followed by discussion on: 

     - Scientific rationale for borrowing existing data to make inference about drug effects under different settings: rare diseases, extrapolation and use of historical controls.

     - Other methods for combining historical and prospective data beyond standard meta-analytic approaches (e.g., robust MAP priors). 

     - Ways in which the Bayesian strategy could be supplemented or adapted to enable the independent contribution of the new trial data to be formally quantified and assessed. 

    We are pleased to announce that the meeting will be chaired by Byron Jones (Novartis)


     Kristina Weber
    Kristina Weber (Institute for Biostatistics, Hannover Medical School) 

    Kristina Weber is since 2014 a research associate at the Institute of Biostatistics, Hannover Medical School. Her research interests are in the development of efficient and effective research strategies in limited populations. Her PhD thesis focuses on the application of Bayesian methods in paediatric and rare diseases extrapolation concepts. She has joined Roche in November 2018.

     Rob Hemmings Rob Hemmings (MHRA)

    Rob has been with the Licensing Division within MHRA for approaching 19 years, has been a co-opted member of CHMP for 11 years; chair of the EMA’s SAWP for the past 8 years; first chair and then member of the EMA’s BSWP since its inception.

     Armin Koch

    Armin Koch (Institute for Biostatistics, Hannover Medical School)

    Professor Armin Koch studied mathematics and chemistry at Heidelberg University, has been a research assistant at the German Centre for the Research on Cancer (DKFZ) between 1984 and 1991. Thereafter he has been an employee at the Institute of Medical Biometry at Heidelberg University until in 1999 when he joined the Federal Institute for Drugs and Medical Devices (BfArM) in Germany. From 2001 to 2008 he was head of the unit „Biostatistics and Experimental Design“. Since 2008 he is Director of the Institute for Biostatistics at Hannover Medical School. Prof. Koch is a member of the Scientific Advice Working Party (SAWP) and the Biostatistics working party (BSWP) at the European Medicines Agency (EMA) and has been a member of the International Council for Harmonisation ICH-E17 working group.



     Nicky Best Nicky Best (GSK) (on behalf of the EFSPI/PSI Historical Data SIG)

    Nicky Best was an academic statistician for 20 years, starting out at the Medical Research Council Biostatistics Unit in Cambridge, UK before moving to Imperial College London, where she was professor of Statistics and Epidemiology. Her research interests focused around the development and application of Bayesian methods in health and social science, and she is a co-developer of the BUGS Bayesian software package. In 2014 she moved to GlaxoSmithKline (GSK), where she is Head of the Advanced Biostatistics and Data Analytics group. She was awarded the RSS/PSI award for Statistical Excellence in the Pharmaceutical Industry in 2015 for her leading role in implementing expert prior elicitation methods and statistical assurance calculations to improve decision making in clinical development at GSK, and the RSS Bradford Hill Medal in 2018 for her contributions to the exposition and application of Bayesian methods to clinical trials, cost-effectiveness, epidemiology and drug development programmes.

     Lisa LaVange Lisa LaVange (University of North Carolina, Chapel Hill)

    Lisa LaVange, PhD, is Professor and Associate Chair of Biostatistics, Gillings School of Global Public Health, UNC-CH.  She is also director of the department’s Collaborative Studies Coordinating Center.  From 2011 to 2017, Dr. LaVange led the Office of Biostatistics, CDER, FDA, where she directed over 200 statisticians involved in the development and application of statistical methodology for drug regulation.  Prior to her government and academic experience, she spent 16 years in non-profit research and 10 years in the pharmaceutical industry.  Dr. LaVange is an elected fellow of the American Statistical Association (ASA) and is the 2018 ASA President. 



     PSI Member  Free
     Non-member  £20 (plus VAT) 

    Please click here to register. Registration closes on December 17th at 12:00 midday (UK Time)
  • PSI Webinar: HTA Submissions in the UK

    Dates: 21 – 21 Jan, 2019
    Time: 10:00 - 12:00 UK time
    Presenters: Jessica Purchase, Group Health Economics Manager (F. Hoffmann-La Roche Ltd, Welwyn) and Monica Daigl, HTA Statistician and Health Economist (F. Hoffmann-La Roche Ltd, Basel)


    There is a simple equation for access in the UK: Access = Reimbursement + Uptake

    Yet, whilst a simple and logical approach, each component is challenging to achieve.

    This webinar focuses on the National Reimbursement side: the National Institute for Health and Care Excellence (NICE) - who they are, what is involved in the Health Technology Appraisal (HTA) assessment, how they make decisions.

    We’ll also review where the devolved nations come in: how do the Scottish Medicines Consortium (SMC) and All Wales Medicines Strategy Group (AWMSG) differ from NICE in decision making?

    Finally, through the use of a real world example, we’ll explore the key drivers and barriers experienced in decision making: specifically the challenges associated with correct comparators and predicting of long term outcomes.

    This will lead to the second part of the webinar. We will focus on two advanced statistical techniques to inform health economic models: modelling of time to event endpoints such as progression free and overall survival beyond the duration of a clinical study to predict long-term outcomes; and network meta analyses to estimate the value of a drug in the absence of direct comparative evidence.

    Finally, we provide our key recommendations for the future of clinical trial design, to support access for the UK market.

    About the Presenters:

    Jessica Purchase
    Jessica Purchase is a Group Health Economics Manager in the Health Economics and Strategic Pricing team in Roche UK. She joined Roche in 2016, following 5 years of Health Economics and Market Access consulting. In her role she has successfully lead on a variety of HTAs resulting in UK access in the oncology space.
    Jessica Purchase is a Group Health Economics Manager She joined Roche in 2016, following 5 years of Health Economics and Market Access consulting. In her role she has successfully lead on a variety of HTAs resulting in UK access in the oncology space.

    Monica Daigl
    Monica Daigl is a medical statistician and epidemiologist with >15 years of experience in the analysis of clinical trials and observational studies in pharma, medical device industry and academia. She joined 2014 the Global Access Center of Excellence at F. Hoffmann-La Roche as HTA Statistician and Health Economist. In her role she supports Roche affiliates with their local HTA submissions in multiple therapeutic areas. 


     PSI Member  Free
     Non-member  £20 (plus VAT) 

    Please click here to register.
  • PSI One Day Meeting: New Emerging Topics around Estimands and ICH Addendum

    Dates: 29 Jan, 2019

    The draft ICH E9 addendum on estimands and sensitivity analysis was released back in July 2017 and (more than 1000) comments are back. All stakeholders are gaining the necessary experience and familiarity with estimands along with the associated challenges and methodologies. The language and thinking behind causal inference is well suited to this area.

    The PSI Scientific Committee have put together this one day meeting to share and discuss new emerging topics around estimands and the ICH addendum. The aims of the event are to:

    • Share the feedback from the public consultation on the draft ICH E9 addendum
    • Explore the estimand concept within health technology assessments
    • Describe how casual inference fits into the area of estimands
    • Present case studies illustrating the implementation of the estimand framework and the use of causal inference methodology


    Time Agenda 
    09:30 - 10:00

    Registration, Welcome and introduction

    10:00 - 10:40

    ICH E9 addendum:  Key themes raised during public consultation
    Chrissie Fletcher (Amgen on behalf of the ICH E9 Working Group)

    10:40 - 11:20

    The exciting new world of the ‘Estimand’
    Anja Schiel (Norwegian Medicines Agency)

    11:35 - 12:15

    Estimand and analysis considerations of Phase 3 clinical trials involving CAR-T – A case study in lymphoma
    Emmanuel Zuber, on behalf of Novartis team 

    12:15 - 12:55

    How causal inference can fit the needs of a clinical trial (well kind of)
    Michael O’Kelly (IQVIA)

    13:45 - 14:25

    Using causal graphs to understand estimands and estimation
    Ian White (UCL)

    14:25 - 15:05

    Towards more reliable Mendelian randomization investigations
    Stephen Burgess (University of Cambridge)

    15:25 - 16:05

    Non-inferiority case study
    Oliver Keene (GSK)

    16:05 - 16:30

    Panel Discussion
    Speakers and Yolanda Barbachano (MHRA)



    Chrissie Fletcher
    (Amgen on behalf of the ICH E9 Working Group)

    ICH E9 addendum:  Key themes raised during public consultation

    Abstract: The draft ICH E9(R1) and addendum to E9 incorporating a new framework on estimands and sensitivity analyses in clinical trials was released for public consultation in the first region at the end of August 2017 and the public consultation ended in the last region by the end of April 2018.  The ICH E9 working group met in June 2018 to review the 1200+ comments that were submitted.  The ICH E9 addendum and E9(R1) is scheduled to reach step 4 and sign-off by all the ICH regions in June 2019. 

    The key themes and topics raised during the public consultation of the ICH E9 addendum will be presented.  A summary of the E9 working group discussion of the key aspects raised during public consultation and an update of how the E9 working group are trying to address the comments in the final E9 addendum will be provided. 

    Anja Schiel
    Anja Schiel (Norwegian Medicines Agency)

    The exciting new world of the ‘Estimand’

    In August 2017 the ‘ICH E9 (R1) Addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials’ was released for consultation and has stirred discussion and excitement, mainly in the regulatory world. But, what does this new framework offer to other stakeholders? The uptake of new concepts into health technology assessment is notoriously difficult because there are fundamental differences in the evidence requirements needed to establish a risk-benefit and those to establish relative effectiveness. The Estimand framework offers new possibilities to allow studies to be designed with both perspectives in mind, wherever possible. To designs studies based on the Estimand concept requires a wider communication between the different specialists involved in drug development, from pharmacologists to clinical experts and statisticians. However, this dialogue should in fact be expanded all the way to the health economists to fully harness the potential of this new framework.

    Emmanuel Zuber, on behalf of Novartis team  Estimand and analysis considerations of Phase 3 clinical trials involving CAR-T – A case study in lymphoma

    Marked by the recent approval of the first chimeric antigen receptor T cell (CAR-T) therapies, these autologous therapies provided patients with new options to fight cancer. Unique challenges arises in the design and analysis of randomized studies involving autologous CAR-T therapies. Because the CAR-T treatment strategy involves personalized manufacturing before patients can receive the final product, the scientific objective and its associated estimand must be carefully thought through to allow appropriate interpretation of study results. Different testing procedures and estimation methods will be discussed in a case study of Phase 3 clinical trial.

    Michael O’Kelly (IQVIA)


    How causal inference can fit the needs of a clinical trial (well kind of)

    Abstract: Randomisation can be thought of as providing “a ‘reasoned basis’ of testing the null hypothesis of no effect without resort to distributional assumptions such as normality” (Fisher); and indeed randomisation has been accepted as providing as close to causal inference as was needed for the approval of new treatments. However, clinical triallists are now seeing that, over the time of follow-up, intercurrent events (ICEs) result in changes to treatment. Because of this, the planned trial of a randomized treatment regimen can morph into no more than a survey whose only inference from randomisation is confined to the mere act of assigning a plan of treatment, a survey whose inference about the treatment regimen itself loses much of its credibility because those ICEs constitute non-randomized changes and distortions of the regimen to be tested. This presentation tries to convey in a non-technical manner the idea of causal inference and how it can work and be of use in clinical trials, making at least a gesture towards inference about outcomes as actually planned. Noting the overlap with missing data research, the presentation then shows a detailed example of the use of one approach to causal inference for an outcome censored by death. From the example it may be concluded that, while causal inference is probably invaluable for many clinical trial designs including the example presented, results from causal inference have their own limitations and will often need to be interpreted alongside other results, even if the other results are more open to bias than those from causal inference.

     Ian White

    Ian White (UCL)


    Using causal graphs to understand estimands and estimation

    I will talk about causal inference and estimands from the perspective of DAGs (directed acyclic graphs), which are widely used for causal inference in observational studies. DAGs allow complex statistical issues to be represented pictorially yet still rigorously. I will briefly describe the ideas of DAGs, then draw suitable DAGs for randomised trials with non-randomised treatment changes, and use them to discuss some key estimands and how these may be estimated. The talk will be conceptual rather than mathematical, and will point to types of approach rather than specific approaches.

    Stephen Burgess (University of Cambridge)

    Towards more reliable Mendelian randomization investigations

    Mendelian randomization is a technique for assessing the causal role of a modifiable risk factor on a disease outcome using genetic data. If genetic variants associated with the risk factor are also associated with the outcome, this increases the plausibility that the risk factor is a causal determinant of the outcome. However, if the genetic variants in the analysis do not have a specific biological link to the risk factor, then causal claims can be spurious. Recent advances in genome-wide association studies and the increasing availability of publicly available summary data on associations of genetic variants with risk factors and disease outcomes in large sample sizes have enabled powerful Mendelian randomization analyses to be performed relatively quickly and simply. I will present an overview of Mendelian randomization approaches from monogenic analyses, in which genetic variants are taken from a single gene region, to polygenic analyses, which include variants from multiple regions. In particular, I will discuss the reliability of such analyses and present statistical approaches for increasing their reliability.

     NI and estimands PSI Jan 19 photo
    Oliver Keene (GSK)

    Non-inferiority trials and the ICH E9 estimands framework

    The estimand framework described in the draft addendum to the ICH E9 regulatory guideline has led to a reappraisal of non-inferiority trials.  Currently, these trials often make use of a Per Protocol Population where subjects who violate the protocol are excluded.  In the estimands framework, protocol violations after randomisation can be seen as intercurrent events and subjects who do not fulfil inclusion/exclusion criteria can potentially be excluded based on the population of interest.  Therefore, the role of a Per Protocol Population is substantially diminished or eliminated entirely.

    The strategy to be employed for intercurrent events such as discontinuation of randomised treatment in the non-inferiority setting has not been established yet.  For example, some statisticians favour use of a hypothetical strategy for key intercurrent events, while others believe a treatment policy strategy provides more robust estimation.

    This talk will use a case study of a trial in COPD to illustrate how to implement the estimands framework to a non-inferiority trial.  The talk will discuss the application of different strategies for intercurrent events in the non-inferiority setting and what additional comparisons of intercurrent events will be helpful. 

     PSI Member  £40 + VAT
     Non-Member  £135 + VAT (This includes PSI membership for 2019)

    To register, please click here.

    If you require overnight accommodation before or after the event the closest hotels are Millennium Hotel and Hilton. Reading is a large town with numerous accommodation options in the town centre a short distance away.  There is a Premier Inn amongst others. Delegates should book directly with hotels.
  • Medical Statistics Careers Event 2019

    Dates: 20 Feb, 2019

    Our annual PSI Medical Statistics Careers Event, will be held at the De Montfort University in Leicester on Wednesday 20th February 2019. 

    The half-day event will include a series of talks, panel discussion, exhibition stands and a networking session. For further details or to register online, click here.  

    We look forward to seeing you there!

    PSI Careers and Academic Liaison Committee (CALC)

  • Network Meta Analysis (NMA) for Statisticians

    Dates: 07 – 08 Mar, 2019

    presented by Georgia Salanti (ISPM, Bern)

    This intensive course will cover all basic and advanced aspects of synthesis of evidence from studies comparing competing treatments for the same health condition. By the end of this course participants will have an understanding of the role and potential of network meta-analysis, the principles, steps and statistical methods involved; the biases that can distort indirect comparisons and network meta-analysis.

    This course is aimed at statisticians, epidemiologists and other quantitatively-minded researchers who are involved or may be involved in the future in the preparation of HTA submissions. Knowledge of systematic reviews and the fundamentals of meta-analysis is expected of all participants.

    The course will consist of lectures, practical examples and discussions. Participants will gain practical experience in performing analyses in R software and the freely available web application CINeMA.

    Key Topics:

    • Assumptions underlying indirect comparisons
    • Statistical methods in network meta-analysis 
    • CINeMA: a framework and software to evaluate Confidence in Network Meta-Analysis 

    Course runs from:

    Day 1: 10:30 – 18:00 
    Day 2: 8:30 – 15:30

    Click here to view the flyer


     Registration on or before 4th February 2019:
    PSI Member £595 + VAT 
    Non-Member £690 + VAT
    Registration after 4th February 2019:
    PSI Member £695 + VAT
    Non-Member £790 + VAT

    Please click here to register. Registration costs include lunch and refreshments. PSI are holding a limited number of hotel rooms on 6th and 7th March which will be allocated on a first come first served basis. Please contact psi@mci-group.com to reserve a room. 

  • PSI Conference 2019

    Dates: 02 – 05 Jun, 2019

    PSI are pleased to announce that the countdown to the 2019 Conference has begun! The theme for the conference is “Data Driven Decision Making in Medical Research”.  The 2019 PSI Conference will take place at the Queen Elizabeth II Centre (QEII), London, from 2nd to 5th June 2019.

    Registration will open in November 2018, with the early bird deadline for registrations on the 20th March 2019.

    The conference will consist of a variety of plenary and parallel sessions, as well as breakout discussion sessions, workshops, a poster session and the Annual General Meeting. Please note that the conference will run over three full days from Monday to Wednesday, with an optional half day training course on the  Sunday afternoon (can booked during registration at an additional cost). 

    Sessions will include early phase innovative trial design, industry best practice - 10 years on, statistical issues in safety drug labelling, model based dose finding designs, an update from Transcelerate and much more, with speakers from industry, academia and regulatory agencies.  A draft agenda will be released later this year.

    Abstract submissions for the 2019 Conference are now open! We welcome abstracts on any subject but are interested in the following topics; decision making, bayesian topics within early or late phase, causal inference, future trends, pre-clinical statistics, patient reported outcomes, and patient-centric data. To view the full list of topics and for information on how to submit an abstract, click here

    Finally, sponsorship and exhibition opportunities are already ongoing. Thank you to those who have already signed up. We will be allocating exhibition spaces in the order in which exhibitors sign-up, so get in early to secure the best spot!

    Should your company be interested in the sponsorship opportunities available, please contact Alex Currie (alexander.8.currie@gsk.com) or Chris Watton (chris@wattonhall.com).

    We hope you will join us in building on the huge success of this year’s event in Amsterdam, to make the 2019 Conference in London an even greater event!

    Kate Taylor

    PSI Conference Chair

    For more information on the conference, please click here.

  • Introduction To Industry Training Course 2019

    Dates: 01 Oct, 2019

    Are you a PSI member with approx. 1-3 years experience as a Statistician or a Statistical Programmer within the industry?


    Final dates to be confirmed

    PSI Member: £1,050 + VAT
    Non-Member: £1,145 + VAT

    AIM: To describe the drug development process from research right through to research, toxicology, data management & role of the CRO, clinical trials, product development & manufacture and marketing.

    Places will be assigned on a first come, first served basis. Please ensure you discuss your application with your manager.



    For further information contact:

    Alex Godwood & Zelie Bailes

    Heptares Therapeutics Ltd
    Broadwater Road
    Welwyn Garden City 
    Hertfordshire AL7 3AX

       Email: alex.godwood@heptares.com ; zelie.a.bailes@gsk.com
    Tel: 01707 448020