• Small Populations and Level of Evidence

    Dates: 27 – 27 Jun, 2018
    Over the last years progress has been made in statistical methodology for the efficient assessment of safety and efficacy of treatments in small populations. This meeting brings together experts to discuss these methods and the level of evidence that is needed to apply them.

    The Basel Biometric Society (BBS) and the European Federation of Statisticians in the Pharmaceutical Industry (EFSPI) are pleased to organize a European Scientific Meeting on this relevant topic. This meeting will provide a forum to hear about the latest development of methods in small populations from representatives from European regulatory bodies, and from practitioners in the pharmaceutical industry and academia.

    Please click here to view the flyer.
  • PSI Journal Club Webinar: Bayesian Methods

    Dates: 12 – 12 Jul, 2018

    Our next journal club features two papers on the topic of Bayesian Methods.  Please join us to hear Qingzhao Yu (Louisiana State University) and Margaret Gamalo‐Siebers (Eli Lilly & Co) present their recent work:

    • Qingzhao Yu, 'A Bayesian sequential design with adaptive randomization for 2‐sided hypothesis test'
      Authors: Qingzhao Yu, Lin Zhu and Han Zhu
      Pharmaceutical Statistics, Vol 16, Issue 6, November/December 2017

    • Margaret Gamalo‐Siebers, 'Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation'
      Authors: Margaret Gamalo‐Siebers and the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group
      Pharmaceutical Statistics, Vol 16, Issue 4, July/August 2017 

    The Chair will be Sara Hughes (GSK).

    The event will be held on Thursday 12th July, 3:30-5:00pm (UK time), just block out the date and time in your calendar.  

    Dial-in details

    In preparation and prior to the day of the webinar, please find below the link you will need to follow in order to obtain your personal dial in details and register with the webinar software. After registering via this link, you will receive a confirmation email containing information about joining the webinar, including details on how to dial-in via the telephone.

    https://attendee.gotowebinar.com/register/1101570305134952706 

    Please ensure you allow enough time before joining to download the correct software.

    Please click here to view the flyer.

  • PSI One Day Meeting and Workshop: Real World Evidence: Generalisability of Treatment Comparisons for Decision Making

    61352 Bad Homburg | Dates: 18 – 18 Sep, 2018

    RWE data are an increasingly valuable resource in drug development. One area where this data is being used regularly is in the generalisability of treatment comparisons. This event will focus on this topic and more specifically on the following three areas:

    • New advances in indirect comparisons
    • Generalizability approaches for clinical trial data into the real world setting
    • Cross-design approaches combining observational and randomized data

    The aims of the event are to:

    • share what research approaches are currently discussed
    • get feedback and inspiration from related fields and researchers
    • obtain feedback and insights from members of HTA bodies
    • raise awareness and education on generalisability methods

    in a very interactive way. The agenda is specifically designed to maximize interaction between participants in a structured way. As such, active participation in the discussions is appreciated. Please note that there is a maximum number of participants (60) for this event due to the interactive nature.

    In the morning there will be presentations by industry and academic speakers. The afternoon will consist of parallel interactive workshop sessions where there will be the opportunity for participants to expand on the topics discussed in the morning, to learn from each other, share examples and experiences. The event concludes with a panel discussion bringing the learnings from the break out discussions back to the overall audience.

    Please click here to register.

    Agenda

    Time  Agenda 
    08:30 - 08:50  Registration
    08:50 - 09:00 Welcome and Introduction
    Alexander Schacht (Lilly)
    09:00 - 10:00          Indirect comparisons with and without adjustment for patient characteristics and related approaches
    Sarah Böhme (Pfizer)
    David Phillippo (University Bristol)
    10:00 - 11:00 Generalizability of clinical trial data into real life settings
    Yann Ruffieux (University Bern)

    Alan Brnabic (Lilly)

    11:00 - 11:15 Break
    11:15 - 12:15 Cross-design approaches combining observational and clinical trial data 
    Mark Belger (Lilly)

    Keith Abrams (University Leicester)

    12:15 - 13:15 Lunch
    13:15 - 14:45  

    Break out #1: Bucher vs matching adjusted indirect comparisons and further refinements of these

    Break out #2: Generalizability of clinical trial data into real life settings

    Break out #3: Cross-design approaches combining observational and clinical trial data

    14:45 - 15:00 Break
    15:00 - 16:00  

    Panel discussion

    Alexander Schacht (Lilly, moderator)
    Carsten Schwenke (SCOSSIS)
    Ralf Bender (IQWiG)
    Nicky Welton (University Bristol)
    Keith Abrams (University Leicester)
    Chrissie Fletcher (Amgen)
    Mark Belger (Lilly)

    16:00 Close 

    Abstracts


    Indirect comparisons with and without adjustment for patient characteristics and related approaches - Sarah Böhme (Pfizer), David Phillippo (University Bristol)

    JP-9032CD_komprimiert
    Sarah Böhme
    Pfizer
    Indirect comparisons with and without adjustment for patient characteristics within the framework of AMNOG

    Abstract: 
    Within the framework of the Act on the Reform of the Market for Medicinal Products (AMNOG) in Germany, indirect comparisons are allowed to assess the extent of added benefit in case of a lack of direct evidence. The method proposed by Bucher et al. has been recognized as one of the standard approaches to perform adjusted IC. Further alternative methods exist, e.g. Matching-based approaches, which aim to overcome different challenges. However, all these methods have certain limitations.

    In this talk the statistical properties of the Bucher approach and the Matching-adjusted indirect comparison as well as their limitations in practice will be discussed.

    Biography: Sarah Böhme holds a Master‘s degree in Statistics from TU Dortmund University. In her master’s thesis she worked on the evaluation of methods for adjusted an unadjusted indirect comparisons within the framework of the German benefit assessment.  She joined Pfizer in 2015 and works in the Health Technology Assessment & Outcomes Research Group at Pfizer Germany.

     David Phillippo


    David M Phillippo,
    University of Bristol

     

    Multilevel network meta-regression for population adjustment based on individual and aggregate level data

    Abstract: Standard network meta-analysis (NMA) and indirect comparisons combine aggregate data (AgD) from multiple studies on treatments of interest, assuming that any effect modifiers are balanced across populations. We can relax this assumption if individual patient data (IPD) are available from all studies by fitting an IPD meta-regression. However, in many cases IPD are only available from a subset of studies.

    In the simplest scenario, IPD are available for an AB study but only AgD for an AC study. Methods such as Matching Adjusted Indirect Comparison (MAIC) create a population-adjusted indirect comparison between treatments B and C. However, the resulting comparison is only valid in the AC population without additional assumptions, and the methods cannot be extended to larger treatment networks. Meta-regression-based approaches can be used in larger networks. However, these typically fit the same model at both the individual and aggregate level which incurs aggregation bias.

    We propose a general method for synthesising evidence from individual and aggregate data in networks of all sizes, Multilevel Network Meta-Regression, extending the standard NMA framework. An individual-level regression model is defined, and aggregate study data are fitted by integrating this model over the covariate distributions of the respective studies. Since integration is often complex or even intractable, we take a flexible numerical approach using Quasi-Monte Carlo integration, allowing for easy implementation regardless of model form or complexity. Correlation structures between covariates are accounted for using copulae.

    We illustrate the method using an example and compare the results to those obtained using current methods. Where heterogeneity may be explained by imbalance in effect modifiers between studies we achieve similar fit to a random effects NMA, but uncertainty is substantially reduced, and the model is more interpretable. Crucially for decision making, comparisons may be provided in any target population with a given covariate distribution.


    Biography: David Phillippo is a statistician at the University of Bristol. His research focuses on methodology for evidence synthesis, Bayesian Network Meta-Analysis, and indirect comparisons. He is the lead author of a recent Technical Support Document published by the NICE Decision Support Unit on population-adjusted indirect comparisons, on which he is also undertaking his PhD.

     

    Generalizability of clinical trial data into real life settings - Yann Ruffieux (University Bern), Alan Brnabic (Lilly)

     Yann Ruffieux


    Yann Ruffieux, MSc, University Bern

     

    Combining RCT efficacy data and real-world evidence to predict drug effectiveness – a case study in Rheumatoid Arthritis.

    Abstract: Decision-makers often need to assess the real-world effectiveness of a new drug before it is on the market. We propose a method to predict drug effectiveness pre-launch, and apply it in a case study in rheumatoid arthritis. Our approach comprises several steps: 1) identify an existing treatment similar to the new drug, 2) quantify the impact of treatment, prognostic factors, and effect modifiers on clinical outcome, 3) determine the characteristics of patients likely to receive the new drug in routine care, 4) predict treatment outcome for patients with these characteristics.

    Biography: 
    Yann Ruffieux is a Statistician at the Institute of Social and Preventive Medecine (ISPM) in Bern, Switzerland. He has an MSc in Mathematical Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL). After briefly working in pharma as Biostatistician, he joined ISPM in 2015, where he has contributed to the GetReal project and to HIV-related epidemiological research.
     Alan Brnabic


    Alan J. M. Brnabic,
    BA Dip Ed, MA Statistics,
    Eli Lilly

     

    Reweighting randomized controlled trial (RCT) evidence to better reflect real life – a case study of the Innovation in Medicine initiative using patients with non-small cell lung cancer (NSCLC)

    Abstract: The objective of the presentation will be to present a case study that assesses the generalizability of efficacy (overall survival [OS]) from the pivotal RCT (JMDB) comparing pemetrexed with gemicitabine to treat non-squamous non-small cell lung cancer using real-world data from a prospective observational study (FRAME) using a reweighting approach. Both inverse propensity scoring and entropy balancing were used to reweight the RCT data based on the real-world FRAME data in an attempt to mirror routine clinical practice in the trial setting.

    Biography: Mr. Brnabic is currently Principal Research Scientist at Eli Lilly working in Real World evidence (RWE) with a focus on specialized analysis that supports this area. Prior to this he was the Asia Pacific Director of the Health Outcomes and Health Economics, Life Sciences for OPTUM. Whilst at Eli Lilly he has been the Health Outcomes and Statistics Asia Pacific statistical sciences group leader and manager. His work has included: designing/reviewing and analyzing concepts and studies (Phase IIIb & IV observational studies), as well as leading and reviewing external methodologies/ guidelines for use within the company as well as consulting/coordinating strategy for analysis on Reimbursement dossiers & other related Health Outcome activities for countries like Australia, Canada & Korea. He worked as a Consultant Biostatistician for 5 years in Public Health NSW Health Department. Following that he was a Senior Biostatistician at the George Institute which is affiliated with UNSW where he worked on epidemiological studies and RCTs. Before joining Eli Lilly he also took a position at the NSW Department of Corrective Services as Deputy Director of the Research & Statistics, Sydney.

    Mr. Brnabic’s interests are in the design and analysis of observational studies with a focus on methodologies related to subgroup identification as well as selection bias adjustment tools including matching, propensity score analysis and local control. He is also interested in Health Outcomes and statistical approaches used to help support the reimbursement of medicines like matched adjusted indirect comparisons as well as mixed treatment comparisons.

    He has A-STAT Professional Accreditation with the Statistical Society of Australia (SSAI). He is co-chair and previous Chair for the Australian Pharmaceutical Biostatistics Group (APBG).

     

    Cross-design approaches combining observational and clinical trial data - Mark Belger (Lilly), Keith Abrams (University Leicester)

     Mark Belger


    Mark Belger, BSc,
    Eli Lilly

     

    Cross-design approaches combining observational and clinical trial data for HTA


    Abstract: The Innovative Medicines Initiative (IMI) “GetReal” project explored methods for combing Randomised Clinical Trials (RCT) data with non-RCT data within the same Network Meta-Analysis (NMA). Methods such as, the design-adjusted analysis, using informative priors and three-level hierarchical models have been summarised in the manuscript. “Combining randomized and nonrandomized evidence in network meta-analysis “[Orestis Efthimiou et al.]. We will discuss how to incorporate these methods within an HTA setting. Outlining the limitations in combining this type of evidence, and exploring how these methods are used to improve our understanding of how a new intervention will perform outside of the clinical trial environment.

    Efthimiou O, Mavridis D1, Debray TP, Samara M, Belger M, Siontis GC, Leucht S, Salanti G; GetReal Work Package 4. Combining randomized and non-randomized evidence in network meta-analysis. Stat Med. 2017 Apr 15;36(8):1210-1226. doi: 10.1002/sim.7223. Epub 2017 Jan 12

    Biography: Mark Belger been a statistician for the last 34 years mainly working in the area of non-RCT studies. I joined the pharmaceutical industry 14 years ago prior to that I worked in the NHS. I draw from extensive experience of conducting studies in Non RCT populations from both an industry and non-industry perspective. My current responsibilities with Eli Lilly are to support the companies submissions to HTA’s with a focus on our Neurodegeneration and pain indications. In addition, I also lead on a number of Real World analytical methodological projects within the company. I was an active member of IMI “GetReal”, and I am currently involved in two Alzheimer’s disease IMI projects “ROADMAP” and “MOPEAD”. I have co-authored publications that focus on methods for analysing non-RCT data, and clinical papers reporting results from non-RCT studies conducted by Eli Lilly.

    Keith Abrams

    Keith Abrams,
    PhD CStat, University of Leicester, UK

     

    Incorporating Real World Evidence (RWE) in Network Meta-Analysis (NMA) – Experiences from the Innovative Medicines Initiative (IMI) GetReal Project

    Abstract: In this talk the possible situations in which Real World Evidence (RWE), both comparative and single arm studies, could be included in a Network Meta-Analysis (NMA) will be described and discussed. These include; sparse networks, disconnected networks, multiple outcome networks, and the use of such NMAs in terms of decision making and designing future Randomised Controlled Trials (RCTs). In particular, methods for the allowance of potential biases and selection effects associated with RWE and how these may also be incorporated into NMAs will be discussed. The methods will be illustrated using examples from the IMI GetReal Project on patients with Multiple Sclerosis or Rheumatoid Arthritis. 

    Biography: Keith Abrams is Professor of Medical Statistics, within the Department of Health Sciences at the University of Leicester, where he heads the Biostatistics Research Group. His research interests, for which he has an international reputation, are primarily concerned with the development and application of Bayesian statistical methods in Health Technology Assessment (HTA), in particular regarding clinical trials, evidence synthesis, and economic decision modelling, and Non-Communicable Disease (NCD) epidemiology. This work is primarily supported with funding from EU, Medical Research Council (MRC), National Institute for Health Research (NIHR) and industry (with a total value in excess of £20M over the last 5 years). Prof Abrams has been extensively involved with the UK NIHR HTA Programme and UK National Institute for Health & Care Excellence (NICE) appraisal process since their inception. He was a member of the NICE Technology Appraisals Committee for over 8 years until 2015, is a member of the NICE Decision Support Unit and NICE Technical Support Unit, acts as a consultant to the NICE Scientific Advice Programme, and is a NIHR Senior Investigator Emeritus.  He is also a Fellow of the Royal Statistical Society, and a Chartered Statistician. He has published widely in both substantive and methodological areas [h-index 69] including co-authoring books on Methods for Meta-Analysis in Medical Research, Bayesian Approaches to Clinical Trials and Healthcare Evaluation, and Evidence Synthesis for Decision Making in Healthcare, in addition to co-editing one of the first texts on Methods for Evidence-based Healthcare. Prof Abrams has extensive experience over the last 25 years as a consultant to both the pharmaceutical and healthcare consultancy sectors, providing both methodological and strategic HTA advice across a wide range of therapeutic areas.   

     
    Registration
    PSI Member £40
    Non-Member £135 (This includes free PSI membership for the remainder of 2018)

    Please click here to register.

    A limited number of hotel rooms have been reserved at the Maritim Hotel Bad Homburg (Ludwigstraße 3, 61348 Bad Homburg vor der Höhe). These will be allocated on a first come first served basis. If you would like to reserve a room for the night of 17th September please contact psi@mci-group.com. Rates are €136 per room including breakfast.

    There will also be a dinner at Restaurant am Römerbrunnen (Kisseleffstraße 27, 61348 Bad Homburg vor der Höhe) on the evening prior to the meeting which attendees are invited to (at their own expense). Please indicate when registering if you would like to attend the dinner and you will contacted by the local organisers with additional details.


  • Statistics Fundamentals of Clinical Trials for Non-Statisticians (or ‘How to speak stats in a day!’)

    Reading | Dates: 20 – 20 Sep, 2018

    This basic but wide-ranging course covers techniques for investigating, visualising and performing basic statistical techniques on data sets typical to industry settings. There are many basic concepts that need to be understood before statistics can be used to its full potential to give useful and informative answers. This course ensures that these concepts are understood in a non-technical way and then demonstrated using data examples.

    Mathematical details are kept to a necessary minimum and we focus on the interpretation of statistical output and illustrate applications with data from dummy clinical trials or published data. The objective of the course is not to teach you how to become a statistician, but to help you work with statisticians and get the maximum value from statistical output.

    The course will consist of lectures, practical examples and discussions. There will not be any computer exercises.

    Target Audience:

    This is a 1-day course, aimed to introduce statistics to people who work on Clinical Trials, but who are not Statisticians. No previous knowledge of Statistics is assumed as we start right at the beginning with the basics. Many practical examples are given and the emphasis is on application and understanding rather than the equations and the technical background.

    The basics of statistics are discussed to give background and a common base to start from and the applications and use of statistics in drug development is then discussed. The role of the statistician and their ability to help with decision making is also discussed.

    It also serves as a useful refresher course to those who once studied statistics as part of a college course.

    The following key topics will be addressed:

    1.  Types of Data
    2.  Measures of Location and Variability
    3.  Basic Inference
    4.  Power Calculations and Sample Sizing
    5.  Design Issues

    For more information on specific topics, please contact the presenter direct on gemma@qistatistics.co.uk

    About the Presenter: 

    Gemma Hodgson, Qi Statistics Ltd. http://www.qistatistics.co.uk

    Gemma Hodgson has worked in the Pharmaceutical industry for over 20 years. After receiving her first degree from Imperial College (Maths with Statistics) and then an MSc in Medical Statistics from London School of Tropical Hygiene and Medicine, Gemma began her career at Pfizer in Sandwich working in experienced global teams on major phase 3 projects. After 13 years at Pfizer and working in all phases of development, from phase 1 to phase 4, Gemma then moved to Takeda R &D in London where she worked on later phase projects, focussing on close liaison with other departments within the organisation. In 2012 Gemma left Takeda to work for a statistical training and consultancy firm, Qi Statistics Ltd, where training of non-statisticians and explaining statistical concepts to non-scientific audiences is key. Gemma has a broad interest in the application of statistics and is an experienced trainer to all types of audience, specialising in translating technical concepts into everyday English.

    Registration:

    Course runs from: 09:30 – 16:30 (registration/coffee from 9:00)

    Please register online at www.psiweb.org and click on Events; payment now available online. Registration costs (includes lunch and refreshments).

     Registration on or before 10th August   2018

    Registration after 10th August 2018

     £425 + VAT  £495 + VAT

    Please click here to register.

    PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible.  Please help us to help you by letting us know if you require additional facilities or have any special requirements.  Please contact us on +44 (0)1730715235 or at psi@mci-group.com for further information.

  • Regulatory Interactions for Statisticians

    Dates: 26 – 27 Sep, 2018

    Presented by:

    Daphne Lin (FDA)

    Image

    Yolanda Barbachano (MHRA)
    Khadija Rantell (MHRA)
    Natasha Jarrett
    Steve Slater
    Andy Stone


    Please click here to view the flyer.

    The course objective is to inform statisticians about the likely interactions they might have with regulatory agencies, both during a submission and at other times during drug development, and give advice on how to make these interactions most effective. The course will focus on clinical development.

    The course is primarily targeted at project statisticians who interact with regulators, but would also be suitable for those who may move into this role in the near future.

    The course will be presented by experienced statisticians from the MHRA, FDA and those with expansive pharmaceutical company employment and representatives from a company regulatory affairs department. The course will consist of lectures, practical examples and discussions. There will not be any computer exercises.

    Key Topics:

    • Introduction to the regulatory agencies
    • Interactions between EU and US regulators and statisticians at each stage of development
    • Overview of regulatory practices in other regions

    Registration:

    Registration on or before 15th August:
     PSI Member  £595 + VAT
     Non-Member  £690 + VAT
     Registration after 15th August:
     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 25th and 26th September which will be allocated on a first come first served basis. Please contact psi@mci-group.com to reserve a room. 

  • IDEAS Dissemination Workshop

    Basel | Dates: 26 Sep, 2018

    The aim of the workshop is to translate and promote novel methodologies developed by IDEAS and is geared towards statisticians and trialists with an interest in novel methods for early phase clinical trials.  Therefore, it will be of interest to those working in academia, industry, HTA or regulatory authorities.

    The event has been timed to coincide with the end of the EFSPI Regulatory Statistics Meeting being held on the 24th & 25th September in Basel.

    Please click here to view the flyer. Further details regarding the event can be found on our website at http://www.ideas-itn.eu/dissemination-workshop 

    Free Registration

    To book your free place, please contact Pamela Forster ( p.forster@lancaster.ac.uk  ). Please note that as places are limited early booking is advised.   

    IDEAS is a H2020 Marie Sklodowska Curie Action Innovative Training Network  for 14 early stage researchers working on statistical methods for early drug development. The network is funded by the European Union and the Swiss Government, and comprises of 8 full partners and 6 associated partners at major European universities, the pharmaceutical industry, and consulting companies.

    We would be delighted if you could join us at what promises to be a very informative and engaging event.

  • Introduction To Industry Training Course 2018

    Dates: 01 Oct, 2018 – 01 Nov, 2019

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


    THE INTRODUCTION TO INDUSTRY TRAINING COURSE NEEDS YOU!

     PLEASE CLICK HERE TO VIEW THE FLYER

    NEXT COURSE STARTS OCTOBER 2018
    PSI Member: £1050 + VAT
    Non-Member: £1145 + 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.

    Limited places available!

    Application forms must be received by 30th June 2018!

    Please discuss your application with your manager
    Final dates to be confirmed.

    CLICK HERE TO DOWNLOAD THE APPLICATION FORM

    For further information contact:

    Alex Godwood & Zelie Bailes

    Heptares Therapeutics Ltd
    Bio-Park
    Broadwater Road
    WELWYN GARDEN CITY, Hertfordshire AL7 3AX

    Tel: 01707 448020   

     

    Email: alex.godwood@heptares.com
    zelie.a.bailes@gsk.com