Historical Data SIG

Objectives

Many approaches for designing and analyzing clinical trials using historical (or other external study) data have been proposed in the recent past. For example, proposals have been made for bridging studies, the combination of randomized and non-randomized evidence, and also for more general problems such as across-phases probability of success calculations. In addition, the ever-increasing number of patient registries and databases for routinely collected data, and recent data sharing initiatives (e.g., TransCelerate), further underline the importance of these approaches. However, there are still many open questions concerning the role which clinical trials that use such data can have in drug development. In our opinion, the three most important questions are:

  • What is the state of the art regarding approaches to incorporate historical data into the formal design and analysis of clinical trials?
  • Which statistical methods should we use to make historical and current data comparable?
  • What are the regulatory requirements necessary for the acceptance of historical data in drug approval?

The scope of this SIG is to provide some answers to the above questions through a variety of activities. These will include:

  • Publishing reviews of the available methods, sources of historical data and case studies.
  • Collaborating with experts to refine and possibly extend the available methods.
  • Interacting with regulators to obtain a better understanding of their requirements.
  • Providing trainings, workshops and talks.
  • Promoting good practice through templates for study protocols and statistical analysis plans.

Who we are

NameCompany/Institution
Nicky Best (co-lead)
 GSK
Simon Wandel (co-lead) Novartis
Byron Jones (Chair) Novartis
Lisa Hampson
 Novartis
Sebastian Weber Novartis
Frank Fleischer Boehringer Ingelheim
Nelson Kinnersley Roche
David Dejardin
 Roche
Ros Walley UCB
Adrian Mander MRC Cambridge
Graeme Archer GSK

How to get in touch

Contact: Byron Jones (Novartis)
Email: byron.jones@novartis.com

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Upcoming Events

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Upcoming Events

A PSI ToxSIG webinar - Big Data, Data Science, AI and other buzzwords: What does the Data-Driven Hype mean for Pharmaceutical Analytics?

The last 15 years has seen a massive shift in the role of data and analytics, driven by the increased hype around big data, data science, machine learning and AI. This presents both challenges and opportunities for analytic teams. This webinar will strip back the hype to look at what these buzzwords really mean, and talk about the impact this is having on the role, remit and operating model of analytic teams in the life sciences industry.

PSI New Starters Half-Day Networking Event

An opportunity to meet statisticians from across the pharmaceutical industry in a relaxed and informal setting. An exciting program of events and a chance to work in small groups on a data analysis challenge. Lunch provided.

A PSI Training Course - Practical Approaches to Designing Adaptive Clinical Trials

This hands-on course will provide a deep dive into 4 software packages used to design adaptive clinical trials. The course will start by providing a general overview of adaptive designs, explaining the different type of adaptations possible and the benefits of each design. Following this, participants will be given the opportunity to have a go at designing trials in R (using RPACTS), EAST, FACTS, and nQuery.

PSI Training Course - Bayesian Practical Course using R and SAS

This practical training course will give a deep dive into performing Bayesian analyses in R and SAS. It is aimed at statisticians who need to be able to conduct Bayesian analyses as part of their day to day work. By the end of the course participants will be able to conduct their own analyses.

Medical Statistics Careers Event 2020

Our annual PSI Medical Statistics Careers Event, will be held at the De Montfort University in Leicester on Wednesday 4th March 2020.

A PSI Training Course - R for SAS Users

This course is aimed at Statisticians and Programmers experienced in SAS, but little or no experience with R. An Introduction to R studio and the R language, statistical graphics, programming statistical models, simulations and more…

Introduction To Industry Training Course 2020

The ITIT course will take 25 delegates new to the industry on a complete drug development experience from discovery to marketing. They will visit 6 companies from October 2020 to July 2021 to learn about 6 topics from experts in their field. The ITIT course will have 6 sessions in continental Europe and 3 - 4 sessions in the UK. It promises to be a truly memorable course.

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