Immunology is a branch of biomedical science that covers the study of all aspects of the immune system; this may include autoimmune diseases, such as Rheumatoid Arthritis; transplant rejection; infections. During this one day meeting, PSI aims to cover a wide range of immunology diseases, design considerations and statistical challenges when working in this therapeutic area. We hope that sharing between different areas on Immunology; will stimulate interesting discussion and an opportunity to knowledge share.
Immunology is viewed as a complex and daunting subject with a multitude of antibodies, interleukins, molecules, cells and pathways that interact in mysterious ways. This perception can worry anyone stating research in a new immunological area or disease. The reality is that the immune system spans almost every disease from aging to zoonosis and that certain concepts are common across all of these. By understanding some of these themes we can demystify immunology and turn the fear into fascination.
Dr Bernd Genser 1,2 1. BGStats Consulting Vienna Austria
2. Mannheim Institute of Public Health, Social and Preventive Medicine, University of Heidelberg, Germany
An approach for integrating existing knowledge into the statistical analysis of multiple immune markers: An application to cytokine data collected in a large immuno-epidemiological study aimed to investigate risk factors for atopy and asthma
BACKGROUND: Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists’ hypotheses about the underlying biological mechanisms to be integrated.
METHODS: We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies.
RESULTS: We demonstrate i) how to deal with interdependencies among multiple
measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach.
CONCLUSION: The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes
Nicola Scott
GSK
Leveraging Data across Multiple Immuno-Inflammation Indications: Early Clinical Development of a Novel Compound
Recent research has identified that necroptosis is the major driver of TNF-α dependent inflammation and disease. A clinical development program for a first in class compound is currently assessing a target which blocks solely the TNF-α necroptosis pathway. Following completion of the First Time in Human study, we will next focus in on the human validation of blocking this pathway, which in turn will result in a greater understanding of the compound and mechanism early in clinical development. This will be achieved through experimental medicine (EM) studies in three Immuno Inflammation indications that are treated with anti-TNFs: Psoriasis, Rheumatoid Arthritis and Ulcerative Colitis. Each study is extremely data rich due to the number of biomarkers, mechanistic and efficacy endpoints that will be collected. These EM studies will be conducted in parallel, thus providing a unique opportunity to leverage data across the three indications in order to benchmark against anti-TNFs, and thus inform the clinical development of this compound
Karine Lheritier PhD
Novartis
Complex study design in patients with Hereditary Periodic Fevers (HPF), an orphan autoimmune disease.
Familial Mediterranean fever (FMF), Hyperimmunoglobulinemia D with periodic fever syndrome (HIDS) and TNF-receptor–associated periodic syndrome (TRAPS) are a cluster of autoimmune disease called HPF syndromes. These are rare and distinct heritable disorders characterized by short and recurrent attacks of fever and severe localized inflammation that occur periodically or irregularly.
The planning of a single study within this cluster of autoimmune disease presents multiple and complex design challenges. Canakinumab is an anti-interleukin-1β monoclonal antibody being developed for the treatment of IL-1β - driven inflammatory diseases and has already been shown to be effective in patients with CAPS which is also classified under this single term of HPF syndromes.
Efficacy and safety of Canakinumab in colchicine resistant FMF, HIDS and TRAPS patients have been shown in phase II studies. However, there are currently no approved treatments for
these conditions. Our challenge was to design a single study on patients suffering from these 3 rare conditions. This required inclusion of a randomised, double-blind, placebo-control and a randomized withdrawal element, a long-term follow-up part, in addition to clinical constraints such as up-titration of the dose, change in the dose frequency, co-primary efficacy endpoints with different timepoints. Requests from different health authorities such as the Paediatric Committee at the European to include patients >28 days in this clinical trial were also built into the design.
Jen Pulley
Roche
A bioequivalence study design which includes the option for sample size re-estimation (SSR) at the Interim Analysis
In Immunology we are currently designing a bio-equivalence study using a two stage sample size re-estimation adaptive design. This design will allow the sample size assumptions to be re-evaluated once approximately half the subjects have completed the study.
Our initial study design used overall power and fixed analysis with no adjustment for type I error. This design was rejected by the health authorities so the team revised the study design. Two revised study designs using conditional power with a promising zone was proposed to health authorities. Each of the two revised designs made the adjustment for the type I error within the 90% CI calculation using either the t-distribution method or adjusted normal method.
This presentation will discuss the methods used for the revised SSR study designs and the ongoing interactions with health authorities.
Kieran Alden York Computational Immunology Lab
Engineering simulations to understand and gain inspiration from biological systems
Simulation is increasingly providing relevant tools to interrogate human biology, to counter a continued reliance on predictions from animal experiments. Yet simulations designed to explore complex biological mechanisms capture a range of uncertain factors that impact the relationship between a prediction and the real world: factors that together act as a barrier to wider simulation use and acceptance in laboratory or clinical studies. Developing robust, evidence-based engineering approaches to simulation composition, implementation, analysis, and application has been a key feature of research in the York Computational Immunology Lab for a number of years, within significant immunological case studies. In this talk I will provide an overview of the techniques we have been developing to overcome barriers to simulation acceptance and increase belief in predictions these simulations derive, in the context of a number of ongoing immunological research studies.
Jacquie Christie GSK
Across immunology indications, a common question is how long should a patient persevere with a treatment if they not initially receive sufficient benefit. In this talk statistical approaches to address this question will be discussed
Brian Tom
MRC Biostatistics Unit
RA-MAP Project - Towards an improved understanding of immune function and response in RA
There is compelling evidence to implicate dysregulated immune function in the pathogenesis (origin and progression) of rheumatoid arthritis (RA). The RA-MAP Project is an MRC/ABPI Inflammation and Immunology Initiative that aims to improve understanding of the human immune system in rheumatoid arthritis, using ex vivo and functional read outs, through the application of established and new technologies and through different complementary studies. We conjecture that discrete, dynamic immunological profiles are present in leucocyte subsets, plasma or serum derived from human blood that are informative of current and future disease states in RA (or health) and thereby relevant immune function.
In this talk, I will describe the plan of investigation adopted, the data collected and the statistical methodology that may be used to investigate immune dysregulation in RA by the RA-MAP consortium.
Registration Costs
Early Bird Rate
PSI Member
£120 + VAT
Non - Member
£160 + VAT
Academic
£60 + VAT
Registration Costs
After 1st June 2016
PSI Member
£160 + VAT
Non - Member
£220 + VAT
Academic
£90 + VAT
Registration closes on 10th June 2016
Please contact the PSI secretariat with your vehicle numberplate if you will require parking. Please also contact the PSI secretariat if you have any dietary requirements.
Please contact the PSI secretariat on psi@mci-group.com if you have any queries.
Upcoming Events
PSI Training Course: Introduction to Machine Learning
This course is aimed at clinical trial statisticians who are new to or with limited experience of machine learning. Attendees will learn about a range of topics in machine learning, including practical sessions in R.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
The event will open with an overview on drug development in women’s health from a clinician perspective. This talk is followed by talks about statistical challenges when planning IVF studies and analysing the menstrual cycles.
This webinar will provide an overview of surrogacy for licensing and reimbursement. In turn, the need of extensions of the SPIRIT and CONSORT statement will be defined and outlined, with case studies to support.
Joint PSI/EFSPI Pre-Clinical SIG Webinar: Virtual Control Groups in Toxicity Studies
Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.
Joint PSI/EFSPI Data Science SIG Webinar: Developing Digital Measures (Digital Biomarkers) in Drug Development – insights from Mobilise D consortium
We will share a brief overview of what Mobilise D is and why it is an important step stone in the development of digital biomarkers, and how Mobilise D outputs can be relevant for you.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Introduction to Industry Training (ITIT) Course - 2024/2025
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
Statisticians in the Pharmaceutical Industry Executive Office: c/o MCI UK Ltd | Unit 24/22 South | Building 4000 | Langstone Park| Langstone Road | Havant | PO9 1SA | UK