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
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
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.
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
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.
Early Bird Rate
£120 + VAT
Non - Member
£160 + VAT
£60 + VAT
After 1st June 2016
£160 + VAT
Non - Member
£220 + VAT
£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.
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 Non-PSI Event - Protecting confidentiality and privacy in clinical trial and medical data sets
We are increasingly living in a data driven world. Data are collected in many different ways for a variety of purposes. As such, concerns around protecting the privacy of individuals have increased in recent times.
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.
This webinar will address operational issues of paramount importance within the healthcare industry with a view to using statistics for the benefit of patients. In attending this webinar, you'll hear more about work being conducted to address some operational issues we face in the health care industrys e.g. patient rectuitment, drug supply and meeting NHS 18 week targets.
PSI Toxicology SIG workshop – 16th and 17th March 2020
The Toxicology SIG provides a forum for statisticians working in regulatory/investigative toxicology, as well as most other pre-clinical areas, to discuss issues and interact with one another.
This 1.5-day workshop will involve approximately 20 statisticians, focusing on discussions around “best practice” in the statistical analysis of various data types.
The afternoon of Day 1 will include a 4.5 hour Bayesian training course focused towards applications in toxicology/pre-clinical, provided by Prof. Dr. Katja Ickstadt and is included in the workshop fee.
The cost will be £270 including VAT per delegate, inclusive of food and one night’s accommodation (and the training course). The workshop is being held at the Crowne Plaza Hotel, Heathrow.
The agenda and topics that will be discussed are yet to be finalised, but please get in touch with email@example.com if you have suggestions. Full details will be circulated in the coming weeks.
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…
Non-proportional hazards and applications in immuno-oncology
Designs of clinical trials with time to event primary endpoints usually rely on hazards being constant over time. A major challenge in immuno-oncology is the delayed onset of benefit with such therapies and the presence of non-proportional hazards. The impact of this needs to be accounted for in sample size calculations, analysis methodology and reporting. At this meeting, we will examine possible strategies to handle such features, which may not be fully known when the trial is initiated.
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 3 sessions in continental Europe and 3 - 4 sessions in the UK. It promises to be a truly memorable course.