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Proposal 1137

Title of the Proposed Research

Immunotherapy trial simulators: Using mathematical, computational and statistical techniques to simulate trial design for new products in the treatment, vaccination and immunoprophylaxis of disease.

Lead Researcher

Roy Anderson, PhD

Affiliation

Imperial College London
London
UK

Funding Source

The research project is fully supported by Crucell Vaccine Institute (CVI), Janssen Centre of Excellence in Leiden, the Netherlands.

Potential Conflicts of Interest

Lead Researcher: Independent Non-Executive Director for GSK

Data Sharing Agreement Date

16 Apr 2015

Lay Summary

Background of the Project

Influenza A infection has a huge impact on human health; the WHO estimates that annual epidemics result in around 3-5 million cases of severe illness, and 250-500,000 deaths. The Influenza virus mutates frequently, meaning drugs and vaccines have a limited lifespan and development of new treatment and vaccines is necessary. Mathematical models can aid our understanding of disease progression and can therefore help in the design of drugs, vaccines and immunotherapies. In addition, simulating clinical trials can help predict outcomes of novel therapy and make the trials more productive for researchers and less intrusive for patients. Sophisticated computational models of the immune response to Influenza can predict various things such as; when to administer treatment, what samples need to be collected, what needs to be measured and how many people must be tested to prove an effect.

Aim and Objectives

The aim of our research project is to design a clinical trial simulator, to examine new vaccines and immunotherapy approaches against Influenza A infection. We will develop deterministic and stochastic mathematical models of the time course of Influenza within the human host and the associated immune response. The aim is to keep these models as simple and tractable as possible and only to include the essential features that characterise the immune response to influenza. To reliably identify these features we will need access to high-quality human data. Once the essential features have been identified we will introduce potential immunomodulatory treatments into the model to predict their effects.

Integral to the development of these model simulators will be the construction of databases for Influenza A. The goal is to collect the best cohort studies from around the world to be able to include reliable data on both the progression and incidence of Influenza A. The compilation of these databases themselves is a valuable exercise, rarely attempted in clinical studies.

Study Data Provided

Study NAI30008: A Double-Blind, Randomized, Placebo-Controlled, Parallel Group, Multicenter Study To Investigate The Efficacy And Safety Of Zanamivir (GG167) 10mg Administered Twice A Day For Five Days In The Treatment Of Influenza In Patients 12 Years Or Over With Asthma Or Chronic Obstructive Pulmonary Disease (COPD)
Study NAI30009: A double-blind, randomized, placebo-controlled, parallel-group, multicenter study to investigate the efficacy and safety of zanamivir (GG167) 10 mg administered by inhalation twice daily for five days in the treatment of symptomatic influenza A and B viral infections in children ages 5-12.
Study NAI30012: A Double-Blind, Randomised, Placebo-Controlled, Parallel-Group, Multicentre Study to Investigate the Efficacy and Safety of Inhaled Zanamivir 10mg Administered Twice Daily for Five Days in the Treatment of Symptomatic Influenza A and B Viral Infections in Subjects Aged >= 65 Years.
Study NAI30015: A double-blind, randomised, placebo-controlled, parallel-group, multicentre study to investigate the efficacy and safety of inhaled zanamivir 10mg administered twice daily for five days in the treatment of symptomatic influenza A and B viral infections in armed services personnel.
Study NAIA1001: A Study to Investigate the Effect of Intranasal GR121167X on Infection Rates in Healthy Male Volunteers when Experimentally Inoculated with Influenza A/Texas/91 (H1N1) Virus
Study NAIA1002: A Study to Investigate the Effect of Intranasal GG167 Initiated at Various Intervals Post Inoculation on Infection in Healthy Volunteers when Experimentally Inoculated with Influenza A/Texas/91 (H1N1) Virus
Study NAIA1003: A Study to Investigate the Effect of Intranasal GG167 at Various Dosing Frequencies on Infection in Healthy Volunteers when Experimentally Inoculated with Influenza A/Texas/91 (H1N1) Virus
Study NAIA1004: A Study to Investigate the Effect of Intranasal GG167 as Nasal Drops and Nasal Spray on Infection in Healthy Volunteers Experimentally Inoculated with Influenza A/Texas/91 (H1N1) Virus
Study NAIA1005: A Study to Investigate the Effect of Intranasal GG167 on Infection in Healthy Volunteers Experimentally Inoculated with Influenza B/YAMAGATA/16/88 Virus
Study NAIA2005: A Double-Blind, Randomized Placebo-Controlled Multicenter Study to Investigate the Efficacy and Safety of GG167 in the Treatment of Influenza A and B Infection
Study NAIA2008: A Double-Blind, Randomized, Placebo-Controlled, Multicenter, Parallel and Group Study to Investigate the Efficiacy and Safety of GG167 Administered Twice or Four Times a Day for the Treatment of Influenza A and B Viral Infections
Study NAIB2005: A Double-Blind, Randomized, Placebo-Controlled, Parallel-Group, Multicentre Study to Investigate the Efficacy and Safety of Inhaled and Intranasal GG167 in the Treatment of Influenza A and B Viral Infections
Study NAIB2008: A Double-Blind, Randomized, Placebo-Controlled, Multicenter, Parallel-Group Study to Investigate the Efficacy and Safety of GG167 Administered Twice or Four Times a Day for the Treatment of Influenza A and B Viral Infections
Study NAIB2009: A Double-Blind, Randomized, Placebo-Controlled, Multicenter, Parallel-Group Study to Investigate the Efficacy and Safety of GG167 in the Prevention and/or Progression of Influenza A and B Viral Infections

Statistical Analysis Plan

Publication Citation

Hadjichrysanthou C, Caue¨t E, Lawrence E, Vegvari C, de Wolf F, Anderson RM. 2016 Understanding the within-host dynamics of influenza A virus: from theory to clinical implications. J. R. Soc. Interface 13: 20160289.