Health & Life Sciences

Correlates of Immunity

Decoding the human immune system
Pursuing a new leap in antibody and vaccine discovery through advanced immunology, artificial intelligence and high-quality data.
Program Co-Lead

Professor Andrew Pollard

"By understanding the precise immune signatures that protect against disease, we can transform how vaccines are designed, dramatically accelerate their development, and create powerful new tools to tackle infectious diseases that have eluded conventional approaches"
Program co-lead

Professor Daniela Ferreira

"One of the key reasons vaccines fail is that they target the wrong immune mechanism or antigen - and because animal models often don’t reflect how humans respond. Within Correlates of Immunity, we’re using human challenge models and cutting-edge immunology to fundamentally transform how we understand protection and accelerate the development of successful vaccines."
The mission

Transforming the body’s protective mechanisms against infectious diseases

While vaccines save approximately 5 million lives annually, over 90% of new candidates still fail due to an incomplete understanding of the body’s immune responses, particularly when it comes to high-burden pathogens, cancer and autoimmune diseases.

Better vaccines start with better insights.

Human challenge models - where volunteers are safely and ethically exposed to the pathogens under study - allow us to observe the immune system in real time, from the exact moment of infection. This approach helps us uncover why some people become ill while others are protected, providing critical insights that animal models simply can’t offer.

We will then undertake detailed laboratory testing of the immune system using immunological and genetic techniques to provide deeper insights into how our bodies combat diseases.

Combined with the latest advances in artificial intelligence, these tools have the potential to transform disease prevention by more effectively identifying the protective immune signatures vaccines must generate.

154mlives saved

Global immunisation efforts have saved an estimated 154 million lives – or the equivalent of 6 lives every minute of every year – over the past 50 years.

25%of global disease burden

Infectious diseases consistently account for approximately 25% of the global disease burden annually - even without factoring in additional impact from major pandemics.

10%success rate

While vaccines save millions annually, vaccine development remains largely empirical, with only a 10% success rate.

The Challenge

We need a new paradigm in antibody discovery and vaccine development

We are living through a unique moment in biological history, where tools can not only define protective correlates, but drive the design of smarter trials, platform selection and vaccine design.

The next leap in immunology must leverage AI and advanced immunologic and genetic tools to overcome complex set of scientific and commercial challenges.

The race against resistance

Antimicrobial resistance is rising and could surpass cancer as a cause of death by mid-century. New approaches to vaccine design are urgently needed to combat pathogens that are becoming increasingly resistant to available treatments.

The protection puzzle remains unsolved

The complexity of the human immune system, the difficulty in studying the course of disease from the moment of infection and highly heterogeneous clinical outcomes all contribute to a massive challenge in understanding of which vaccines will work. Traditional approaches too often struggle to identify the precise immune mechanisms that lead to protection against disease.

Current development timelines are long

The infections with the highest disease burdens are complex and traditional vaccine development has mostly failed. Current approaches are time-consuming, costly and often unsuccessful. Many easy-to-target diseases are now prevented and some of the most the most challenging pathogens like S aureus, E coli causing urinary tract infections and the cause of gonorrhoea.  These will be studied in our program.

Mouse models to predict protective immunity in humans

Mouse testing is a key part of traditional pre-clinical vaccine development and often candidates that then proceed to clinical development fail as results do not translate from mice to humans.

The scale of the problem demands a systematic approach

Innovation requires a new paradigm with the aim of reimagining vaccine development. Rather than simply testing vaccines to see if they work, we aim to harness new knowledge of the immune system to design vaccines that will work.

Our approach

Unlocking the power of the immune system

Our vision is to move beyond traditional approaches to disease prevention, to precisely and systematically “tune” immunity against infectious diseases.

We are currently exploring new approaches that bring together cutting-edge immunology, AI capabilities and human challenge models to better understand ‘Correlates of Immunity’ – the measurable signs that a person is immune to a pathogen.

Building a better understanding of these correlates are crucial to designing vaccines and antibodies that stimulate the immune responses needed for protection from disease.

Our areas of exploration:

  • Unique controlled human infection models (CHIMs)
  • Advanced assays
  • Predictive immunology using AI
  • A fast-track cycle
team

Correlates of Immunity is led by scientists who have already driven key immunology breakthroughs

Program Co-Lead

Professor Daniela Ferreira

Professor of Mucosal Immunology and Vaccinology at the Oxford Vaccine Group, Paediatrics Department, University of Oxford.

Consultant

Dr Malick Gibani

Clinician scientist and infectious diseases physician at Imperial with an interest in applying human infection challenge models to accelerate vaccine development.

Join our team

We’re gathering the greatest minds

EIT is growing rapidly and we are recruiting at pace. Thrive in a dynamic and fast-paced work environment, learning and growing every day alongside experts in science and technology.