91桃色

An atlas of human immune responses to candidate vaccines could give health systems an advantage when faced with the next pandemic. Developing this knowledge should be a top priority to protect people from future biosecurity threats. 

Pre-emptive immunology uses immunological tools and knowledge to prevent or limit a pandemic. It is a cornerstone of preparedness, as it allows scientists to predict human immunity to potential threats and respond rapidly if they materialise. However, we lack data about how the human immune system responds to potential infectious threats. 

Biosecurity risks are multiplying from both natural sources and man-made threats. In 2024, the international Global Preparedness Monitoring Board said that the world was 鈥渁cutely vulnerable鈥� to pandemic threats¹, despite improvements in surveillance and responses. Increased globalisation and urbanisation, antimicrobial resistance, climate and environmental change, and human-animal interactions are driving the risk of novel pathogens emerging and larger outbreaks of more transmissible organisms. 

For example, Avian influenza 鈥� which has killed billions of farmed and wild birds and has been detected in dairy cows 鈥� is a couple of mutations away from being transmissible between humans. It is one of several known zoonotic pathogens that scientists expect to eventually jump into humans.

At the same time, technological advances, such as gene-editing and artificial intelligence tools, increase the risk that bad actors intentionally develop harmful, transmissible pathogens. 鈥婱eanwhile, t鈥媓e rise of antimicrobial resistance means that prevalent bacterial infections may become untreatable. 

The Coalition for Epidemic Preparedness Innovations (CEPI) aims to produce safe, effective and accessible vaccines within 100 days of identifying a new pandemic threat. But there is currently a theoretical gap between the detection of a novel pathogen and being able to design effective vaccines tailored to induce protective human immunity.  

Emerging pathogens are likely to arise in similar families. For example, the COVID-19 pandemic causing SARS-CoV-2 is a coronavirus, a family whose members also cause Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. When COVID-19 hit, there was already a wealth of knowledge about how humans responded to vaccines targeting those diseases. It was fortunate that this knowledge existed, as it accelerated the development of COVID-19 vaccines. The recent outbreak of 鈥媡he 鈥婤undibugyo strain of Ebola 鈥媔s鈥� another example. 鈥婭t鈥� is one of three strains known to cause large outbreaks, 鈥媋nd 鈥媋dvancing our understanding鈥� of the鈥� human immune response will accelerate the development of pan-Ebola vaccines. 

To increase biosecurity resilience, research institutes and companies could already be testing candidate vaccines against potential infectious threats and mapping how the human immune system responds to them. Rather than embarking on full-scale vaccine development, which is costly and time-consuming, researchers can use predicted designs of infectious threats to challenge the immune system in small clinical trials. These studies could also identify potential therapeutic monoclonal antibodies (mAbs) for those who respond poorly to vaccines, 鈥媠uch as those whose immune system is suppressed鈥� during cancer therapy. 

滨尘辫别谤颈补濒鈥檚 Centre for Precision Vaccinology has the expertise to develop and test a number of these potential threats in advance.

Its researchers have built the capacity to use RNA technology and to manufacture clinical-grade material affordably. These skills could be harnessed to generate a seedbank of candidate vaccines and an atlas of human immune responses. Such knowledge could offer a blueprint for vaccines against emerging or engineered pathogens.  

Currently, there is insufficient data to predict how human immune systems will respond to novel infectious threats, and this knowledge gap presents a significant vulnerability to our biosecurity. 

AI and machine-learning tools thrive on data, and the lack of human immunological information is limiting scientists鈥� ability to harness the AI revolution to develop potential candidates鈥嬧�嬧��. Generating data 鈥嬧�媜n鈥� immune response鈥媠鈥� to different pathogen families will鈥� further facilitate鈥� AI use and help us respond even more rapidly to biosecurity threats.  

This approach represents a new model for biosecurity. Generating vaccine candidates and human immune-response data before a crisis emerges shifts preparedness from reactive to predictive, enabling potential countermeasures to be developed and evaluated in advance rather than under the pressure of an unfolding emergency.  

It is no longer a matter of time before humanity faces another novel pathogen that could cause a pandemic: it is a matter of when鈥�. Now is the time to generate the knowledge needed to develop vaccines more rapidly, ultimately saving lives and enhancing our biosecurity.