The pandemic has underscored the value of understanding individual vulnerability to disease, and scientists think they have a promising means of identifying it. But, argues Professor Kourosh Saeb-Parsy – chief medical officer at Oxford Immune Algorithmics – we need to be collectively courageous enough to make the commitment to further research.
After two years of a pandemic, some people have seen the dreaded double lines on lateral flow tests more than once – sometimes even when vaccinated and boosted – while others have remained infection-free throughout. Why is this?
Certainly different levels of exposure play a part. These are linked to complex and interconnected social determinants.
Risk of infection has been shown to vary with, for example, deprivation, physical environment, race and ethnicity.
Importantly, however, research also suggests that our ability to effectively combat Covid is down to variations in our individual immune systems.
Simply put, it seems some people have immune systems better equipped to deal with Covid than others.
These differences are partly driven by factors such as age, previous medical conditions or use of medications. But, importantly, such variations are also seen in young, healthy adults.
We know, for instance, that the level of antibody produced by different healthy individuals to the same vaccine dose can vary as much as 10,000 fold.
Given that vaccines are a precious resource, and that administering them at scale is complex and time consuming, there is a strong argument for becoming more selective in our administration of them.
The approach to date has involved repeated mass vaccination of entire populations. Moving instead to vaccinate based on need, as determined by an individual’s immune response, would be more efficient and may support more equitable worldwide distribution of vaccines.
To be able to do this would require further research. It would be necessary to test for antibody levels in large groups of people, regularly, and then conduct expert analysis of that data.
This sort of data collection would allow researchers to determine the boundaries at which boosters need to be given, to understand which people are at most risk of infection, and to understand the immune system risk factors for developing Long Covid.
The benefits of such work would go far beyond dealing with the pandemic, however. There is increasing recognition that the immune system has a critical role in the development of most, if not all, diseases.
Having an understanding of an individual’s immune baseline would make it much easier to identify when there had been a change, and also to understand the clinical significance of that change for you as an individual.
It would also support the development of treatments precisely targeted to a patient.
The technology to make this happen is increasingly available. At home blood testing will enable monitoring of core blood values, providing a full blood count with just a finger prick sample of blood.
A data platform that enables the collection and storage of such information at scale, and allows clinicians and researchers to analyse it, already exists.
From this it will, in the longer term, be possible to apply responsible artificial intelligence algorithms which help clinicians understand which patients need which interventions.
Such technology can also improve the care of patients whose immune responses we already monitor by routine blood tests.
Some children with cancer, for instance, have to have invasive blood tests regularly: either to monitor their response to chemotherapy, or to confirm they are still in remission.
A device which requires only a finger prick to provide important results, and which can be used at home, would transform quality of life for such patients and their families – and it’s an approach already being piloted.
In addition, greater research gives the potential to become much more sophisticated in how we view the results of such tests.
At present, the interpretation of blood tests tends to be binary – ‘normal’ or ‘abnormal’, based on broad ranges determined by averages in a population.
Were we to analyse readings for a greater range of people, and to take readings from people even when they are well, clinical evidence tells us that we could deliver far more precise information, prevent disease and save lives; by gaining a sense of what is normal and abnormal for a specific individual, it would show that medical treatment is not the same for everyone.
We should start on this mission now. That will require government leaders across nations and research institutions to commit to exploring this area.
But the sooner we start collecting data on immune response, the quicker researchers can capitalise on this promising approach and develop new protocols which identify ill health sooner, improve treatments, and support improved welfare for all.
