What is Vaccinomics?
The current medical practice is to universally administer the same set of vaccines to everyone. There are a set of assumptions underlying the current approach, and that is that everyone will react in the same way immunologically by developing protective levels of antibody, with near non-existent side effects. The approach also assumes that everyone is at approximately the same level of risk against a particular disease and that vaccine dose number and dose amount that are needed to develop immunity are about the same for everyone. These assumptions have resulted in a population level paradigm. And this has been hugely successful as a public health tool where vaccines have become widespread and in some cases, low cost, saving millions of lives worldwide. The weakness of this approach is that it ignores individual variability. And this has led to studies of vaccinomics or personalised vaccines.
What does vaccinomics mean? Omics refers to the set of technologies and understandings that have emerged in the post genetics era. These include genomics, proteomics, metabolomics etc. It is about understanding biology at a systems level, looking at overall architecture, and the processes that cause and follow gene transcription, rather than just what the DNA code tells us. Probably the most succinct definition is given by Poland et al. who coined the term vaccinomics;
“ Vaccinomics examines the influence of immune response gene polymorphisms on the heterogeneity of humoral, cell mediated and innate immune responses to vaccines both at the individual and population level”. (Poland et al., 2008).
The development of vaccinomics was made possible by the completion of the first phase of the Human Genome project and the international HapMap and also by the discovery of biomarkers and new molecular assay tools that allow high through-put detection of gene variations. From these projects and technological progress, came the idea that polymorphisms in key immune response genes can lead to heterogeneity in immune responses to vaccines. In particular studies of the Human Leukocyte Antigen system (involving a group of genes located on chromosome 6 which are related to immune system function) have added to our understanding. It is believed that the HLA region contributes significantly to genetic susceptibility to infectious disease and to variations in immune response to vaccines.
What do personalised vaccines aim to do?
Just as with pharmacogenomics, which aims to provide personalised or stratified medicine, vaccinomics is being talked about as the next generation of personalised vaccines. ‘Personalised’ can refer to different target levels: the individual level (for example recognising that presence of polymorphism ‘x’ or haplotype ‘y’ which might predict a high risk of an adverse reaction), the gender level (studies for example, have shown that for certain vaccines females have responded with higher antibody levels to vaccine antigens), the racial or ethnic level (where certain ethnicities have poor responses to vaccine antigens) and the sub population level (e.g. where a drug being taken by that population supresses transcription of an immune response gene causing in turn poor response to a vaccine antigen).
The reasons for developing, or targeting vaccines at different levels are:
1) To reduce the risk of adverse events following immunisation. Each year the costs linked to adverse drug reactions are estimated to be between $1.56 and $5.6 billion dollars annually in the US and affect over 770,000 people. In the UK they are estimated to cause approximately 6.5 per cent of all admissions to UK hospitals.
2) To maximise dose effectiveness or exercise dose sparing strategies.
3) To possible reduce costs by limiting clinical trial population sizes. If you can pinpoint which patients are likely to respond best to a treatment, you can increase the likelihood of demonstrating drug efficacy in clinical testing. Researchers can preselect patients for studies – a process known as 'enriching the clinical trial pool'. It is also possible to de-select subsets which are prone to adverse reactions, which are costly in trials.
Innovation systems and around vaccinomics
An interesting question is how would the vaccine innovation system need to change in order to allow for vaccinomics development? Are there additional actors and skills that need to be developed or integrated? Are there different systems needed for feedback or knowledge flow between actors? And does regulation facilitate or hinder progress in vaccinomics?
Structurally the market will change as personalised vaccines are made for specific sub populations. This will have impact for investment and funding of R&D. In the short term this might at first mean that costs are likely to rise as it is more expensive to collect genetic and biological data and develop a vaccine for a small subset of the population, rather than develop a one-size-fits all solution. However, in the last couple of years, there have been massive efforts by the academic, public and charitable sectors to develop basic science and infrastructure that can directly contribute to the development of vaccinomics and personalised medicines, for example, the UK Biobank and the Human Variome Project.
Importantly, firms, markets, researchers and customers operate under the influence of a regulatory framework. Our work has found that regulation both shapes and is shaped by products and progress in science. For example Health Canada’s proposed Progressive Licensing Model might encourage or eventually demand the submission of vaccinomics information when issuing licenses for new vaccines. The new model intends to monitor vaccines and evaluate associated risks throughout their life cycle. As adverse reactions to vaccines may only become apparent after their commercialization, testing for genetic factors affecting immune response may be one way to evaluate risk factors associated with the product and can be used to develop strategies to avoid these risks. The FDA has had risk based approach since 2002 as laid out in its Pharmaceutical cGMP initiative. Similarly a ‘Risk-based approach’ was introduced to EMA legislation with the revision of Annex 1, part IV of Directive 2001/83/EC.
General issues and problems for developing countries
Using different vaccines for different groups will require more time and effort in the vaccination process. An important question will be; do the savings from fewer adverse events, more effective dosing and potentially smaller clinical trials, outweigh the costs of creating and administering companion diagnostic tests for genetic variation or any other sort of screening? Currently, vaccinating is cheaper than testing. There is also a marginal benefit problem - to develop personalised vaccines is costly, and might only improve immune response for a relatively small fraction of the population. A wider question is will this different approach compromise herd immunity, and the public benefits that we are able to achieve by administering vaccines in a rapid and timely way. With a personalised approach to vaccines, there are also difficulties with ethics and public trust. Whenever genetic or biological data is used or stored, there are questions about who owns that data, who has access to it and how the data is used.
Given the commitment of the public and charitable sector in the contribution to datasets and basic science, we must ask the following question; if private companies use publically donated samples and public resources, and if they make a subsequent profit, how should the private sector be expected to contribute or ‘give back’? Will intellectual property rights and gene patenting present a problem for future innovation, And also how can this system which increasingly relies on publically funded large scale infrastructure, like UK biobank, be made sustainable given the move towards cuts in government funding?
Linked to the ethics issue is possibility of exclusion. If industry begins 'cherry picking' more 'valuable' subsets of the population for clinical trials which are those where efficacy is likely to be proved or are less likely to be susceptible to side effects, this might leave many other subsets of the population with no treatments.
Access to medicine medical, scientific and technological developments is a central tenant of the UNESCO Universal Declaration on Bioethics and Human Rights In addition The Millennium Development Goals (goals 4, 5 and 6) similarly aim to reduce child mortality rates, improve maternal health and combat HIV/AIDS, malaria, and other diseases (United Nations, 2011).
With progress in vaccinomics there comes a risk of excluding the poorest nations and the most vulnerable populations. To develop a vaccine for a specific subset requires study of that population’s genetic and genomic and even proteomic and other omic characteristics. To collect this kind of data requires significant infrastructure and capability. A strong regulatory framework is needed with capability for enforcing as well as legislating, particularly where there is data collection of biological samples and patient history, and clinical trial sites involved. Countries need to have capacity for adequate knowledge translation between the stakeholders involved in vaccine development, including publics. They need to have physical infrastructure for storage and analysis of genetic data and samples and they also need to have a public health system capable of integrating vaccinomics technologies and complimentary diagnostic tests. This represents a massive task for countries where the basic cold chain for everyday vaccine delivery is often compromised. In the case of vaccinomics, developing countries need to be involved in the development of the technology if they are to benefit from it. The importance of partnerships and capacity building becomes increasingly important.
For further discussion, see: Huzair, F., Borda-Rodriguez, A and Upton, M. (2011) Twenty-First Century Vaccinomics Innovation Systems: Capacity Building in the Global South and the Role of Product Development Partnerships (PDPs). OMICS Vol 15, No 9, pp1-5. DOI: 10.1089/omi.2011.0036