VACCINES AND OTHER THERAPIES AGAINST CANCER AND EMERGING DISEASE
Hello, and welcome to my online portfolio! I am an independent research fellow in Data Science and Health Research working between the Universities of Edinburgh (UK), Victoria (Canada) and as well as in Poland. Through these activities, I lead an international research programme focused on the development of computational tools for RNA therapeutics and vaccines. Here’s a link to my Linkedin and Scholar Profile.
With the recent success of mRNA therapeutics including the mRNA vaccines used during the pandemic, we have a therapeutic tool that can adjust gene expression or alternatively can be used for vaccines presenting antigens to both the cell-mediated and humoral immune response. My research programme is dedicated to the development of computational tools used to design these therapies and vaccines in cancer and other diseases.
Our scientific understanding of the human immune-system is now progressing at a rapid rate, allowing for the development of computational models that could predict the immune-systems of specific individuals and populations. Simultaneously, the last 2 months have seen breakthroughs in our ability to leverage Artificial Intelligence and Natural Language Processing techniques to design proteins with new functions, with tremendous implications for synthetic protein drug design and vaccine design. I am particularly interested in how these fields will converge through mRNA therapeutics and vaccine technologies. In order for these therapeutics to work, the designed proteins must avoid immune clearance or other immune-related toxicities. And for vaccines, the opposite is true, the immune-response must be broad across a defined population. In addition, mRNA therapeutics must conform to design constraints provided by manufacturers and ofcourse must express well in order to be functional. For these reasons there are interesting computational challenges in designing mRNA therapeutics and vaccines that require integrative -omics to identify drug targets, to develop theranostic and prognostic biomarkers for precision medicine, to survey different facets of immunity and keep progressing predictive immunology, and to combine this knowledge with AI-methods computational protein and mRNA design to progress the field of mRNA therapeutic or vaccine design.
In short, I am developing a highly collaborative and translational research programme dedicated to the identification of prognostic/theranostic biomarkers and therapeutic targets in complex diseases including cancers towards the development of new lines of RNA therapeutics to treat these diseases. My research leverages multi-omic interrogation of mass-spectrometry and high-throughput sequencing data and is progressing towards single cells. Because better predictive immunology models are fundamental to mRNA therapeutics and vaccines, high-throughput methods to interrogate the immune-disease synapse will be fundamental to the programme. The combination of the different streams described here will lead to the eventual development of AI-driven tools for mRNA therapeutic design, where the goal is to produce end-to-end solutions to deliver new protein drugs and vaccines as mRNA constructs with defined immunological profiles. I outline four interrelated research streams below, with a few publications.
Vision
My research group is dedicated to advancing cancer biodiagnostics and immunotherapy through four key research streams. We focus on multi-omic analyses to discover biomarkers and therapeutic targets, laying the foundation for precise interventions. My work in descriptive and predictive immunology harnesses high-throughput technologies to understand immune responses, crucial for personalizing treatments. We also employ single-cell and spatial proteogenomic technologies to delve into the complexities of the immune-cancer interaction, aiming to enhance immunotherapy outcomes. Finally, I leverage artificial intelligence in the design of mRNA therapeutics and vaccines, striving to create tailored solutions that integrate immune-modulatory elements for effective cancer treatment.
Collaborations
Javier Alfaro’s research in infectious disease and cancer biodiagnostics has led to meaningful collaborations worldwide. By integrating multi-omic data and AI-driven tools, his work has focused on developing precise diagnostic methods and personalized treatments. These international partnerships have facilitated the sharing of knowledge and resources, advancing the understanding of disease mechanisms and the development of mRNA therapies and vaccines. These efforts are helping to enhance the healthcare community’s capacity to address complex health challenges with innovative and accessible solutions.
Publications
A full list is available here.
Join the RNA-therapeutics and vaccines international research cluster
To support the next generation of therapeutics, a data driven approach is essential. I employ Software Engineers, Data Engineers, Mathematicians and Statisticians to play critical roles in our research and development programs. Join as an undergraduate, Masters student or PhD students with either biology or computational expertise. Regardless of your background, we provide an environment to help you develop in pharmaceutical data science with the ultimate goal of advancing the design of mRNA therapeutics and vaccines. Students joining can do so through the University of Gdansk, The University of Edinburgh or the University of Victoria. Students with their own project ideas are encouraged to bring up their ideas.