Advanced Immune Monitoring To Revolutionize Vaccine Development

A Detailed Perspective on Vaccine Safety and Efficacy Using Comprehensive Immune Monitoring In this insightful conversation with Dr. Eugenia Ong, Principal Research Scientist at the Programme in Emerging Infectious Diseases, Duke-NUS Medical School, we get a behindthe-scenes look at the critical work required to advance promising vaccine and antiviral candidates through clinical trials. Dr. Ong shares her rigorous approach to identifying robust molecular correlates of safety and efficacy, leveraging multiple platforms for data-rich immune monitoring, including multiplex cytokine measurements. By encompassing a broad range of cytokines and rigorously validating assays, Dr. Ong’s work ensures the reliability and consistency needed to generate actionable insights across long-term studies. Careful study planning, combined with high-quality data and advanced bioinformatic analyses, provides insights into the mechanisms of vaccine-mediated protection and enables the identification of meaningful biomarkers of vaccine response. This is a must-read for anyone interested in the latest innovations in immune monitoring and data-driven methodologies in vaccine development. ® “Our interest has centered on identifying molecular correlates for safety and immunogenicity in new drugs or vaccines. To support this, we leverage multiple omics platforms to rapidly generate data that can identify molecular correlates as potential endpoints in the clinical development of promising vaccine or antiviral candidates” Dr. Eugenia Ong Principal Research Scientist at the Programme in Emerging Infectious Diseases, Duke-NUS Medical School Could you briefly describe the focus and aims of your current research? I began my research with wet lab work in virology. During my PhD, I focused on the dengue virus, investigating the molecular mechanisms of viral entry into target cells, particularly when complexed with an antibody. This was driven by the phenomenon of antibody-dependent enhancement in dengue, which was not well understood at the time, especially in terms of how it modulates the host response for enhanced viral replication. From there, I transitioned to more translational work, focusing on a therapeutic antibody against dengue virus. At that stage, I was heavily involved in preclinical work, characterizing the effects of the therapeutic antibody and setting up numerous assays to evaluate its potency. This experience built my foundation in translational research and got me hooked on doing even more of it. Fast forward to now and we are focusing on early-phase clinical trials, trying to get through that hurdle of driving a candidate that works in preclinical research all the way to clinical research. Our interest has centered on identifying molecular correlates for safety and immunogenicity in new drugs or vaccines. To support this, we leverage multiple omics platforms to rapidly generate data that can identify molecular correlates as potential endpoints in the clinical development of promising vaccine or antiviral candidates. This is a very data-rich approach, particularly valuable when little is known about a candidate and decisions need to be based on robust data. We continually work towards validating new assays to generate as much data as possible to support the clinical development of new drugs and vaccines. What would you identify as essential considerations in the clinical development of vaccines and antivirals? An important consideration is having a well-planned study, which we typically develop together with the collaborating principal investigators (PIs) or clinicians. A critical aspect is the choice of sampling points, especially when there is limited information in the literature on optimal timing and sampling points that would yield the most meaningful data. This is usually where we begin. From there, we work with our collaborators to refine the main methods appropriate for their research questions. Since we generate large datasets, data analysis is a key part of the conversation. This includes bioinformatics pipelines and techniques like principal component analysis or unsupervised clustering to analyze data based on specific parameters relevant to different patient groups or correlations with clinical outcomes. What are eventual challenges to consider in the clinical development of vaccines and antivirals? I think with clinical trial samples, it is very important to have high confidence in the assays we perform. Clinical trials can take a long time, considering patient recruitment and other factors, often spanning months or even years. We have to be very careful with concerns like batch effects. We ensure thorough assay validation and include appropriate assay controls and bridging samples to make sure all of the data can be used reliably. There are often trade-offs that require careful planning. You may need data soon after patient recruitment, but you also want to compare it with data generated much later in the clinical trial. This is something we typically discuss with collaborators to ensure everyone is on the same page. Another challenge is that we generally aim to generate as much data as possible from each sample. This multi-omics approach can make the cost per test significant. We are actively working with various partners to explore ways to reduce costs and pass these savings on to users, supporting them in their studies. In what ways do you apply multiplex cytokine measurements in your work? The most common way we have applied multiplex cytokine profiling is in immune monitoring studies focused on assessing safety or immunogenicity for new vaccines or drugs. We can also use it to understand disease biology in less well-defined pathologies. These kinds of immune monitoring studies typically generate data that help identify underlying correlates of treatment response or non-response, or if a side effect is observed, you can investigate correlations with specific cytokines. These are the various ways we apply cytokine profiling. At what stages of the clinical trial process do you run these immunomonitoring studies? I would say it depends on the need of the PI, but it typically makes the most sense to look at this very early on in the trial process. Perhaps a proof of concept trial or phase I study, where you have smaller sample numbers, but you want to get as much data as possible to support safety or efficacy of a potential candidate. Once you see the early data, it gives you confidence to continue measuring that through the continued development of that product. In the early stages, if a set of cytokines is clearly associated with a safety signal or correlates with a distinct efficacy signal, it would make sense to narrow down to a smaller panel that could then be deployed in a larger phase II or phase III trial. With the growing interest in personalized medicine, one can envision the increasingly prevalent use of biomarkers in clinical trials. Notably, for biomarkers that correlate with a specific clinical outcome, incorporating them into a clinical trial protocol could be highly valuable. Are there specific categories of immune-related proteins or specific groups of cytokines that have high potential for informing vaccine efficacy or safety? To begin, it’s helpful to have a broad overview of key cytokine types, such as those included in the Olink Target 48 Cytokine panel, which we routinely use in most of our clinical studies. The panel is largely sufficient for the types of cytokines we are interested in, like proinflammatory mediators. But it is also interesting to measure anti-inflammatory mediators, as disease biology often exists in a cyclical pattern. When observing lower levels of pro-inflammatory mediators, the question arises: Is this due to an effective anti-inflammatory response or could other, yet unidentified cytokines be influencing the process? A 45-plex panel does give you a good sense of what is at play. Besides using the Olink® Target 48 Cytokine panel in early clinical trials, are there other ways you incorporate this panel in your research? Apart from clinical trials, we do use the Olink Target 48 panel in various smaller clinical studies addressing specific questions in collaboration with clinicians at Singapore General Hospital. These studies can extend beyond serum and plasma, since the platform is versatile and amenable to other sample types. For example, we have collaborations with clinicians interested in inflammation or immuno-oncology and we work with the PIs to come up with sample processing strategies for the downstream protein profiling. With a multiplex approach that uses minimal sample volumes (as low as 1 uL) , you are clearly going to be able to get a lot more data compared to conducting a singleplex ELISA. Is the ability to do absolute quantification of these key immune mediators critical to you? I would say that in general, it does not really matter so much. Even with the Olink® Target 96 panels, we get relative quantification, so we have reported values. However, clinicians may prefer absolute concentrations, as this is more similar to the types of clinical tests conducted in hospitals and may also enable some level of comparison. Having the data in a quantitative format can be very useful, especially with the substantial data now available from biobanks and similar sources. If you’re observing higher or lower levels and lack a well-defined control group, this format enables comparisons with available data from a healthy cohort. Would the integration of Olink® Target 48 Cytokine with the new Olink® Target 48 Immune Surveillance panel add value to your studies? If so, in what capacity? It does add value with the additional targets we can now focus on, such as interferons, as well as T cell-related biomarkers, like granzymes, CD28 and so on. Whether or not we eventually run both panels routinely, I don’t know. It will depend on the requirements of individual studies. For a more T cell-centric study, it might make sense to include the Olink Target 48 Immune Surveillance panel to expand knowledge on additional protein targets of interest. This could help generate more data to strengthen the case for how the molecular environment is changing. Could you expand on the usefulness of measuring interferons and other T cell related markers? Interferons have always been very important inflammatory as well as antiviral mediators. If the mechanism you are studying is proinflammatory driven, or perhaps antiviral driven, then it does make sense to include measurements of interferons in the study. T cellrelated markers are particularly relevant in vaccine studies, where we now know that, beyond antibody response, the T cell response plays a significant role in mediating vaccine protection. www.olink.com © 2024 Olink Proteomics AB, part of Thermo Fisher Scientific. Olink products and services are For Research Use Only. Not for use in diagnostic procedures. This document is not intended to convey any warranties or representations of any kind. 1578, v1.0, 2024-12-25 ® Use of T cell related biomarkers can also be used to evaluate safety since imbalance of Th1 and Th2 cytokines have been linked to safety signals, particularly with some inactivated vaccines in the past. What are the next steps or emerging directions in your research that you are particularly excited about? We initially focused heavily on human samples, particularly clinical samples, but we now have interest from collaborators to focus on profiling preclinical samples. This is great because now we have the Olink Target 48 Mouse Cytokine panel. We can essentially use the same protein measurement platform from preclinical all the way to clinical trials, making for a very easy transition. Using the same platform throughout also ensures that results are more comparable and robust. We are currently working on a fairly interesting study involving the yellow fever (YF17D) and chimeric Japanese encephalitis (JE)-YF17D vaccines. Both vaccines share the same backbone, so they have shared T cell epitopes. However, they encode different structural pre-membrane and envelope proteins, such that vaccination with either produces neutralizing antibodies that are protective only against that virus (1). Our primary question is to determine the extent to which the T cell response contributes to protection, independent of antibodies. To investigate this, we are giving the vaccines in two sequences: YF17D followed by JE-YF17D, and JE-YF17D followed by YF17D. Both vaccines induce infection that result in detectable vaccine RNAemia. Observing the T cell responses after the initial vaccine dose, we aim to identify specific T cell responses that might correlate with protection to the challenge dose. We have early data from the Olink Target 48 Cytokine panel and are about to start using the Olink Target 48 Immune Surveillance panel, which we believe will be very useful for this study because it will provide us with a better understanding of protein biomarkers related to T cell response during vaccination. Reference: 1. Kalimuddin S, Chan YFZ, Sessions OM, Chan KR, Ong EZ, Low JG, Bertoletti A, Ooi EE. An experimental medicine decipher of a minimum correlate of cellular immunity: Study protocol for a double-blind randomized controlled trial. Front Immunol. 2023 Mar 10;14:1135979. doi: 10.3389/fimmu.2023.1135979. PMID: 36969244; PMCID: PMC10038230.