KT: What is an immune correlate?

UWR: An immune correlate is a measurable parameter that tells us whether a person will be protected against an infectious agent, such as a virus, bacteria, or in our case, a parasite. For us, it means that we’re looking for a measurable immunological parameter that will tell us if someone is going to be protected against malaria after he or she is vaccinated.

KT: Why is the identification of an immune correlate important?

UWR: One of the key problems for malaria, but also for other vaccines like HIV, is that there is no correlate and so most of the approaches to vaccine development are empirical, meaning that for most candidates that are tested in clinical trials, we don’t really know how they work.  There are some vaccines, for example certain types of flu vaccines, where we know that the vaccine needs to reach a specific antibody titer in order to be protective. We don’t have anything similar for malaria yet.

There are two parts to the immune response: One is the humoral or antibody-mediated response and one is the cellular response. Both humoral and cellular responses are interconnected.  Following vaccination, a complex interaction between different pathways within the immune system gets triggered, and as we are trying to identify an immune correlate, we are looking at the antibody as well as the cellular response.

So when you ask why it’s important to identify immune correlates, there are two aspects to this question. One is an academic consideration: We’d like to generate new hypotheses about the mechanisms of vaccine-induced protection. The more information we have about what correlates with protection, what mediates protection, the greater the probability we can develop vaccines where none exist or improve existing ones that confer only modest levels of protection.  

The other reason for identifying immune correlates is a practical one. We’d like to have a surrogate for vaccine-induced protection that allows future trials to proceed more readily. If you have an immune correlate, clinical trials would use that surrogate as an endpoint, and that would save money and time and streamline vaccine evaluation.  An immune correlate that is acceptable to a regulatory agency, as a predictor of protection, is critical for us. We could use this immune correlate to determine if a vaccine is going to be effective, before assessing it under conditions where people would actually become infected. This would help us to avoid very large, expensive, and time-consuming Phase 3 trials. And even for the smaller trials—the Phase 1 and Phase 2 trials—we would save time and money by focusing efforts on vaccines that induce immune response that are proven to be protective in humans.

In the meantime, in malaria, we have the advantage of the Controlled Human Malaria Infection (CHMI) model, which is extremely valuable for us to use as we look for immune correlates. CHMI studies in malaria are possible because malaria infection can be readily treated with no long-term consequences, if managed appropriately. In CHMI studies, relatively small numbers of volunteers are deliberately exposed to the bites of infected mosquitoes; since we know that everyone got infected, and precisely when they got infected, we can compare the immune responses in protected versus non-protected volunteers toward determining the key differences. The CHMI model has been critical at informing malaria vaccine development, and efforts are underway to develop similar models for other infectious diseases.

KT: What kind of immune correlate studies does MVI support?  

UWR: Since biomarkers, or immune correlates, are a critical component for malaria vaccine development, we’ve initiated a whole battery of studies focusing on immune correlates. And we know that antibodies seem to play an important role in protection after immunization with RTS,S/AS01, the most advanced vaccine candidate in our portfolio that has been shown to protect young African children from malaria. Therefore, we’d particularly like to gain a better understanding of the antibody response and the cell populations that are involved in mounting a strong antibody response. 

We are targeting three major research areas that allow us to look—in an unbiased way—at a massive number of biological parameters following vaccination. These research areas involve the use of relatively new screening technologies. For example, we are targeting a large systems biology approach to screen peripheral blood mononuclear cells for gene expression after vaccination and to connect the gene expression data with immunological readouts. We also use a systems serology approach to screen serum antibodies for more than 1,000 parameters. In addition, we use antibody transcriptomics to look at sequences from the entire antibody repertoire elicited following vaccination. In the past years, these unbiased screening technologies have become more broadly available and we are increasingly tapping into them.

KT: Are there new developments or anything on the horizon that you are looking forward to?

UWR: The screening technologies that we are now starting to work with are all fairly new technologies, and the verdict is still out on whether they will help us identify an immune correlate.  We are at the cutting-edge of this work, in large part because of the CHMI model that affords us and our partners access to samples with highly defined characteristics.

KT: What are some of the main challenges you encounter in your work?

UWR: It’s challenging to undertake the search for an immune correlate in the context of something as complex as the human immune system. It’s like looking for a needle in a haystack. We don’t really know where to start and that’s why these high-throughput screenings are helpful, because you can look at a lot of different parameters at the same time in an unbiased way.

Scientifically, it’s challenging that we have to work with extremely large data sets. You can imagine, when you do such broad scans there’s an immense amount of data being collected, so you have to be very careful with how you mine through these data. It’s not an easy task. And while many of our collaborators are specialists in the technology they’re using, they don’t come from a malaria background; therefore, one of MVI’s key roles is to ensure that we guide our partners throughout the project and maintain connectivity to the overall project goals. Specifically, we help to link the data that our partners generate to what we consider to be front and center in malaria vaccine development, ensuring that the integration of new data that arise in our ever-changing knowledge of malaria, remains optimal.

And then there are obviously a lot of logistical challenges that we need to navigate to ensure timelines are met. All of the projects are large, multi-partner collaborations, and since the different stakeholders have their own goals, we work to align the stakeholders. While the work is challenging from both a technical and operational standpoint, the massive importance of the vision we are jointly working toward—a world free from malaria—makes the work tremendously rewarding.