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Innovative and continuous remote patient monitoring, along with AI-based predictive analytics, are advancing progress toward replacing the one-size-fits-all, population-driven vaccination model.
The COVID-19 pandemic brought the importance of vaccine development to the public forefront. The virus has killed over one million people in the US and infected more than half of Americans. Many more would have been impacted without the rapid development of lifesaving vaccines. The first viral genetic sequence of SARS-CoV-2 was produced in record time followed closely by FDA approval of messenger RNA (mRNA) vaccines by Pfizer and Moderna, and emergency use authorization of the J&J viral vector vaccine. These approved vaccines are safe with side effects that are generally mild.
Valuable research and developments during the pandemic will have a lasting impact on healthcare delivery and the future development of vaccines. Discoveries are only beginning to emerge around the subtle physiological responses that occur due to immune-mediated inflammation. Vaccines trigger the innate immune system, generating an inflammatory response that activates the adaptive immune system. The adaptive immune system generates antibodies and cellular immunity specific to an antigen, which provide long-term protection from infections.
Therefore, the primary goal in vaccine development is to achieve the immune activation required to protect a patient while minimizing side effects caused by it. These side effects, referred to as reactogenicity, are the physical manifestations of the inflammation caused by a vaccine. There’s been ongoing debate in scientific communities as to whether reactogenicity to a vaccine specifically correlates to a robust active immunity.
Vaccine side effects, safety, and efficacy translated into heightened public discourse with the widespread rollout of COVID vaccines. A built-in bias exists to blame the vaccine for any perceived negative change in one’s well-being, and evaluation of the placebo-controlled COVID vaccine studies found that over 50% of reported systemic side effects could be explained by a nocebo effect—negative effects experienced due to the anticipation of negative effects. For this and other reasons, self-reporting is innately limited in our attempt to understand inter-individual differences in reactogenicity.
To address this, several investigators have conducted studies using digitally connected consumer devices to track changes in vital signs following vaccination. Despite the limited data available through consumer devices, these studies confirmed detectable, individual changes for the majority of people following vaccination. Importantly, these changes were so subtle that the majority would have been unrecognizable without knowledge of that person’s normal baseline.
However, because consumer devices only allow for tracking of a single daily value for a changing vital sign, like daily resting heart rate, important measures such as the peak changes and the duration of their deviation from normal, as possible correlates of the full inflammatory response, can be missed.
The small number of people who have undergone testing of immune response following vaccine have confirmed variability that spans multiple orders of magnitude in antibody levels achieved. Certain people may benefit from a higher dose vaccine and/or a sooner booster, while others may not require a booster as often or a lower dose. Currently, we are not yet able to differentiate between the former and latter. That’s because vaccine development, like most of medicine, historically looks to population-based data—in this case, by assessing mean levels of antibody production, or reported side effects, and, most importantly, the percentage of people who contract an illness after receiving a vaccine. Clinical studies of immunogenicity are carried out in small subpopulations and extrapolated to essentially the global populations, despite there being a heterogenous immune response to vaccines. As the COVID journey unfolded, the emergence of variants has made the landscape even more complex. Ultimately, the goal of all vaccination programs is to identify the safest possible dose and frequency delivering the optimal immune response to protect the individual.
Powerful wearable sensor technologies, especially when supported by artificial intelligence (AI)-driven personalized analytics can provide a comprehensive and objective individual physiologic profile of a person’s unique response to vaccination. Medical-grade biosensors capture and learn a person’s pre-vaccination baseline and create a physiologic digital twin. Going forward, the individual is continuously compared to their digital twin, which effectively removes expected variations, leaving only vaccine-induced differences. By doing so in real time, the system can precisely determine the onset, duration, and extent of an inflammatory response.
An important study is underway to generate new insights into a more targeted approach to vaccine development. The Vaccine-Induced Inflammation Investigation (VIII) Study: The “Eight” Study and its Immunologic Response Sub-study seeks to identify individual differences in physiologic changes associated with immune system activation in patients receiving vaccinations against COVID. For the VIII study, participants wear a biosensor beginning two to five days prior to vaccine and continue for up to seven days after. The digital twin created over the baseline period allows subtle physiological changes in the hours and days after receiving a vaccination to be detected and tracked until they return to that individual’s normal.
Beyond identifying the inter-individual variability in the physiologic measure of vaccine-induced inflammation, a key goal is to explore the association between that inflammation and that person’s subsequent immune response to the vaccine. In a sub-study, participants will also undergo serial blood testing to identify vaccine-induced humoral and T-cell immune responses in the short and medium term. The correlations between immediate physiological responses, antibody production, and cellular immunity will help define new metrics for targeted vaccination delivery.
The VIII study moves well beyond the traditional method of testing the collective response of a vaccine in large populations. The personalized predictive analytics provide a precision method to identify how an individual’s immune system responds to a vaccine, offering an unprecedented opportunity to measure vaccine efficacy and safety. The VIII study is expected to provide the most rigorous, detailed, objective evaluation of vaccine-induced reactogenicity and immunogenicity to date.
Steve Steinhubl, MD, Chief medical officer, physIQ