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Leveraging Biosimulation to Inform Optimal Use of COVID-19 Vaccines

Being a team of results-oriented scientists working to address the medical challenges of an unprecedented pandemic has fueled Certara’s propensity for innovation. Since the early days of COVID-19, we have been working alongside pharmaceutical companies, global health foundations, academia, and regulators to advance therapies and vaccines. Key to our work has been building upon our existing technologies to determine applicability for COVID.

This blog focuses on how we have innovated a technology and approach that was initially used to solve a completely different challenge to address COVID.

Certara’s mechanistic models allow researchers to study how a drug or a biologic is handled by the human body in computer-generated, virtual patients. They enable virtual computer-based trials to be conducted that may be impractical or unethical to perform with real subjects due to a range of recruitment challenges such as age, concurrent diseases, or comedications. The benefits of biosimulation are many, but the speed factor is pivotal for COVID-19, especially as we grapple with how to optimize the vaccine supply chain.

Optimizing Vaccine Dosing

One of the most recent challenges that we believe can be addressed with mechanistic modeling has been around the limited supply of regulatory-approved COVID-19 vaccines, to help answer key questions, such as:

  • Do elderly people require a higher dose of the vaccine?
  • Might a lower vaccine dose be effective for young people?
  • Can the interval between doses be increased and by how much?
  • Can people receive their first dose of one vaccine and their second dose of a different vaccine?
  • How long does a vaccine’s antibody response last? Will a booster shot be required in a year?
  • If people have had COVID-19, should they still get a vaccine, and do they need the full dose?

Developing the COVID-19 Vaccine Model

Certara’s immunogenicity (IG) model, which has been focused on unwanted immunogenic effects, has been validated using data from more than 20 clinical case studies, shared with global regulators and is being applied today to the development of new biologics. The team, recognizing that maximization of the immune response was needed for effective vaccine development, reworked, calibrated, and validated the IG model for COVID-19. Leveraging the Simcyp Simulator, Certara’s vaccine model generates virtual populations of different ages, allowing a series of virtual clinical trials to be run using the COVID-19 vaccine model that will determine which vaccine dose will generate the maximum antibody response for each age group.

The team demonstrated that they could predict with a virtual trial the outcomes of an actual clinical trial using those vaccines. Certara’s COVID-19 vaccine model is now being used to investigate dose selection for different populations and determine optimal timing for the second vaccine dose. Results from the COVID-19 vaccine model have already been submitted to a global regulatory agency to support clinical trial designs.

Determining the Best Dosing Interval

The COVID-19 vaccine model shows in graphical form the antibody response (or how many antibodies a person produces against the COVID-19 vaccine) when the second vaccine dose is given three, four, five, six, or 12 weeks after the first dose. Antibody response is used as a surrogate for efficacy in vaccinology and is considered the best biomarker. This approach can show when the maximum antibody response is generated by the second vaccine dose and at what interval after the first dose that response begins to diminish. For example, in the hypothetical case below, the data show how long the second dose can be delayed before it starts to have a negative impact on the level of antibody response generated. This information is used to guide the next clinical steps.

To learn more about how we’re supporting vaccine optimization, download the white paper:

About the author

By: Piet van der Graaf

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