Current VE evaluations rely on expensive and time-consuming clinical trials or observational studies that cannot quickly assess how new variants impact vaccine performance.
BethBio's VE-GD technology estimates VE in-silico using viral genome data, predicting vaccine performance against past, present, and hypothetical variants. This approach is faster, cost-effective, and highly accurate.
VE-GD aids antigen optimization, enhances clinical trial designs, reduces costs, and supports regulatory approvals by providing rapid and reliable VE evaluations, ensuring vaccines are better prepared for emerging variants and market demands.
Vaccine effectiveness (VE) – or vaccine efficacy in clinical settings – is the primary metric for evaluating a vaccine’s performance. However, obtaining reliable VE data has traditionally required clinical trials or real-world observational studies. Vaccines would first have to be manufactured, administered, and then one would still have to wait for enough participants to develop clinical outcomes (e.g. symptomatic infection) before VE can be assessed. This process is time-consuming, expensive, and resource-intensive.
Moreover, conventional VE evaluation cannot immediately assess how newly emerged variants impact vaccine performance. This delay leaves pharmaceutical companies and public health authorities unable to act quickly in response to evolving pathogens, which is a critical limitation in a fast-changing viral landscape.
To overcome these limitations, BethBio developed the world’s first systematic method, VE-GD, to estimate and predict the VE of a vaccine against any given virus variants in-silico. Using bioinformatics, this innovative technology calculates the likely VE of a vaccine against past, present, and even hypothetical future variants. By analyzing genetic differences in key antigenic regions, VE-GD delivers rapid and cost-effective VE predictions once the target variant's genome data becomes available – without the need to wait for costly trials or lengthy observational studies.
Published in Nature Medicine in 2022, the basic version of the VE-GD model already achieved a remarkable 95% prediction accuracy in predicting VE of different COVID-19 vaccine products against symptomatic infection, against different variants. The model also takes other important factors into account and adjusts predictions accordingly, such as vaccine platform, target age group, geographical region etc. In addition, VE-GD can provide VE estimates for different clinical outcomes such as symptomatic infection, hospitalization and death, offering high versatility for different client needs.
VE-GD also empowers antigen optimization towards a meaningful clinical endpoint. It complements other BethBio solutions, such as virus evolution prediction, to assess the importance of different genome regions to VE and inform the best antigen design. For instance, the VE-GD model for Influenza simultaneously evaluates both the HA and NA genes to determine the best antigen combination for influenza vaccines.
BethBio has developed specialized VE-GD models for Influenza and COVID-19 vaccines and is expanding its application to other infectious diseases such as RSV.
Besides supporting antigen design, gaining access to early VE evaluation provides unparalleled strategic advantages across the vaccine development cycle.
To begin with, evaluating VE becomes a readily accessible tool that no longer requires extended time and experimental costs. Once the viral genome data of the target strain is available, VE-GD allows vaccine producers to assess their products’ performance against different circulating strains and predict the impact of future mutations. This helps companies make informed decisions about vaccine formulation, anticipate product lifecycles, and plan timely updates to stay ahead of competitors.
On top of that, BethBio also provides suggestions for our clients’ clinical trial designs to improve probability of achieving optimal VE outcome, such as the optimal time and location to conduct the trial. Accurate estimation of VE also improves the precision of sample size calculations, reducing unnecessary subject enrollment and associated costs. In case of drastic changes to circulating strains and anticipated VE, BethBio could also alert vaccine companies and discontinue the trial timely when necessary. In one instance described by our client, VE-GD could have saved them millions of dollars in their COVID-19 vaccine trial, during which the Omicron variant emerged and severely reduced VE. Retrospectively applying VE-GD using data available until the trial produces VE estimates that differed from actual trial outcomes by only 0.4% and 3.1%, demonstrating the model’s accuracy and potential in avoiding sunk costs.
VE-GD has also proven valuable for regulatory submissions, successfully assisted clients in getting regulatory approval for vaccines. In one case, a client was asked by a drug authority to provide additional VE information of the COVID-19 vaccine for specific prior variants – data the client did not have and could no longer acquire. Using VE-GD, BethBio provided the client with a detailed VE estimation report, which was accepted by the drug authority. Approving the drug application, the drug authority also remarked on their recognition of the VE-GD and highlighted its potential to facilitate future vaccine drug approvals.
The ability to estimate VE early, accurately, and cost-effectively with VE-GD is transforming how vaccines are developed, optimized, and approved. BethBio empowers pharmaceutical companies to respond quickly to emerging variants, streamline clinical trials, and design vaccines with better clinical outcomes. Contact us today at business@bethbio.com to learn how we can transform your vaccine development process and keep you ahead of competition.