The Rapid Assessment of Platform Technologies to Expedite Response (RAPTER) program will be able to help researchers understand key host and pathogen factors that lead to the success of vaccines.
The COVID-19 pandemic highlighted the need to shrink the timeline of effective vaccine design from bench research to Food and Drug Administration (FDA) approval. Vaccine design, testing, and manufacturing are not only time consuming but also expensive. One approach to developing a predictive capability for matching a specific bacteria, virus, or toxin with the most appropriate vaccine platform is the Rapid Assessment of Platform Technologies to Expedite Response (RAPTER) program.
The Defense Threat Reduction Agency’s (DTRA) Chemical and Biological Technologies Department in its role as the Joint Science and Technologies Office (JSTO) for Chemical and Biological Defense is investing with researchers across multiple fields, such as computational biology, virology, bacteriology, and vaccinology, to develop this machine learning (ML)-based capability to rapidly choose a suitable vaccine platform for any viral and bacterial pathogen. This would allow the Department of Defense to rapidly counter current, new, and emerging biological threats.
Currently, there are several approaches vaccinologists use to develop vaccines that generate appropriate immune responses, including:
- Attenuated vaccines, which are weakened pathogens also known as live attenuated vaccines
- Inactivated pathogens also known as killed vaccines
- Subunit vaccines where a part of the pathogen is introduced through a delivery mechanism like a conjugate vaccine, which combines a weak antigen with a strong antigen as a carrier
- Nucleic acid vaccines that use genetic code
- Viral vectored vaccines that use a part of the pathogen and put it in a harmless virus that you give as a vaccine
While each of these approaches has proven effective, the trial-and-error approach common to vaccine development can be costly, labor intensive, and often does not adequately generate long-term protection against the pathogen of interest. RAPTER will make predictions based on aligning immune responses between natural immunity to a certain pathogen with those generated by each vaccine platform to predict which platform will have the most appropriate immune response. Several common platforms will be evaluated, initially with the Ebola virus, Burkholderia pseudomallei that causes Melioidosis and SARS-CoV-2.
Led by the Los Alamos National Laboratory, researchers at myriad universities and laboratories anticipate the RAPTER tool will be able to help researchers understand key host and pathogen factors that lead to the success of vaccine platforms and will incorporate data from testing vaccine prototypes for a variety of different pathogens. Using existing data and targeted experiments, the team will develop ML prototype tools and optimize them by incorporating additional data and testing for 10 to 20 representative pathogens followed by validating the tool on an untested pathogen. Researchers can also add new platforms to the RAPTER tool as they receive data generated for those platforms to address the need to protect the Joint Force from current and anticipated new chemical and biological threats.
Adapted from original story by DTRA Chemical and Biological Technologies Department