Advances in machine learning have enabled the prediction of immune system responses to prophylactic and therapeutic vaccines. However, the engineering task of designing vaccines remains a challenge. In particular, the genetic variability of the human immune system makes it difficult to design peptide vaccines that provide widespread immunity in vaccinated populations. We introduce a framework for evaluating and designing peptide vaccines that uses probabilistic machine learning models, and demonstrate its ability to produce designs for a SARS-CoV-2 vaccine that outperform previous designs. We provide a theoretical analysis of the approximability, scalability, and complexity of our framework.

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new combinatorial machine learning system that could both decrease research time needed for a COVID-19 vaccine and make it more effective, researchers said. The platform, called OptiVax, focuses on developing peptide vaccines, which are a different approach from common whole virus, DNA, and RNA vaccines currently among the more than 100 vaccines in development. Peptide vaccines are a relatively recent development in the vaccination game that are designed around one specific short amino acid string, called a peptide, that can be found in the target disease. Peptide vaccines use a synthetic version of the peptide that is created in a laboratory and not harvested from the disease itself. Traditional vaccines have a larger amount of genetic information in them that isn't useful in developing resistance and can lead to unwanted immune responses and dangerous reactions--it's these genetic elements that peptide vaccines are designed to eliminate, MIT said.

NEC Corporation has established a new company that promotes the development and application of therapeutic cancer peptide vaccines using advanced Artificial Intelligence (AI) technology. The new company, CYTLIMIC Inc. (CYTLIMIC), will use NEC the WISE AI technologies combined with machine learning and experimentation to produce a unique "immune function prediction technology" that is able to efficiently discover peptides that are potential vaccines in a short period of time and at a low cost. NEC has been engaged in collaborative research since 2014 with Yamaguchi University and Kochi University, and in clinical research with Yamaguchi University, resulting in the discovery of a peptide vaccine that promises to be effective in the treatment of hepatoma and esophageal cancer and is compatible with the genetic profile of approximately 85 percent of Japan's population. Currently, it is also advancing its application as a new cancer drug through CYTLIMIC, by developing investigational use formulations of the discovered peptide vaccine, confirming its safety and efficacy through nonclinical and clinical tests, and investigating its commercialization with pharmaceutical companies. In recent years, advances in life science have been accompanied by advances in elucidating the human immunity mechanism, and new cancer therapies that utilize immunity are being administered.