Internet Knowledge Mining tools and A.I. For Rapid Response to New Pandemics with Proposals for Synthetic Vaccines and Therapeutics. The Example of COVID19

This presentation will describe the use of knowledge gathering and management tools, and A.I. methods, to respond rapidly to pandemics. This is exemplified by the experience of COVD-19. The methods used are new but based historically on experience in the early responses to AIDS, Mad Cow Disease, and veterinary issues. Emphasis is placed on identifying and studying highly conserved features of the SARS-CoV-2 proteins that suggest importance and promise diminished problems due to escape mutations that could otherwise make vaccines and therapeutics obsolete in weeks.

The Hyperbolic Dirac Net and associated Q-UEL language, based on the Dirac Notation and algebra, are employed. These methods represent an unusual approach to interoperability in healthcare and translational research for medicine, and will be explained. They are tailored to initiate “wet lab” approaches that include lesser known strategies in synthetic vaccine design and peptidomimetic design, based on peptides made with D-amino acids. These will also be described.

Predictions and designs from these methods, tailored to the above laboratory approaches as methods for responding quickly to new pandemics, are described.

Fast responses to new pandemics are possible, in terms of proposals for peptide synthetic vaccines and peptidomimetics that can serves also as a first step in “drug in a pill” development. The important point is that these responses took just a very few days. However, like all computer-based proposals made since, they have yet to be realized.