A population of bang-bang switches of defective interfering particles makes within-host dynamics of dengue virus controllable

Viral pathogens pose a continuous and shifting biological threat to military readiness and national security overall in the form of infectious disease with pandemic potential. Today’s limited vaccines and other antivirals are often circumvented by quickly mutating viruses that evolve to develop resistance to treatments that are carefully formulated to act only specific strains of a virus. The Defence Advanced Research Projects Agency (DARPA) has launched the INTERfering and Co-Evolving Prevention and Therapy (INTERCEPT) program that aims to harness viral evolution to create a novel, adaptive form of medical countermeasure, Therapeutic Interfering Particles (TIPs), that outcompetes viruses in the body to prevent or treat infection.

Whereas current preventive and therapeutic approaches are designed to target viruses in their original state at the time of discovery or diagnosis, INTERCEPT uses viral evolution as the basis for its protective effect. Because TIPs are harmless, virus-derived particles with defective genomes that can only replicate in the presence of virus, they interfere with viral infection by competing for essential viral components. And, just like their parent virus, TIPs are susceptible to mutation over time and co-evolve with the mutating virus, thus diminishing the virus’ ability to evade the therapeutic. INTERCEPT aims deliver new treatments for fast-evolving viruses such as Ebola, SARS, Dengue, Zika, and Chikungunya—providing broad coverage against multiple strains—and make available a platform technology that could be readily adapted to confront even engineered viral threats using novel molecular and genetic design tools, high throughput genomic technologies, and advanced computational methods to address TIP safety, efficacy, long-term co-evolution, and generalizability.

The Dengue research team of the INTERCEPT program works at QUT, QIMR and NUS Singapore. The mathematical and computational team is based in the QUT node of ACEMS. Tarunendu Mapder (ACEMS AI) and Kevin Burrage (ACEMS CI) have worked with John Aaskov (QUT IHBI, PI of DARPA ITERCEPT Dengue TIPs) and Sam Clifford (former ACEMS AI) to calibrate a virtual patient population using data from hospitalised dengue patients’ blood serological record. This virtual population has predicted the within-host dynamics of dengue virus and natural production of defective particles. We predict that these naturally generated defective particles can be purified and used as a co-evolving vaccine as a potential intervention strategy against Dengue. At the end of this paper we have proposed an efficient, precise, and personalised dose and duration of intervention for each individual in the virtual patient population using optimal control theory.

Link to publication: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006668