March 31st, 2020
Sachi co-founder highlighted by American Physical Society
Creating the right medications to fight back against ever-evolving bacteria and viruses can be a long, multi-year process—but in cases of deadly pandemics, like COVID-19, therapeutic development has to happen much faster. New approaches called smart therapeutics could be a key to changing the drug-discovery landscape.
“When it comes to pathogens such as bacteria and viruses one of the biggest strengths they have is that they can change…smart therapy means that we can keep up with evolving pathogens,” says Chatterjee. “If you think of a traditional drug discovery and development pipeline, it takes 10 years or so to create therapies, and ... $1 to 2 billion worth of investment. And that model doesn't really work with evolving pathogens, which are going to evolve by the time the drug is out.”
Versatility comes, almost counterintuitively, from its ability to be specific: using computational models. Our platform attempts to identify targets for therapeutics that can best disrupt each specific pathogen
“We have a platform that generates nucleic acid molecules that can go and bind DNA or RNA and prevent certain genes in these bugs from being expressed. The nice thing about this platform is that it is actually pretty agnostic [as] to the disease, the species, and so on,” says Chatterjee. “It's an entire package where we design, we build, and we test these molecules.”
Traditional drug discovery methods often rely on identifying molecules from bacteria and fungi that they use in their chemical warfare against other bacteria and fungi. As Chatterjee points out, bacteria are able to quickly gain resistance to such therapeutic methods because they’ve been adapting to similar attacks for billions of years of evolution. These discovery methods can also take 10 to 15 years to identify an effective therapy for a specific bug, which is too slow and too expensive. The computational tool box enables speedy identification, construction, and testing of molecules that target new mechanisms in pathogens.
“[We] create a molecule for every single gene in an organism of interest and directly target that and identify whether or not it has strong therapeutic potential, [and] train our computational models in a way that we can predict what genes to go after,” says Chatterjee. “We very quickly get information about what genes are good targets…after this discovery process, which we accelerate and finish within a week, [we take] the best molecule to do animal work