Truvitech’s idTRAX (Identification of Drug TaRgets and Anti-targets by cellular and molecular Cross-referencing) technology revolutionizes the process of drug target identification by querying functional kinases directly. Current technologies search for drug targets by genetically manipulating all genes, one-by-one, and checking which genes can treat the disease when modified. If we draw an analogy to searching for oil fields, this would be akin to “drilling everywhere”, which is costly, wasteful, and is bound to fail more often than not. Truvitech has designed a specialized collection of compounds, each of which binds a different combination of kinases. These compounds are not themselves fit to become drugs, but they serve as “probes” that reveal the identity of the best kinase drug targets for any given disease. First, these compounds are tested with a cellular model of disease to identify the compounds that induce a therapeutic effect on the cells. In the case of cancer, these would be compounds that kill cancer cells but not healthy cells. Next, Truvitech’s custom machine-learning algorithm uses biochemical information about the compounds to quickly “learn” the identity of kinases that are mediating the therapeutic effect. As such, idTRAX reveals drug targets in a single step, circumventing all gaps of knowledge surrounding information transfer across DNA→proteins→molecular networks inside cells. In the context of our “finding oil” analogy, idTRAX’s approach would be the equivalent of newer more efficient technologies for detecting oil fields, which utilize seismic waves as “probes” to perturb the landscape, collect the readout from the terrain, and then algorithmically hone in on the location of the oil.

The value proposition of idTRAX for drug discovery is three-fold:

1.    idTRAX cuts the time and cost required to identify novel and effective drug targets that work in living cells;

2.    idTRAX identifies anti-targets that medicinal chemists must avoid in their lead development campaigns, and thus increases the likelihood of producing an efficacious drug; and

3.    By predicting synergistic targets, idTRAX helps develop drug combinations that dramatically increase therapeutic outcome.

We are developing the first iteration of the platform around kinases for a number of important reasons:


  • kinases are involved in mediating most cellular processes, and can, therefore, serve as drug targets in a wide range of therapeutic applications

  • kinases are readily druggable

  • the existence of a large number of kinase inhibitors allows us to develop our chemical probe set without a resource and time-consuming chemical synthesis program

  • reliable kinase assays available commercially or through our partners make profiling kinase activities relatively easy

  • the polypharmacology between kinases can be used to therapeutic advantage

  • we have more than 10 years of experience with screening small-molecule kinase inhibitors in phenotypic assays.


The successful deployment of our platform requires two critical components: a specially formulated chemical probe set and a companion target deconvolution algorithm .