Cancer

We have developed a novel series of FLT3 inhibitors with activity against several cell lines when tested at the NCI. These molecules are undergoing in vivo testing against models for glioblastoma.

In partnership with the NIH National Cancer Institute (NCI), we have tested over 250 novel small molecules against 60 different cancer cell types to identify lead molecules against 9 different types of cancer. Our small library of compounds represents an unexplored chemical space of potent therapeutics which are under active development as potential new anticancer drugs.

Our most potent therapeutic leads display up to 85% growth inhibition against melanoma and CNS cancer cells in vitro. Other compounds in our library inhibit the growth of colon, renal, lung, prostate, breast, and ovarian cancers between 60 and 80%. We hypothesize that these compounds are a novel class of kinase inhibitors, and current work with this library involves discerning the specific biological mode of action.

Neuroblastoma

We have identified several novel molecules with in vitro activity in neuroblastoma cells.

Chordoma

Along with collaborators in the UNC Catalyst group we determined that a combination of 2 kinase inhibitors appears to demonstrate synergy in vitro and initial in vivo studies appear promising. Animal studies have been performed by the Chrodoma Foundation. We have also used our machine learning models to identify a kinase inhibitor that appears just as active (nM) as the most potent molecules in clinical trials. We have an orphan drug designation for this disease.

Anderson E, Havener TM, Zorn KM, Foil DH, Lane TR, Capuzzi SJ, Morris D, Hickey AJ, Drewry DH, Ekins S. Synergistic drug combinations and machine learning for drug repurposing in chordoma.Sci Rep. 2020 Jul 31;10(1):12982. doi: 10.1038/s41598-020-70026-w.PMID: 32737414

Rank L, Puhl AC, Havener TM, Anderson E, Foil DH, Zorn KM, Monakhova N, Riabova O, Hickey AJ, Makarov V, Ekins S. Multiple approaches to repurposing drugs for neuroblastoma. Bioorg Med Chem. 2022 Nov 1;73:117043. doi: 10.1016/j.bmc.2022.117043. Epub 2022 Oct 4. PMID: 36208544