San Diego Core

Janusz M. Sowadski, PhD., CSO

Janusz Sowadski is the co-founder and President and Chief Executive Officer of DNA-SEQ Inc. Mr. Sowadski was trained as a protein crystallographer - a scientist focused on the crystal structures of proteins as well as structure-based drug design - and the modeling of signaling molecules (kinases and phosphatases).  Mr. Sowadski’s crystallographic team in La Jolla, sponsored by the University of California at San Diego, “solved” the first structure of protein kinases in 1991, which in turn established a firm structural foundation for the entire extended family of specific cancer cell inhibitors that exists today.  This work was awarded the U.S. Supercomputing Award conferred annually by the U.S. Supercomputing Society to an individual or team who has done the most in the prior year to advance the field of supercomputing.

Mr. Sowadski was also a critical member of the team of industry scientists assembled by Ciba-Geigy (now Novartis AG Basel) who together designed the first three-dimensional model of an inhibitor/protein kinase complex, and this model led to the design of Gleevec, the most effective targeted oncology drug used in the treatment of a form of leukemia (CML) and stomach cancer (GIST.)  Gleevec is among the top 30-revenue-producing pharmaceuticals in the world today.  After these achievements, Mr. Sowadski co-founded two successful ventures, one of which was focused on small-molecule drugs in the field of protein kinase inhibition, and the other focused on cancer diagnostic and cancer therapeutic platforms.

Mr. Sowadski received a Ph.D. in Physical Chemistry from Warsaw University (Poland), and an M.S. in Biophysics from the University of Virginia.  He also completed post-doctoral work at Yale University.  He has held research faculty positions at the University of California, San Diego and at Tufts University.

David Doyle, Co-Founder and CEO

David is a Co-Founder of a Los Angeles based technology group developing proprietary IP in three areas of digital technology that were designed to increase the efficiencies of the server side hardware infrastructure, enrich the user experience through client side software, and enhance search methodologies by implementing cognitive resources to the management of data.

Davide Moiani, PhD, Crystallographer

Mr. Moiani obtained a M.S. in Chemical Industry in 2004 from University of Parma and a Doctorate in Chemical Engineering in 2008 from Politecnico di Milano. After obtaining his doctorate he moved to La Jolla, California, to start a postdoctoral training at The Scripps Research Institute in Structural and Molecular Biology of DNA repair machinery under the supervision of Prof. John A. Tainer. This project was founded by the prestigious Skaggs Fellowship.  During 5 years of postdoctoral experience, Mr. Moiani accumulated a strong background in data collection using high energy synchrotron radiation facilities for X-ray crystallography (beamline 11-1 at SSRL, Stanford and SIBYLS beamline at ALS, Berkeley).

Mr. Moiani also used his background in chemistry to optimize small molecules (design, chemical synthesis, purification) as inhibitors of DNA repair enzymes. Challenging the cost of production of compounds for analytical characterization through scale-up for preclinical test. Knowledge in Chemical Biology, Structural Biology, X-ray diffraction, SAXS, ComputationalChemistry. (Scientific network: Canada-USA-Europe).

In 2009, Mr. Moiani was invited to spend a sabbatical semester at the Erasmus Medical Center in Rotterdam to be trained in SFM microscopy for the characterization of DNA-protein complex.

Amir Tabaian, Intern

Amir Tabaian is a Jefferson Scholar at the University of Virginia currently pursuing B.S in Biomedical Engineering. He is currently working with Mr. Davide Moiani at DNA-SEQ, specifically focusing on identifying targeted cancer drug specificity profiles using machine learning algorithms. Amir is also implementing genomic annotation software to provide DNA-SEQ rapid and comprehensive identification of cancer mutations.