The Shamay Lab
What We Do
The main goal of our lab is to develop novel nanomedicines for personalized cancer drug delivery and informatics solutions to the field of nanomedicine in both research and the clinic to eventually benefit patients.
Topics studied in our lab
The digital age brought an information revolution with automated data analysis, machine learning and data mining applied to almost every field of research including drug delivery and nanomedicine. Nanoinformatics uses data science and information science to optimize, standardize, and understand the synthesis, characterization, and biological effects of nanomaterials.
Personalized Cancer Nanomedicine
Precision medicines, personalized medicines, or targeted drugs are so named for their perceived specificity to molecular targets in cellular signaling networks. The activities of precision drugs can be limited by the triggering of adaptive signaling pathways in the treated cells. We wish to develop ways to overcome these limitations with nanomedicine and combination therapy
Literature Data Mining
Humanity has generated an enormous amount of scientific and clinical data in the form of papers, books and patents, which are stored in large databases and used by scientists as grounds for new discoveries. With the rapidly increasing wealth of available information, it has become practically impossible for individual scientists and physicians to perceive what is known and even more difficult, what is unknown in a scientific field. We are developing a path towards navigation, organization and prediction within the many layers of cancer complexity from molecular drug formulations and into personalized combination therapy.
We still have only a very limited understanding of what is an optimal drug combination for certain diseases. And even more difficult is how to formulate drug combinations into nanoparticles. We wish to employ computer science, data mining and machine learning to clarify what are optimal drug combinations in nanomedicine.
Crossing challenging barriers
We have developed a powerful tool in vitro for use in the identification and characterization of matrix penetration processes in our model system. A major advantage of this development is its improved sensitivity, which allows it to detect subtle dynamic property in dense cellular environments.