Thank you for Subscribing to Life Science Review Weekly Brief
Protai, a startup, is working on proteomics, the study of proteins and their interactions after it raised an 8 million dollars seed round.
FREMONT, CA:With advances in processing power and algorithms, technology is becoming an increasingly important part of the complex drug discovery and testing process, and it is opening up new areas for analysis. Proteomics, the study of proteins and their interactions, is next up while Protai, a startup, is working on the 8 million dollars seed round it raised. Protai is placed below the cells and systems layer, where problems are visible as symptoms and above the genome and transcription level, where genetic factors can be identified. The largest proteomic database was put together by the company with some 50,000 samples from 6,000 papers, and harmonized the chaotic data where AI natural language was helpful so it can act as a single source of information.
Eran Seger, CEO and co-founder, explained the idea was not to analyze a small sample study but instead they intended to analyze all of the data out there on a specific disease but since proteins were collected and sequenced from a variety of conditions, instruments, protocols and controls it was like comparing apples to oranges. Anyway, by placing all the data together a higher level map of proteins and their interactions in the context of a particular given disease can be produced. Getting to know everything that can happen at a molecular level is always helpful. Seger further added that advances in biological explainability can give rise to better drug targets and drug candidates. Several high-value targets that are currently pursuing in the independent drug program can be pinpointed in the lung cancer proof of concept, along with other markers that can assist in expanding the utilization of known drugs into this indication. The company aims to gain the ability to span the drug discovery and testing process from tissue testing all the way to final clinical testing.