This site is part of the Informa Connect Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 3099067.

BIO-Europe
Save the date!
November 6–8, 2023Munich, Germany

Oncocross

Profile

Oncocross was, established in 2015, an AI drug development company that predicts the interaction between drugs and diseases using AI (Artificial Intelligence) based on gene expression patterns. We started based on a platform technology that searches for a disease that is predicted to have this effect or, on the contrary, searches for a drug that is expected to have an effect on the disease.

Patient database: 100,000+

Drug database : 25,000+ 

(all data are gene expression patterns at transcriptome level)

RAPTOR AI: As an AI drug development platform that focuses on screening the optimal indications for drugs, it is possible to derive new indications for new clinical drugs or approved drugs already on the market, or to improve efficacy through concurrent administration. It plays a role in reducing the risk of failure in the new drug development stage and shortening the development period by deriving treatment combinations.

ONCO-RAPTOR AI: AI platform that focuses on screening optimal cancer indication and biomarker to maximize the success rate of new drug for oncology in development period.

ONCOfind AI: Predicts the optimal treatment option and timing to increase the survival rate of cancer patients by quickly and accurately predicting the primary site of primary and unknown metastatic cancer, which accounts for 2-6% of all cancer cases. 


1. Indication Expansion : Find additional indications for drugs in clinical phase trial 2 or 3

2. Rescue drug: Find additional indications for drugs failed in phase 2 or 3 trial

3. Incrementally Modified Drug: Using Proprietary ReDrug algorithm, find two drugs that will synergistically enhance efficacy of each other

4. Using big data containing 81,000 cancer patients data and prognosis information, we can find the best cancer indications for a given chemical compound or any anti-cancer drugs.