Over 150 target cancer therapeutics are currently on the market, but there is often no easy or effective way to decide which of these drugs to give to a cancer patient.
Oncobox is personalized genetic profiling to help oncologists decide which drug to use. Oncobox has been shown to increase the effectiveness of target therapies up to three times.
The main difference between Oncobox:Integral test and others currently on the market is that we analyze full DNA and RNA profiles, not just mutations or expression of individual genes (though we do that too). Our original bioinformatics algorithms then distinguish which molecular targets are most crucial for individual cases and find the most appropriate personalized treatment.
Oncobox is cost-effective personalized genetic profiling to help doctors decide which drug to use in late-stage cancer patients. Oncobox analyzes the molecular characteristics of a particular tumor and calculates the probability of a positive effect using specific cancer drugs. Learn more
The Oncobox:Integral test is available now to help finding the best treatment option for a patient. To perform the test a sample of tumor biomaterial is required (FFPE block). Once the analysis is complete in 7-10 days, Oncobox delivers a report containing a list of drug options ranked by expected effectiveness, including the results of their previous clinical trials in similar cases. To order or for more information, get in touch with us using the form below.
Encouraging results on our Oncobox:Integral Test were presented at ASCO Annual Meeting 2017. Among 23 advanced, mainly metastatic, solid tumor patients, to whom target treatments were prescribed according to our recommendations, 82.3% had complete or partial response or stabilization.
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Our team includes world-renowned scientists, molecular biologists, bioinformaticians and medical doctors, who have been investigating molecular mechanisms of cancer for years and been published in many peer-reviewed scientific journals, such as Nature and the Journal of Clinical Oncology. Our mission is to develop solutions that help doctors find the most effective treatment for late-stage cancer patients, who often face few options.
Andrew GarazhaChief Executive Officer
Anton Buzdin, PhDChief Scientific Officer
Max Sorokin, PhDHead of Bioinformatics
Victor TkachevChief Technology Officer
Alex Poltorak, Prof., PhDMolecular Immunology Advisor. Tufts University
Ilya Muchnik, Prof., PhDBiostatistics Algorithms Advisor. Rutgers University
Our team has a successful history of partnering with biotech and research institutions to provide state-of-the-art comprehensive bioinformatics analyses of DNA, RNA, and microRNA. Oncobox offers the original bioinformatics techniques and molecular oncology expertise to assist and optimize research or clinical trials as well as the platform to create companion diagnostics tests for existing or prospective drugs.
ONCOBOX AT TOPS-2019 SYMPOSIUM AT STANFORD UNIVERSITY
Oncobox test used for off-label personalized prescription of targeted therapeutics in ALK-mutated lung cancer: case report
FORTHCOMING: DECEMBER 2019. FIND ONCOBOX AT CANCER METASTASIS CONFERENCE IN SEEFELD
FORTHCOMING: DECEMBER 2019. FIND ONCOBOX AT BioDataWorld CONGRESS 2019 IN BASEL
FORTHCOMING: NOVEMBER 2019. FIND ONCOBOX AT "BRAIN TUMORS: FROM BENCH TO CLINIC" CONFERENCE IN LJUBLJANA
ONCOBOX AT WIN-2019 MEETING IN PARIS
ONCOBOX AT ASCO-2019 MEETING IN CHICAGO
Oncobox opened its Atlas of RNA sequencing profiles to research community
Oncobox test used for off-label personalized prescription of targeted therapeutics in recurrent granulosa cell tumor of the ovary: case report
Oncobox on EORTC Groups Annual Meeting (EGAM)-2019 in Brussels
Oncobox on BIO-ASIA 2019 Meeting in Tokyo
Mutation Data Complement Gene Expression Profiles for Personalized Ranking of Target Cancer Drugs
New Oncobox Prospective Clinical Trial Registered On NIH Clinicaltrials.gov
Using molecular pathway activation to select anticancer combination therapies: proof of concept
Oncobox test helped to personalize therapy in unresectable metastatic cholangiocarcinoma and obtain prolonged control over disease
Proof of concept for using molecular pathway activation to personalize selection of target drugs
First Oncobox Prospective Clinical Trial Registered On NIH Clinicaltrials.gov
Machine Learning helps predicting cancer drug efficiency by transferring genetic data from cell lines to cancer patients
Resistance to target drugs may be linked with the decreased sensitivity to radiation therapy
Molecular signatures of MYCN-amplified neuroblastomas
BIO 2017 - San Diego
ASCO Annual Meeting 2017