is developed to choose drug therapy for difficult and late-stage cancer cases.
The platform analyzes the molecular characteristics of a patient's tumor and calculates an individual efficacy rating for over 160 cancer drugs.
Oncobox technology is protected by international patents, and its effectiveness has been proven in prospective and retrospective clinical studies.
Learn more in the brochure
40 years old
The patient underwent 6 surgeries, and after last recurrence the tumor was declared inoperable. Chemotherapy and hormone therapy attempts for 2 years were ineffective with further tumor progression being noted. In 2016, the list of recommended drugs was completely depleted, while DNA diagnostics (mutations analysis) didn’t predict any potentially effective target drugs.
Based on the integral Oncobox Dx results, a tyrosine kinase inhibitor (Sorafenib) was prescribed. There was a partial response to treatment with great tumor size reduction, but the treatment was canceled due to the side effects. Additionally, a drug with a different mechanism of action (Imatinib) was selected, and significant tumor size reduction in 6 months of treatment allowed complete surgical removal. As of February 2021, the patient continues her treatment with no side effects and no signs of recurrence.
Oncobox analysis generated a list of potentially actionable compounds, which when used clinically lead to partial response and later long-term stabilization of the patient's disease.
48 years old
Patient underwent surgery and 4 subsequent courses of chemotherapy (Vinorelbin + Cisplatin). After 8 months, brain metastases were revealed. He underwent radiation therapy, after which received Ceritinib. After 21 months, the cancer progression and brain metastases growth were detected. Within the next 6 months, the patient received 3 more various treatments and underwent radiosurgery (cyberknife), but his condition still worsened, and new lung metastases were revealed.
Based on the Oncobox Dx results, a treatment regimen including an ALK inhibitor, an angiogenesis inhibitor and taxanes (Crisotinib + Bevacizumab + Docetaxel) was prescribed. Treatment resulted in significant improvement in the patient's condition, and a progression-free survival at 2 years.
Survival of our patient after developing resistance to ALK inhibitor was longer for 16 months than previously reported average survival for such cases.
79 years old
The patient firstly received chemotherapy (FOLFOX and FLOT regimens), which initially resulted in the tumor size reduction. However, soon thereafter she developed drug tolerance with no changes in tumor size. Oncologists decided to switch to another treatment regimen.
Based on the Oncobox Dx results using the molecular profile of the tumor, a high response to immunotherapy was predicted. Oncologist decided to stop chemotherapy and proceed with the surgery. After that, the patient received immunotherapy (Pembrolizumab) for 6 months, which resulted in complete remission. No signs of recurrence are observed for 2 years since starting immunotherapy.
According to Oncobox results, the patient received immunotherapy with anti-PD1 therapy and is now free of disease for 2 years.
72 years old
Patient received four courses of chemotherapy (2 courses of Gemcitabine + Cisplatin with subsequent 2 courses of Gemcitabine + Capecitabine). Despite the treatment according to clinical guidelines, the tumor progression was noted and the patient's condition worsened.
Based on the integral Oncobox Dx results, a tyrosine kinase inhibitor (Sorafenib) was prescribed. Sorafenib monotherapy resulted in tumor stabilization and significant pain reduction. After 6 months, the tumor progression was revealed, and the patient was prescribed with another tyrosine kinase inhibitor (Pazopanib), also selected by Oncobox. This change in treatment regimen alleviated the side effects of Sorafenib and improved the patient's condition and lab test results. Worldwide statistics show that the survival rate of cholangiocarcinoma patients is no more than 6 months. As a result of personalized treatment selection by Oncobox, the patient lived for more than two years and was physically active.
After 2 years from the diagnosis of MCC the patient was alive and physically active, which is substantially longer than median survival for standard therapy.
The effectiveness of Oncobox technology has been proven in retrospective and prospective clinical studies in which hundreds of patients with advanced cancer received targeted cancer drugs following personalized Oncobox ratings.
The clinical study results demonstrate a twofold decrease in the incidence of disease progression, a significant increase in response to therapy (up to 76%), and an increase in progression-free survival. In 2020, details of the research were presented at the American Society of Clinical Oncology (ASCO) convention, as well as at the WIN International Personalized Oncology Consortium conference.
Oncobox Dx includes analysis of genomic (DNA) and transcriptomic (RNA) data obtained from a tumor sample. The final report contains a rating of the effectiveness of targeted and immunotherapeutic drugs for a particular patient. Additionally, the report includes baseline data on molecular abnormalities and the results of relevant clinical trials.
This approach provides high clinical value and allows the clinician to build an evidence-based roadmap for further treatment.
Our team includes world-renowned scientists, molecular biologists, bioinformaticians, and medical doctors, who have been investigating molecular mechanisms of cancer for years and have 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 limited 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
Machine learning application for finding bortezomib success gene expression biomarkers in multiple myeloma
First of its kind gene signature for minimum-invasive diagnosis of endometriosis
Oncobox CSO elected as the Chair of EORTC subgroup