We presented the preliminary results of a clinical trial we have initiated. This was a trial which was, to our knowledge, the first trial based purely on RNA sequencing data. So based on RNA sequencing data and molecular pathway analysis targeted drugs were suggested for cancer patients. The clinical competency was recommending or not the drugs based on the rating generated by the Oncobox analytic platform. Then local clinicians, local treating doctors, were taking clinical decisions either to use Oncobox recommendations or not. The patients were then followed up and the clinical response results, such as progression, stabilisation or partial or complete response were collected for the groups of patients who received Oncobox recommended therapy and who did not receive this therapy and for those who did not receive any therapy and were on palliative care.
We compared some of the primary outcomes for those patients and showed that RNA guided molecular diagnostics was significantly more efficient than standard of care therapy which is reflected by a proportion of clinical benefit of 73% in Oncobox guided therapy versus 55% for the other therapies group which looks to us truly encouraging results. We now want to organise a new trial, it would be fantastic if it could be done within the auspices of WIN, that would include both transcriptomic and genomic profiling. For transcriptomic it will be RNA sequencing, for genomics it will be whole exome sequencing. This will be sponsored by the Oncobox consortium so all those interested to participate are warmly welcome.
We hope that this trial will last for approximately four years, one year to organise a consortium and three years to do the study. The gene expression and genetic data will be shared within the consortium participants and, of course, the primary goal is to obtain better clinical responses than the standardly used therapies. Our major goal is the clinical benefit of cancer patients.
So considering the distinguishing features of the Oncobox technology this is that it uses molecular data on gene expression, not only on the level of analysis of single genes but also at the level of molecular pathway activation which can be calculated using high throughput molecular data. It has shown its better applicability as a biomarker compared to individual genes. Now this can be applied also at the genomic level based on mutations identified; also what’s called pathway instability score can be calculated which can be also transformed into a drug ranking score.