Our technology is backed by science, working to stop cancer before it develops.
Scientific support of the technology
At Amadix, we are committed to create value for patients, physicians, and health authorities.
Clinical Studies
The company has conducted clinical studies in more than twenty hospitals and for different types of cancer.
PreveCol® is the result of a long-term clinical development program. In order to train and validate the PreveCol® diagnostic algorithm, AMADIX has analyzed plasma samples from more than 1,000 patients recruited in case-control studies in Spain, and 3,460 samples from real CRC screening patients collected in a prospective study conducted in Germany and Poland.
We are validating PancreaDix® through a national clinical study in more than 14 hospitals around Spain. The Amadix team is currently recruiting human samples to further validate the technology.
If you are interested in learning more about PancreaDix® clinical study, please contact us.
On-going clinical studies
Big data cancer
Development of an algorithm for the early detection of colorectal cancer based on risk factors identified with Big Data and Artificial Intelligence tools and molecular markers.
Status
- Approved by Ethics Committee
- Recruitment not started
Main objective:
Development of an algorithm for the early detection of colorectal cancer based on risk factors identified with Big Data and Artificial Intelligence tools and molecular markers.
BIGDAT CANCER
Development of an algorithm for the early detection of colorectal cancer based on risk factors identified with Big Data and Artificial Intelligence tools and molecular markers
Status:
- Approved by Ethics Committee
- Recruitment not started
Main objective:
Calculate the diagnostic capacity of the application of a predictive model based on risk factors for early detection of CRC and high-risk polyps together with PreveCol® molecular signature in a population of 225 patients.
Design:
In the first part of the study, the electronic medical records of 5,000 patients who have undergone a colonoscopy in the last 5 years will be anonymized, extracted and analyzed to create a predictive model based on risk factors associated with the risk of developing CCR or high-risk polyps.
In the second part, 225 patients will be recruited as part of a case-control study (75 patients with CCR, 75 patients with high-risk polyps and 75 healthy patients). These patients will donate a blood sample to measure the molecular biomarkers in plasma and they will grant access to their medical records to validate the performance of applying a combination of the molecular and risk factor algorithms.
Highlighted publications
Validation of miR-1228-3p as Housekeeping for MicroRNA Analysis in Liquid Biopsies from Colorectal Cancer Patients
Noninvasive early detection of colorectal cancer by hypermethylation of the LINC00473 promoter in plasma cell-free DNA.
A model based on the quantification of complement C4c, CYFRA 21-1 and CRP exhibits high specificity for the early diagnosis of lung cancer.
