• Barcelona Criteria

    BIOPROGNOS’ Multiple Biomarkers Disease Activity Algorithms (MBDAAs) are based in “Barcelona Criteria”:

    1. Tumor Markers Serum concentrations.
    2. Discard benign pathology by the exclusion of main source False Positive results.
    3. Follow-up if Tumor Markers moderate results (Grey Zone/Undetermined).
    4. Technical interference.

    Thanks them, our MBDAA Tests perform the highest sensitivity as well as highest specificity if compared with other Tests.

  • Big Data Trial Studies

    BIOPROGNOS has signed Bidirectional Partnership Agreements (BPA) with several Medical Centers, Research Centers, as well as Public Health Systems in order to run several Assays and Trials Studies and give BIOPROGNOS the chance of analyze a big quantity of qualified data that it is used for the development of Multiple Biomarkers Disease Activity Algorithms (MBDAAs).

  • Higher ROC Curves Performance

    Receiver Operating Characteristics (ROC) plots are generated to help clarify the test performance. ROC curves are used to measure the test accuracy in regard to sensitivity and specificity. The overall performance of the test is measured by the position of the ROC line. The line for a perfect test will rise rapidly and reach close to the top left-hand corner, where both the sensitivity and specificity are located. A test with poor performance will have a line close to the rising diagonal.

    In this way, all our Lung Cancer MBDAA has the best performance in the market.

  • AI-Based Machine Learning

    BIOPROGNOS offers to all customers (Medical Centers, Researchers and Public Health Systems) the option to lower the price of our Multiple Biomarkers Disease Activity Algorithms (MBDAAs) if they agree to share with our Computation Algorithms based in Artificial Intelligence (AI) their patient’s data anonymously and for statistical purposes only. That is done in order to increase the performance of our MBDAAs thanks to incorporating more and more data, making truth the expression “The more you use, more they learn”.

  • Secure Cloud Platform

    All our Research and Development core as well as our production Multiple Biomarkers Disease Activity Algorithms (MBDAAs) are allocated in a High Scalability Architecture (HSA) and High Availability (HA) Cloud Platform that meet the highest standards in the field of medical and software industries.

    That’s allow to lower the Total Cost of Ownership (TCO) by reducing or removing costs related to Hardware and Software (Network, Server, Workstations, Application Installation, Warranties and Licenses, Migration Expenses or Risks, among others); Operation Expenses (Infrastructure, Electricity, Testing, Downtime, Outage, Failure Expenses, Diminished Performance, Security, Backup, Recovery Process, Technology Training, Internal and External Audits, Insurance, IT Personnel or Corporate Management Time, among others); Long Term Expenses (Replacement, Future Upgrade, Scalability Expenses or Decommissioning) and optimize the financial resources in a Pay-per-Use basis.

  • Proprietary RALD Framework

    Rapid Algorithm Development (RALD), is our own self-developed Framework for reducing time to Multiple Biomarkers Disease Activity Algorithms (MBDAAs) creation, based on Product Family Engineering (PFE).

    Product Family Engineering is a relatively new approach to the creation of new products. It focuses on the process of engineering new products in such a way that it is possible to reuse product components and apply variability with decreased costs and time.

    Thanks that, all new MBBDA creation is quick and quality assured: by reusing blocks (both functional or programming ―as if building bricks is about―), means reduce development time, testing time, integration time as well as deploying time, what increase time-to-market with maintaining all the guarantees.