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Danny Platform

Analytics platform for selecting high risk patients of rare & other diseases via AI algorithms

Danny Platform

Overview

Danny is an analytics platform able to evaluate massive amounts of real-world data from multiple sources in the oncology and cardiology fields.

Danny provides comprehensive searches, in-depth analyses, predictions and treatment solutions to physicians, researchers and payers.

The platform is powered by the SAP Hana Database – the world’s leading Big Data platform.

Danny’s launchpad offers fast access to its add-on applications – Danny Analytics, Danny Predictions and Danny Cardio.

Highlights

  • Security

    • EU General Data Protection Regulation (GDPR) compliance
    • Data is de-identified to protect the privacy of patient
    • HIPPA compliance
    • Well-structured authorization policy

  • System Integration

    • Can be installed on-premises or on a private cloud between oncology centers
    • It extracts data from any EHR or HIS systems
    • It can be integrated to any payers’ data base

  • UI & Velocity

    • Quick and easy access to real-world data analytics
    • Intuitive user interface
    • Application flexibility – specific access level based on your preferred package

Applications

Danny Analytics

Danny Analytics provides real-time aggregated analyses of structured and unstructured health data with integration of registries, external clinical and drug databases, etc. The application delivers insight on how specific factors influence patient outcomes and the effectiveness of regimens for value-based care.

Analytics Tools

Danny Predictions

Danny Predictions provides quantitative predictive insights based on real world data. We utilized a suite of state-of-the-art and validated statistical and machine learning algorithms to provide real-time analyses and feedback. This includes important clinically-relevant endpoints. This application works in conjunction with Danny Analytics to predict valuable insight into real-world effectiveness of treatment, clinically-relevant diagnostic markers of response, etc.

Danny Predictions UI

Features:

  • “What If” scenarios of clinical endpoints
  • “What If” scenarios of drug pricing and reimbursement
  • “What If” scenarios of regimens vs treatment outcomes for the patients
  • It measures outcomes trough predictive machine learning algorithms for OS, PFS, etc.
  • Tight specifically to the value-based healthcare system

Danny Cardio

Danny Cardio is collecting, processing and analyzing real-world data from leading cardiac centers in order to seamlessly extract statistical summaries in an practical, understandable way. Danny Cardio includes these three main divisions: Invasive cardiology, Cardiovascular disease and Cardiac surgery.

Danny Cardio UI

Features:

  • SYNTAX Score implemented
  • Analysis based on various type categories:
    • Stent Types
    • Guidewire Types
    • Diagnostics and Therapy Procedures Types
    • Cardiac Procedures Types
  • Visualizations by bar charts, pie charts and tabular form

Use cases

Physicians / Real World Evidence

The application provides physicians with immediate summary of healthcare data – in aggregate or of individual patients – for delivery of high-quality cost-effective care. Danny Analytics provides statistical data, benchmarks and real-world evidence of therapeutics. Predictive analytics evaluates based on retrospective data for extrapolation of clinically important endpoints
see more use cases
Physicians / Real World Evidence

Physicians / Real World Evidence

The application provides physicians with immediate summary of healthcare data – in aggregate or of individual patients – for delivery of high-quality cost-effective care. Danny Analytics provides statistical data, benchmarks and real-world evidence of therapeutics. Predictive analytics evaluates based on retrospective data for extrapolation of clinically important endpoints
Pharmaceutical Industry

Pharmaceutical Industry

Danny enables better tracking and evaluation of real-world data to uncover newly approved drug adaptation patterns, market access, and drug effectiveness. Cost-benefit analyses and economic evaluations using accepted models with real-world evidence for survival extrapolations and ICER calculations, in support of HTA submissions
Payers

Payers

Due to rising costs of therapeutics, there is an urgent need to move away from fee-for-service toward performance-based care. As such, evaluating effectiveness of drugs and comparators based on clinical and real-world evidence are critically important. Danny provides pharmacoeconomic models to evaluate and extrapolate survival and costs based on clinical and local data for cost-effectiveness analyses. This gives budgetary predictability and assessment of effectiveness within public budget spending
CROs/Patient Recruitments

CROs/Patient Recruitments

Danny Analytics provides real-time access to patients eligibility for clinical trials of interest. Using pre-defined inclusion and exclusion criteria, eligible patients are automatically updated for improved efficiency and reduced costs in patient recruitment

The algorithm achieved by Sqilline is the first of its kind in the CEE region.

It has the full potential to provide the necessary tools for real-time assessment of the benefits and effects of newly approved drugs. This will ensure the use of effective therapies for patients, which is of key importance for the future development of healthcare in our country

  • Dr. Borislav Borissov

  • Former director of Bulgarian Drug Agency and member of International Society for Pharmacoeconomics and Outcomes Research.

For us, oncologists, this way of collecting and analyzing Big Data in the broadest possible way is invaluable.

It enables us to make conclusions based on large amount of important information when deciding on the appropriate therapy for patients. Danny Analytics give us access to specific parameters such as five-year overall survival, progression-free survival, etc. All this is of the utmost importance for the fate of our patients - especially when we need to make the best decision quickly.

  • Prof. Dr. Galina Kurteva

  • Head of Medical Oncology Clinic, University Oncology Hospital, Sofia, Bulgaria

We will be provided with enormous volume of data which is quick and easy to access.

It encompasses large time periods and reports on the patient's condition and the results of therapies for long-term observation and continuous follow-ups. This type of application would also expedite the use of medical devices in healthcare technology assessments (HTAs) for areas where they still have not be used.

  • Prof. Dr. Ivo Petrov

  • Medical Director and Head of Cardiology and Angiology at Acibadem City Clinic Sofia, national cardiology consultant

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