Danny Platform is a Big Data healthcare solution that integrates massive amounts of Real-World Data from various hospital sources (EHRs, lab tests, registries).
Powered by SAP HANA and built with propriety ML and NLP algorithms, Danny Platform extracts both structured and unstructured (free text) data to preprocess, normalize and ensure high Data Quality.
The software provides comprehensive searches, in-depth analyses, predictions, and treatment solutions and decision support to physicians, researchers, and payers.
Sqilline has already accumulated powerful data reports and insights from the oncology, cardiology, ophthalmology, rare diseases, and other specific disease areas.
Currently, Danny Platform processes more than 1.2 million unique patient records from leading hospitals in CEE.
Danny Platform is the foundational layer that aggregates and harmonizes all heterogeneous data sources.
Build on top of the core platform are these add-on applications – Danny Analytics, Danny Dashboard, Danny Predictions, Danny Cohorts, Danny My Patients, Danny Decision Support for FH, Danny Decision Support for Rare Diseases
Danny Platform provides physicians with immediate summary of healthcare data – in aggregate or of individual patients – for delivery of high-quality cost-effective care. The platform provides statistical data, benchmarks and Real-World Evidence of therapeutics. Predictive analytics evaluates based on retrospective data for extrapolation of clinically important endpoints
Danny Platform 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
Evaluating the effectiveness of drugs and the comparators based on clinical and real-world evidence are critically important. Danny Platform 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
Via Danny Platform as a eSource, sponsors can conduct high-efficient clinical trials by identifying patients who meet the criteria while analysing massive amounts of RWD.
RWE to validate hypotheses compared to RCT data.
Speed up R&D in medicine to improve patient access and outcome through technology
Danny Platform provides overall optimization of faster patient enrollment in clinical trials, medical publications, and study analyses. Digitalized and structured medical records to support informed clinical decisions. Real-time RWD analyses to engage more patients in clinical trials and conduct effective research and facilitate personalized therapy for better outcomes
The cardiology study we made possible via Danny Platform technology and the algorithm developed calculates for us necessary points and informs us whether a patient carries the FH gene at the time of hospitalization. The implementation of such technology solutions with accurate interpretation of existing data will empower early diagnosis and prevention of subsequent acute accidents.
Through the algorithm developed by Sqilline, the results from any type of equipment can be read and plotted in a graphical form for the convenience of physicians. The innovative approach gives us a broader view of the ophthalmology field and its development on a national level.
At a glance, with one click, all information about the patient's treatment from the start of therapy to the time of evaluation is displayed in front of me. It helps me, in my daily work, before each oncology commission, to have access to the summarized medical documentation in one place!
Danny Platform is extremely useful in accelerating rare diseases medical diagnosis using AI and ML models to screen patient cohorts and identify high-risk ones from EHRs-based RWD. I am grateful for the opportunity to work with such software.
We were able to reach valuable conclusions based on reports on the patient’s condition over a period and the long-term observation of therapies performed
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