Clinical Research
Democratise Clinical Research and facilitate In House Research Accelerators
Dedalus is built on a foundational commitment to help the healthcare industry improve the quality of care, and to provide solutions that give Healthcare decision makers and patients real time knowledge at the point of care. Dedalus helps Life Sciences organizations deliver on their Clinical Research and Value Based Care goals, allowing our clients to accelerate drug development and to create real,scalable and differentiateddigital initiatives that support innovative care and commercial models.
Clinical Research
Real world data (RWD) and evidence (RWE) are playing an increasing role in revolutionising clinical research studies, allowing more affordable and effective drugs to reach the market faster than ever before.
Leveraging our extensive healthcare experience and deep expertise in digital healthcare solutions such as Electronic Health Records (EHRs) provides us with a unique opportunity to bridge the divide between healthcare and Life Science organisations as they converge around the common goal of improving patient outcomes.
Our technology platform enables the data orchestration required to develop Real World Evidence datasets and analytics insights for our clients.
Analytics capabilities provide the necessary tools to answer research questions andour digital platform enables a tighter integration between EHR data and clinical research processes and tools.
RWE Enabler
Dedalus proposes an open, flexible and composable platform alongsidea set of Digital Health Accelerators, facilitating self –service analytics and research capabilities for Life Sciences organisations to support Pre-Clinical and Clinical Development processes.
Companies are more frequently looking to data for answers and insights, but data itself has no value if this is not manipulated, refined and converted into useful business insights to share with the right stakeholders at the right point. Through Dedalus Digital Health Accelerators we help our customers to move progressively forward and extend those insights and value, informing multiple stakeholders across the value chain (patients, physicians, nurses, pharmacies…), providing valuable and timely insights which can be integrated in clinical workflows and support more informed interventions
- Ability to collect and effectively ingest different sources of patient data.
- Integrating data in a Common Data Model is key to supporting data interoperability across industry, Our solutions support FHIR (Fast Healthcare Interoperability Resources) and/or OMOP (Observational Medical Outcomes Partnership) depending on the clinical or business use case: Clinical Research or Value Based Healthcare.
- Experimented Terminology Services are key for interoperability and to map local definitions of clinical concepts to an unlimited number and variety of coding standards and structures.
- Remote patient monitoring, telehealth and Clinical Decision Support System Integration features
Pre Clinical and Clinical Research
- Cross Clinical Trials insights Help Clinical Development and Operations areas to standardise and simplify actual business processes for collecting Pre-Clinical and Clinical data and images from external partners (CROs)
- Deliver Clinical insights to other areas of the company: Discovery, Research, Commercial, Medical Affairs…
- Access Innovative Dashboards / Queries across multiple PreClinical and Clinical Studies to accelerate Clinical Development
- Map CDISC data to FHIR to enhance Clinical Research
- Manage other Real-World Data to optimise Clinical Trial Design, Patient Localisation, Trial Site Feasibility, …
- Support Translational Research between Pre-Clinical and Clinical Areas
- Optimisation of Development Plans through Clinical, Non-Clinical and Real World Data
- Enable clinical data exploration and Self Service Analytics through a new generation Data Platform for research
- Research Analytics Platform for Contract Research Organizations (CROs)
- Support CROs with an Open Composable Research Analysis Platform, allowingclients to accelerate their product’s development across multiple disciplines covering epidemiology, data science, HEOR, study feasibility, market access and regulatory affairs.
- CROs can aggregate data from diverse sets of global RWD sources with a proven advanced analytics platform, and build potential partnerships to access Dedalus installed base of EHRs.
Enable clinical data exploration and Self-Service Analytics through a new generation Data Platform for research:
Key Benefits
- Help reduce Development times
- Predict Drug Effectiveness
- Apply granular Inclusion / Exclusion Criteria
- Enable improved disease understanding (Factor Search)
- Enable Disease Progression and Correlation with Expression
Key features
- Cohort Builders
- Basic statistics with Stratification
- Organise, visualise, and standardise data
- Pattern Recognition (Discriminant analysis, cluster analysis, etc.)
- Multivariant analysis
- Data Ingestion/ Integration and Clinical Tagging
- Market Data aggregators and Partners
- Self Service Research Analytics
- Self Service Investigative and Graph Analysis
- NLP - Text analysis & indexing from Literature & EHR data
- Data anonymisation or pseudonymisation
Support CROs with an Open Composable Research Analysis Platform, allowing clients to accelerate their product’s development across multiple disciplines covering epidemiology, data science, HEOR, study feasibility, market access and regulatory affairs.
CROs can aggregate data from diverse sets of global RWD sources with a proven advanced analytics platform and build potential partnerships to access Dedalus installed base of EHRs.
Key Benefits
- Ability to bring your own Data and combine the data sets to provide enhanced value more effectively
- Gain actionable insights from data through advanced analytics
- Enable easy exchange and manipulation of data in near real time
- Connect and ingest a wide range of datasets for investigative analysis
- Support self-service analytics and visualisations
Key features
- Pre-configured RWD platform
- Built in disease classification
- Integrated canonical data model
- Data linkage and enrichment
- Prospective & Descriptive Linked Analytics
- AI Marketplace
- Self Service Research Analytics
- Self Service Investigative and Graph Analysis
- Regulatory compliant infrastructure where patient confidentiality and privacy is maintained