Applying Transportability to Strengthen Pharma Evidence in the Nordics
Transportability and generalizability refer to the ability to apply evidence from a single study to different patient populations, clinical settings, or geographical regions.
Data Science
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Target Trial Emulation brings the logic of randomized trials into real-world data
Target Trial Emulation does not replace randomized controlled trials, but it applies their logic and rigor to real-world data analysis.
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Data Team is the Backbone of Medaffcon, Ensuring the Reliability of Research Results
The data team keeps Medaffcon's research projects on track and ensures that the research findings are scientifically sound. At the heart of the team’s work is the processing and analysis of patient data, particularly in RWE studies.
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Medaffcon’s Machine Learning Algorithm Adapts to Various Research Needs
The algorithm was originally developed to extract smoking status from patient texts with purpose to analyze the effects of smoking on postoperative complications. Today, it is also being utilized in lung cancer research.
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AI Brings New Opportunities to RWE Research – Its Use in Health Data Analysis is Limited
Artificial intelligence (AI) is transforming research and working life across various industries. But what is its significance in health data analysis and real-world evidence (RWE) research? Medaffcon’s experts, Juhani Aakko and Lisse-Lotte Hermansson, share their perspectives on AI in their work.
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Finland: An Ideal Environment for the Pharmaceutical Industry’s Real-World Evidence (RWE) Studies
Finland boasts numerous strengths that make it an outstanding choice for real-world data-based (RWD) research.
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The OMOP Common Data Model facilitates the utilization of healthcare data – Medaffcon was involved in a Finnish OMOP pilot study
In healthcare, there is a vast amount of data being generated and processed. Sometimes, its utilization is cumbersome because the data is scattered, and its analysis requires a lot of preprocessing.
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Matching techniques go beyond virtual control arms, reminds senior data scientist at Medaffcon
Real-world data (RWD) can, however, be utilised also in a variety of non-clinical medical and pharmaceutical studies to compare aspects such as treatment outcomes and resource utilisation between different geographies and treatment options, reminds Samuli Tuominen, senior data scientist at Medaffcon.
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Medaffcon’s matching know-how on display in immunosuppressant study
The study utilised propensity-score matching to compare the performance of two immunosuppressive drugs in patients with primary sclerosing cholangitis after liver transplantation.
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Medaffcon strengthens data science team as customer demand grows
Medaffcon in September added two new members to its team of data scientists, preparing itself for an era where pharmaceutical development and innovation are driven increasingly by real-world data. “Real-world evidence is getting bigger and bigger and we’re getting more and more research assignments, so we need smart minds and quick fingers to do all the data science,” sums up Iiro Toppila, data analysis lead at Medaffcon.
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Smoking clearly increases the risk of postoperative complications
Register study undisputedly confirms that a smoker’s risk for any postoperative complications is significantly higher than non-smokers’.
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Text mining helped analyse a million entries on smoking
How to review and analyse a million sentences? Text mining decreased the work of clinical experts and accelerated the research process.
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Unstructured healthcare data contributes to solving new issues
Finland has unique data for pharmaceutical purposes and unstructured healthcare data can also be already effectively utilised.
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Virtual control groups in pharmaceutical development – What are they and can they be trusted?
Single-arm research designs are challenging for a pharmaceutical reimbursement and marketing authorisation process.
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Findata reformed the processing of data permit applications – customers benefit in a diversity of manners
Finnish Social and Health Data Permit Authority Findata has significantly reformed and accelerated the processing...
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Synthetic data and a common data register – the future of real-world evidence is fast approaching
Utilisation of real-world evidence (RWE) progresses at speed and development steps are fast. Utilising real-world...
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New RWE themed blog to start in March!
Interested in RWE research? Health from data is the first real-world evidence themed blog written...
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Machine learning based tools in the analysis of RWD; focus on image recognition
Healthcare provides various types of Real World Data (RWD) that can be used to generate...
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AI-based tools for mining electronic health record data
Analyzing electronic health record (EHR) data has already provided us with new insights in medical...
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Possibilities of machine learning and artificial intelligence in RWE studies
Currently huge piles of health care data have been collected in Finland through national, regional...