In the dynamic environment of biotechnology trials, the significance of Clinical Data Management systems (CDMs ... and due to the decentralised trial design, we tend to see larger amounts of ...

As data volume and complexity rise, maintaining data integrity and complying with regulatory requirements have become more difficult, underscoring the need for more efficient systems. Cloud-Based ...

Randomised controlled trials are the gold standard to assess the effectiveness and safety of clinical interventions; however, ...

And this transformation significantly impacts database administration. From regulatory compliance to data quality and security, DBAs must navigate an evolving landscape where effective data management ...

Clinical Quality Language (CQL) is an HL7 specification for the expression of clinical knowledge that can be used within both the Clinical Decision Support (CDS) and Clinical Quality Measurement (CQM) ...

The plan is intended to assure researchers can readily address foreseen risks to participants, or identify and manage instances when there may be issues with the study design, interventions or plan ...

DataStax’s AstraDB will enhance the existing vector capabilities of IBM watsonx.data, while Langflow will add flexible middleware capabilities to watsonx.ai, IBM said. Console apps are ...

Databases, including MEDLINE, Embase, Cochrane Database of ... criteria will undergo data abstraction using a standardised, pre-piloted form for assessment of study quality and knowledge synthesis.

In today’s pharmaphorum podcast, Orr Inbar, co-founder and CEO of QuantHealth, a Tel Aviv-based AI-powered clinical trial design company, discusses how advances in data and AI can help.

In a peer-reviewed study authored by Sunil Yadav, a research scholar with a strong academic background in information systems, the author emphasizes how foundational database design strategies shape ...

These architectures integrate fine-grained access controls, encryption, and audit logging to ensure that data is protected while remaining accessible for analytical purposes. The robust metadata ...

In this course you´ll learn about new database technologies to handle Big Data: Data Stream Management Systems, Complex Event Processing, Distributed and Heterogeneous Database Systems, Data ...