You need experts to manage your clinical data.
Our Biometrics Services
BDLS Biometrics services cover all activities of data management, biostatistics, programming and medical writing.
BDLS provides an experienced and competent project teams to deliver integrated solution for our clients.
As CDISC Solution Provider, we consider data as a continuum; from database set-up, data collection and monitorin through to analysis and reporting,
BDLS Data Management, Biostatistics, Programming and Medical Writing teams collaborate closely to ensure the integrity of the data is maintained throughout the study life cycle, with traceability and transparency of your data underpinned by CDISC CDASH, SDTM, and ADaM data standards.
At BDLS, we use a standardized library of documents, programs, and processes to produce regulatory compliant submission-ready packages. BDLS teams
are GCP- trained, and follow our robust SOPs which ensure adherence to strict Quality Control (QC) processes and documentation of procedures and/or clients’ SOPs.
Since July 21st 2014, it has become mandatory for all sponsors to enable transparency by posting their clinical trial results in the European Clinical Trials (EudraCT) Database, managed by the European Medicines Agency (EMA).
To ensure compliance with regulatory standards, BDLS has developed a wide range of industry-leading solutions to assist clients with entering clinical trial summary results into the EudraCT Database. Our processes reduce backlog and aid in the development of processes for ongoing studies, including the provision of general consultancy advice, requirements and the technical aspects of these requirements.
De-identification of data (De-I.D.)
Following the introduction of Policy 0070, it has become critical to ensure patient privacy without limiting access to patient data. At BDLS, we understand the balance between the usability of propriety clinical data and protecting patient privacy and apply the principle of 7 PhUSE de-identification methods across all clinical trial data. This consists of three steps:
- Assessing the role of each variable by determining its identification potential, quasi and direct identifiers across all datasets;
- Assigning primary and alternative rules for de-identification;
- Understanding all rationale and addressing exceptions and special considerations.
BDLS also provides a residual risk analysis that provides evidence to regulators that the risk of specific data re-identification is low and allows for the release of highly granular data.