Data management

BIOP’s objective is to ensure the accuracy and completeness of clinical study data, to deliver validated data on time and at competitive prices. Strict adherence to quality control processes, a forward thinking attitude and frequent contact with study teams and study sites are key to this.

Medical Coding (MedDRA, WHO)

Coding is done according to sponsor specific study procedures, or if requested, according to BIOP SOPs
Coding of Adverse events, Medical history (MedDRA)
Coding of Concomitant medications and non drug Treatments (WHO)
Goal: to standardize the method of coding of medical and therapeutic terms to achieve consistency and accuracy within and across studies

Data Entry

Independent double data entry with interactive reconciliation
Error rates between the database and the CRFs in 3 studies performed by BIOP were 0.0109%, 0.0214% and 0.0285%
Tracking and backups of the data collection system are periodically performed
Data entry system used is based on our EDC system, OpenClinica, or scanning hardware
Central Laboratory Database Imports
Incorporating third party databases
Goal: ensure quality, on time data entry processes with a minimum error rate.

EDC

Database Lock and Database Documentation

Interim and final database locks with associated documentation
Final dry-run is performed by the statistician
Goal: BIOP’s aim to shorten the period between the receipt of the last batch of CRFs (LPLV CRFs) and study database closure (DBL) without compromising on data quality.

SAE Reconciliation

Review of data from the CRF and SAE forms
Performed ad-hoc, continuously or after all patients completed treatment
Resolution of discrepancies to be documented in clinical and safety database
Goal: ensure consistency of the SAE information in the safety database with that in the clinical database

Documentation and Tracking

Creation and maintenance of Data Management documents, including status reports and administrative listings
QC/QA as detailed in project-specific guidelines and SOPs
Presentation of Data Management processes during initial study meetings or upon request
Filing and archiving of study documentation
Goal: documentation and reproducibility of all data management steps

Data Validation and Query Management

Creation and maintenance of data validation documents
Preparation and central maintenance of computerized data plausibility checks and manually created queries
Accommodation of third party queries
Query generation and tracking
Database quality control
Goal: to minimize queries during the study by site education through regular feedback and training