Wednesday, December 30, 2009

Data Management for Clinical Studies

The management of data at the clinical study level is the foundation of what will eventually become one of the many building blocks of your clinical submission to FDA. Considerations that must be processed and planned by regulation and guideline regarding FDA, EMEA, ICH, TGA, DEC, other, must be current in compliance and compatible and equivalent to pharmaceutical industry standards. Engage experts to manage your data - it is impossible to do otherwise and achieve the integrity of data and accuracy that is required by regulation. At the Clinical Study Level, there are steps in "handling" data, from CRF development to Database Lock to Database and Program Transfers at the end of the clinical study.

Here are important steps and points to consider, and without question, each step and/or action must be recorded, processed and managed by quality management data plans specific for the task - all of the following require "Standard Operating Procedures (SOPs)". On FDA Audit, for sure, these plans must be available for review by the agency. Each respective plan must include data handling versions specific for each task, as reviewed below.
  1. CRF Development.
  2. Database Setup - "Oracle" is the choice and CDISC versions 2.0 and 3.1 are used by pharma at this writing and are compliant with regulatory standards and compatible with industry use and FDA review.
  3. Data Validation.
  4. Data Coding - The management of data for clinical signs and symptoms, AE coding using MedDRA Version 9.1 or previous versions. Treatment Coding using WHODRL Version 6.4 or previous versions. Pharmacovigilance database reconciliation.
  5. Quality Control Management Procedures for Interim Data Analysis (IA), Data Entry Audits, Data Review, Data Change, Database Lock and Data/ Program Transfer at the end of the Clinical Study. Data/Program Tranfers can be formatted in .sas., csv., txt., xml, other - the format must be agreed upon by the pharma, all CROs, FDA and WW agencies slated for submission.
  6. Quality Control (QC) Plans to ensure accurate, compliant data. Expert QC teams work with raw data captured in the CRF, DCFs, listings, PPs, other source data documentation to ensure correct management and accuracy of data until the database is locked and the data is transferred to the sponsor or to the next step - the clinical submission team.
  7. End of Clinical Study Data Management.
  8. Data Tools - Clinical Data Management "Systems" that are used by the industry and compatible and compliant with FDA 21 CFR Part 11 Guidance. For example, "Capture System", Version 5.5, Editor "Clinsight".
  9. Audit Trail Systems and SOPs to capture all data changes, database actions and data and procedural change and standard deviations.

Expert data management teams work onsite and offsite and integrate with the sponsor, the CROs, the monitors and clinical study site personnel, CRC, CRA, PIS, sub-PIs, from the first data point - and from CRF development to end of study transfer of data and programs. Monitor and Track Data. Develop Plans. Adhere to Plans. Record Changes. Manage Change. Lead the team and manage the plans.

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