Martin Valania

Pharmaceutical companies recognize the benefits of carefully managing the quality of data from their drug development and clinical trials. To ensure clinical data accuracy and integrity, it is necessary to thoroughly review these data, to assess the validity of outlying data points, and to carefully document query identification and resolution throughout a study's duration.  

Maintaining accuracy and quality throughout a clinical study is a continual, dynamic process.  Although study requirements are carefully set forth initially in detailed documents such as an approved clinical protocol, a data management plan, and an accompanying project plan, expectations and requirements can change during a study. This ongoing process requires revising mechanisms and communicating these revisions clearly to all investigators and support staff.  

PHOTOGRAPHY: PHOTODISC  ART DIRECTION: PAUL A. BELCI			

the total set of characteristics of a product or service that affect its ability to satisfy a customer's stated or implied needs. 

the organizational structure, responsibilities, procedures, processes, and resources for implementing quality management. 

the systematic and independent examination of all trial-related activities and documents. These audits determine whether the evaluated activities were appropriately conducted and that the data were generated, recorded, analyzed, and accurately reported according to protocol, standard operating procedures (SOPs), and good clinical practices (GCPs).

periodic operational checks within each functional department to verify that clinical data are generated, collected, handled, analyzed, and reported according to protocol, SOPs, and GCPs.

The ongoing challenge in managing the quality of clinical data is to continually monitor data collection procedures and data management practices at every level of the study. This includes: 					

ensuring that data generated during the study reflect what is specified in the protocol (case report form [CRF] vs. protocol)

comparing data in the CRF and data collected in source documents for accuracy (CRF vs. source documents)

ensuring that the data analyzed are the data recorded in the CRF (database vs. CRF).

Quality surveillance continues after the trial has ended and plays an important role in ensuring that: 					

data presented in tables, listings, and graphs (TLGs) correctly match data in the database (TLGs vs. database)

data reported in the clinical study report (CSR) are the data analyzed (CSR vs. TLGs)

all aspects of the data management processes are compliant with SOPs and GCPs.

The quality plan describes how the quality control and quality assurance processes will be applied throughout the clinical trial. It definitively defines the various quality-related tasks in the study. A quality plan documents specific quality practices, resources, and activities relevant to a specific project. This includes both operational QC and QA activities. 

It is critical that trial managers develop a QC plan for each key operational stage of the study that defines standards against which QC will be conducted, including: 					

data source to be used for QC at each operational stage

appropriate methods to report and distribute results.

During the study design phase, QC personnel provide an independent review of the approved proposed protocol. The QC plan includes comparison of the study's CRF to the objectives set forth in the protocol to ensure that it is designed to collect all necessary data. A requirement to review CRF completion guidelines is also an element of the QC plan. 

For overall site management, a complete QC plan addresses the following: 					

investigator selection and qualifications

		– experience in conducting clinical trials

			– experience with the specific indication

			– not on the FDA's restricted or debarred lists

			– subject informed (signed informed consent form)

			– subject's eligibility (inclusion/exclusion)

			– adverse events (AEs) and concomitant medication

			– drug accountability and storage									

			– completed data clarification forms									

			– EU Clinical Trial Directives 2001/20/EC and 2005/28/EC

Articles

A system of checks and examinations that helps ensure the quality of clinical trials.

Quality Control and Assurance

Pharmaceutical companies recognize the benefits of carefully managing the quality of data from their drug development and clinical trials. To ensure clinical data accuracy and integrity, it is necessary to thoroughly review these data, to assess the validity of outlying data points, and to carefully document query identification and resolution throughout a study's duration. 

 Photography: PhotoDisc  Art Direction: Paul A. Belci			

Maintaining accuracy and quality throughout a clinical study is a continual, dynamic process.  Although study requirements are carefully set forth initially in detailed documents such as an approved clinical protocol, a data management plan, and an accompanying project plan, expectations and requirements can change during a study. This ongoing process requires revising mechanisms and communicating these revisions clearly to all investigators and support staff. 

Quality: the total set of characteristics of a product or service that affect its ability to satisfy a customer's stated or implied needs. 

Quality system: the organizational structure, responsibilities, procedures, processes, and resources for implementing quality management. 

Quality assurance (QA): the systematic and independent examination of all trial-related activities and documents. These audits determine whether the evaluated activities were appropriately conducted and that the data were generated, recorded, analyzed, and accurately reported according to protocol, standard operating procedures (SOPs), and good clinical practices (GCPs).

Quality control (QC): periodic operational checks within each functional department to verify that clinical data are generated, collected, handled, analyzed, and reported according to protocol, SOPs, and GCPs.