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LABORATORY INFORMATICS GUIDE 2016 | DATA INTEGRITY


HOW TO IMPROVE DATA INTEGRITY I


Peter Boogaard worries about the integrity of data in the laboratory


n 2013, the US Food and Drug Administration (FDA) reported that laboratory processes, and deficiencies


associated with laboratory controls, were ranked in the top three most frequent causes of ‘observations’ following FDA inspections. The same report also cited an increase of 50 per cent in warning letters related to data integrity. During the annual meeting of the


International Society for Pharmaceutical Engineering (ISPE) held in 2014 in Las Vegas, it was reported that the FDA had identified more than a dozen Indian pharmaceutical manufacturers who had problems with the data integrity practices at their facilities. That number is significant, since India and China account for 80 per cent of active pharmaceutical ingredient (API) production. Many of these companies in Asia are privately held and therefore not mandated to submit corporate information. In these countries labour is plentiful and cheap, so facilities tend to use paper-based manual processes, which increases


Table 1: Laboratory data integrity observations


Alteration of raw, original data and records Multiple analyses of assay with the same sample without adequate justification


Manipulation of a poorly defined analytical procedure and associated data analysis in order to obtain passing results


Backdating stability test results to meet the required commitments Creating acceptable test results without performing the test Using test results from previous batches to substitute testing for another batch


4 | www.scientific-computing.com/lig2016


the potential for inconsistencies in data and lack of data integrity. Other regulatory bodies, including the


European Medicines Agency, have made similar observations (Table 1). It is expected that this trend will continue to grow. Many international corporations externalise significant parts of their operations to cut costs, but it has been observed that the number of occasions is growing when poor data integrity practices outweigh the savings in cost.


The FDA reported an increase


of 50 per cent in warning letters related to data integrity


Data integrity is currently one of the highest


cited areas in regulatory observations. Yet, data integrity is not a new requirement. For years, the basic principles have been described in international good manufacturing practice (GMP) guidelines. In this article I will highlight the ways in which organisations, to


their own benefit, can reduce data integrity inconsistencies within their operations. Before zooming in on the details, however, we need to set a baseline to ensure we have a common understanding.


CONTEXT IS KING FDA regulations define an electronic record as any combination of text, graphics, data, audio, pictorial, or other information represented in digital form that is created, modified, maintained, archived, retrieved, or distributed by a computer system1


. Data integrity is the


assurance that data records are accurate, complete, intact, and maintained within their original context, including their relationship to other data records. In short, data integrity aims to prevent


unintentional changes to information. It refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle, including the usage of any system which stores, processes, or retrieves data. The definition applies to data recorded in electronic and paper formats or a hybrid of both. Ensuring data integrity means protecting


original data from accidental or intentional modification, falsification, malicious intent (fraud), or even deletion (data loss). It is the opposite of data corruption! Data integrity and security are closely linked to the 21 CFR Part 11 for electronic records and electronic signatures, but also to other directives relating to data, regardless of format.





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