Guidance on good data and record management practices (ALCOA) – WHO free PDF Download

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1. Introduction

1.1 Medicines regulatory systems worldwide have always depended upon the
knowledge of organizations that develop, manufacture and package, test,
distribute and monitor pharmaceutical products. Implicit in the assessment
and review process is trust between the regulator and the regulated that
the information submitted in dossiers and used in day-to-day decisionmaking
is comprehensive, complete and reliable. The data on which
these decisions are based should therefore be complete as well as being
attributable, legible, contemporaneous, original and accurate, commonly
referred to as “ALCOA”.

1.2 These basic ALCOA principles and the related good practice expectations
that assure data reliability are not new and much high- and mid-level
normative guidance already exists. However, in recent years, the number of
observations made regarding good data and record management practices
(GDRP) during inspections of good manufacturing practice (GMP) (1),
good clinical practice (GCP) and good laboratory practice (GLP) has been
increasing. The reasons for the increasing concern of health authorities
regarding data reliability are undoubtedly multifactorial and include
increased regulatory awareness and concern regarding gaps between
industry choices and appropriate and modern control strategies.

1.3 Contributing factors include failures by organizations to apply robust
systems that inhibit data risks, to improve the detection of situations where
data reliability may be compromised, and/or to investigate and address
root causes when failures do arise. For example, organizations subject to
medical product good practice requirements have been using validated
computerized systems for many decades but many fail to adequately review
and manage original electronic records and instead often only review and
manage incomplete and/or inappropriate printouts. These observations
highlight the need for industry to modernize control strategies and apply
modern quality risk management (QRM) and sound scientific principles to
current business models (such as outsourcing and globalization) as well as
technologies currently in use (such as computerized systems).

 

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