This book contains essays on data integrity.

Data integrity is the most basic element of work in any scientific discipline.

Nothing of lasting value in the hard sciences (physics, chemistry, biology,

astronomy, et al.) lacks integrity in the data used to support the premises,

the logical arguments proposed, and the conclusions drawn. The point of

validation is, after all, to ensure that all results obtained and reported are

true.

The original premise of our book was to merge the global standard for

pharmaceutical analytical methods for regulatory applications [ICH

Q2(R1)] with contemporary thinking on ensuring data quality by

thoroughly understanding a method and its intended application (QbD).

During a preproduction meeting, an incisive question led to expanding the

scope of the original five chapters: "Can this be applied to fields other than

pharmaceuticals?" The answer was: Yes.

Three chapters were added to explore the applications of Quality by Design

theory to real world problems that are bound not only by regulations, but by

business constraints, professional ethics, time, resources, and technology. They

may serve as case studies for classes of advanced students.

The scientific approach is rigorous, drawing on, and integrating, classical wet

and modern instrumental analytical chemistry knowledge. The reasoning is

detailed and well-documented. Examples are carefully explained. Two are

based on historical events. The other is a problem that is not yet fully resolved

despite its importance and significant risks to human health globally.

The tone throughout is conversational. It is intended to involve students -

and any reader who has a vested interest in data integrity, which includes the

global scientific communities from academia, industry, and government, and

producers and consumers of quantitative measurements and the goods and

services obtained by their use.

The objective is to impart an intuitive understanding of method validation:

planning, execution, and documentation,

with examples of practices and

problems, and with practical strategies for addressing both.

A special feature is the inclusion of "Hints" - brief comments offering

experience-based advice acquired while developing, validating, reviewing, and

auditing analytical methods (and data) in a variety of industries

and countries.