prioritization approach is factor screening, which aids in choosing statistically

significant CMAs and CPPs, while ignoring the “idler” ones. Such factor screening

studies and subsequent factor optimization studies employ the DoE approach,

indispensably employing suitable experimental designs (Armstrong et al. 1991;

Akesolo et al. 2004; Singh et al. 2005a, 2011a).

Generally, simpler linear experimental designs, like fractional factorial design

(FFD) or Taguchi design (TgD), are apt to screen the influential factors from the

“possible so many” (Lewis et al. 1998; Singh et al. 2005b, 2011a; Aksu et al. 2015).

Figure 18.6 portrays a panoramic layout of various experimental designs employed

in factor screening and optimization. The experimental runs, i.e. the experimental

studies to be exercised as per a particular experimental design, are organized as a

Men

Materials

CAUSES

EFFECTS

Methods

Milieu

Management

Machines

Measurements

Pharma

quality

Fig. 18.4 A typical graphic of an Ishikawa fishbone diagram illustrating varied potential sources of

variability which can significantly influence the drug product quality

Fig. 18.5 Salient steps of a quality risk management (QRM) approach and the consequent risk

estimation matrix (REM)

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B. Singh et al.