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PharmTech.com Regulating Innovation, Quality, and Risk eBook January 2024 Pharmaceutical Technology ® 49 Qualit y • The company has applied its product and pro- cess knowledge, as well as its technical knowl- edge about its equipment, to construct the fol- lowing Qualit y Quartets: • Qualit y Quartet 1: • CQA=% impurit y X in t he f inished active substance • CPP–pH of the batch during the hydrolysis reaction at Stage 3 of the process • CA–Controlling pH during this hydrolysis reaction • CDE–In-line pH probe. • Qualit y Quartet 2: • CQA=% impurit y X in t he f inished active substance • CPP–Volume of f i rst MeOH cha rge to t he batch in the filter dr yer, while the batch is under agitation • CA–Controlling the quantit y of the MeOH addition • CDE–F low-meter wh ich measures t he vol- ume of MeOH charged. • Qualit y Quartet 3: • CQA=% impurit y X in t he f inished active substance • CPP–Volume of second MeOH charge to the wet cake in the filter dr yer while the batch is not under agitation • CA–Controlling the quantit y of the MeOH addition • CDE–F low-meter wh ich measures t he vol- ume of MeOH charged. The above is an example of how one CQA can be part of three different Quality Quartets. This is not unusual; many CQAs relate to more than one CPP. The above examples of Quality Quartets are illus- trative only. The authors are aware that the above types of CPPs are not always registered within mar- keting authorisation dossiers; however, they still remain valid, when they relate to the protection or achievement of CQAs. Doc u ment i ng Qu a l it y Qu a r tet s such a s t hose above is considered usef u l, as it ca n help reduce t he level of subject iv it y i n r isk assessments t hat m ay be per for med on a m a nu fac t u r i ng process, a nd i n t he r isk rat i ngs t hat a r ise f rom such r isk assessments, specif ica lly by mak ing the severit y, probabi l it y of occ u r rence a nd detec t ion rat i ngs, more objective. This is illustrated by the following: • I f f a i lu re mo des re l at i n g to t he i n-l i ne pH probe a re bei ng r i sk a ssessed , or i f f a i lu re modes relating to that step of the Stage 3 pro- cess are being risk assessed, t he severit y rat- ings that are assigned to those failure modes ca n be i n for med by ut i l izi ng t he k nowledge represented by Qua l it y Qua r tet 1. T h is i nd i- cates t h at s uc h f a i lu re modes m ay d i rec t ly i m p a c t u p on a CQ A (% I m p u r i t y X). T h i s helps reduce any subjectivit y in those ratings, because t he process k nowledge t hat Qua lit y Quartet 1 is based on, lends objectivity to such severit y ratings. • T h i s i s a l so t he ca se w it h rega rd to f a i lu re modes per taining to the isolation unit opera- tion involving the MeOH addition steps. • Subjectivity can also be minimized when prob- abi l it y of occ u r rence a nd detec t ion rat i ngs a re bei ng assigned to fa i lure modes per ta i n- ing to the pH probe or to the f low-meter used i n t he MeOH add it ions. T h is is because it is li kely t hat t here w i l l be clea rly documented good manufacturing practice (GMP) controls in place to ensure t he correct f unctioning of those t wo items of equipment, given the fact that Qualit y Quartets have been documented wh ich l i n k t hose t wo items of equipment d i- rectly with a CQA (% Impurit y X), and which i nd icate t h at t hose item s of equ ipment a re critical in nature. Thus, any probabilit y of oc- currence or detection ratings related to failure modes for the pH probe and f low-meter can be based directly on a consideration of those GMP controls and not on subjective failure rate es- timates with questionable validit y (6). O vera l l, a nd a s i nd icated above, Qua l it y Qua r- tets t hat lin k CQAs and CPPs w it h CAs and CDEs can be used to directly help minimise the level of subjectivit y in risk assessment work. Formality in QRM ICH Q 9(R1) highlights that formality in QRM is not a binar y concept (i.e., forma l/in forma l); it states that var ying degrees of formalit y may be applied du r i ng QR M ac t iv it ies. It a l so i nd icates t h at a n understanding of formalit y may lead to resources bei ng used more ef f icient ly, where lower r isk is- sues are dealt with via less formal means, freeing up resources for managing higher risk issues and more complex problems that may require increased levels of rigour and effort. T he re v i sed g u idel i ne refer s to t he fol low i ng t h ree fac tors t hat m ig ht be con sidered when de- termining how much formalit y to apply to a given QRM activit y: • Uncertainty. T h is relates to a lack of k nowl- edge about hazards, harms, and consequently, their associated risks, and it may be reduced via effective knowledge management in mak- ing risk-based decisions. • Importance: The more important a risk-based de c i s ion i s w it h rega rd to pr o duc t qu a l it y, the higher the level of formalit y that may be