these might act as nano, micron or submicron particles. The size and shape of

particle, surface charge and activity and nature of the material used for the develop-

ment of such nanoparticles, accordingly, must be taken into wide consideration to

diminish the probable lacunae associated with stability and agglomeration of

particles while embarking upon the usage of novel materials (Sathigari et al. 2011;

Chopra et al. 2015). Several studies report the dependence of physical stability of a

nano-based drug delivery system on the kind, effectiveness and concentration of the

stabilizer used for the development of such formulations (Pallagi et al. 2015;

Alshweiat et al. 2018, 2019; Ismail et al. 2019). In this context, QbD paradigms

are recognized as an asset to aid in categorizing the optimal type of stabilizer and

concentration, i.e. basically vital to circumvent the aggregation of particles

(Alshweiat et al. 2018, 2019).

Freeze-drying of the drug-loaded nanoparticles is a common practice to overcome

the long-term stability issues associated with nanoparticles. For the lyophilization

process, choice of apt lyoprotectants and their concentration becomes crucial factors

for prohibiting the aggregation of these nanoparticles. These influential lyophiliza-

tion factors have also been witnessed in various literature reports to be optimized

using QbD principles (Chung et al. 2012; Niu and Panyam 2017). While nanomilling

is one of the other most commonly used mechanical tools for deagglomeration of

nanoparticles, influential factors including time and speed of milling, kind and

amount of milling medium, size and amount of beads, drug amount and milling

design exhibit maximal effect on end-product properties (Sanganwar et al. 2010;

Sathigari et al. 2011; Peltonen 2018). Among many possible input variables, a few

vital ones are screened during preliminary studies and later systematically optimized

using QbD principles (Ghosh et al. 2013; Peltonen 2018).

18.6

Computer Usage During FbD of Drug Nanoconstructs

The salient benefits of FbD approaches are abundant and their acceptability upbeat.

The implementation of this entire exercise, nevertheless, involves a great deal of

logical, statistical, mathematical and graphical intricacies, making it quite cumber-

some for a scientist to analyse the consequent data manually. With the comprehen-

sive and user-interactive software, together with the powerful and economical

hardware, the computational hassles of QbD have been grossly simplified and

streamlined. Pertinent computer software is available not merely for DoE optimiza-

tion for steering the scientists efficiently on every step during whole drug product

development cycle but also for chemometric analysis through multivariate

techniques, QRM execution using REM or FMEA, use of other algorithmic matrices

and constructing fishbone diagrams. The computational problems get invariably

surmounted through the usage of appropriate software and subsequent logical

interpretations. Besides, the pertinent software package also ameliorates the presen-

tation aesthetics of FbD outcomes in the form of response surface plots, design

spaces and so on and so forth. Several dependable software are available in com-

mercial circulation to satiate the requirements of DoE, QRM, chemometrics, etc., to

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