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Posaconazole-conjugated graphene microgel for fungal infection treatment: Development, optimization, and in vitro evaluation against Aspergillus niger Cover

Posaconazole-conjugated graphene microgel for fungal infection treatment: Development, optimization, and in vitro evaluation against Aspergillus niger

Open Access
|Jul 2026

Figures & Tables

Table 1

Independent variables with their levels and codes in BBD

Independent variables (factors)Levels
Low (−1)Medium (0)High (+1)
X= PVA (%w/v)1.522.5
Y= Stirring speed (rpm)7508751000
Z= Stirring time (min)304560
Table 2

BBD of the study and their observed responses

RunPVA (%w/v)Stirring speed (rpm)Stirring time (minutes)PS (nm)PDIEE%
1.00025000.73270.56
2.+10−139500.28382.64
3.−1+1015000.99167.87
4.0+1−128200.78553.57
5.−10+146700.96265.47
6.+10+138000.21489.18
7.−10−132500.69968.49
8.+1−1016000.30898.36
9.00023000.65278.08
10.0−1+129500.68573.61
11.00028800.81681.59
12.−1−1015400.70871.38
13.0+1+147700.79558.32
14.+1+1025000.21164.32
15.0−1−132300.61080.85
16.00019800.59269.14
17.00020100.75973.75
Figure 1

Calibration graph and absorption spectra at various concentrations of posaconazole

Figure 2

FTIR spectra of posaconazole (A), graphene (B), PVA (C), and PCZ-G (D)

Figure 3

FE-SEM image of PCZ-G

Figure 4

DSC thermogram of PCZ-G

Table 3

Physicochemical properties of optimized PCZ-G gel

S.N.ParametersObservations
1ColorBlack
2OdorNone
3ConsistencyHomogenous and smooth
4GrittinessNil
4pH5.89±0.03
5Viscosity15.377±6.37 Pa.s
5Spreadability6.9±0.36 cm
7Extrudability19.44±0.73 g/cm2
Table 4

Coded coefficient and p-value for that coefficient between experimental factors or its combinations and responses

ConstantABCAXBBXCAXABXBCXC
PSCoefficient2334111.25283.75367.5117.95557.5−37−5121620.5
p-value0.38410.0490.0180.38120.0130.82910.017<0.0001
PdICoefficient0.7102−0.2930.0580.034−0.0950.016−0.167−0.011−0.003
p-value<0.00010.0480.2000.0290.6550.00170.739−0.927
% EECoefficient74.627.661−10.010.1280.002.995.35−4.49−3.53
p-value0.00190.00040.9370.000.2240.0440.0790.150
Figure 5

Effect of independent variables on PS: (a) contour plots and (b) 3D response surface plots

Figure 6

Effect of independent variables on PDI: (a) contour plots and (b) 3D response surface plots

Figure 7

Effect of independent variables on EE%: (a) contour plots and (b) 3D response surface plots

Table 5

Parameters for optimization of posaconazole and graphene-loaded microparticle by BBD

S. No.ResponseGoal
1.Average particle size (nm)Minimize
2.PdIMinimize
3.% EEMaximize
Table 6

Optimized solution by BBD

Independent variables (factors)Formulation parameter setting
A = PVA (%w/v)2.5
B = Stirring speed (rpm)752.85
C = Stirring time (min)52
Table 7

Validation of the experimental model

S.No.Dependent variablesPredicted valueExperimental value
1.R1= Average PS (nm)1499.98±338.9151600±252.47
2.R2= PDI0.280±0.0690.308±0.029
3.R3= %EE99.62±4.4998.36±3.89

[i] Values are represented as mean ± SD (n=3)

Table 8

In Vitro Drug Release Kinetics Model

S. No.In vitro drug release kinetics modelParameters (R2 values)
1.Zero-order kinetics0.9638
2.First-order kinetics0.6112
3.Higuchi release kinetics0.9797
4.Korsmeyer–Peppas model0.9619
Figure 8

In vitro drug release analysis

Figure 9

Antifungal activity of PCZ-G gel (A), plate showing zone of inhibition (B)

DOI: https://doi.org/10.2478/afpuc-2026-0005 | Journal eISSN: 2453-6725 (formerly 1338-6786) | Journal ISSN: 0301-2298
Language: English
Page range: 44 - 58
Submitted on: Jan 15, 2026
Accepted on: May 10, 2026
Published on: Jul 3, 2026
Published by: Comenius University in Bratislava, Faculty of Pharmacy
In partnership with: Paradigm Publishing Services
Related subjects:

© 2026 Shanti Bhushan Mishra, Shradhanjali Singh, Anil Kumar Singh, Preetam Singh, Pradeep Kumar Vishwakarma, published by Comenius University in Bratislava, Faculty of Pharmacy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.