Research Article - Journal of Drug and Alcohol Research ( 2023) Volume 12, Issue 7

# PREPARATION, EVALUATION AND STATISTICAL OPTIMIZATION OF PRASUGREL NANOSUSPENSION

P. Bhaskar Reddy^{1}, C.K. Dhanapal

^{1}and Shaik Harun Rasheed

^{2}

^{*}

^{1}Department of Pharmacy, Annamalai University, India

^{2}Department of Pharmaceutics, Guru Nanak institutions Technical Campus, India

**Shaik Harun Rasheed, Department of Pharmaceutics, Guru Nanak institutions Technical Campus, India,**

^{*}Corresponding Author:**Email:**shaikharunrasheed@gmail.com

**Received: **01-Aug-2023, Manuscript No. JDAR-23-114567;
**Editor assigned: **03-Aug-2023, Pre QC No. JDAR-23-114567 (PQ);
**Reviewed: **17-Aug-2023, QC No. JDAR-23-114567;
**Revised: **22-Aug-2023, Manuscript No. JDAR-23-114567 (R);
**Published:**
29-Aug-2023, DOI: 10.4303/JDAR/236254

## Abstract

**Background: **To enhance the solubility of Prasugrel it was made in the
form of Nanosuspension.

**Objectives: **The study focused on the preparation of Nanosuspension
which could improve the bioavailability.

**Methods:** Various stabilizers were taken and verified in order to understand
the solubility in suitable stabilizer. It was found that it had high
solubility in Trilaurin and Evaporative Precipitation method was selected
as a suitable choice.

**Results: **The nanosuspensions prepared were statistically optimized using
3 level factorial design and from the overlay plot, it was further confirmed
about optimized results obtained.

**Conclusion:** The preparation of Prasugrel Nanosuspension resulted in
improving the solubility, bioavailability when compared to the pure drug.
Statistical optimization technique helped in selection of best formulation
among the various formulations prepared. Hence, from the results obtained
it is confirmed that delivery of Prasugrel into NP one of the best
dosage form.

### Keywords

Prasugrel nanosuspension; Trilaurin; Statistical optimization

### Introduction

Prasugrel is a novel 3^{rd} generation oral thienopyridine
mainly used to reduce the risk of thrombotic cardiovascular
events such as stent thrombosis or myocardial infarctions
in patients with Acute Coronary Syndrome (ACS). Prasugrel
is a BCS class II drug and exhibits pH dependent
solubility and it is very soluble at low pH conditions and
least soluble with increase in pH. The active metabolite of
prasugrel has an elimination half-life of 7 hours with an
approximate bioavailability of 80%. Even it has high bioavailability;
it is variable because of poor solubility [1-5].
It is more potent and has lower inter-individual variability
in platelet response, and faster onset of activity.

In order improve the solubility of the drug various techniques were studied and it was proved that complexation with cyclodextrins, nanosuspensions both methods gave enhanced solubility [6-8]. However, in the present study nanosuspensions were prepared and observed that they had better solubility.

### Materials

Prasugrel is a gift sample from Lupin pharma, Trilaurin and Triolein obtained from Merck, PVA, PVP K-30, HPC, Pluronic F 68, Pluronic F-127 purchased from indiamart.

### Methods

**Appearance and melting point**

The organoleptic characteristics like colour, odour and texture were observed by sensory organs. The melting point was determined using capillary fusion method where a small amount of drug was filled in a capillary sealed from one side and kept inverted i.e. sealed end downwards into the melting point apparatus [9-11]. The temperature at which drug started liquefy was recorded and compared with literature value.

**Solubility study**

The solubility study of prasugrel was carried out in various solvents. Accurately weighed 20 mg of drug was added to screw capped vials containing 10 ml of solvent. The vials were kept in a water bath shaker at 37°C ± 0.5°C and shaken for 24 h. The mixtures were then filtered through millipore filter membrane of pore size 0.45 μm, diluted and drug was analyzed using UV spectrometer.

**Determination of absorption maxima (λ _{max}) of prasugrel
using UV spectrophotometer**

1000 μg/ml of stock solution of Prasugrel was prepared by
dissolving 50 mg of drug in 0.1 N HCl and diluting 1 ml of
above solution to 10 ml with 0.1 N HCl. The 10 μg/ml of
drug concentrations were then prepared and scanned using
UV spectrophotometer to determine the λ_{max} of drug. Observed
λ_{max} of Prasugrel was at 222 nm.

**Preparation of calibration curve of prasugrel**

The calibration curve of prasugrel was prepared in 0.1 N HCl. Accurately weighed 50 mg of drug was dissolved in 50 ml of 0.1 N HCl to obtain concentration of 1 mg/ml. The 1 ml of prepared solution was further diluted 10 times to obtain stock solution of 100 μg/ml. Different aliquots were withdrawn and diluted to form concentrations of 10 μg/ml, 20 μg/ml, 30 μg/ml, 40 μg/ml, 50 μg/ml. The absorption was linear in the concentration range of 10 μg/ml-50 μg/ ml.

**Preparation of prasugrel nanosuspensions**

**Selection of stabilizer:** 0.1% (w/v) solution of PVA, PVP
K-30, HPC, Pluronic F 68, Pluronic F-127, Trilaurin and
Triolein were used as candidate to select the appropriate
stabilizers for preparing Prasugrel nanosuspension. The results
show that Trilaurin and Triolein allowed the production
of submicronsized particles with the small diameter
of 380 nm and 385 nm respectively. Trilaurin showed the
narrow particle size distribution, in comparison of other
stabilizers. So in this current study Trilaurin was employed
as stabilizer.

**Method of preparation of prasugrel nanoparticles using
evaporative precipitation of nanoparticles:** Nanosuspensions
were prepared by evaporative precipitation Ultrasonication
method. 100 mg of Prasugrel was dissolved in 10
ml methanol at room temperature. Trilaurin was dissolved
in water to form a series of anti-solvents ranging in concentration
from 0.5% w/v-1.5% w/v. Solution was filtered
through a 0.22 μm syringe filter (RanDisc nylon syringe filter).
10 ml of organic solution was added slowly drop wise
with a syringe into the 20 ml of Trilaurin solution and kept
at a low temperature (4°C) in an iced water bath. During
injection, the mixture was stirred continuously by the mechanical
stirrer at 1000 rpm for 2.5 h. After the antisolvent
precipitation, the volatile solvent was evaporated by subsequently
stirred the mixture at 300 rpm for next 3 h then
sample was transferred to a test tube having the capacity
of 30 ml. Each of samples was treated with an ultrasonic
probe (Bandelin Sonoplus, Berlin, Dermany) at various
cycles ranging from 2 × 10%-7 × 10%, and power input
ranging from 30%W-80%W) and for various duration
(5 min-40 min). The probe (tip diameter, 8 mm) was immersed
about 10 mm-12 mm in the liquid by which waves
was travelled downwards and reflected upwards. During
ultrasonication the temperature was also controlled by using
ice water bath.

**Factorial design: **A 3^{2} randomized full factorial design
was used in this study and 2 factors were evaluated, each
at 3 levels, experimental trials were performed at all 9 possible
combinations. Concentation of Trilaurin (X1) and
Ultrasonication time (X2) were selected as 2 independent
variables which were varied at 3 levels, low level (-1), medium
level (0), high level (+1).

Amount of Prasugrel (10 mg) was kept constant. Particle
size (Y1), zeta potential (Y2) and Polydispersibility index
(Y3) were selected as dependent variables. Values of variables
and formulation codes are shown in the **Tables 1 and
2**. Design-Expert® 12 software trial version was used for
the generation and evaluation of statistical experimental
design.

**Table 1:** Variables in 3^{2} factorial designs

Independent variable | Levels | ||
---|---|---|---|

Low (%w/v) | Medium (%w/v) | High (%w/v) | |

X1: Trilaurin | 0.5 | 1 | 1.5 |

X2: Ultrasonication time | 10 | 15 | 20 |

Dependent variable | - | - | - |

Y1: Particle size (nm) | - | - | - |

Y2: Zeta potential (Mv) | - | - | - |

Y3: Polydispersibility index (PDI) | - | - | - |

**Table 2:** Compositions of Prasugrel Nanosuspension

Formulation | Conc of Trilaurin (%w/v) | Ultrasonication time (days) |
---|---|---|

F1 (-1,-1) | 0.5 | 10 |

F2 (-1,0) | 0.5 | 15 |

F3 (-1,+1) | 0.5 | 20 |

F4 (0,-1) | 1 | 10 |

F5 (0,0) | 1 | 15 |

F6 (0,+1) | 1 | 20 |

F7 (+1,-1) | 1.5 | 10 |

F8 (+1,0) | 1.5 | 15 |

F9 (+1,+1) | 1.5 | 20 |

**Determination of particle size distribution, Polydispersity
Index (PDI), and zeta potential of SLN: **The particle
size distribution, polydispersity index, and zeta potential of
Prasugrel loaded nanosuspension were measured using a
Malvern Zetasizer. About 100 μl of the prepared nanosuspension
was diluted to 5 ml with double distilled water and
analyzed with Zetasizer. Photon correlation spectroscopy
is the most widely used technique for measurement of particle
size and zeta potential. The principle of dynamic light
scattering at a scattering angle of 90° is used to measure
particle size.

**Statistical analysis of the data and optimization: **Response
surface modelling and evaluation of the quality of
fit of the model for the current study were performed employing
Design Expert® 12 software trial version. Polynomial
models including linear, interaction and quadratic
terms were generated for all the response variables using
Multiple Linear Regression Analysis (MLRA).

A second order polynomial equation that describes the effect of independent factors on the response is expressed in the following forms:

Where, Y is the dependent variable, β0 is the arithmetic mean response of the 9 runs, and β1 and β2 are the estimated coefficients for the factors X1 and X2 respectively. The main effect (X1 and X2) represents the average result of changing 1 factor at a time from its low to high value. The interaction term (X1X2) shows how the response changes when 2 factors were changed simultaneously. The polynomial terms (X1X1, X2X2) are included to investigate nonlinearity. The equation enables the study of the effects of each factor and their interaction over the considered responses.

The polynomial equation was used to draw conclusions after considering the magnitude of coefficients and the mathematical sign it carries, i.e., positive or negative. A positive sign signifies a synergistic effect, whereas a negative sign stands for an antagonistic effect. The best fitting mathematical model was selected based on the comparisons of statistical parameters which include the Coefficient of Variation (CV), the coefficient of determination (R2), adjusted coefficient of determination (adjusted R2) and the Predicted Residual Sum of Square (PRESS), provided by Design Expert software.

Among them, PRESS indicates how well the model fits the data and for the chosen model it should be small relative to the other models under consideration. Level of significance was considered at p<0.05. Mathematical relationships in the form of polynomial equations are generated using Multiple Linear Regression Analysis (MLRA) and used to find out the relative influence of each factor on the response.

Analysis of Variance (ANOVA) for the responses was performed to identify significant effect of factors on responses and the model parameters were obtained. The relationship between the dependent and independent variables was further elucidated using contour and response surface plots. These plots are very useful to study of the effects of 2 factors on the response at one time and predict the responses of dependent variables at the intermediate levels of independent variables. Subsequently, a numerical optimization technique by the desirability and graphical optimization technique by the overlay plot approach were used to generate the new formulation with the desired responses. An optimized formulation was developed by setting constraints (goals) on the dependent and independent variables.

### Results and Discussion

**Appearance and melting point**

In order to confirm the nature of drug, it is studied for appearance, odour and Melting point. All the characters were tabulated below as Table 3.

**Table 3:** Organoleptic characters of Prasugrel

Drug | Parameter | Reported | Observed |
---|---|---|---|

Prasugrel | Appearance | Brown color | Light brown |

Odour | None | None | |

Melting point | 122°C | 123°C |

**Determination of solubility**

The solubility test was performed using different solvents. It was found that the drug has highest solubility in 0.1 N HCl. As shown in Table 4.

**Table 4:** Solubility of Prasugrel in various solvents

Solvent | Prasugrel |
---|---|

Solubility (µg/ml) | |

Distilled water | 3.2 ± 0.2 |

0.1 N HCl | 156.3 ± 0.1 |

pH 4.0 | 102.6 ± 0.2 |

Phosphate buffer pH 6.8 | Insoluble |

Ethanol | 103 ± 0.05 |

Methanol | 92 ± 0.3 |

**Determination of λ _{max}**

Wavelength of the drug plays major role in studying various other parameters. Hence, the wavelength was studied and found that at 222 nm. It was shown as Figure 1.

**Figure 1:** **λ**_{max} of Prasugrel was at 222 nm

**Construction of calibration curve**

Calibration curve of Prasugrel was constructed and found that concentration ranges from 10 μg/ml-50 μg/ml. The Table 5 shows the relationship between concentration and absorbance and graphically represented as Figure 2. The statistical parameters were tabulated as Table 6.

**Table 5:** Concentration *vs* Absorbance

Concentration (µg/ml) | Absorbance (nm) |
---|---|

0 | 0 |

10 | 0.223 ± 0.02 |

20 | 0.445 ± 0.55 |

30 | 0.653 ± 0.35 |

40 | 0.869 ± 0.67 |

50 | 0.979 ± 0.44 |

**Table 6:** Statistical parameters for standard curves of Prasugrel in pH 1.2

S. No | Parameter | pH 1.2 |
---|---|---|

1 | λ_{max} (nm) |
222 |

2 | Linearity range (µg/ml) | 10-50 |

3 | Regression equation | y=0.0201x+0.0252 |

4 | Intercept | 0.0252 |

5 | Slope | 0.0201 |

6 | Correlation coefficient (R2) | 0.991 |

**Figure 2:** Standard plot of Prasugrel in pH 1.2

Identification of particle size distribution, polydispersity index (PDI), and zeta potential of SLN

The prepared NS as per the formulation were studied for particle size, PDI, Zetapotential. These help in understanding the nature of SLN. As shown in Table 7.

**Statistical optimization of prepared nanosuspension**

All the responses observed for 9 runs (3 different bases of Nanosuspension) were simultaneously fitted to linear, interaction and quadratic models using Design Expert software trial version 12.

**Table 7:** Observed responses of Prasugrel loaded Nanosuspension

Batch | Conc of Trilaurin (%w/v) | Ultrasonication time (days) | Particle Size (nm) | Zeta potential (mV) | PDI |
---|---|---|---|---|---|

PF1 | 0.5 (-1) | 5 (-1) | 0.226 | -20.3 | 0.54 |

PF2 | 0.5 (-1) | 10 (0) | 0.282 | -22.4 | 0.5 |

PF3 | 0.5 (-1) | 15 (+1) | 0.378 | -23.9 | 0.49 |

PF4 | 1 (0) | 5 (-1) | 1.28 | -25.5 | 0.47 |

PF5 | 1 (0) | 10 (0) | 1.35 | -27.1 | 0.42 |

PF6 | 1 (0) | 15 (+1) | 1.54 | -29.2 | 0.4 |

PF7 | 1.5 (+1) | 5 (-1) | 1.34 | -26.4 | 0.39 |

PF8 | 1.5 (+1) | 10 (0) | 1.49 | -28.2 | 0.35 |

PF9 | 1.5 (+1) | 15 (+1) | 1.57 | -30.5 | 0.3 |

The comparative values of R2, adjusted R2, predicted R2, PRESS, s.d, %CV at significant p values (P<0.05), are given in Table 8. A suitable polynomial model for describing the data was selected based on coefficient of determination (R2) and PRESS values. The 3 responses Y1, Y2, Y3 of nanosuspension were independent, for nanosuspension prepared, the responses Y1, Y2 followed quadratic model whereas Y3 followed linear model.

**Table 8:** Regression analysis summary of Prasugrel based Nanosuspension for responses Y1, Y2 and Y3

Model R2 | R2 | Adjusted R2 | Predicted R2 | PRESS | s.d. | F-value | p-value | Remarks | ||
---|---|---|---|---|---|---|---|---|---|---|

Response Y1 (Particle size (nm))=1.38+0.58A+0.107B+0.0195AB-0.509 A²+0.015 B² | ||||||||||

Linear | 0.802 | 0.736 | 0.5822 | 1.1 | 0.29 | 12.15 | 0.007 | - | ||

Interactive | 0.802 | 0.684 | 0.2476 | 1.9 | 0.3 | 0.014 | 0.908 | - | ||

Quadratic | 0.998 | 0.9951 | 0.9823 | 0.0467 | 0.0392 | 168.36 | 0.00082 | Suggested | ||

Response Y2 (Zeta Potential mV)=-27.2-3.08 A-1.9 B-0.125AB+1.9A²-0.06B² | ||||||||||

Linear | 0.906 | 0.8758 | 0.802 | 17.1 | 1.16 | 29.21 | 0.0008 | - | ||

Interactive | 0.907 | 0.852 | 0.647 | 30.5 | 1.26 | 0.03 | 0.851 | - | ||

Quadratic | 0.998 | 0.995 | 0.981 | 1.57 | 0.217 | 83.2 | 0.002 | Suggested | ||

Response Y3 PDI=+15.57+0.10667*A+0.24667*B | ||||||||||

Linear | 0.5466 | 0.4459 | 0.1473 | 1690 | 9.99 | 5.43 | 0.0285 | Suggested | ||

Interactive | 0.6873 | 0.14 | -35.966 | 73263.1 | 12.45 | 0.057 | 0.9453 | - | ||

Quadratic | 0.6784 | 0.4103 | -1.1821 | 21 | 4324.668 | 1.06 | 0.4036 | - |

The fitted polynomial equations relating the responses are given in Table 9. Model parameters obtained from analysis of variance (ANOVA) for the responses Y1-Y3. These parameters were used to construct the models that describe the effect of the independent variables on the responses (Y1-Y3).

**Table 9:** Model parameters (ANOVA) for the dependent responses of Prasugrel based Nano suspension

Source | SS | df | MS | p-value | Significance |
---|---|---|---|---|---|

Response Y1 | |||||

Model | 2.64 | 5 | 0.52 | 343.7 | S |

X1 | 2.07 | 1 | 2.05 | 1336.2 | - |

X2 | 0.068 | 1 | 0.064 | 44.6 | - |

X1X2 | 0.0015 | 1 | 0.002 | 0.987 | - |

X12 | 0.518 | 1 | 0.518 | 336.4 | - |

X22 | 0.0004 | 1 | 4E-04 | 0.29 | - |

Residual | 0.0046 | 3 | 0.001 | - | - |

Total | 2.6515 | 8 | - | - | - |

Response Y2 | |||||

Model | 86.64 | 5 | 17.32 | 366.2 | S |

X1 | 57.04 | 1 | 57.04 | 1205.5 | - |

X2 | 21.66 | 1 | 21.66 | 457.7 | - |

X1X2 | 0.0625 | 1 | 0.063 | 1.32 | - |

X12 | 7.86 | 1 | 7.86 | 166.2 | - |

X22 | 0.008 | 1 | 0.008 | 0.187 | - |

Residual | 0.141 | 3 | 0.04 | - | - |

Total | 86.7 | 8 | - | - | - |

Response Y3 | |||||

Model | 1083.3 | 2 | 541.6 | 0.0285 | S |

X1 | 170.6 | 1 | 171.6 | 0.2235 | - |

X2 | 912.6 | 1 | 912.6 | 0.0144 | - |

Residual | 898.5 | 9 | 99.8 | - | - |

Total | 1981.8 | 11 | - | - | - |

From the ANOVA data, the F values were 168.36, 83.2 and 5.43 respectively. The P value less than 0.05 for the response factors indicated that the models are significant (Figures 3-8)

**Figure 3:** Contour plots for the effects of Trilaurin (X1) and Ultrasonication time (X2) on particle size (Y1) in Prasugrel based nanosuspensions

**Figure 4:** Response surface plots for the effects of Trilaurin (X1) and Ultrasonication time (X2) on particle size (Y1) in Prasugrel based nanosuspensions

**Figure 5:** Contour plots for the effects of Trilaurin (X1) and Ultrasonication time (X2) on zeta potential (Y2) in Prasugrel based nanosuspensions

**Figure 6:** Response surface plots for the effects of Trilaurin (X1) and Ultrasonication time (X2) on zeta potential (Y2) in Prasugrel based nanosuspensions

**Figure 7:** Contour plots for the effects of Trilaurin (X1) and Ultrasonication time (X2) Polydispersibility index (Y3) in Prasugrel based nanosuspensions

**Figure 8:** Response surface plots for the effects of Trilaurin (X1) and Ultrasonication time (X2) on Polydispersibility index (Y3) in Prasugrel based nanosuspensions

### Optimization

To optimize 3 responses with different targets, a multi-criteria decision approach, like a numerical optimization technique by the desirability function and graphical optimization technique by the overlay plot were used. The optimized formulation was obtained by applying constraints (goals) on dependent (response) and independent variables (factors). Optimum formulation was selected based on the criteria of minimum particle size (1.57 nm ± 0.2 nm), higher zeta potential (-30.5 mV ± 1.1 mV) and low PDI. Various feasibility and grid searches were executed to establish the optimum formulation by plotting desirability function response plot and overlay plot, where one solution was found with a desirability of 1.0. The recommended Trilaurin (X1) and Ultrasonication time (X2) were calculated by the Design Expert 12 software trial version.

Optimization was carried out by both numerical optimization and graphical optimization techniques. Nanosuspensions desirability and overlay plots are shown respectively in Figures 9 and 10. The desirability function was found to be higher (which are near to 1) for the optimized formula indicating the suitability of the formulations.

The optimized nanosuspension contain 1.5% w/v of Trilaurin and 15 days of ultrasonication time. Predicted model formulations were found matching with the optimized PF9 formulation.

**Figure 9:** Nanosuspensions desirability of Prasugrel

**Figure 10:** Overlay plot of Prasugrel optimized formulation

The optimized nanosuspension contain 1.5% w/v of Trilaurin and 15 days of ultrasonication time. 10 mg of Prasugrel was kept constant in all the formulations. The prepared optimized formulations were found to be of good quality fulfilling all the requirements of nanosuspension.

### Conclusion

The preparation of Prasugrel Nanosuspension resulted in improving the solubility, bioavailability when compared to the pure drug. Statistical optimization technique helped in selection of best formulation among the various formulations prepared. Hence, from the results obtained it is confirmed that delivery of Prasugrel into NP one of the best dosage form.

### Acknowledgement

None.

### Conflict Of Interest

Authors have no conflict of interest to declare.

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**Copyright:** © 2023 P. Bhaskar Reddy, et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.