INTRODUCTION:

Pharmaceutical companies develop a wide range of therapeutic agents intended to produce specific effects when administered to patients. Despite the availability of various dosage forms, the oral route remains favored by patients due to its distinct advantages. They have a high rate of patient compliance, which is better than other routes.

There are numerous patient populations, including kids, the elderly, patients with mental retardation, those who have trouble in swallowing and those with insufficient food and drink intake. Oral disintegrating tablets (ODTs) represent a unique pharmaceutical technology designed to address such challenges and accommodate these specific patient needs¹.

ODT is a unit dosage form formulated to disintegrate and dissolve fast. ODT can thus be utilized for people who struggle with swallowing as well as for those who require a rapid and simple method of administration even in the absence of water². After the Agency received and reviewed the applications for the initial ODT products, A definition for an ODT was created in 1998 by the Centre for Drug Evaluation and Research (CDER) Nomenclature Standards Committee. "A solid dosage form that dissolves quickly on the tongue, typically in a few seconds, and contains medicinal substances"³.

A long-term condition called asthma results in inflammation of the respiratory tract's airways. It can occur in people of all ages but most common in children around 10 to 14 years of age and older aged of 75 to 79. Around 300million worldwide individuals are affected by disease asthma. According to published reports, both children and adults have a 2%-4% prevalence rate in Asian countries like China and India. However, the incidence of occurrence is much higher at (15-20%) in developed countries like New Zealand, Canada, the UK, and Australia. The pathogenesis of asthma is mostly caused by environmental factors interacting with inflammatory mediators such as cytokines and leukotrienes. One way these environmental factors manifest is through cysteinyl LTs (Cys LTs) which have the ability to increase the permeability of the lungs' vascular system. This leads to pulmonary edema and subsequently, mucus hypersecretion. Therefore, airflow into the lungs of asthmatic patients is decreased due to the swelling, sensitivity, and inflammation of their airways.

Mast cell stabilizing and a strong antagonist of leukotriene receptors, montelukast selectively inhibits the cysteinyl leukotriene CysLT1 receptor. At the present time, asthma is treated with it. Other conditions that can be managed with montelukast sodium include allergic bronchopulmonary aspergillosis and chronic obstructive pulmonary disease (COPD). Montelukast sodium has been shown to be effective in relieving perennial and seasonal allergic rhinitis, at 25°C, montelukast is said to dissolve in water at a rate of 0.2 to 0.5g/ml. Montelukast is a Class II chemical rendering to the biopharmaceutics classification system (BCS) because of its strong permeability but low solubility⁴. It is possible to increase the rates at which BCS class II medications dissolve by using a variety of techniques, such as the use of surfactants, complexation with cyclodextrins, and the production of solid dispersions with water-soluble materials such as poloxamer⁵. Solid dispersion was one of several methods used to increase montelukast sodium's solubility; this method was then used to produce a novel oral dosage form for montelukast sodium, known as ODT, which is readily taken and may enhance the drug's absorption and solubility⁶.

An inert carrier or matrix that contains one or more active chemicals in a solid state is called a solid dispersion (SD). These substances can be generated by fusion, solvent, or melting solvent techniques. Melts are the term commonly used to describe dispersions obtained by the fusion process, while co-precipitates or evaporates are the term commonly used to describe dispersions obtained by the solvent technique⁷. The present paper aims to formulate and characterize montelukast sodium into ODT by direct compression method along with increasing their solubility by solid dispersion method. Hence, in order to give a quick onset of action for asthma, the development of an ODT may be advantageous⁸.

The concept of "Quality by Design" (QbD) describes a methodology that involves refining scientific understanding of crucial process and product attributes, creating controls and tests during the development stage based on the boundaries of scientific knowledge, and applying the knowledge acquired over the course of the product's life cycle to work on an environment of continuous improvement. The design, development, and manufacturing processes of formulations are referred to as QbD, a pharmaceutical development approach, in order to maintain the necessary product quality⁹. The process of creating and refining ODT formulations involves the use of Design of Experiments (DOE) called custom design. The custom design was created using the JMP® 14 Pro program (SAS Institute, Cary, NC, USA). Disintegration time, drug content, percentage of drug release, and hardness were among the Critical Quality Attributes (CQA) that were measured. The study included sodium starch glycolate, magnesium stearate, mannitol, and microcrystalline cellulose as Critical Material Attributes (CMAs)¹⁰.

MATERIALS AND METHODS:

Materials:

Aristo Pharmaceutical Pvt. Ltd. of Sikkim, India, provided montelukast sodium. Mannitol, microcrystalline cellulose, and magnesium stearate were obtained from SD Fine Chem PVT. LTD, while sodium starch glycolate was bought from ACS Chem, Ahmedabad. The remaining materials that were purchased were either reagent grade or pharmaceutical grade.

Methods:

Preparation of Solid Dispersion:

The solid dispersion of Montelukast was prepared by fusion method. The water-soluble carrier chosen was urea and the ratio selected for this formulation was 1:1 ratio. The API and urea were physically combined, heated to melt in the heating mantle up to 135^oC, By immersing the porcelain dish in an ice bath for five minutes while stirring constantly, the mixture was quickly cooled, and the hardened mass was crushed, pulverized, and filtered via a screen with 100 mesh. The prepared mixture was further characterized and formulated into ODT¹¹.

Characterization of Montelukast Sodium Solid Dispersion:¹²

Angle of Repose:

The angle of repose is the internal angle formed by the horizontal surface and the blend pile's surface. To find the blend's angle of repose, a funnel was placed through it and fastened to a burette stand at a particular height (4 cm). The funnel was placed on a table with a graph paper underneath it. Measurements like pile's height and radius were recorded. The following formula was used to get the blend's angle of repose:

θ = tan -1 (h/r)

Where, h = Height of the pile; r = The pile's radius.

Carr's Index:

The density of the prepared solid dispersion was checked by using USP Tap density tester, the following calculation was used to determine the blends % compressibility.

Tapped density – Bulk density

Carr' s index = ------------------------------------------ x 100

Bulk density

Solubility Studies:

Montelukast sodium was measured using a technique that involved mixing the drug with solid dispersion materials in varying ratios. The mixture of montelukast sodium and carriers was shaken for 48hours. The solution was then filtered using Whatman filter paper. The filtrate, containing montelukast sodium, was analyzed using UV spectroscopy at its maximum absorbance.

Determination of Log P Value:

The shake-flask method, is used to experimentally measure the partition coefficient (P), In this method, 20 mg of Montelukast Sodium was added into 25ml of aqueous solution (Phosphate buffer with Ph7.4) and 25 ml of organic solvent (n-octanol) was mixed in the flask. Following that, the flask was shaken for a 24hrs to allow the sample to distribute between the two phases and allowed to stand in the separating funnel for 30 minutes to obtain separate phases. the samples were subjected for the determination of drug content in both the phases by using UV Spectrophotometer at 283nm and partition coefficient was determined using the formula that follows:

Conc. of drug in organic phase

Partition coefficient (P) = ----------------------------------

Conc. of drug in aqeous phase

Fourier Transform Infrared (FTIR) Spectroscopy:

ALPHA II equipped with the horizontal attenuated total reflectance (HATR) mode and a zinc selenide crystal were used for the Fourier Transform Infrared Spectrophotometer (FTIR) analysis. The spectrums were recorded during the trials, which used air as the background noise. The scanning range was 4000-650 cm-1 with a resolution of 4.0cm¹³.

Differential scanning calorimetry:

A Perkin Elmer STA 6000 Thermal Analyzer was used to perform Differential Scanning Calorimetry (DSC). The instrument was calibrated with an indium standard. Samples were weighed precisely (the range is 3–5mg) and Placed in a ceramic sample pan that is open. The sample was heated at a constant frequency of 8°C/min to produce the thermograms. All runs were performed using a dry argon gas purge (60ml/min). Samples were heated between 37 to 400°C. For pure drug and mixture, the DSC thermogram was recorded.

Scanning Electron Microscopy:

The mixture's surface morphology has been examined using SEM. The mixture was spread out on an aluminum stub and let it to air dry. After that, the dried sample was sprayed for 40 seconds with gold using a Hitachi Ion-Sputter E1010 sputter gun. The image was taken with a scanning electron microscope from Hitachi, model S 3400¹⁴.

Defining the Quality Target Product Profile (QTPP) and CQAs:

QTPP is a fundamental aspect of Quality by Design (QbD) methodology. It represents a complete description of the product, representing the necessary quality attributes to ensure optimal performance, stability, safety, and efficacy. By delineating the essential characteristics, QTPP facilitates the assessment of the product's clinical effectiveness and safety profile. For Oral Disintegrating tablet, the constituent elements of QTPP encompass the dose type, strength, and administration method, stability considerations, and the container closure system. Each of these elements has been meticulously selected to uphold the integrity and functionality of the final product¹⁵(Table 1).

Critical Quality Attributes (CQA) :

The CQA is used to characterize the product's performance and its factors. The incorporation and control of Critical Quality Attributes in orally disintegrating tablet formulation offer a range of benefits, including improved patient compliance, enhanced bioavailability, optimized manufacturability, and adherence to regulatory standards. These factors collectively contribute to the development of safe, effective, and patient-friendly ODTs in the pharmaceutical industry¹⁶.

Table No. 1: QTPP and CQAs of ODT with Justification

QTPP		CQAs
QTPP ELEMENTS	TARGET	The drug product's Quality Attributes	Target	Is it a CQA?	Justification
Dosage form	Tablets	Appearance	Shape and color of the product	No	It is not directly related to safety and effectiveness. The goal is established to guarantee patient acceptability.
Dosage type	Orally disintegrating tablets	Odor, taste	No pleasant odor and taste	Yes	Due of patient convenience, odor and taste are important in ODTs.
Dosage Strength	40mg	Hardness	Pharmacopeia acceptability	Yes	Hardness has an impact on drug efficacy and disintegration time.
Route of administration	Oral	Disintegration Time	< 1 minute	Yes	Disintegration time influences onset of action.
Pharmacokinetics	Immediate release Cmax, Tmax, AUC	Wetting Time	< 30 sec	Yes	Disintegration time is affected by wetting time.
Stability	Minimum two-year shelf life at room temperature	Content Uniformity	Pharmacopeia acceptability	Yes	Variations in content uniformity will affect both safety and effectiveness. It is essential that OTDs have uniform content.
		Dissolution	Complies to Pharmacopeia Specification	Yes	Bioavailability may be impacted if the dissolving specification is not met.

Design Of Experiment (DoE):

Custom design accommodates various types of factors, constraints, and disallowed combinations. By using custom design, we can specify which effects are necessary to estimate and which are desirable to estimate, by given the number of runs and we can also specify the number of runs that matches the cost of experimental condition. The (table no.3) represents the design factors and responses selected in the current study¹⁹.

Table No: 3 Variables and limits in Custom Design and Responses in Custom Design

Variables	Variables	Lower Limit	Upper Limit
	Sodium Starch Glycolate	2%	8%
	Magnesium Stearate	2%	5%
	Microcrystalline Cellulose	5%	10%
	Mannitol	10%	90%
Responses	Goal	Lower Limit	Upper Limit
Disintegration Time (in secs)	Minimize	30	60
Dissolution Time (in min)	Maximize	80	100
Hardness	Target	3	5
Drug Content	Maximize	95	100

Design Evaluation/Design Diagnostic:

Using the JMP's design diagnostic tool and color map on correlations, the design was evaluated. The color map on correlations, which is a component of the Design Evaluation framework in the Custom Design, allows you to view the absolute values of the correlations among the effects. Absolute correlations of one are indicated by the dark red color. The red cells, which indicate how model terms correlate with one another. The other cells are either pale blue or deep blue in color. The correlations between the quadratic terms are represented by the light blue squares²⁰.

Preparation of ODT Formulation:

Montelukast fast-dissolving tablets were developed as per the custom design by using direct compression approach. Each ingredient was weighed separately and sieved individually through No. 40. Magnesium stearate served as a lubricant while microcrystalline cellulose served as a diluent. To create a consistent mixture, all of the ingredients were combined together. The final mixture was then compressed using a tablet punching machine Rimek mini press²¹.

Table No. 4 Formulation Table of Montelukast Sodium ODT

Formulation	Montelukast Sodium (%)	Sodium Starch Glycolate (%)	Magnesium Stearate (%)	Microcrystalline Cellulose (%)	Mannitol (%)
1	20	4	5	5	70
2	20	4	2	10	70
3	20	4	2	5	50
4	20	8	2	10	70
5	20	8	5	5	70
6	20	4	2	5	50
7	20	8	2	5	70
8	20	4	5	10	50
9	20	4	5	10	70
10	20	8	2	10	50
11	20	8	5	5	50
12	20	8	5	10	50

Checking CQAs:

Hardness Test:

A tablet's strength can be determined by its hardness. It is tested by measuring the amount of force required to break the tablet. In terms of force, a hardness of three to five kg/cm² is considered appropriate for uncoated tablets. Using a Monsanto hardness tester, the hardness of ten tablets from each formulation batch was measured ²².

Drug Content Uniformity:

Using a phosphate buffer pH 7.4, ten powdered tablets with 10mg drug equivalent powder was mixed and subjected to UV spectroscopy analysis. For Montelukast sodium, the sample preparations' absorbance was measured at 𝜆max 283nm²³.

Disintegration Test:

The in-vitro disintegration test was conducted using disintegration test apparatus (LAB-HOSP). Six tablets tested in total, and the disintegration medium employed was phosphate buffer with a pH of 7.4 at 37°C±2°C. The time taken by the tablets to completely disintegrate was recorded²⁴.

% Drug Release:

The USP dissolving equipment II (Paddle type, DISSO 8000, Labindiana) was used to conduct in vitro dissolution tests. which was thermostatically controlled at 37±0.5⁰C at a speed of 50rpm. At various intervals, one ml samples of the dissolving fluid were removed and tested for Montelukast at 283nm by using UV spectroscopy²⁵.

Model Fit:

The ODT formulation data obtained for all the different batches was incorporated in the design to check the model fit. A multiple regression model was fitted to the data and its intercept was set to zero for statistical analysis. It was concluded that models with p values<.05 were statistically significant for the variables of hardness, drug content, disintegration time, and time of maximal drug release. The different three-dimensional (3D) and contour plots were designed, analysed, and plotted using the JMP software.

Desirability based Numerical Optimization:

The optimization of the independent variables involved in the design was done using the prediction profiler that was produced for each individual response. Once the models were created and verified, the design space was established by going through each CMA's distinct acceptance regions. The confirmation trials for each individual response were conducted in accordance with the prediction profiler in order to validate the model²⁶.

Evaluation of Optimized ODTs:

The optimized formulation was checked for Hardness, Drug content, Disintegration time and Drug release study as per the procedure discussed in the section CQA checking.

Weight Variation:

By utilizing an electronic balance (Mettler Toledo) to weigh each of the twenty tablets separately and collectively, the weight variation was checked by computing the average weight and comparing the weight of each tablet with the average hardness²⁷.

Tablet thickness:

The tablet thickness was determined by checking the diameter of tablet, ten tablets were measured using a micrometre to determine their thickness.

Tablet Friability:

Using ten tablets of previously weighed were taken in the plastic chamber of Roche friabilator. The percentage of friability of the tablets was determined using the following formula:

Percentage friability = W1 – W2 / W1 × 10, Where, W1 = Initial weight of tablet, W2 = Final weight of tablet ^28,29.

Wetting Time:

In a 10cm diameter petri plate, 10ml of distilled water was mixed with the water-soluble dye Eosin. The wetting time was measured by carefully placing tablets in the centre of the petri dish and measuring how long Water takes a while to reach the tablet's top surface. The test results are shown as the average of the three findings³⁰.

Water Absorption Time:

Six ml of water was added to a small Petri dish containing a folded piece of tissue paper. The time it took for the paper to get entirely wet was measured using a tablet on the paper. After that, the wet tablet was weighed. R represents the water absorption ratio, which may be computed using the formula below³¹.

Wa -Wb

R = ---------------x 100

Where, Wa is the weight of tablet after water absorption, Wb is the weight of tablet before water absorption.

RESULTS AND DISCUSSION:

The primary aim of the study was to enhance the solubility of montelukast sodium through solid dispersion method among which fusion method was selected using urea as carrier the 1:1 ratio of drug and carrier has shown the better results as compared to other ratio. There were fine, free-flowing particles in every solid dispersion that was made. The prepared powders were further formulated into ODTs using sodium starch glycolate as super disintegrants, mannitol as diluent, magnesium stearate as lubricant, microcrystalline cellulose as binder. The JMP software JMP Statistical Software, (SAS Institute Inc., Cary, NC) was used to analyze the results produced by different combinations of independent variables.

Fourier transform infrared spectroscopy:

The drug and drug's physical combination absorption bands were close to one another indicates that the functional groups in montelukast sodium were not altered chemically or physically (Figure no 2).

Figure No.2 FTIR Spectrum of, a. Montelukast Sodium, b. Drug with excipients

Differential scanning calorimetry:

DSC allows for a detailed description of a substance's energetic and physical properties. When a guest molecule interacts with montelukast sodium, it usually causes its melting, boiling, or sublimation point to change or vanish within the range where montelukast sodium gets degraded. The drug's DSC thermogram revealed a distinct heat-absorbing peak at 135°C, which is close to its melting point and indicates crystallinity. According to the data, the drug's endothermic peak in physical mixtures is located around 133°C. (figure no.3) This implied that neither the appearance of new peaks nor the elimination of existing peaks had occurred. Thus, under the experimental circumstances, there was no discernible impact on the drug's thermal behaviour when combined with the excipients. Whereas the endothermic peak was seen at solid dispersion indicated that the drug had been significantly included in the urea cavity indicating no chemical interaction between drug and the carrier.

Figure No.3 a. DSC Study Montelukast Sodium, b. Montelukast Sodium Solid Dispersion

Scanning Electron Microscopy:

The SEM photograph of selected SD is shown in (figure no.4). The SD revealed that the particle size was less than 3µg, with a nearly smooth surface and spherical shape.

Figure No.4 SEM of Drug and Carrier

Evaluation of CQAs:

Model Fit:

The data from all twelve batches of ODT formulation (table no.5) were statistically examined using several regression models that had the intercept set to zero. There was statistical significance observed in the models for hardness test, drug content, drug release, and disintegration time in seconds. To assess the model's fit, the adjusted R2 and p-value for each response were esitimated. The Figure shows the prediction plots that were obtained for each of the four responses.

Table No. 5 CQA’s for all 12 formulations

Formulations	Average of Hardness (kg/cm2)	Average Disintegration Time (in sec)	Average of Drug Content (%)	Average of Drug Release (%)
F1	3.8 ± 0.081	40.22 ± 0.319	95.56 ± 0.02	85.98 ± 0.043
F2	4.5 ± 0.163	27.85 ± 0.634	96.28 ± 0.011	89.25 ± 0.045
F3	4 ± 0.081	45.11 ± 0.537	90.65 ± 0.015	89.27 ± 0.073
F4	4.8 ± 0.081	18.84 ± 0.284	99.71 ± 0.012	98.86 ± 0.055
F5	4 ± 0.163	20.74 ± 0.160	95.56 ± 0.022	95.73 ± 0.285
F6	3.8 ± 0.081	39.65 ± 0.221	90.08 ± 0.061	85.21 ± 0.03
F7	4.2 ± 0.081	22.85 ± 0.703	98.87 ± 0.030	96.66 ± 0.295
F8	4.5 ± 0.081	40.89 ± 0.278	89.95 ± 0.034	85.77 ± 0.02
F9	4.5 ± 0.163	46.24 ± 0.408	97.87 ± 0.019	82.24 ± 0.035
F10	4.5 ± 0.163	19.34 ± 0.30	94.67 ± 1.50	90.78 ± 0.025
F11	3.8 ± 0.081	20.78 ± 0.159	95.76 ± 0.029	89.56 ± 0.242
F12	4.8 ± 0.081	28.16 ± 0.319	92.89 ± 0.018	91.21 ± 0.12

Figure no. 5 a. Actual by Predicted Plot for Disintegration time, Drug release, Drug content and Hardness and b. Prediction Profile

Numerical Optimization:

Prediction Profiler:

The solid dispersion based ODT optimization was done with the help of prediction profiler (figure no.5). The global desirability of 0.94 obtained for the current formulation developed using custom design ensures the statistical validity of the model.

The evolution report obtained for the optimized formulation is presented in the (table no.6) ensuring all the quality attributes of the drug product.

Table No.6 Characterization of Optimized Formulation of ODT

S. No.	Parameters	Results
1	Hardness (Kg/cm²)	4.04 ± 0.041
2	Thickness (mm)	3.03 ± 0.02
3	Friability (%)	0.85 ± 0.036
4	Weight Variation (%)	104.13 ± 0.158
5	Disintegration Time	19.56 ± 0.065
6	% Drug Content	97.64 ± 0.241
7	% Drug Release	96.69 ± 0.127
8	Water absorption ratio (%)	84.19 ± 5.825
9	Wetting time (seconds)	13.03 ± 0.075

A comparison of the pure drug and optimized formulation release study showed that the percentage cumulative release of montelukast sodium during 30 minutes was found to be 43.35 % and 93.18 %, (figure no.6) respectively. The release of Montelukast Sodium was significantly increased in ODT as compared to pure drug due to the solid dispersion form of the drug, showing good increment in the solubility enhancement.

Figure No. 6 In-vitro Drug Release Profile Pure Drug Montelukast Sodium and Optimized Formulation

CONCLUSION:

The current study shows the significance of integrated lean QbD for the effective creation of an ODT formulation of solid dispersion based Montelukast sodium. It was evident from the generated solid dispersion evaluation data,that the drug was integrated into carrier without causing the pure drug to degrade and there was an incremental improvement in the drug's solubility. It was evident from batches of ODTs that super disintegrant have a predominent role in reducing the disintegration time. Using the Custom Design response surface approach, DoE combined with an optimization process via desirability function to produce a design space for creating the formulation with the required characteristics. The results of the current studies illustrate that it is easier to comprehend how formulation and process parameters affect the quality attributes of ODTs when risk assessment, screening, experimental design, and optimization tools are combined with QbD tools.

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Received on 11.09.2024 Revised on 15.01.2025

Accepted on 21.03.2025 Published on 05.09.2025

Available online from September 08, 2025

Research J. Pharmacy and Technology. 2025;18(9):4117-4125.

DOI: 10.52711/0974-360X.2025.00592

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

CMA, CPP CQAs	Disintegration Time	% Drug Release	Content Uniformity	Hardness
Super Disintegrant	High	High	Medium	Medium
Binder	High	High	Low	Medium
Diluent	Medium	Medium	Low	Low
Blending/ lubrication	Medium	High	High	Medium
Compression	High	High	High	High