Department of Pharmacy, Bhagwant University, Ajmer (Raj)305004, India.
Objective Migraine is a complex neurological disorder that affects a significant portion of the global population. As traditional pharmacological approaches often fall short in alleviating symptoms, the development of innovative therapies has garnered significant interest. This text aims to summarize the current pharmacological options for managing migraine and to explore the potential impact of novel therapies. The concept of fast dissolving dosage form has become popular as new delivery system. Material and Methods: The formulations were prepared by solvent casting method and characterized using UV-visible spectroscopy, XRD, SEM, and FTIR. The RDF was prepared using a Quality by Design (QbD) approach for film optimization. Design of experiments and statistical analysis have been applied widely to formulation development, and are useful in process optimization and process validation. The optimized formulation was evaluated for folding endurance, disintegration time, and drug release. Stability studies were performed as per ICH guidelines. Results: Quality by Design (QbD) is a systematic and scientific approach that enhances product quality while ensuring the robustness and reproducibility of RDFs, as outlined in the Quality Target Product Profile (QTPP). DoE was integrated into the QbD framework to systematically evaluate the effects of predefined factors, particularly Critical Material Attributes (CMAs) and Critical Process Parameters (CPPS), on the desired responses (Critical Quality Attributes/CQA), ultimately leading to the identification of the optimal RDFs formulation. Conclusion: The integration of QbD and DoE, approaches holds significant potential in the development of RDFs. These strategies enable a more efficient, rational, and predictive formulation process. The drugs can be effectively incorporated in RDFs and can be a promising approach as a novel drug delivery system for promising therapeutic action.
Headaches, particularly migraines, remain one of the most common and disruptive neurological disorders, significantly impacting the lives of millions worldwide [1]. Migraine is the second highest cause of global disability in the general population, but first among women aged 15−49. Specific triggers, such as stress or irregular sleep, can provoke a migraine episode. Migraines are classified as episodic or chronic, with the two most common types being migraine with and without aura [2]. Migraine is a prevalent and recurrent primary headache disorder characterized by unilateral, throbbing, moderate-to-severe pain, often accompanied by symptoms such include such as light and sound sensitivity, osmophobia, and reduced mobility as nausea, vomiting, photophobia, and phonophobia. Its etiology is influenced by both genetic and environmental factors, with a global prevalence of approximately 15% [3]. Migraine often imposes significant limitations on daily activities and functions, contributing to considerable disability. The impact of migraine can extend to substantial loss in work productivity and missed opportunities for social engagement and family responsibilities [4]. Migraines have a multifaceted socioeconomic impact on Lower-Middle Income Countries (LMICs), including India. Previous studies have shown that point prevalence of migraine is close to 25%. As a result, migraine is associated with significant economic challenges, including high healthcare costs, reduced workplace productivity and high costs for society [5]. Individuals with chronic migraine experience headache on most days of the month for at least three months, with migraine features occurring on at least eight of those days each month. Chronic migraine can severely impact an individual’s quality of life and productivity as they must endure these episodes often. The current standard of care for migraine prevention includes various conventional oral medications, such as antihypertensives, anticonvulsants, and antidepressants as well as botulinum toxin for chronic migraine. While these medications can be helpful, they often have limited efficacy and are associated with substantial adverse events [6]. Drug delivery systems (DDS) are formulated using advanced technology to accelerate systemic drug delivery to the specific target site, maximizing therapeutic efficacy and minimizing off-target accumulation in the body. As a result, they play an important role in disease management and treatment. Recent DDS offer greater advantages when compared to conventional drug delivery systems due to their enhanced performance, automation, precision, and efficacy. The demand for rapid onset of action and improved bioavailability has driven the development of dosage forms that quickly disintegrate and dissolve in the buccal cavity, facilitating direct absorption through the buccal mucosa into the systemic circulation [7]. The need for innovative formulations arises from the recognition that traditional oral dosage forms, such as rapid dissolving film (RDF) has recently gained popularity in the pharmaceutical industry because of its immediate release action and its development based on the transdermal patch technology. RDF disintegrates within a minute when it comes in contact with the saliva and releases the drug. This innovative approach emerged as an economical way of administering unit doses of medication to normal, paediatric, and geriatric patients who have difficulty swallowing standard pills, capsules, liquid orals, or syrup. The delivery method comprises a thin oral strip that quickly absorbs saliva, hydrates rapidly, and sticks to the application site when placed under the patient's tongue [8]. The Quality by Design (QbD) principle has led to significant advancements in drug delivery, especially in formulation optimization [9]. The preparation and characterization of solid lipid nanoparticles for bioavailability enhancement follow a QbD approach to ensure quality and performance [10]. The systematic use of QbD helps to improve product quality consistency, optimize formulation process parameters, regulatory compliance, faster approval, and cost-time efficiency in development [11, 12]. Large amounts of financial resources are usually devoted to drug development studies. Therefore, maintaining quality attributes at an affordable cost within a short period of time has become important to both academia and the pharmaceutical industry, and consequently, the implementation of the Quality by Design (QbD) approach has received much attention [13]. The elements and the QbD approach are detailed in the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines, such as ICH Q8, Q9, Q10, Q11, Q12, and more recently Q13[14]. The elements of QbD include the description of the Quality Target Product Profile (QTPP), in particular the ideal parameters that the product should achieve, the identification of characteristics in the formulation named Critical Quality Attributes (CQAs), Critical Material Attributes (CMAs) and Critical Process Parameters (CPPs), the results of the Risk Assessment (RA), which is the crucial step because it supports the impact of the CQAs and the CPPs on the target product profile, key points of the Design of Experiments (DoE), and the definition of Design Space (DS) [15]. This approach has been proven successful in oral drug delivery systems, using different experimental designs that resulted in improved bioavailability and stability [16]. Triptans are generally considered safe overall, but they are contraindicated in patients with uncontrolled hypertension and other cardiovascular and cerebrovascular diseases. Migraine, neurogenic inflammation and cerebral vasodilatation are significant factors. Activation of 5-HT1D prevents neurogenic inflammation, and activation of 5-HT1B reverses cerebral vasodilatation. Frovatriptan has a high affinity for 5-HT1D and 5-HT1B receptors. Nonetheless, frovatriptan has a moderate affinity for 5-HT1A and 5-HT1F receptors subtypes, and it is most potent 5-HT1B agonist. Incomplete absorption from the gastrointestinal tract is attributing to the low oral bioavailability of frovatriptan that is 22%–30% [17]. Hence, based on the rationale of the proposed research work, the aim of present investigation was to develop and formulate pullulan based fast dissolving films of aprepitant by solvent casting method for the direct absorption of drug via transmucosal lining to the systemic circulation. The proposed formulation has the potential to improve compliance and presents multiple competitive advantages over its marketed oral dosage forms. The film was prepared using the solvent casting method and a simplex lattice mixture design based on the QbD approach. Key parameters such as disintegration time, tensile strength, and folding endurance were evaluated.
MATERIALS AND METHODS
MATERIALS
Frovatriptan succinate, all other ingredients were used of analytical grade without any further modification.
Formulation development of fast dissolving films
Preliminary trials for screening of components
Development of successful fast dissolving film is based on selection of polymer nature and concentration; several polymers were tried for their film forming property. Blank formulations were prepared by dissolving different polymers and plasticizer compositions in distilled water as shown in Table No. 1. The resulting solution was casted and dried in the oven at 45 °C for 24 h.
Based on drug-polymer compatibility studies HPMC, HPC, PVP of different grades and ratio were used for the primary selection between the polymers. Films were formed using the selected polymers as individual film formers and in combination. Grades were attributed for the best film forming polymer based on its film forming capacity, appearance, peel-ability, disintegration time and strength by personal examination [18].
Table No: 1 Initial Trials for Polymer Selection
|
Ingredients |
RDF-I-1/01 |
RDF-I-1/02 |
RDF-I-1/03 |
RDF-I-1/04 |
RDF-I-1/05 |
|
HPC EF |
60% |
- |
- |
- |
- |
|
HPC LF |
- |
60% |
- |
- |
- |
|
HPMC E 3 LV |
- |
- |
60% |
- |
- |
|
HPMC E15LV |
- |
- |
- |
60% |
- |
|
PVP |
- |
- |
- |
- |
60% |
|
PEG 400 |
10% |
10% |
10% |
10% |
10% |
|
Citric acid |
10% |
10% |
10% |
10% |
10% |
|
Aspartame |
10% |
10% |
10% |
10% |
10% |
|
Brilliant Blue |
0.03% |
0.03% |
0.03% |
0.03% |
0.03% |
|
Wild Cherry |
2.15% |
2.15% |
2.15% |
2.15% |
2.15% |
Table No: 2 Initial Trials for Polymer Selection
|
Ingredients |
RDF-I-1/06 Polymer ratio (50:50) |
RDF-I-1/07 Polymer ratio (75:25) |
RDF-I-1/08 Polymer ratio (85:15) |
|
HPMC E 3 LV |
30% |
45% |
51% |
|
HPMC E15LV |
30% |
15% |
9% |
|
PEG 400 |
10% |
10% |
10% |
|
Citric acid |
10% |
10% |
10% |
|
Aspartame |
10% |
10% |
10% |
|
Brilliant Blue |
0.03% |
0.03% |
0.03% |
|
Wild Cherry |
2.15% |
2.15% |
2.15% |
In the present investigation PEG 400, Propylene glycol and Glycerol were selected and compared. The plasticizer suitable for the polymer was selected based on folding endurance, tensile strength and percentage elongation and of the formulations.
Table No: 3 Initials Trials for Plasticizer Selection
|
Ingredients |
RDF-I-1/08 R |
RDF-I-2/01 |
RDF-I-2/02 |
|
HPMC E3: E15 (85:15) |
60% |
60% |
60% |
|
PEG 400 |
10% |
- |
- |
|
Propylene glycol |
- |
10% |
- |
|
Glycerol anhydrous |
- |
- |
10% |
|
Citric acid |
10% |
10% |
10% |
|
Aspartame |
10% |
10% |
10% |
|
Brilliant Blue |
0.03% |
0.03% |
0.03% |
|
Wild Cherry |
2.15% |
2.15% |
2.15% |
The diluents used in this investigation were selected based on extensive literature search which includes research articles. Maltodextrin, Mannitol, Xylitol were a few excipients used for preliminary trails after they were found to be compatible with the drug. The diluents were selected based on appearance of the film which includes any recrystallization and texture of the film along with-it disintegration time of the film was also measured [19].
Table No: 4 Initial trails for Diluent Selection
|
Ingredients |
RDF-I-3/01 |
RDF-I-3/02 |
RDF-I-3/03 |
|
HPMC E3: E15 (85:15) |
50% |
50% |
50% |
|
Propylene glycol |
10% |
- |
- |
|
Maltodextrin |
10% |
- |
- |
|
Mannitol |
- |
10% |
- |
|
Xylitol |
- |
- |
10% |
|
Citric acid |
10% |
10% |
10% |
|
Aspartame |
10% |
10% |
10% |
|
Colour |
0.03% |
0.03% |
0.03% |
|
Flavour |
2.15% |
2.15% |
2.15% |
In the present study all three super-disintegrants, Sodium starch glycolate (SSG), Croscarmellose sodium (CCS) and Crospovidone were used. Disintegrants were selected based on the disintegration time of the RDF and the surface feel of the formulation; since all the disintegrants are water insoluble they should not impart roughness to the RDF.
Table No: 5 Initial Trials for Disintegrant Selection
|
Ingredients |
RDF-I-3/01 |
RDF-I-3/02 |
RDF-I-3/03 |
RDF-I-3/04 |
RDF-I-3/05 |
|
HPMC E3, E15 (85:15) |
45% |
45% |
45% |
45% |
45% |
|
Propylene glycol |
10% |
- |
- |
- |
- |
|
Xylitol |
10% |
- |
- |
- |
- |
|
Sodium starch glycolate |
5% |
- |
- |
- |
- |
|
Croscarmellose sodium |
- |
5% |
- |
- |
- |
|
Crospovidone XL |
- |
- |
5% |
- |
- |
|
Crospovidone XL 10 |
- |
- |
- |
5% |
- |
|
Kollidone CLSF |
- |
- |
- |
- |
5% |
|
Citric acid |
10% |
10% |
10% |
10% |
10% |
|
Aspartame |
10% |
10% |
10% |
10% |
10% |
|
Brilliant Blue |
0.03% |
0.03% |
0.03% |
0.03% |
0.03% |
|
Wild Cherry |
2.15% |
2.15% |
2.15% |
2.15% |
2.15% |
The concentration of sweetener, citric acid and flavour was evaluated from panel testing. The formulations were tested for initial taste. If the initial taste of the formulation was found acceptable then the formulation was tested for after taste, overall acceptability and in-vivo disintegration time. Evaluation was done by panel testing volunteers, rank was given to each testing parameter and the volunteers were asked to rank the film for each of these evaluating parameters.
Table No: 6 Initial Trails for Taste Masking
|
Ingredients |
RDF-II-1/1 |
RDF-II-1/2 |
RDF-II-1/3 |
RDF-II-1/4 |
RDF-II-1/5 |
|
HPMC E3, E15 (85:15) |
45% |
45% |
45% |
45% |
45% |
|
Propylene glycol |
10% |
10% |
10% |
10% |
10% |
|
Xylitol |
10% |
10% |
5% |
5% |
15% |
|
CCS |
5% |
5% |
5% |
5% |
5% |
|
Citric acid |
10% |
5% |
10% |
15% |
5% |
|
Aspartame |
10% |
15% |
15% |
5% |
10% |
|
Brilliant Blue |
0.03% |
0.03% |
0.03% |
0.03% |
0.03% |
|
Wild Cherry |
2.15% |
2.15% |
2.15% |
2.15% |
2.15% |
Fig. 1: Blank Polymeric Film Image of Initial Trial Batch
The API and suitable excipients were finally selected for final optimization of the formulation using statistical design or Design of Experiments.
Table No: 7 List of Final Formula Selected for RDF Preparation
|
S. No |
Material |
Category |
Justification |
|
1 |
Frovatriptan Succinate |
Antimigraine drug |
API |
|
2 |
HPMC E3 & E15 |
Polymer |
Film formation |
|
3 |
Propylene glycol |
Plasticizer |
Strength, Flexibility, Penetration enhancer |
|
4 |
Xylitol |
Diluent |
Natural sweetener, increases porosity, penetration enhancer |
|
5 |
Aspartame |
Sweetener |
Taste Masking |
|
6 |
Citric acid |
Saliva stimulant |
Stimulates salivary production for dissolution of film in mouth |
|
7 |
Croscarmellose Sodium |
Super disintegrant |
Rapid disintegration & increases rate of dissolution |
|
8 |
Brilliant blue |
Colour |
Elegance |
|
9 |
Wild Cherry |
Flavour |
Mouth feel |
Preparation of drug loaded fast dissolving films
Polymeric solution (Solution A) was prepared by dissolving desired amount of polymer in sufficient quantity of distilled water (70%) under constant stirring at 600 rpm, followed by the addition of plasticizer, sweetener, citric acid, disintegrant, drug, colour and flavour. The solution was stirred for 2 hours to ensure a perfect homogeneous mixture is obtained. Specific quantity of drug dissolved in remaining water (30%) with continuous stirring (Solution B). Solution B was slowly added in polymeric solution A with continuous stirring. Final solution obtained was kept aside for 30 mins for defoaming. After defoaming, solution was poured in petri plate and dried at 45 °C in hot air oven for 24 h. Film casted in petri plate was then carefully peeled off and cut into pieces of desired shape and size. Different optimized combinations of film containing pullulan with PEG 400 were prepared and evaluated for the disintegration time, wetting time, folding endurance and drug release [20].
Fig. 2: Schematic Process for the Casting Film Containing Drug
Calculation for the amount of solution to be poured for film casting
Petri plate method
A good formulation must be manufacturable, chemically and physically stable throughout the manufacturing process and product shelf life, and bioavailable (i.e., it must contain the exact amount of API in each dose that can be readily absorbed by the human body). In addition, many quality standards and special requirements must be met to ensure the efficacy and safety of the product. All of these formulation goals can be described as the Quality target product profile (QTPP). It is important to establish the QTPP so that the formulation effort will be effective and focused. The QTPP usually includes the route of administration, dosage form and size, special-delivery requirement, maximum and minimum doses, and aspects of pharmaceutical elegance (appearance). The QTPP guides formulation scientists to establish formulation strategies and keep formulation effort focused and efficient [21].
Table No: 8 Quality Target Product Profile of RDF
|
QTPP |
|||
|
QTPP Elements |
Target |
Justification |
|
|
Dosage form |
Rapid dissolving film |
For a better conventional dosage form. |
|
|
Dosage design |
Taste masked Rapid dissolving film |
For patient compliance & palatability |
|
|
Route of administration |
Oral |
Same as RLD |
|
|
Strength |
2.5 mg |
Same as RLD |
|
|
Pharmacokinetics |
Rapid release enabling Tmax in less than 2-4 h with increased bioavailability |
Needed to ensure rapid onset and efficacy |
|
|
Drug product quality attributes |
Physical attributes |
Pharmaceutical equivalence requirement: Must meet quality standards (i.e., identity, assay, purity, and dissolution). |
|
|
Identification |
|||
|
Assay |
|||
|
Related substances |
|||
|
Uniformity of Dosage (UOD) |
|||
|
Dissolution |
|||
|
Water content |
|||
|
Stability |
Shelf life at room temperature |
Needed for commercialization |
|
|
Container-closure system |
Container closure system qualified as suitable for this drug product. |
Needed to achieve the target shelf-life and to ensure formulation integrity |
|
Initial risk assessment
Relative risk ranking
Low risk – Broadly acceptable risk. No further investigation is needed.
Medium risk – Risk is acceptable. Further investigation may be needed in order to reduce the risk.
High risk – Risk is unacceptable. Further investigation is needed to reduce the risk.
Table No: 9 Initial Risk Assessment of Drug Substance Attributes
|
Drug Product CQAs |
Taste |
Particle Size Distribution (PSD) |
Hygroscopicity |
Solubility |
Moisture Content |
|
Assay |
Low |
Low |
Low |
High |
Low |
|
Content uniformity |
Low |
Low |
Low |
High |
Low |
|
Dissolution |
Low |
Medium |
Low |
High |
Low |
|
Palatability |
High |
Low |
Low |
Medium |
Low |
|
Film formation |
Low |
Low |
Medium |
High |
Low |
|
Degradation |
Low |
Low |
High |
Low |
Medium |
Table No: 10 Initial Risk Assessment of the Formulation Variables
|
Drug Product CQAs |
Formulation variables |
|||||
|
HPMC |
Prop. Glycol |
Croscarmellose sodium |
Xylitol |
Citric acid |
Aspartame |
|
|
Film formation |
High |
Low |
High |
Low |
Low |
Low |
|
Palatability |
Low |
Low |
Low |
Medium |
High |
High |
|
Dissolution |
High |
Low |
High |
Medium |
Low |
Low |
|
Tensile strength |
High |
High |
High |
Low |
Low |
Low |
|
Degradation products |
Low |
Low |
Low |
Low |
High |
Low |
Formulation optimization study by simplex lattice mixture design
Optimization by experimental design leads to the evolution of a statistically valid model to understand the relationship between independent and dependent variables. The application of simplex lattice experimental design is well documented in pharmaceutical literature. A polynomial first order linear interactive model may be evolved using the values of dependent and independent variables.
Y= B1X1 + B2X2 + B3X3 + B12X1X2 + B23X2X3 + B13X1X3 + B123X1X2X3... Eq. No 2.3
Where Y is the response parameter and Bi………. are estimated coefficients for the factors Xi. The main effects (X1, X2 and X3) represents the average results of changing one factor at a time from its low to high value. The interaction terms (X1X2, X2X3, X1X3) show how the response changes when two or more factors are simultaneously changed. The effect of amount of HPMC E3 LV, amount of HPC LF and amount of plasticizer PEG 400 on the film properties namely film separation, in-vitro disintegration time and mechanical properties was studied using simplex lattice design. The amount of HPMC (X1), PG (X2) and CCS (X3) were chosen as independent variables. The design layout of the fourteen batches of the simplex lattice design [22, 29]. The study was to evaluate the relative proportion of polymer, plasticizer and disintegrant. Mixture design was selected and the responses studied were the In-vitro disintegration time, Tensile strength and Percentage elongation. Simplex lattice mixture design with four replicate point was performed to optimize the formulation. Below table summarise the study design.
Table No: 11 Simplex Lattice Mixture Design to Optimize the Formulation
|
Design Constraints |
||
|
Low |
≤ Constraint ≤ |
High |
|
40 |
A: HPMC |
45 |
|
5 |
B: Prop. Glycol |
10 |
|
0 |
C: Croscarmellose sodium |
5 |
|
A+B+C |
55 |
|
Fig. 3: Images of contour plots and three-dimensional response surface plots showing the effect of In-vitro disintegration time, Tensile Strength and % Elongation
Evaluation of prepared aprepitant loaded FDF
Drug excipient interaction study
Fourier transform infrared spectroscopy (FTIR). The FTIR absorption spectra of the pure drug, pullulan and their mixture were recorded in the range of 4000–400 cm−1 by KBr disc method using FTIR spectrophotometer (Spectrum GX, Perkin-Elmer, USA).
Physical appearance and surface texture
Visual inspection of the RDF was done and was evaluated based on the surface texture and elegance by feel or touch.
Weight variation
Weight variation test of the optimized formulation was carried out using a sensitive digital balance (RADWAG AS 220 lX), by weighing three films of the same size from each formulation. The standard deviations (SD) were calculated from individual weight of the film [23].
Thickness uniformity
Thickness of the film was measured using Digital vernier calliper (Mitutoyo Japan). Three readings were taken from different locations of the film and mean thickness was recorded and standard deviation was calculated from individual readings. This procedure was repeated for all 14 DOE formulations and results were recorded.
Uniformity of dosage units
The films were tested for uniformity of dosage form by UV-Spectrophotometric method. Three different RDF of the same formulation were dissolved in 100 ml of Phosphate buffer pH 6.8 medium; 2ml of this solution was diluted up to 10ml with Phosphate buffer pH 6.8 medium to give a 7.8 ppm solution. The absorbance of the solution was measured at 244nm using UV/visible spectrophotometer (Perkin Elmer lambda 20).
Assay
20 films of each formulation were taken and dissolved in a 100 ml volumetric flask with purified water as medium (Stock I). From the Stock I solution equivalent to a single dose was calculated and was diluted with 100 ml of purified water. 2ml of this solution was diluted up to 10ml with purified water its absorbance was measured at 244nm using UV/visible spectrophotometer (Perkin Elmer Lambda 20). Standard solution of the raw drug of the same concentration was used as a bracketing standard after every 10 samples. The % drug content in each formulation was calculated using standard graph. This procedure was repeated for every formulation and the assay was calculated [24, 25].
In-vitro disintegration
Each film was placed in a petri dish containing 10 ml of Phosphate buffer pH 6.8. The time taken by each film when it starts to disintegrate was recorded. Average and standard deviations from 3 RDF were measured and recorded. This procedure was repeated for each formulation and the disintegration time was recorded.
In-vivo disintegration
In-vivo disintegration time of the Rapid dissolving film was carried out in healthy volunteers (aged 25-40 years, n=6). Prior to the test the volunteers were educated with the procedure and purpose of test. They were asked to rinse their mouth with distilled water before a piece of the RDF was placed on their tongue. They were asked to monitor for the time required by the film to completely disintegrate and wash off. In-vivo disintegration times of the selected optimized batches were only carried out due to safety reasons.
In-vitro dissolution
As there was no official method prescribed for in vitro drug release studies of RDF, a suitable in-house method was used, dissolution study was carried out in USP type I (basket apparatus) with 500 ml of Phosphate buffer pH 6.8 medium. The medium was maintained at a temperature of 37±0.5oC stirred at 100 rpm. The samples were withdrawn at 2, 5, 10-, 15-, 20- and 30-min time interval. 10 ml of sample was collected at every time interval and was replaced with the same amount of medium. The samples were analysed in UV/Visible spectrophotometer (Perklin Elmer Lambda 20), bracketing standard after every 6 samples was measured which was prepared by dissolving same amount of drug in 500ml Phosphate buffer pH 6.8 medium.
Solid state form of the drug by XRD
The form of input drug and the drug in the formulation was studied with the help of X-ray diffractometer (BRUKER D8 ADVANCED). The PXRD pattern of input drug was compared with the placebo film and final formulation containing drug. The D8 advanced has an automatic recognition of optics, the software DIFRAC.DAVINCI displays the components in the beam path. The software automatically recognises if any modular component was mounted. In this case twin optics were mounted on the diffractometer. The detector LYNXEYE was mounted later on the device. The samples are packed in aluminium sample holders and the sampling assembly is kept inside the instrument. The autosampler automatically takes the sample and places it in the X-ray beam, the 2T peaks are measured and by using Bragg’s equation, the inter atomic distance in the crystal structure is determined [26]. It is important that the drug in the formulation should not recrystallize, if the drug in the formulation recrystallizes it gives a non-elegant appeal to the film.
Folding endurance
The flexibility and strength of the film was measured quantitatively in terms of what is known as folding endurance. Folding endurance of the film was determined by repeatedly folding the film at the same place till it breaks. The number of times the films can be folded at the same place, without breaking gives the value of folding endurance of the film. Folding endurance of each optimized formulation was done. Average and standard deviations from 3 RDF were measured and recorded. This procedure was repeated for each formulation and the folding endurance was recorded [27].
Tensile strength and Percentage elongation
Tensile strength and percentage elongation of the film was determined with the help of Universal Testing machine (Shimadzu UTM EZ Test), which consists of two load grips. The lower clamp is fixed and upper clamp is movable. The test film of specific size (3cm x 1cm) is fixed between these two cell grips and force was gradually applied till the film breaks. The tensile strength of the RDF was calculated by dividing the maximum force at the time of breaking of the film by the cross-section area of the RDF [28].
Tensile strength=(Max. force at breaking point)/(cross-section area of film)
Percentage elongation was calculated by dividing the difference in length of the film with the length of the film at time of breaking. It is shown as in the formula no 2.5.
% Elongation=Initial length-final lengthFinal lengthx 100
Surface morphology of the Formulation by SEM
Surface morphology of the optimized formulation was studied with the help of Scanning Electron Microscopy (LEO 400). The samples were cut and mounted on studs with the help of an adhesive tape. the samples were then coated with gold and targeted with an electron beam, the beam or electron ray when falls on the sample is reflected, these reflected beam or electron ray is then captured by a detector. based on the angle of reflection the surface image of the sample is processed to be viewed on the monitor screen [29].
RESULT AND DISCUSSION
Appearance
Rapid Dissolving Film appearance is visually observed.
λ-max of Drug in pH 6.8 Phosphate Buffer
The Frovatriptan succinate standard solution (1mg/ml) was prepared in phosphate buffer pH 6.8 and scanned using spectrophotometer (Perkin Elmer, Lambda 20). The range for scanning was 200-400nm. The UV spectrum of Frovatriptan succinate was found to have the working λmax at 244nm.
Fig. 4: UV Spectrum of Frovatriptan Succinate
Standard Curve of Frovatriptan Succinate
Accurately weighed 50 mg of Frovatriptan Succinate was dissolved in 50 ml of phosphate buffer pH 6.8 to give a solution of 1000µg/ml (Stock Solution I). A 1ml of this solution was diluted to 100 ml using phosphate buffer pH 6.8 to obtain a solution of 10µg/ml, this solution served as the stock solution II. Into a series of 10 ml volumetric flasks, aliquots of standard solution (i.e. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10ml) were added and volume made up to 10 ml using phosphate buffer pH 6.8. The absorbance of these solutions was measured against reagent blank at 244nm.
IR Spectrum of Drug
Fig. 5: IR Spectrum of Frovatriptan Succinate
Fig. 6: IR Spectrum of Drug and Polymer Taken Together
Drug-Excipient Interaction Study by DSC
Drug-Excipients interaction study was also performed by Differential scanning calorimetry (DSC Q1000). The instrument was calibrated using Indium (156C), Tin (232C) and Zinc (419.5C) as internal standards. sample of 2-10 mg were placed in aluminium pans. The probes were heated from 0 to 300 C. Samples were heated in an open pan at a rate of 10 C min -1 under nitrogen purge of 50 ml/ min. and graphically represented in Fig.7 and 8.
Fig. 7: DSC of Drug and HPMC
Fig. 8: DSC of Drug and Excipients
Selection Of Excipients for RDF
Selection of Polymer
RDF formulated using individual polymers were evaluated for their film forming property, appearance and peelability. Each effect was given a rank. The best ranking polymer/polymers were selected for further analysis.
Table No: 12 Table Indicating Ranking for Polymer Selection
|
Rank |
Effect |
|
1 |
Very good |
|
2 |
Good |
|
3 |
Acceptable |
|
4 |
Poor |
|
5 |
Worst |
Table No: 13 Initial Trial Results for Polymer Selection
|
Property tested |
RDF-I-1/01 |
RDF-I-1/02 |
RDF-I-1/03 |
RDF-I-1/04 |
RDF-I-1/05 |
|
Film forming property |
2 |
2 |
1 |
1 |
3 |
|
Appearance |
2 |
2 |
2 |
1 |
4 |
|
Peelability |
5 |
4 |
2 |
1 |
3 |
|
In-vitro disintegration time (sec) |
- |
- |
152 |
193 |
- |
RDF formed using HPC as a polymer (RDF-I-1/01 & RDF-I-1/02) though had good appearance and film forming property, were very sticky and didn’t have good peelability. These films tend to break while removing. RDF formed using HPMC (RDF-I-1/03 & RDF-I-1/04) as a polymer was found to have good film forming property and peel-ability. The film forming ability of HPMC E15 was even better than HPMC E3 and had good strength when observed under physical evaluation. But HPMC E15 films were having very high in-vitro disintegration time. RDF formed using PVP K30 (RDF-I-1/05) as a polymer didn’t have good film forming property or appearance. The RDFs were worn out at many places while peeling it off the glass plate. RDF formed using HPMC were found to have the best film forming capacity. HPMC E15 though having best film forming capacity and strength, had a high disintegration time. In order to achieve both the property i.e. good film formation with strength and less disintegration time, a combination of these two polymers can be used in various ratios. A combination of HPMC low viscosity grades polymer in various proportions are used to achieve a good film forming property with strength and less disintegration time.
Table No: 14 Result of Polymer Selection Trials
|
Property Tested |
RDF-I-1/06 |
RDF-I-1/07 |
RDF-I-1/08 |
|
Film forming property |
1 |
1 |
1 |
|
Appearance |
1 |
1 |
1 |
|
Peelability |
1 |
1 |
2 |
|
In-vitro disintegration time (sec) |
182 |
171 |
163 |
Observation: With the increase in E3 concentration in the proportion to 85% the disintegration time was reduced to 163 sec. The use of combination of polymers also improved the elegance of the film in formulation RDF-I-1/08, with a better strength.
Inference: A combination of HPMC polymers in the ratio 85:15 (RDF-I-1/08) was selected as a film forming polymer based on its least disintegration time, very good appearance and a good strength as examined physically.
Selection of Suitable Plasticize
Plasticizers improve the flexibility of the film and may also help in improving the tensile strength of the polymeric films. Here polyethylene glycol (PEG 400), propylene glycol and glycerol anhydrous were evaluated based on their ability to impart flexibility and strength to the formulation. The plasticizers were evaluated by measuring the folding endurance, tensile strength and disintegration time of the RDF formed.
Table No: 15 Result of Trials for Plasticizer Selection
|
Property tested |
RDF-I-1/08 R |
RDF-I-2/01 |
RDF-I-2/02 |
|
Folding endurance |
127 |
231 |
153 |
|
Tensile strength (N) |
5.95 |
11.57 |
8.81 |
|
Percentage elongation |
2.3% |
8.7% |
3.7% |
|
Disintegration time (sec) |
161 |
165 |
176 |
It was observed that Film formed using PEG400 (RDF-I-1/8 R) was found to have less folding endurance, tensile strength and percentage elongation than the film with propylene glycol and glycerol anhydrous. The films formed using propylene glycol (RDF-I-2/01) had better tensile strength and percentage elongation when compared with the films formed using glycerol (RDF-I-2/02), there wasn’t much difference in the disintegration time of the individual films.
The stress-strain graphs clearly indicate that the films formed using propylene glycol and glycerol had better strength and flexibility when compared to PEG 400. Among these two plasticizers, propylene glycol was found to have the best strength and flexibility. Propylene glycol as a plasticizer was selected because of its good tensile strength, and ability to impart good flexibility to the film.
Selection of A Suitable Diluent
Diluents were added to the formulation to reduce the concentration of the polymer in the film in order to achieve the required disintegration time. Maltodextrin (a film forming polymer), Sorbitol (a sugar) and Xylitol (a natural sugar) were selected as diluents for the preparation of RDF. The formed RDFs were evaluated on appearance of the formulated RDF. The diluent which recrystallizes, imparts texture or is incompatible with the drug or other excipients were excluded from this study. Since the concentration of the polymer was also reduced in these formulations, they were also tested for their in-vitro disintegration time
Table No: 16 Result of Trials for Diluent Selection
|
Property tested |
RDF-I-3/01 |
RDF-I-3/02 |
RDF-I-3/03 |
|
Recrystallization |
No |
Yes |
No |
|
Texture |
Rough |
- |
Smooth |
|
In-vitro disintegration time (sec) |
156 |
- |
137 |
Maltodextrin in the formulation (RDF-I-3/01) did not recrystallize but gave a rough texture to the film. The film also had higher disintegration time. Mannitol as a diluent in the formulation was found to recrystallize in the formulation and so no further studies were conducted on the same. Xylitol as a diluent in the formulation did not recrystallize nor gave any texture to the film. The disintegration time of the film also reduced to 137 seconds, since the concentration of the polymer was reduced. Xylitol containing films were also found to develop pores during formulation Xylitol as diluent was selected in the formulation of RDF as it did not recrystallize nor gave any texture to the formulation but helped in improving disintegration by forming pores.
Selection of A Suitable Disintegrant
Even after reducing the concentration of the polymer in the formulation of RDF the desired disintegration time of less than a min was not achieved. Super disintegrants were added to the formulation to improve the disintegration time of the RDF. Sodium starch glycolate, Croscarmellose sodium and Crospovidone were used and best possible disintegrant was selected on the basis of the time required for the formulation to disintegrate in suitable medium.
Table No: 17 Result of Trials for Disintegrant Selection
|
Formulation |
In-vitro Disintegration time (sec) |
|
RDF-I-3/01 |
63 |
|
RDF-I-3/02 |
49 |
|
RDF-I-3/03 |
Formulations took more than 12 hours in drying and so was not considered for study |
|
RDF-I-3/04 |
|
|
RDF-I-3/05 |
The film containing SSG (RDF-I-03/01) were having a little rough texture when compared to CCS and had a higher disintegration time of 63 sec. The films containing CCS (RDF-I-3/02) were having the least possible disintegration time when compared to the rest of the super disintegrants. The films containg crospovidone (RDF-I-03/03) as disintegrant were having rough texture and were brittle, so a finer grade crospovidone XL 10 (RDF-I-03/04) was used but the problem persisted. An even finer grade of crospovidone i.e. kollidone CLSF (RDF-I-03/05) when used as a super disintegrant took more than 24 hrs in drying whereas the other formulation took 3.5-4 hrs. Croscarmellose sodium as a superdisintegrant was used in the formulation of RDF, since it had the least disintegration time and had a better texture when compared to the other formulations.
Final Formula Optimization
Formulations were prepared according to the run order obtained by the software Statease design expert. The response obtained by the formulation is shown in the table 3.15
Table No: 18 DOE Batches and Their Results in Terms of Actual Values
|
Std run |
Run order |
A:HPMC |
B:Prop. Glycol |
C:CCS |
Disintegration time (sec) |
Tensile strength (N) |
% Elongation |
|
4 |
1 |
45 |
5 |
5 |
31 |
5.35 |
2.58 |
|
1 |
2 |
40 |
10 |
5 |
48 |
7.12 |
2.91 |
|
11 |
3 |
40 |
10 |
5 |
51 |
7.54 |
3.26 |
|
9 |
4 |
44.166 |
9.166 |
1.666 |
67 |
7.84 |
5.43 |
|
12 |
5 |
45 |
5 |
5 |
35 |
4.92 |
2.76 |
|
8 |
6 |
44.166 |
6.666 |
4.166 |
31 |
5.97 |
4.37 |
|
10 |
7 |
43.333 |
8.333 |
3.333 |
42 |
7.36 |
4.66 |
|
2 |
8 |
42.5 |
7.5 |
5 |
66 |
5.07 |
4.09 |
|
7 |
9 |
41.666 |
9.166 |
4.166 |
52 |
7.79 |
3.56 |
|
14 |
10 |
42.5 |
7.5 |
5 |
68 |
5.35 |
4.37 |
|
13 |
11 |
45 |
10 |
0 |
124 |
9.83 |
5.97 |
|
5 |
12 |
45 |
7.5 |
2.5 |
48 |
6.73 |
5.12 |
|
6 |
13 |
45 |
10 |
0 |
112 |
10.20 |
5.81 |
|
3 |
14 |
42.5 |
10 |
2.5 |
58 |
8.31 |
4.96 |
Disintegration time as a response
Table No: 19 ANOVA Result for Disintegration Time Response
|
ANOVA for Mixture Special Cubic Model |
|||||
|
*** Mixture Component Coding is U_Pseudo. *** |
|||||
|
Analysis of variance table [Partial sum of squares - Type III] |
|||||
|
Source |
Sum of Squares |
Mean Square |
F Value |
p-value Prob > F |
Comment |
|
Model |
9847.943 |
1641.324 |
69.39755 |
< 0.0001 |
significant |
|
Linear Mixture |
6542.62 |
3271.31 |
138.3157 |
< 0.0001 |
|
|
AB |
870.5254 |
870.5254 |
36.80707 |
0.0005 |
|
|
AC |
490.6039 |
490.6039 |
20.74344 |
0.0026 |
|
|
BC |
682.3541 |
682.3541 |
28.85092 |
0.0010 |
|
|
ABC |
147.9374 |
147.9374 |
6.255006 |
0.0409 |
|
|
Residual |
165.5572 |
23.65103 |
|||
|
Lack of Fit |
79.05724 |
26.35241 |
1.218609 |
0.4114 |
not significant |
|
Pure Error |
86.5 |
21.625 |
|
||
|
Cor Total |
10013.5 |
||||
Tensile strength as a response
The analysis of variance (ANOVA) result for Tensile strength is presented in table no 20.
Table No: 20 ANOVA Result for Tensile Strength Response
|
ANOVA for Mixture Special Cubic Model |
||||||
|
*** Mixture Component Coding is U_Pseudo. *** |
||||||
|
Analysis of variance table [Partial sum of squares - Type III] |
||||||
|
Source |
Sum of Squares |
df |
Mean Square |
F Value |
p-value Prob > F |
Comment |
|
Model |
35.1224 |
6 |
5.853733 |
37.18432 |
< 0.0001 |
significant |
|
Linear Mixture |
33.25962 |
2 |
16.62981 |
105.6366 |
< 0.0001 |
|
|
AB |
1.259292 |
1 |
1.259292 |
7.999326 |
0.0255 |
|
|
AC |
0.118113 |
1 |
0.118113 |
0.750284 |
0.4151 |
|
|
BC |
0.797967 |
1 |
0.797967 |
5.06888 |
0.0591 |
|
|
ABC |
0.675196 |
1 |
0.675196 |
4.289005 |
0.0771 |
|
|
Residual |
1.101973 |
7 |
0.157425 |
|||
|
Lack of Fit |
0.813673 |
3 |
0.271224 |
3.763086 |
0.1165 |
not significant |
|
Pure Error |
0.2883 |
4 |
0.072075 |
|||
|
Cor Total |
36.22437 |
13 |
||||
Percentage elongation as a response
The analysis of variance (ANOVA) result for Percentage elongation is presented in table No 21.
Table No: 21 ANOVA Result for Percentage Elongation Response
|
ANOVA for Mixture Quadratic Model |
||||||
|
*** Mixture Component Coding is U_Pseudo. *** |
||||||
|
Analysis of variance table [Partial sum of squares - Type III] |
||||||
|
Sum of |
Mean |
F |
p-value |
Comment |
||
|
Source |
Squares |
df |
Square |
Value |
Prob > F |
|
|
Model |
15.81714 |
5 |
3.163428 |
36.00903 |
< 0.0001 |
significant |
|
Linear Mixture |
12.98774 |
2 |
6.493868 |
73.91914 |
< 0.0001 |
|
|
AB |
2.218838 |
1 |
2.218838 |
25.25684 |
0.0010 |
|
|
AC |
0.028382 |
1 |
0.028382 |
0.323075 |
0.5854 |
|
|
BC |
0.543001 |
1 |
0.543001 |
6.180928 |
0.0377 |
|
|
Residual |
0.702808 |
8 |
0.087851 |
|||
|
Lack of Fit |
0.573358 |
4 |
0.143339 |
4.429183 |
0.0893 |
not significant |
|
Pure Error |
0.12945 |
4 |
0.032363 |
|||
|
Cor Total |
16.51995 |
13 |
||||
3.3.4 Numerical optimization
The formulation were optimized based on the Disintegration time, tensile strength and percentage elongation as response, for this purpose first goal has been set as shown in table No 22.
Table No: 22 Goal and Limits of Responses for Numerical Optimization
|
Name |
Goal |
Lower Limit |
Upper Limit |
Importance |
|
HPMC |
is in range |
40 |
45 |
3 |
|
Prop. glycol |
is in range |
5 |
10 |
3 |
|
CCS |
is in range |
0 |
5 |
3 |
|
Disintegration time (sec) |
minimize |
31 |
60 |
3 |
|
Tensile strength (N) |
maximize |
5.7 |
10.2 |
3 |
|
Percentage elongation (%) |
maximize |
3 |
5.97 |
3 |
Design space: The DOE models were used to establish acceptable range for formulation variables. Figure shows overly plot of all responses. The yellow zone indicates that all of the responses were achieved. At any point in the given area, the response obtained will be within the optimized range. This plot is also called as the design space. The formulator can play within the design space and choose the formulations accordingly to get the optimized result.
Fig. 12: Overlay Plot of the Design Displaying Design Space after Numerical Optimization
EVALUATION OF RAPID DISSOLVING FILM
Appearance
The prepared RDF appeared translucent, confirming the uniformity of drug and polymer.
Tensile strength
Fig. 13: Tensile strength of different formulations
Weight variation
The weights of the Optimized Formulations was found to show good uniformity indicating a uniform distribution of the excipients in the polymer.
Fig. 14: Weight Variation of different formulations
Thickness uniformity
The thickness of the optimized formulations were in the range of 0.08±0.01 mm. This means that the RDF had good uniformity in thickness.
Fig. 15: Thickness of different formulations
Uniformity of dosage units (UOD)
The films were tested for uniformity of dosage form by UV-Spectrophotometric method. The Uniformity of the dosage units were found within limits of 5% RSD.
Fig. 16: UOD of different formulations
Assay
Assay of the optimized formulation was done by dissolving 20 dose equivalent films in purified water and collecting solution equivalent to 1 film dose. This was diluted to a suitable degree before recording the absorbance at 244nm. The quantity of drug in all the optimized formulations were within the range of 95-105%.
Fig. 17 Assy of different formulations
In-vitro disintegration time
There is no official guidance available for the procedure to evaluate the disintegration time of the oral film, nor the disintegration time limit.
Fig. 18: Weight Variation of different formulations
Fig. 19: In-vitro disintegration time
In-vitro dissolution
The drug release studies showed that the rapid dissolving films, dissolved to release at least more than 90% of the drug in fist 5 min.
Fig. 20: In vitro release studies of formulations
Fig. 21: In vitro release studies of formulations
Fig. 22: In vitro release studies of formulations
Fig. 23: In vitro release studies of formulations
Fig. 24: In vitro release studies of formulations
Folding endurance
The number of times the films can be folded at the same place, without breaking gives the value of folding endurance of the film.
Fig. 25: Folding Endurance of different formulations
Surface morphology of the Formulation by SEM
Scanning electron microscopy of the RDF at 500x magnification showed smooth surface with little pores and without any scratches or transverse striations. This shows that the films formed were having good smooth surface and were easily peeled off due to the absence of any striations.
Fig. 26: SEM Image of RDF at 500x Magnification
Drug and RDFs morphology study by P-XRD
Morphology of the drug in the RDF was studied by X ray diffraction technique. Bruker AXS D8 advanced diffractometer was used for the study. The drug, final optimized formulation and placebo of the final optimized formulation were taken for the study. The form of standard reference drug and the input drug in the formulation was studied with the help of X-ray diffractometer (BRUKER D8 ADVANCED). The PXRD pattern of input drug was compared with the standard reference drug. The D8 advanced has an automatic recognition of optics, the software DIFRAC.DAVINCI displays the components in the beam path. The autosampler automatically takes the sample and places it in the X-ray beam, the 2T peaks are measured and by using Bragg’s equation, the inter atomic distance in the crystal structure is determined.
Lambda=2d sinθ
Fig. 27: P-XRD of the Reference Standard Drug
Fig. 28: P-XRD of Input Drug used for Formulation
Fig. 29: P-XRD Comparison of Reference Standard and Input Drug
Table No: 23 Theta Peak Comparisons of Reference Drug and Input Drug
|
Compound |
Characteristic 2T peaks |
|
Reference standard |
7.835, 15.767, 16.620, 17.453 |
|
Input drug |
8.099, 16.033, 16.897, 17.734 |
Fig. 30: P-XRD Result of Optimized Formulation
The P-XRD studies of the the final optimized formulation and its placebo film did not show any 2T peaks, meaning the drug in the formulation had not recrystallized and is in amorphous form.
Stability Studies
Stability study of optimized batch was carried out at accelerated condition and was found to be stable with no colour change when packed and sealed in aluminium foil, for 4 weeks.
Table No: 24 Result of Accelerated Stability Studies
|
Storage condition |
Duration |
Type |
Colour change |
Assay |
In-vitro disintegration time (sec) |
|
40±2oC, 75±5%RH |
2 weeks |
Open |
Yes |
95.41±0.67 |
35±0.34 |
|
40±2oC, 75±5%RH |
2 weeks |
Closed |
No |
98.87±2.64 |
31±0.5 |
|
40±2oC, 75±5%RH |
4 weeks |
Open |
Yes |
94.79±0.94 |
37±0.73 |
|
40±2oC, 75±5%RH |
4 weeks |
Closed |
No |
97.62±1.93 |
33±1.5 |
Challenges And Limitations
While QbD and DoE have been increasingly adopted in Rapid dissolving films formulation, several practical limitations remain, particularly when considering their broader implementation in real-world and industrial settings. A common challenge is the variability in the design. Some reported studies utilize relatively simple optimization designs, which may not fully account for complex interactions between formulation components. Furthermore, inconsistencies in experimental conditions, such as emulsification techniques, dilution ratios, or digestion models, can hinder reproducibility and make it challenging to draw generalized conclusions across studies. Although the QbD framework emphasizes the definition of a design space and the identification of CPPs, many studies predominantly focus on formulation-related variables, such as the polymer and plasticizer ratios, disintegrant, and natural sweetener and diluent. Modifications are essential to ensure process reproducibility and product robustness at larger production scales. The lack of such considerations in early-stage studies highlights a significant gap in translating QbD-optimized RDFs formulations from the laboratory to industrial settings.
CONCLUSION
The successful development of RDFs is a complex process due to the intricate interrelationships among its key components (Polymer, plasticizer, disintegrant and sweetener and diluent), which significantly influence formulation stability. By integrating DoE, QbD facilitates the quantitative evaluation formulating ingredients and their impact on CQAs. This approach enables the optimization of component ratios in RDFs, reduces variability, and enhances overall product robustness. The application of DoE, such as simplex lattice mixture design, response surface methodology, and factorial design, not only deepens process understanding but also supports the development of RDFs with improved disintegration time, tensile strength, and percentage elongation. By integrating molecular simulations with machine learning, this approach enables rational and efficient optimization of formulations through the identification of stable and effective component combinations. It can be concluded from the above study that Rapid dissolving films of Frovatriptan succinate can be formulated using simplex lattice mixture design of statease design expert software. The solvent casting method was used to prepare the optimized batch (OB) using the concentrations of Polymer, Plasticizer and Disintegrant as 43.33, 8.33 and 3.33 respectively. OB had in- vitro disintegration time of 42sec, tensile strength of 7.36 MPa and percentage elongation of 4.66%.
Author’s Contributions
Ajeet Kumar: Conceptualized the project, data collection, developed the methodology, and drafted the manuscript. Dr. K. Saravanan: Reviewed the manuscript, and provided supervision.
Conflict Of Interest
We explicitly state that there is no conflict of interest.
Funding
None
ACKNOWLEDGEMENTS
The author is highly thankful to the Chairman, Department of Pharmaceutical Sciences, for providing necessary facilities.
Abbreviations
The following abbreviations are used in this manuscript:
AI-Artificial Intelligence
API-Active Pharmaceutical Ingredient
AUC-Area Under the Curve
CMA-Critical Material Attributes
DoE-Design of Experiment
QbD-Quality by Design
QTPP-Quality Target Product Profile
RAM-Risk Assessment Matrix
REM-Risk Estimation Matrix
RDFs-Rapid dissolving films
REFERENCES
Ajeet Kumar*, Dr. K. Saravanan, Using the Quality by Design (QBD) Approach to Optimize Formulation for Rapid Migraine Relief, Int. J. of Pharm. Sci., 2025, Vol 3, Issue 9, 1239-1274 https://doi.org/10.5281/zenodo.17103629
10.5281/zenodo.17103629