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Technical Review Article | Open Access | Published 2 July 2026
Formulation, Optimization, and Predictive Modelling of Naratriptan Hydrochloride Dry Powder Inhaler for Enhanced Pulmonary Delivery in Migraine Management
Dr. Milind Thosar *(a) , Madhav Zinzuvadiya(b), Ajay Savaniya (a) | EJPPS | 3102 (2026) | https://doi.org/10.37521/ejpps31205
Abstract
Naratriptan Hydrochloride, a selective 5-HT1B/1D receptor agonist, is clinically used for the acute treatment of migraines. Despite its effectiveness, conventional oral administration suffers from delayed onset, gastric stasis during migraine attacks, and extensive first-pass metabolism. To overcome these drawbacks, a dry powder inhaler (DPI) formulation was developed to achieve rapid systemic drug delivery through pulmonary absorption. The DPI formulation was optimized using Box-Behnken Design (BBD) with Inhalac 230, Inhalac 400, and magnesium stearate as formulation variables. Preformulation studies such as FTIR and XRD confirmed drug purity, crystallinity, and compatibility with excipients. The optimized batch displayed excellent flowability (angle of repose: 31.25°), high fine particle fraction (FPF: 35.90%), and satisfactory in-vitro drug release (67.25%). Scanning Electron Microscopy (SEM) confirmed uniform morphology and efficient drug-carrier adhesion. In-vitro diffusion using Franz diffusion cells and ex-vivo permeation studies using goat lung tissue demonstrated improved drug permeability and sustained release behaviour. A Multiple Linear Regression (MLR) model was established using formulation and physicochemical descriptors to predict lung deposition (%FPF), yielding a predictive R² value of 0.74. The model highlighted significant variables influencing aerosol performance, such as MMAD, GSD, and carrier size. This study successfully presents the first DPI formulation of Naratriptan HCl, addressing the unmet need for non-oral, rapid-acting migraine therapies. It demonstrates enhanced drug delivery, improved patient compliance, and potential for early intervention during migraine episodes. The combined experimental and modelling approach supports the feasibility of Naratriptan DPI for clinical translation.
Keywords: Naratriptan Hydrochloride, Dry Powder Inhaler, Pulmonary Drug Delivery, Migraine, Box-Behnken Design, Fine Particle Fraction, Lung Deposition, Multiple Linear Regression
Introduction
Pulmonary drug delivery is an advanced therapeutic approach that enables direct administration of drugs into the lungs via inhalation. This route offers several advantages, including rapid onset of action, avoidance of first-pass hepatic metabolism, and improved bioavailability, owing to the lungs’ large surface area (~70–100 m²), thin epithelial lining, and extensive vascularization.¹ Pulmonary drug delivery is especially beneficial for respiratory disorders such as asthma and Chronic Obstructive Pulmonary Disease(COPD), and has gained traction in the systemic delivery of medications including peptides, proteins, and small molecules through devices like dry powder inhalers (DPIs), metered-dose inhalers (MDIs), and nebulizers.
Naratriptan hydrochloride is a selective 5-HT1B/1D receptor agonist used for the acute treatment of migraine. It is a synthetic tryptamine derivative with good lipophilicity and moderate oral bioavailability (~63%). While oral tablets are the conventional form, they face limitations including delayed onset (peak plasma concentration in 2–3 hours), reduced absorption due to gastric stasis during migraine episodes, and first-pass metabolism that may compromise therapeutic efficacy. ² These limitations make Naratriptan a promising candidate for non-oral delivery routes such as pulmonary inhalation.
Various studies have explored novel formulations of Naratriptan, including orodispersible tablets, lyophilized fast-dissolving tablets, intranasal mucoadhesive gels, and sublingual routes to overcome the drawbacks of conventional oral delivery.³ Researchers have explored fast-dissolving films, orally disintegrating tablets (ODTs) prepared by direct compression, lyophilization, and sublimation techniques, as well as taste-masked ODTs and intranasal mucoadhesive in situ gels ⁹. These formulations aimed to offer faster onset and improved patient acceptability. However, despite these advancements, there was a notable absence of any dry powder inhaler (DPI) formulation of Naratriptan HCl in the market or literature prior to the present work. However, no dry powder inhaler (DPI) formulation for Naratriptan has yet been developed, representing a clear research gap.
The aim of formulating Naratriptan HCl as a DPI is to achieve faster systemic absorption and improved patient compliance by providing a needle-free, propellant-free, and self-administered dosage form.⁴ The DPI formulation can offer rapid drug action, essential for early intervention in acute migraine attacks, especially when nausea or vomiting impairs the effectiveness of oral medications. This approach also addresses the need for better pharmacokinetic consistency and minimizes systemic side effects by reducing required dosage.
2. Materials and Methods
2.1 Materials
Naratriptan HCl was gifted from Emcure Pharmaceuticals, Ahmedabad, and used as the active pharmaceutical ingredient. Inhalation-grade lactose carriers including Inhalac 70, Inhalac 120, Inhalac 230, and Inhalac 400 were obtained from Meggle Pharma, India. Formulac 200 MgRa and Formulac 450M, used as additional lactose-based carriers, were supplied by Lactose India Limited, Baroda. Magnesium stearate (MgSt), used as a lubricant, was purchased from LOBA CHEMIE PVT. LTD. All materials used were of pharmaceutical or analytical grade and were utilized without further purification.
2.2 Methods
2.2.1 Micronization for Dry Powder Inhaler of Naratriptan Hydrochloride
Naratriptan Hcl DPI was formulated by blending micronized Naratriptan with inhalation-grade lactose monohydrate, which serves as a carrier to enhance flow properties and facilitate uniform drug dispersion.⁵ The drug was micronized by media milling (mechanical size reduction) using top-down size reduction, where extremely hard zirconia beads (zirconium oxide) used to physically crush drug Naratriptan HCl into micro sized particles to achieve a particle size of 1–5 µm , suitable for pulmonary delivery. Accurate amounts of drug and carrier were mixed using geometric dilution followed by blending in a low-shear mixer for uniformity. The blend was evaluated for flow properties, particle size, and drug content uniformity. The optimized mixture was filled into size 3 or 4 hard gelatin capsules using a capsule-filling machine. The filled capsules were tested for aerosolization performance using a compatible DPI device and characterized by in-vitro deposition studies using a cascade impactor to determine parameters like fine particle fraction (FPF) and mass median aerodynamic diameter (MMAD).⁶ Stability studies were conducted as per ICH guidelines to ensure formulation integrity over time
2.2.2 Drug-Excipient compatibility study using FT-IR
In the development of pharmaceutical formulations, drug-excipient compatibility is a crucial aspect that must be thoroughly investigated to ensure the stability, safety, and efficacy of the final product. The FTIR spectra of pure drug and excipients are obtained to determine which functional groupings the sample contains.¹⁰ To determine whether Naratriptan HCl was compatible with the coarse and fine Carrier and glidant used in the formulation, a physical mixture of the Drug, Lactose Monohydrate and Magnesium Stearate was prepared in a 1:1:1 ratio and analysed using Fourier-transform infrared (FTIR) spectroscopy. The FTIR spectra of the physical mixture were obtained using an IR Tracer spectrometer manufactured by Shimadzu in Japan. The spectra were recorded over a wavelength range of 4000-400 cm-1 with a resolution of 4 cm-1. The FTIR spectra of the physical mixture were compared to those of the pure drug, carrier and glidant to identify any changes in the spectral characteristics that could indicate drug-excipient incompatibility. The presence or absence of characteristic absorption bands corresponding to the functional groups in the drug, Carrier, glidant were also analysed to assess the compatibility of the components.
The spectra of drug-excipient were then compared to identify any shifts, disappearance or broadening of the peak. Any observed changes in the spectral characteristics could indicate drug-excipient incompatibility, which could have significant implications for the safety and efficacy of the final product.
2.2.3 Preliminary studies of conventional dry powder inhaler formulation
Preliminary studies were carried out to select suitable carrier materials and processing conditions for the development of a Naratriptan Hydrochloride Dry Powder Inhaler (DPI). Different grades of lactose carriers, namely Inhalac® 70, Inhalac® 120, Inhalac® 230, and Inhalac® 400, were evaluated for their applicability in DPI formulations. Naratriptan HCl was micronized by trituration to obtain particles within the respirable size range required for pulmonary delivery. Particle size analysis was subsequently performed using a laser diffraction particle size analyser. Drug–excipient compatibility studies were conducted using Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction (XRD) analysis to assess possible interactions between Naratriptan HCl and the selected excipients. Magnesium stearate was incorporated as a glidant to improve powder flow characteristics and aerosolization performance. Trial formulations were prepared by blending micronized drug with different carrier combinations and glidant concentrations ⁷. The prepared blends were evaluated for powder flow properties, content uniformity, and aerosolization behaviour. The findings obtained from these preliminary investigations were utilized to identify critical formulation variables and establish suitable factor ranges for further optimization using the Box–Behnken Design (BBD).
2.2.4 Optimization of the dry powder inhaler formulation
Box Behnken Design (BBD)
A Box–Behnken Design (BBD) was employed to optimize the formulation variables affecting the performance of the Naratriptan HCl dry powder inhaler. Three independent variables were selected: Inhalac® 230 (85–90%), Inhalac® 400 (10–15%), and magnesium stearate (0.5–1.5%). Table 1(a) and (b) represents experimental independent variables and dependent variables respectively where were evaluated at low (−1) and high (+1) levels to study their individual and interactive effects on formulation performance. The critical quality attributes selected as dependent variables were in-vitro drug release and Fine particle fraction (%FPF). Both responses were targeted for maximization to achieve enhanced drug release and improved pulmonary deposition ²². The selected factor ranges were established based on preliminary studies and their suitability for DPI formulation development. ¹¹
Table 1 (a) and (b): Constraints for BBD
(a) Independent Variables
(b) Dependant Variables
2.2.5 Characterization
The DPI formulations were characterized for the following physico-chemical properties.
Angle of repose, Compressibility index, Content Uniformity
The flow properties of the dry powder formulations were assessed using angle of repose and compressibility index methods. The angle of repose was determined by allowing the powder to flow through a funnel fixed at a height of 2 cm onto a flat surface. The height (h) and radius (r) of the resulting conical pile were measured, and the angle was calculated using the formula:
θ=tan−1(h/r)
The compressibility index (CI) was evaluated as per USP (2001) guidelines. The initial bulk volume (Vo) and final tapped volume (Vf) after 500 taps were measured, and CI was calculated using:
CI=(Vo−Vf)/ Vo×100
These parameters indicate the flowability and packing behavior of the powder.
Content uniformity
Content uniformity was assessed using UV spectrophotometry (Shimadzu 1900, Kyoto, Japan) at 283 nm with methanol AR as solvent. The analysis was performed for both prepared and marketed formulations. All formulations showed acceptable drug content within ±10% of the theoretical value, with an average NAR recovery of approximately 94%. The % coefficient of variation was influenced by the formulation components and mixing sequence.
Particle size determination
Particle sizes of DPI formulations, particle sizes of DPI and the mass median aerodynamic diameter of DPI formulations were determined.
Particle sizes distributions of liposomal dry powders were measured using laser diffraction particle size analyser (Malvern Master Sizer-2000). The size analysis was carried out by dry powder dispersing method at a pressure of 2 bars and feed rate of 70%. Each measurement was performed in triplicate.¹³ The size distributions were expressed in terms of the volume mean diameter (VMD) and the diameters below which 10% and 90% by volume of the particles in the powder resided. The mean liposomal dry powder size is summarized
The theoretical mean aerodynamic diameter (MAD) was determined by the following formula (Gonda, 1991):
daer (MAD) = Vp x d (VMD)
where, p is tapped density m units of g/cm3and d is volume mean diameter in micron.
SEM photomicrographs
Scanning electron microscopy of the representative LDPI formulation was carried using
Environmental SEM, (Philips XL30), The Netherlands ¹⁴
Residual water content and moisture sorption determination
The residual water content of prepared DPI formulations was determined by Karl-Fischer titration (Van Winden et al, 1997). Commercially available pyridine free reagent was used analysis. The reagent was standardized with addition and determination of known quantity of water (250mg). Firstly, 40ml of methanol was added into the titration vessel and titrated with the reagent to determine the amount of water present in the samples. The water content determined for the DPI and its formulations are recorded. ¹⁵ The moisture sorption attributes of the formulation was carried out by finding the moisture uptake at different relative humidity at fixed time interval.
In-Vitro Lung Deposition Study:
The American and European Pharmacopoeias have explained methods based on inertial impaction to assess the in vitro inhalation performance of formulations by determination of the fine particles
Mass median aerodynamic diameter (MMAD)
Mass median diameter of an aerosol means the particle diameter that has 50% of the aerosol mass residing above and 50% of its mass below it. The concept of aerodynamic diameter is central to any aerosol measurements and respiratory drug unit density that has the same settling velocity as the particle of interest regardless of delivery. The aerodynamic diameter relates the particle to the diameter of a sphere of its shape or density. ¹⁷. The mass-mean aerodynamic diameter (MMAD) is read from the cumulative distribution curve at the 50% point. The theoretical mass-mean aerodynamic diameter (daero) was determined from the geometric particle size and tap density using the following relationship
daero =dgeo((p/pref)^0.5/y) (4)
Where dgeo=geometric diameter, y=shape factor (for a spherical particle, y=1), p=particle bulk density and pref=water mass density (1 g/cm³). Tapped density measurements underestimate particle bulk densities since the volume of particles measured includes the interstitial space between the particles. The true. particle density, and the aerodynamic diameter of a given powder, is expected to be slightly larger than reported.
Geometric standard deviation (GSD)
The degree of dispersity is an important consideration for both quality and efficacy of pharmaceutical aerosols The nature of the aerosol distribution must be established accurately if its implications for deposition and efficacy are to be understood. The degree of dispersion in a lognormally distributed aerosol is characterized by the geometric standard deviation (GSD). A larger GSD implies a longer large particle size tail in the distribution GSD for a well-functioning stage should ideally be less than 1.2 (the GSD for an ideal size fractionors would be 1.0 and indicates a monodisperse aerosol) GSD is a measure of the variability of the particle diameters within the aerosol and is calculated from the ratio of the particle diameter at the 84.1% point on the cumulative distribution curve to the MMAD. For a log-normal distribution, the GSD is the same for the number, surface area or mass distributions The GSD was determined as where sizes X and Y are particle sizes for which the line crosses the 84% and 16% mark, respectively). Mostly, particle size distributions are log-normal, for which type of distributions the geometric mean diameter (GMD) and GSD are frequently used as the characteristic parameters.
Fine Particle Dose (FPD) and fine particle fraction (FPF)
The aerodynamic evaluation methods of fine particles permit the determination of the fine particle dose (FPD), which corresponds to the mass of drug particles that have an aerodynamic diameter less than 5 um. Such particles can theoretically be deposited in the deep lung after inhalation. ¹⁸ The fine-particle fraction (FPF), which is the percentage of the The Role of FPD usually related to either the nominal dose (total drug mass contained in the device) or the recovered drug (sum of the drug collected in the device and in the different parts of the impingers or impactors after inhalation ¹⁶
Emitted dose
FPF can be calculated from emitted dose instead of total or recovered dose of drug from impingers or impactors. The ability of the powder to be fluidised by the airflow through an inhaler is usually indicated by the emission dose, whilst the FPD and FPF measure the capability of the formulation to be fluidised ¹⁶. The inhaler body, capsule shells & mouthpiece were washed with methanol, and the same procedure was followed for throat, upper & lower stages of the twin stage impinger. ¹⁹ All samples obtained were analysed for concentration of Naratriptan using UV Spectrophotometrically as described above. FPD is a quantity of drug (um) per capsule that deposited in the lower stage of ACI shown in Figure 1 (cut-off diameter, 6.4 um).
In Vitro drug diffusion studies
In vitro diffusion studies were carried out using a vertical Franz diffusion cell system shown in Figure 2. A dialysis membrane (250-9U, MWCO: 12,000 Da; Sigma, Hyderabad, India) of 200 µm thickness, pH range 5.8–8.0, breaking strength 2.75 kgf/cm², and porosity 0.45 µm was used as an artificial membrane due to its simplicity, uniformity, and reproducibility.²⁰ Before the experiment, the membrane was pretreated by soaking in 95% ethanol, followed by hydration in phosphate-buffered saline (PBS, pH 7.4) containing 1 mM EDTA for 24 hours.
The diffusion system consisted of a hollow glass tube (inner diameter 18 mm, length 6 cm), serving as the donor compartment, with the membrane affixed to one end using a nylon string. This assembly was placed flush onto a 100 mL beaker containing PBS (pH 7.4) as the receptor medium. The receptor solution was stirred at 100 rpm with a magnetic stirrer and maintained at 37 ± 0.5°C using a surrounding water bath. The donor compartment was simultaneously stirred at 50 rpm using a Teflon-coated triple-blade stirrer.
The study was conducted using plain drug (NAR) and DPI formulations (equivalent to 15 doses; 1000 µg × 15). Each was dissolved in 1 mL PBS and added to the donor compartment. At predetermined time intervals, 1 mL aliquots were withdrawn from the receptor compartment and replaced with an equal volume of fresh PBS. All experiments were performed in triplicate over two consecutive days. The mean values and standard error of the mean (SEM) were calculated.
Ex-vivo Lung permeation study
A harvested goat Lung Tissue was kept at -20°C until it was required for Naratriptan HCl Dry Powder Inhaler permeation research. A Franz diffusion cell with a 20 ml receptor chamber was used for the evaluation. The receptor compartment was filled with PBS 7.4 pH buffer for this experiment. And a circular water bath was used to keep the receptor’s compartment temperature at 37°C. The Lung Tissue sample has been thawed at room temperature before the to the permeation experiment. The Lung skin sample was kept on the soft sponge pad for 30 minutes while PBS 7.4 was used to impregnant the Lung tissue. This was done to achieve equilibrium. Lung tissue was place between donor and receiver chamber of Franz diffusion cell as shown in Figure 3(a) and drug formulation was sprayed in donor chamber over tissue surface Figure 3(b). Using Franz diffusion cells, the penetration of drugs through excised goat Lung tissue was investigated for 30 min and percentage drug permeated across Lung skin was calculated. To maintain the sink condition at 37°C, magnetic stirrer was used and magnetic stirring bar was put in receiver chamber of Franz diffusion cell to ensure that the receptor media was evenly mixed. ²¹ The DPI preparation was sprinkled to the donor compartment membrane in a quantity equal to 50 mg. At specific time intervals (0, 2,4,6,8,10,15,20,25, and 30), 1 millilitre aliquots were taken out of the receptor chamber's sampling arm. In the receptor compartment, fresh diffusion media should be added at the same time. These samples were then subjected to UV spectrophotometric analysis at a wavelength of 270 nm to determine the drug concentration. Flux and apparent permeability were calculated using following equations.
Flux (Jss) = Qt / t x S (5)
Where,
Qt/S is the cumulative drug permeation per unit of surface area (μg/ cm2), t is time expressed in h
Permeability (P)= Jss / Cd (6)
Where, Jss is steady state Flux and Cd is the concentration of drug in donor compartment
The permeation enhancement ratio (PER) was calculated from DPI using following equation:
PER = 𝐽𝑠𝑠 (𝑡𝑒𝑠𝑡)𝐽𝑠𝑠 (𝑐𝑜𝑛𝑡𝑟𝑜𝑙) (7)
Where,
Jss (test) = flux obtained from DPI
Jss (control) = flux obtained from drug solution
Lung Deposition Prediction by Multiple Linear Regression (MLR) Model
To develop a reliable predictive model for lung deposition, a set of thirteen physicochemical, pharmacokinetic, and aerosol performance descriptors were initially selected based on their reported influence on pulmonary drug delivery. These descriptors included molecular weight, half-life, solubility, log P, pKa, oral bioavailability, fine particle fraction (%FPA), particle size, mass median aerodynamic diameter (MMAD), geometric standard deviation (GSD), size of fine carrier, size of coarse carrier, and dose. The selected variables collectively represent critical factors governing drug dissolution, absorption, aerosolization efficiency, particle transport, and pulmonary deposition. Multiple Linear Regression (MLR) was employed to establish a mathematical relationship between these descriptors and the percentage of lung deposition. The general MLR model can be represented as:
Lung Deposition (%)= β0+β1(MW)+β2(Half-life) +β3(Solubility)+⋯+βn(Dose)
where β₀ is the intercept, β₁–βₙ are regression coefficients, X₁–Xₙ are independent descriptors, and ε represents the residual error. To improve model accuracy and minimize overfitting, a descriptor optimization strategy based on one-at-a-time variable elimination was implemented. In each iteration, a single descriptor was removed while retaining all remaining variables, and the model was rebuilt using the training dataset.
Figure 4 flow chart describes the overall scheme of the MLR model for Lung deposition prediction. The performance of each refined model was assessed using statistical parameters such as coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE). Descriptors whose removal resulted in improved model performance were considered less influential and excluded from subsequent model development. Conversely, descriptors that significantly contributed to prediction accuracy were retained in the final model. This systematic optimization process enabled identification of the most relevant variables influencing lung deposition and resulted in a robust MLR model with enhanced predictive capability. The optimized model can subsequently be used as a computational tool to estimate pulmonary deposition behaviour of DPI formulations based on their physicochemical and aerodynamic characteristics, thereby reducing experimental workload and accelerating formulation development.
3. Results and Discussion
3.1 Particle size distribution
The particle size reduction study demonstrated a progressive decrease in the size of Naratriptan hydrochloride particles with increasing trituration time showed in Table 2. The initial particle size of 908.13 μm was reduced to 4.15 μm after 180 minutes of trituration, indicating successful micronization of the drug. The most significant reduction was observed between 120 and 180 minutes, suggesting that prolonged trituration effectively disrupted particle aggregates and produced particles within the respirable size range required for pulmonary delivery.
Table 2: Particle size reduction with time
No | Time(min) | Size(μm) |
1 | 0 | 908.13 |
2 | 30 | 858.36 |
3 | 60 | 667.54 |
4 | 90 | 351.58 |
5 | 120 | 281.52 |
6 | 150 | 7.31 |
7 | 180 | 4.15 |
Particle sizes between 1–5 μm are generally considered optimal for deep lung deposition because they can bypass the upper respiratory tract and reach the alveolar region. Therefore, the final particle size achieved in this study is expected to facilitate efficient pulmonary delivery and rapid systemic absorption of Naratriptan HCl ⁸.
Based on the Mesmerizer report Figure 5, the particle size analysis confirmed successful micronization of Naratriptan HCl into the respirable range suitable for pulmonary delivery. The measured particle size distribution showed a median diameter (d (0.5)) of 2.743 μm, while 90% of the particles were below 4.15 μm, indicating a narrow and uniform particle size distribution. The volume-weighted mean diameter (D [4,3]) was 2.630 μm, which is within the optimal range for deep lung deposition. Furthermore, the low span value (1.149) and uniformity index (0.364) suggest good homogeneity of the powder system. These findings demonstrate that the micronization process produced particles with appropriate aerodynamic characteristics for efficient pulmonary drug delivery and enhanced lung deposition
3.2 FT-IR Drug-Excipient interference study
The FTIR spectrum of pure Naratriptan HCl exhibited characteristic absorption peaks corresponding to its functional groups Figure 6. The spectrum showed in Figure 7 and was obtained from the physical mixture containing Naratriptan HCl, lactose monohydrate, and magnesium stearate retained all major characteristic peaks without significant shifting, disappearance, or broadening.
The absence of significant spectral changes indicates that no chemical interaction occurred between the drug and excipients during formulation development. This finding confirms the compatibility of Naratriptan HCl with lactose carriers and magnesium stearate, suggesting that the selected excipients are unlikely to adversely affect drug stability or therapeutic performance.
3.3 XRD Drug-Excipient interference study
The X-ray diffraction pattern of pure Naratriptan HCl exhibited sharp and intense diffraction peaks characteristic of a crystalline material presented in Figure 8. The XRD pattern of the physical mixture showed retention of the major crystalline peaks of the drug, although minor variations in peak intensity were observed due to dilution by excipients appropriately evident from Figure 9.
The preservation of characteristic diffraction peaks confirms that the crystalline structure of Naratriptan HCl remained unchanged following blending with lactose carriers and magnesium stearate. These findings indicate the absence of drug–excipient incompatibility and demonstrate that the formulation process did not induce significant polymorphic transformation or amorphization.
3.4 Preliminary studies and optimization by BBD results and discussion
Inhalac 70 and Inhalac 120 were procured and evaluated during preliminary carrier screening. Based on flowability and aerosolization characteristics, they were not selected for further optimization studies. Further Inhalac 230 and Inhalac 400 showed good flow properties and aerosolization features appropriate for formulating dry powder for inhalation.
Table 3. Box–Behnken Design for Optimization study of Naratriptan HCl Dry powder for Inhalation
STD | RUN | Inhalac 230(%) | Inhalac 400(%) | MgSt(%) | IDR(%) | %FPF |
1 | 3 | 85 | 10 | 1 | 52.27 | 29.22 |
2 | 4 | 90 | 10 | 1 | 69.07 | 30.95 |
3 | 11 | 85 | 15 | 1 | 57.2 | 30.63 |
4 | 6 | 90 | 15 | 1 | 46.57 | 31.17 |
5 | 5 | 85 | 12.5 | 0.5 | 51.13 | 30.04 |
6 | 7 | 90 | 12.5 | 0.5 | 62.82 | 30.95 |
7 | 9 | 85 | 12.5 | 1.5 | 58.65 | 29.94 |
8 | 1 | 90 | 12.5 | 1.5 | 52.81 | 31.54 |
9 | 82 | 87.5 | 10 | 0.5 | 56.63 | 30.18 |
10 | 10 | 87.5 | 15 | 0.5 | 55.32 | 30.6 |
11 | 12 | 87.5 | 10 | 1.5 | 63.01 | 30.35 |
12 | 2 | 87.5 | 15 | 1.5 | 48.45 | 31.05 |
The Box–Behnken Design presented in Table 3 was employed to evaluate the influence of Inhalac 230, Inhalac 400, and magnesium stearate concentrations on in-vitro drug release and fine particle fraction. Experimental results demonstrated that both responses were strongly influenced by carrier composition and glidant concentration.
Among the evaluated formulations, the percentage FPF ranged from approximately 29.22% to 31.54%, while in-vitro drug release varied from 46.57% to 69.07%. These variations demonstrate the critical influence of formulation variables on aerosolization performance. The combination of coarse and fine lactose carriers created a balance between drug adhesion and detachment forces, while magnesium stearate improved powder flow and reduced interparticle cohesion ⁷,²³. The results confirmed that optimization of carrier composition is essential for achieving efficient pulmonary delivery and maximizing respirable drug fraction.
3.4.1 Response Surface for %FPF:
The response surface plot Figure 10 illustrates the combined effect of formulation variables on fine particle fraction. An increase in fine carrier concentration generally enhanced FPF because fine lactose particles occupy high-energy active sites on coarse carrier surfaces, thereby facilitating drug detachment during inhalation.
Magnesium stearate further improved aerosolization performance by reducing cohesive interactions between particles. However, excessive levels of fine particles or glidant may increase agglomeration, leading to reduced dispersion efficiency. Therefore, an optimum balance among formulation variables was required to maximize respirable fraction.
3.4.2 Model Diagnosis:
Model diagnostic plot Figure 11 demonstrated satisfactory agreement between experimental and predicted responses, indicating adequate fitting of the statistical model. The absence of major deviations suggests that the developed model reliably describes the relationship between formulation variables and aerosol performance.
The diagnostic evaluation confirms the suitability of the Box–Behnken Design for optimization of Naratriptan DPI formulations.
3.4.3 Contour Plot For %FPF:
The contour plot Figure 12 provides a two-dimensional representation of factor interactions affecting fine particle fraction. Elliptical contour patterns indicate significant interaction between variables, whereas circular contours suggest weaker interactions.
The plot revealed that intermediate concentrations of coarse carrier, fine carrier, and magnesium stearate produced the highest FPF values ²³. These results support the selection of the optimized formulation identified through desirability analysis.
3.4.4 ANOVA Analysis for invitro drug Release
The regression equation demonstrates the influence of formulation variables on drug release behavior. Positive coefficients indicate a direct relationship with drug release, whereas negative coefficients suggest an inverse effect.
The interaction terms reveal that simultaneous changes in carrier concentrations significantly affect drug release characteristics. The ANOVA analysis confirms that formulation composition plays a major role in controlling drug dissolution and release from the DPI system.
Final equation in terms of coded factors:
In-Vitro Drug release=+56.16+1.50*A-4.18*B-0.3725*C-6.86*AB-4.38*AC- 3.31*BC
3.4.5 Response surface for In-vitro drug release:
The response surface plot Figure 13 demonstrates the influence of carrier composition and magnesium stearate concentration on in-vitro drug release. Higher drug release values were generally observed when the carrier system provided optimal drug dispersion and increased exposed surface area.
The observed response indicates that careful selection of carrier ratio can improve dissolution behavior and enhance pulmonary drug availability.
3.4.6 Contour plot for In vitro drug release:
The contour plot Figure 14 further confirms the interaction between formulation variables affecting drug release. The optimum region corresponds to combinations of formulation variables capable of producing both high drug release and acceptable aerosolization performance. These findings support the use of a multivariate optimization strategy for DPI formulation development.
3.4.7 Design space:
The design space Figure 15 represents the multidimensional combination of formulation variables capable of producing acceptable product quality. The shaded region identifies operating conditions where both FPF and drug release meet predefined optimization criteria. The existence of a well-defined design space demonstrates formulation robustness and supports a Quality-by-Design (QbD) approach to DPI development. ¹²
3.4.8 Check point batch analysis:
Table 4: comparison of predicted and observed value
Response | Predicted Value | Observed Value |
%FPF | 31.34 | 30.75 |
In-Vitro Drug Release | 67.25 | 65.84 |
Checkpoint batch analysis was performed to verify the predictive capability of the optimization model. Table 4 presents observed values for FPF (30.75%) and in-vitro drug release (65.84%) were in close agreement with the predicted values of 31.34% and 67.25%, respectively.
The small prediction errors confirm the validity and reliability of the developed optimization model.
3.4.9 Final Optimized Formulation
The optimized formulation exhibited a desirability value of 0.918, indicating successful simultaneous optimization of all critical quality attributes. The selected formulation contained 90% coarse carrier, 10% fine carrier, and 1.49% magnesium stearate, which collectively provided favorable aerosolization performance and drug release characteristics showed in Table 5.
Table 5: The optimized batch formula as per Design of Experiment (DOE)
Variables | Solution | Desirability |
Conc of Coarse Carriers | 90 | 0.918 |
Conc of Fine Carriers | 10 | |
Conc of Glidant | 1.49 | |
% FPF | 31.34 | |
In-Vitro drug release | 67.25 |
3.5 Particle Size Characterization on optimized Naratriptan HCL DPI
The optimized DPI formulation was characterized for particle size. There was no significant change in the DPI size as the particle size obtained at different intervals of time were same as that obtained from optimized formulation. Thus, it could be concluded that after Trituration according to this protocol provided sufficient DPI Formulations. The measured VMD values of the dry powder formulations were in the range of 15.4–17.4 μm. However, VMD represents the geometric particle diameter, whereas pulmonary deposition is primarily governed by aerodynamic diameter (MMAD). Due to their low density, particles with geometric diameters greater than 5 μm can exhibit aerodynamic diameters within the respirable range and therefore achieve effective deep lung deposition.
3.6 Fine Particle Fraction of optimized Naratriptan HCL DPI
The Fine Particle Fraction (FPF) of the optimized Naratriptan HCl DPI formulation was 35.90%, indicating that approximately 35.90% of the emitted dose consisted of respirable particles capable of reaching the deep lung region. This value was comparable to that of the marketed Asthalin Rotacap, which exhibited an FPF of 43.64% showed in Table 6 and Figure 16. Although the marketed product showed a higher FPF, the developed Naratriptan DPI demonstrated satisfactory aerosolization performance and efficient pulmonary deposition characteristics.
Table 6: % FPF of optimized Naratriptan DPI in comparison to Asthalin Repulse
3.7 SEM of optimized Naratriptan HCL DPI formulation
Scanning Electron Microscopy (SEM) was performed to evaluate the surface morphology and particle distribution of the Naratriptan HCl dry powder inhaler formulation. The SEM micrographs Figure 17, revealed the presence of coarse lactose carrier particles with irregular and rough surfaces, which provide suitable sites for drug adhesion.
Fine lactose and micron drug particles were observed to be uniformly distributed and adhered onto the surface of the coarse carrier particles. The smaller particles occupied surface asperities and active sites on the carrier surface, promoting the formation of an interactive powder mixture. No evidence of particle fusion or excessive agglomeration was observed, indicating efficient blending and good dispersion characteristics. The observed carrier–drug association suggests that the micronized drug particles can readily detach from the carrier during inhalation, thereby facilitating aerosolization and deep lung deposition. These findings confirm the suitability of the selected carrier system for achieving effective pulmonary delivery of Naratriptan HCl.
3.9 Naratriptan HCL DPI Optimized Batch In-Vitro Drug Release:
The in-vitro drug release profile of the optimized Naratriptan HCl DPI formulation was evaluated using a Franz diffusion cell. The formulation exhibited a gradual and sustained increase in drug release throughout the study period. From Figure 18, an initial release of 5.61% was observed at 2 min, which increased to 14.32%, 19.84%, and 23.64% at 4, 6, and 8 min, respectively. The release reached 35.61% at 10 min and further increased to 40.32%, 46.32%, and 52.14% at 15, 20, and 25 min, respectively. The maximum cumulative drug release of 67.25% was achieved at 30 min. The rapid release observed during the initial phase can be attributed to the micronized particle size and increased surface area of the drug, while the subsequent sustained release may be due to gradual diffusion through the membrane. These results indicate that the DPI formulation provides efficient drug dissolution and has the potential to achieve rapid pulmonary absorption following inhalation.
3.10 Ex-Vivo Drug Release Study optimized Naratriptan HCL DPI
The ex-vivo permeation study demonstrated successful transport of Naratriptan HCl across goat lung tissue. The permeation profile indicated efficient diffusion through the pulmonary membrane, supporting the suitability of the DPI formulation for systemic drug delivery.
The enhanced permeation may be attributed to the large surface area of the lung tissue and the respirable particle size of the formulation. Figure 19 explain drug diffusion across tissue and further prove the potential of Naratriptan HCL DPI formulation.
3.11 Multilinear Regression Model for Lung deposition prediction of Naratriptan HCL DPI
A Multiple Linear Regression (MLR) model was developed to predict lung deposition using experimentally reported physicochemical and aerosolization parameters of inhalable drug formulations. Relevant descriptors, including oral bioavailability, fine particle fraction (FPF), particle size, LogP, pKa, solubility, MMAD, GSD, fine carrier size, coarse carrier size, and dose, were collected and subjected to statistical analysis. The MLR algorithm established quantitative relationships between these independent variables and the dependent variable (lung deposition), and regression coefficients were estimated using the least-squares fitting method. The final predictive equation was selected based on statistical significance, goodness-of-fit, and predictive performance, enabling estimation of lung deposition from the combined contribution of formulation, particle, and drug-related descriptors.
Lung Deposition= 6.614 + 0.010X₁ + 0.075X₂ − 0.1796X₃ − 0.276X₄ + 0.1796X₅ + 0.0008X₆ − 2.1868X₇ + 1.196X₈ + 0.0033X₉ − 0.0023X₁₀ + 0X₁₁ + 0.0001X₁₂ + 0.0001X₁₃ (9)
where:
X₁ = Oral Bioavailability
X₂ = FPF
X₃ = Particle Size
X₄ = Log P
X₅ = pKa
X₆ = Solubility
X₇ = MMAD
X₈ = GSD
X₉ = Fine Carrier
X₁₀ = Coarse Carrier
X₁₁ = Half-life
X₁₂ = Dose
X₁₃ = Molecular Weight (M.W.)
3.11.1 Model Evaluation:
The developed MLR model demonstrated good predictive capability with an R² value of 0.7435 and an adjusted R² value of 0.7007, indicating that approximately 74% of the variability in lung deposition could be explained by the selected descriptors.
Among the evaluated variables Table 7 and 8, FPF exhibited the strongest positive contribution toward lung deposition, while MMAD showed a negative influence. These findings are consistent with aerosol science principles, where increased respirable fraction improves deposition and larger aerodynamic diameters reduce deep lung penetration.
The model therefore provides a useful predictive tool for screening and optimizing DPI formulations during early-stage development.
Table 7: Analysis of Variance of MLR model
Source | df | SS | MS | F-statistic | p-value |
Regression | 13 | 8851.6474 | 680.896 | 2.6979 | 0.0035 |
Residual Error | 78 | 19685.3762 | 252.3766 |
|
|
Total | 91 | 28537.0235 | 313.5937 |
|
|
Table 8: Fit summary
R-Squared | R2=0.7435 |
Adjusted R-Squared | R2adj=0.7007 |
Residual Standard Error | 9.6877 on 78 degrees of freedom |
Overall F-statistic | 17.3898 on 13 and 78 degrees of freedom |
Overall p-value | 0 |
Table 9 represents estimated regression coefficients indicate the direction and magnitude of the effect of each predictor on lung deposition.
TABLE 9: Multiple Linear Regression (MLR) Model Coefficients and Statistical Parameters for Lung Deposition Prediction
Predictor | Coefficient | Estimate | Standard Error | t-statistic | p-value |
Constant | Β0 | 6.614 | 6.8699 | 0.8972 | 0.3724 |
Oral Bioavailability | Β1 | 0.01 | 0.0325 | 0.3088 | 0.7583 |
FPF | Β2 | 0.075 | 0.0542 | 13.0648 | 0 |
Particle Size | Β3 | -0.1796 | 0.7333 | -0.245 | 0.8071 |
Log P | Β4 | -0.276 | 0.3433 | -0.804 | 0.4239 |
Pka | Β5 | 0.1796 | 0.2033 | 0.8833 | 0.3798 |
Solubility | Β6 | 0.0008 | 0.0025 | -0.314 | 0.7543 |
MMAD | Β7 | -2.1868 | 1.3788 | -1.586 | 0.1168 |
GSD | Β8 | 1.196 | 2.9331 | 0.4708 | 0.6846 |
Fine Carrier | Β9 | 0.0033 | 0.0546 | 0.0601 | 0.9523 |
Coarse Carrier | Β10 | -0.0023 | 0.0213 | -0.107 | 0.915 |
Half life | Β11 | 0 | 0.0096 | 0.003 | 0.9977 |
Dose | Β12 | 0.0001 | 0.0002 | 0.6807 | 0.4981 |
M.W. | Β13 | 0.0001 | 0.0001 | 0.1635 | 0.8705 |
Positive coefficients for oral bioavailability (0.01), FPF (0.075), pKa (0.1796), solubility (0.0008), GSD (1.196), fine carrier size (0.0033), dose (0.0001), and molecular weight (0.0001) suggest that increases in these variables are associated with increased lung deposition. In contrast, negative coefficients for particle size (-0.1796), Log P (-0.276), MMAD (-2.1868), and coarse carrier size (-0.0023) indicate an inverse relationship with lung deposition. Among all predictors, FPF exhibited the strongest positive influence, whereas MMAD showed the greatest negative effect on the response. The coefficient estimates therefore demonstrate that aerosolization characteristics, particularly FPF and MMAD, are the most influential factors governing pulmonary deposition in the developed DPI formulation.
4. Conclusion
The present study successfully developed and optimized a dry powder inhaler (DPI) formulation of Naratriptan Hydrochloride for pulmonary delivery using a Box–Behnken Design approach. Micronization reduced the drug particle size to the respirable range, facilitating efficient lung deposition. FTIR and XRD studies confirmed the compatibility of Naratriptan HCl with lactose carriers and magnesium stearate without affecting its crystalline nature. The optimized formulation exhibited satisfactory flow properties, high content uniformity, and a fine particle fraction of 35.90%, indicating efficient aerosolization. In-vitro and ex-vivo studies demonstrated enhanced drug release and permeation across lung tissue, suggesting the potential for rapid systemic absorption. SEM analysis confirmed appropriate particle morphology and carrier–drug interactions. The developed Multiple Linear Regression (MLR) model showed good predictive capability (R²=0.7435) for estimating lung deposition based on physicochemical and aerodynamic descriptors. Among the evaluated variables, FPF positively influenced lung deposition, whereas MMAD showed a negative effect. Overall, the optimized Naratriptan DPI represents a promising non-invasive alternative to oral therapy for rapid migraine management and warrants further in-vivo and clinical investigations.
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Authors
Authors: Dr. Milind Thosar *(a), Madhav Zinzuvadiya (b), Ajay Savaniya (a)
a. Faculty of Pharmacy, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat
b. Emcure Pharmaceuticals Ltd., Ahemdabad, Gujarat
Corresponding Author: Dr. Milind M Thosar,
Address: Faculty of Pharmacy
The Maharaja Sayajirao University of Baroda
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