Molecular Dynamic Simulation Approach to Predict the Compatibility of Formulation Components of Salbutamol Sulfate Metered Dose Inhaler Free off Ethanol

 

Alaa Aldabet, Mohammad Haroun, Marof Alkhayer, Wassim Abdelwahed

Tartous City- Syria Lattakia City-Syria Lattakia City-Syria Aleppo City- Syria.

 

ABSTRACT:

More than 50 years since the first introduction of metered dose inhaler (MDI) by Riker laboratories 1956. The major development in MDI manufacturing was the transformation from chloroflouro carbon (CFC) to hydroflouro alkane (HFA) which required a new engineering design to the MDI components and reformulation of existing MDI to fit the new propellant. Evolution of MDI formulation was challenging due to the low solubility profile of most excipients in HFA propellants and the limitation of generally recognized as safe (GRAS) excipients that could be delivered to the lung. The main purpose of this study was to develop a new salbutamol sulfate (SS) MDI using PEG400(1%) w/w as suitable alternative co-solvents to ethanol (10%)w/w. PVP-k30(0.001-0.0001%) w/w and Brij72(0.001-0.005-0.01%) were used separately as suggested stabilizer. In silico molecular dynamic (MD) simulation was carried out to investigate the compatibility of new excipients with SS and PEG400 before adding the HFA134a. Differential scanning calorimeter(DSC) was also run to evaluate the compatibility between formulations components that passed the visual observation test. Content per actuation was also used to estimate the developing formulation at accelerated stability conditions (40°C/75%RH).(N=10). MD simulation results demonstrated the compatibility of PVP-k30(0.0001%) w/w with other formulation's components before adding HFA134a propellant(small or negative value for  and ). MD simulation results were also confirmed by DSC thermograms which indicate the compatibility between PVP-k30 based formulation due to a small change in endothermic maximum melting point compared with Brij 72 based formulation.Content per actuation of PVP-k30(0.0001%)w/w based formulation passed the accelerated stability test and there is a significant effect of stabilizer type and concentration on the emitted dose (p-value >0.05). This work confirms that MD simulations could save time and reduce the cost of experiments during the early stage of reformulation process of MDI.

 

 

 

INTRODUCTION:

Since the introduction of Metered dose inhaler (MDI) by Riker laboratories in 1956, it spread widely and became the drug of choice in treating asthma and COPD^1-4. MDI consists of Several components such as metered valve, actuator, canister, formulation and propellant each of them is necessary to the performance of the whole device^5,6. This mechanical dosage form could be either solution, suspension or emulsion of the active pharmaceutical ingredient (API) in the propellant^6-8. The first propellant used in MDI was chloroflouro carbon (CFC) which was phased out by Monterial protocol due to its harmful effect on the ozon layer. CFC was replaced by hydroflouro Alkane (HFA) the ozone friendly propellant⁹. HFA134a and HFA227 were considered the most used HFA propellants in MDI. This transition imposed a new design for metered valve, actuator and re formulation of exiting MDI using new excipients compatible with HFA^10,11. Surfactants are most commonly used excipients in MDI formulation. they are used as stabilizer for their properties in preventing agglomeration and crystal growth beside their roles as solubility enhancer, and valve lubricants^12,13. Most surfactants have a low solubility profile in HFA propellants which could be optimized by adding cosolvents such as ethanol^5,14. MDI considered as a targeted drug and its therapeutic effect related to the amount of drug that could reach the lung, therefore the particle size of emitted dose should be (1-5µ).^15-17

 

Development of MDI formulation is so difficult and require a lot of time and cost due to the limitation of generally recognized as safe GRAS excipients that is compatible with HFA propellants and could be delivered to the lung^12,18. Therefore Novel technique was developed to predict the compatibility between MDI formulation components such as Raman Spectroscopy which can provide data on phase and phase transitions, hydrogen bonding, polymorph, hydrates, anhydrates, molecular conformation, polymer chain conformation and foreign particulate contamination^19-21. Differential scanning calorimeter apparatus (DSC) could be used to study phase transition such as melting, exothermic decompositions, glass transition, and to study compatibility between formulation components, polymer interactions, crystallinity and polymorphism^22-25. Xray diffraction (XRD) could be used to study excipients compatibility, detection of impurities, crystallinity, degree of polymorpholism and monitoring batch or dosage uniformity.^26-28

 

Computational methods could also be used in developing MDI formulations. Several in-silico models which increase productivity and decrease the cost of experiments have been developed such as using ADME/TOX model to predict the absorption, distribution, metabolism, excretion and toxicological effect of developing formulation on the Lung²⁹. Gastro Plus™ model was used to predict the level of absorbed API in the blood^30,31. Computational fluid dynamic (CFD) model based on Navier Stokes theory can be used to predict the distribution of emitted dose, spray pattern, spray velocity and in developing releasing dose apparatus^32-34. Sou and Bergstorm used molecular dynamic(MD) simulation to investigate the compatibility of celecoxib and cyclodextrin with other dry powder inhaler (DPI) formulation components.³⁵

 

This study aims to develop a new suspension-based formulation of salbutamol sulfate MDI using PEG400(1%) as suitable alternative cosolvent to ethanol (10%)⁵. PVP k30 and Brij 72 were suggested as stabilizer for MDI formulations.MD simulation depending on Florry Huggins's theory was used to predict the compatibility of suggested stabilizers and other formulation components such as PEG400 and SS before adding the HFA134a propellant. The results were compared with DSC results for the previous formulations. Ethanol free formulations were evaluated by determining the content per actuation during (0, 3, 6 months) at accelerated stability condition (40°C/75%RH).

 

MATERIAL AND METHODS:

Material:

Reference salbutamol sulfate powder, micronized salbutamol sulfate powder, PEG400, Brij72, PVP-k30, HFA134a, metering valves, aluminium cans and actuators were obtained as a gift from Allied Pharmaceutical Industries (Syria). PET vials were obtained as a gift from Enlighten Scientific LLC (NC, USA). Methanol (HPLC grade), acetonitrile (HPLC grade), and ammonium acetate were purchased from Merck (Darmstadt, Germany).

 

Apparatus:

High-performance liquid chromatography (HPLC) was performed using a Merck-Hitachi Lachrome L-7000 system consisting of an L-7100 pump, L-7250 programmable autosampler, and L-7420 UV- VIS detector (all items from Merck–Hitachi, Tokyo, Japan). DSC screening was performed using Linseis DSC-PT10 (Selb, Germany). Ultrasonication was performed using Starsonic 90 (Liarre, Italy). Gravimetric measurements were made with an XB 220A SCS Analytical Balance (Precisa Gravimetrics AG, Dietikon, Switzerland).

 

HPLC-UV method:

British Pharmacopoeia BP2013 HPLC assay conditions for salbutamol sulfate MDI were operated at 276 nm. Separation was carried out on reversed phase using Lichrocart®100-RP-18 column (5µm x 10cm) (Darmstadt, Germany). The elution was carried out with an isocratic solvent system with a 2 ml/min flow rate at ambient temperature. The mobile phase consisted of methanol, ammonium acetate (800ml:225ml), and the injection volume was 20 µl.

 

Differential Scanning Calorimetry screening method:

Samples were analyzed using Linseis DSC-PT10 instrument for prepared suspensions S-Br(0.01%), S-Pv(0.0001%) and SS. Experiments were run using sealed aluminium pans containing approximately 10 mg. Samples were heated over a range of 25-300°C at a heating rate 5°C/min.

 

Statistical Analysis:

Data are shown as mean ± standard deviation (SD). All statistical analyses were performed using one-way analysis of variance ANOVA by JMP version 13.2.0 (SAS Institute, Cary, NC, USA). p-values ˂ 0.05 were considered statistically significant.

 

Figure 1.3D molecular structures of (A) salbutamol sulfate,  (B) PEG400,  (C) PVP-k30,  (D) brij72

 

 

Molecular Dynamic Simulations method:

Molecular dynamic (MD) simulations were performed using Material Studio v.6.0.0 (Accelyres Software Inc., San Diego, CA). Molecular Structures of SS, PEG400, PVP-k30, and Brij72 were obtained from PubChem data base and Minimization was carried out using Forcite Module. The number of geometry optimization iterations was set to 5000 to ensure results convergence. Flory-Huggins interaction parameter, chi; and E_mix, the free energy of mixing between two components in a binary system were used to represent intra- and intermolecular interactions³⁶. These were calculated using the Blends module based on a modified Flory-Huggins model and molecular simulation techniques. Phase diagrams, mixing thermodynamic variables (enthalpy and free energy of mixing), the temperature-dependent interaction parameters, binding energy, and the identification of favorable binding configurations between molecular pairs were obtained. Quality convergence tolerance was set to medium to do the blends simulations. None contact mode was utilized for the head and tail atom, and the number of frames was set to 50.

 

By MD simulations, atomic models were constructed to calculate intended properties and allow the prediction of miscibility. Figure 1 shows the 3D molecular structures of the studied components.

 

Experimental Procedure:

PEG400(1%) was used as possible alternative cosolvents for ethanol. Brij72 and PVP-k30 were used as stabilizer with different concentration in preparing the suggested initial suspension based formulation free off ethanol. All formulation were prepared using fixed concentration of salbutamol sulfate and PEG400 as mentioned in table(1)

 

Table 1. Suggested formulation of S-Br,  and S-Pv

Simulations were performed using Material Studio Blend Protocol to estimate calculated chi and E_mix for S-Br and S-PV.

 

Then, HFA134a was added and the suggested formulation were filled in 10 metal canisters and,  separately,  two poly ethylene terephthalate (PET) vials using a double-stage filling technique. All formulations were designed to release 108mcg of salbutamol sulfate per dose,  and the nominal number of total doses per canister was 200. Visual observation was used to aid selection of the optimum percentage of stabilizer.

 

Initial Suspension of suggested formulations with optimum percentage of stabilizer were evaluated using DSC apparatus.

 

Content per actuation for formulation that passed visual observation were evaluated experimentally under accelerated stability conditions at (40°C/75%RH). Four actuations were released into the air in priming the MDI and Ten actuations were collected into British Pharmacopeia sampling apparatus. The apparatus was rinsed with 11.5ml ammonium acetate buffer and 10ml methanol. The collected liquid was transferred to a graduated 50ml volumetric flask and methanol added to achieve a final volume of 50ml. Following sonication for 10 minutes,  aliquots of the analyte solution were transferred to HPLC vials for subsequent analysis.

 

RESULTS:

MD Simulation results:

The geometry optimization of the SS,  PEG400,  PVP-k30 and Brij72 was performed by setting the optimization parameters using SMART algorithm with medium quality and energy tolerance convergence of 10^-3 kcal mol^-1. Force tolerance convergence was set to 0.5 kcal mol^-1 Å^-1,  while the maximum number of iterations was 5000. The geometry-optimized molecular structures were introduced to the Blends module for the MD simulations,  and the chi parameter and E_mix were calculated for the studied components mixtures. Table 2 shows the calculated parameters for the studied component pairs at 298 K.

 

Figure 2. Mixing energy and Chi parameter diagram of all studied binary mixtures(A, B) for S-Br and (C, D) for S-PV at the temperature range of 298 to 773 K.

 

 

Table 2. Chi parameter and mixing energy for the mixtures of S-Br and S-PV

 

Compatible compounds have lower chi and E_mix values (negative values or approximately equal to zero are preferred). Table 2 shows that PVP-K30 had a small and/or negative value of chi and E_mix with PEG400 at 298 K. Therefore,  PVP-K30 was more compatible with PEG400 more than Brij72. SS was also more compatible with PVP-k30 than Brij72 at 298 K which indicates that at this particular temperature,  molecules components have a favorable interaction. Likely,  a mixture each two components will show just one phase at this temperature, while S-Br components had a significant and positive chi and E_mix which indicates that the molecules prefer to be surrounded by similar components rather than each other due to the free energy overcomes the combinatorial entropy,  and a mixture of the two components will separate into two phases.³⁷Figure 2 shows the chi parameter diagram and mixing energy of all studied binary mixtures at the temperature range of 298 to 773 K.

 

Visual Observation results:

PET vial of Suggested formulation S-Br and S-Pv were evaluated optically by naked eye to choose the optimum percentage of stabilizer. Any sticky formulations of SS to the surface of PET vial would be refused. Figure 3 shows that S-Br (0.01%) and S-Pv(0.0001%) could be the optimum  formulations.

 

DSC results:

The endothermic transitions were presented in all thermogram as shown in Figure 4.The endothermic maximum melting point was employed to assess compatibility in this work. Table 3 demonstrated a detectable change in the endothermic maximum melting point of S-Br(0.01%) 186, 3 °C compared with 197.5°C for SS and 199.5 for S-Pv(0.0001%). S-PV endothermic maximum melting point is approximately equal to SS which reflects a good compatibility between S-Pv components compared with S-Br.

 

Figure 3.  Visual observation results of S-Br(0.01%) and S-Pv(0.0001%)

 

Table 3. Endothermic onset and maximum melting point of SS,  S-Br and S-PV

 

Content Per Actuation Assay:

Stability studies were done according to ICH. S-Br(0.01%) and S-Pv(0.0001%) were evaluated by determining the content per actuation during (0-3-6 months) at (40°C/75%RH).

 

 

Figure 4.  DSC thermogram for (A) S-Pv ,  (B) S-Br formulation compared with SS

 

 

MDI canisters were primed by releasing four actuations into the air; then, ten actuations were collected using the sampling apparatus and analyzed by HPLC (wavelength 276nm). Results are shown in Table4.

 

Table 4. accelerated stability test results of content per actuation S-Br and S-Pv. 

 

It is evident from the table that the Content per actuation of S-Br(0.01%) is 88.05±3.83 , 58.85±4.07,  24.09±2.38 at zero, three,  and six months. S-Br(0.01%) failed to pass accelerated stability study and the content per actuation was out of BP 2013 pharmacopeia accepted range (80-120%) during the second and third point. This is due to the precipitation of Brij 72 that may occur with phenolic substances like salbutamol sulfate.³⁸ While content per actuation of S-Pv (0.0001%) was respected the range (80-120%) during the whole period of accelerated stability test.

 

All the results were statistically analyzed by one-way analysis of variance (ANOVA) which indicated that stabilizer type and concentration had significant effect on the content per actuation (p-value>0.05). The content per actuation test demonstrates that  PVP k-30 (0.0001%) in presence of PEG400(1%) could be a good alternative cosolvent to EtOH(10%) and this needs a further in vitro estimation of delivered dose.

 

DISCUSSION:

The results demonstrate that thermodynamic simulation could effectively predict the compatibility between salbutamol sulfate and Stbilizer in the presence of PEG400 based on Flory-Huggins theory. Chi parameter and E_mix of S-Pv indicate that all formulation components are compatible with each other (small or negative values). While, simulation results for S-Br indicate that the component is not compatible (large positive values of chi and E_mix). DSC thermograms confirm the MD simulation results with a small change in the endothermic maximum melting point for S-PV compared with SS.

 

Simulation results correlate with content per actuation which demonstrate that S-Pv (0.0001%) meet the requirements of ICH and BP2013, whereas S-Br(0.01%) does not. Therefore PEG400(1%) could be a suitable alternative cosolvent to Ethanol (10%) in the presence of PVP-k30, while ANNOVA test demonstrates that both PVP-k30 and Brij 72 have a significant effect on the content per actuation (p-value < 0.05).

 

CONCLUSION:

This study aimed to design an ethanol-free salbutamol sulfate metered-dose inhaler formulation using PEG400 as a possible alternative cosolvent to ethanol. PVP-k30 and Brij72 were used separately as a suggested stabilizers The compatibility of formulation components before adding HFA134a was studied using in-silico molecular dynamics simulation. Differential scanning calorimeter was used also to study the compatibility between formulation components. Accelerated stability test for Content per actuation was also studied. According to the results the predicted, mixing energy, and chi parameter indicated that PVP-K30 compatibility with formulation components is higher than Brij72 and these results were confirmed by DSC thermograms. Content per actuation assay indicates that ethanol (10%) could be replaced by PEG400(1%) in presence of PVP-k30(0.0001%).

 

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

 

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Accepted on 27.08.2022         © RJPT All right reserved

Research J. Pharm. and Tech 2023; 16(3):1385-1390.