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Formulation optimization of smart thermosetting lamotrigine loaded hydrogels using response
surface methodology, box benhken design and artificial neural networks
Siyabonga Melamane, Roderick B. Walker & Sandile M. M. Khamanga
To cite this article: Siyabonga Melamane, Roderick B. Walker & Sandile M. M. Khamanga (2020) Formulation optimization of smart thermosetting lamotrigine loaded hydrogels using response surface methodology, box benhken design and artificial neural networks, Drug Development and Industrial Pharmacy, 46:9, 1402-1415, DOI: 10.1080/03639045.2020.1791163
To link to this article: https://doi.org/10.1080/03639045.2020.1791163
Published online: 21 Aug 2020.
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RESEARCH ARTICLE
Formulation optimization of smart thermosetting lamotrigine loaded hydrogels using response surface methodology, box benhken design and artificial neural networks
Siyabonga Melamane, Roderick B. Walker and Sandile M. M. Khamanga
aDivision of Pharmaceutics, Faculty of Pharmacy, Rhodes University, Grahamstown, South Africa
ABSTRACT
The aim of this research was to develop lamotrigine containing thermosetting hydrogel for intranasal administration to manage and treat generalized epilepsy. Thermosetting hydrogels were prepared using different ratios of poloxamer 407 (L127), poloxamer 188 (L68) and CarbopolVR 974 P NF (C974) using the cold production process. Thein situthermosetting hydrogel was optimized using Box Behken design. Co- solvency approach was used to increase the solubility of lamotrigine by dissolving it in propylene glycol and polyethylene glycol 400 (0.2: 0.8) and the resultant solution was incorporated in the hydrogel to manufacture an LTG hydrogel. The presence of a higher amount of L127 resulted in higher viscosity at 22C and 34C and decreased the overall release of LTG. An increase in the amount of C974 resulted in a decrease in the pH of the hydrogel. The results show that formulations F10, F12, F13, F14, F15, F16 and F17 exhibited acceptable thermosetting behavior, pH and released adequate Lamotrigine above the min- imum effective concentration to treat generalized epilepsy. The optimized formulation exhibited accept- able thermosetting behavior, pH and lamotrigine release but formed a stiff gel at 22C. The average LTG content of the optimized hydrogel was 5.00 ± 0.0225 mg/ml with % recovery of 99.17%. The amount of LTG released at 12 h from the optimized hydrogel was 3.21 ± 0.0155 mg and will be therapeutically effect- ive in the brain after absorptionviathe olfactory region in the nasal cavity.
ARTICLE HISTORY Received 21 March 2020 Revised 31 May 2020 Accepted 23 June 2020 KEYWORDS
Lamotrigine; artificial neural networks; Box-behken design; preformulation;
thermosetting; hydrogel
Introduction
Epilepsy is a disorder of the central nervous system whereby there is recurrent and unpredictable disruption of normal nerve cell activity in the brain which cause recurring epileptic seizures [1].
Epileptic seizures are divided into two types viz, generalized and partial (focal) seizures. Generalized seizures involve the whole of both hemispheres of the brain whereas partial seizures only involve a localized part of the brain [2,3].
Lamotrigine (LTG) (Figure 1) is a broad-spectrum anti-epileptic drug which is indicated for use in the management and treatment of epilepsy [4]. LTG [2,3-diamino-6-(2,3-dicholorophenyl)-1,2,4-tria- zine] is a novel anti-epileptic active pharmaceutical ingredient, chemically unrelated to other antiepileptic agents in current use [5,6].
In humans, LTG is rapidly and completely absorbed with an oral and nasal bioavailability of about 98 and 116.5% [4,7]. LTG has an elimination half-life of about 24 h and is 55% protein- bound in plasma suggesting that a lower concentration of unbound LTG will be available to exert an effect in the brain [4].
To account for protein-bound LTG, higher dosages of LTG (25, 50 and 100 mg) are administered orally to patients to increase the concentration of unbound LTG and achieve therapeutic efficacy.
In urine, 70% of LTG is recovered and 90% of which is recovered in the form of a glucuronide conjugate [4]. High doses of LTG may induce adverse effects such as hepatotoxicity, headache, fatigue and Stevens Johnson Syndrome, which would affect patient adherence [4,8]. The adverse effects, protein binding and hepatic first pass metabolism may be avoided by direct delivery
of LTG to the target site in the brainvianasal mucosa. The nasal cavity is made of three main regionsviz, vestibule, olfactory and respiratory region [9]. Absorption of an API to the brain may occur through olfactory epithelium via transcellular, paracellular and olfactory nerve pathways and/or the respiratory regionviathe tri- geminal nerve pathway, which are found on the roof of the nasal cavity [10,11]. Olfactory neural cells project axons from the soma in the olfactory epithelium through the small foramina of the cri- biform plate of the ethmoid bone to synapse on the mitral cells of the olfactory bulb [12,13]. Mitral and tuft cells of the olfactory bulb project to several locations found on the ventrolateral sur- face of the brain [14]. Mitral cells project to various locationsviz., amygdala, piriform plexus, entorhinal plexus and hypothalamus and tuft cells project to the olfactory nucleus of the cerebrum [14]. These cells ensure the distribution of molecules to every region of the brain. The respiratory region as an ideal target for API absorption for systemic circulation if the API is able to cross the mucus layer [12,15]. The trigeminal nerve extends from the brain stem and hence has the potential for transporting API dir- ectly to the brain [12,16].
Direct delivery of LTG to the brain may be achieved via the nasal cavity in a suitable dosage form which will overcome physiological limitations. A dosage form with high viscosity viz, hydrogels, will increase contact time between the API and the nasal mucosa by resisting muco-ciliary clearance [17,18].
Hydrogels are hydrophilic polymer networks that are three- dimensional and swell in response to the nature of a gelling agent and the external environment viz, temperature, pH, CONTACTSandile M. M. Khamanga [email protected] Division of Pharmaceutics, Faculty of Pharmacy, Rhodes University, Grahamstown 6139, South Africa ß2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
2020, VOL. 46, NO. 9, 1402–1415
https://doi.org/10.1080/03639045.2020.1791163
electromagnetic radiation and ionic strength [19,20]. These gels hold a large amount of water and retain their intact structure in water [21].
Poloxamersviz, 188 (L68), 237 (L87), and 407 (L127), are used as gelling agents in an aqueous solution at a certain concentra- tion to produce an in situ thermosetting hydrogel. An in situ thermosetting hydrogel undergoes phase transition from solid to liquid, liquid to solid, shrinking or swelling with a change in tem- perature above or below the solution to gel (sol-gel) transition temperature [22]. An increase in temperature results in monomers of L127 aggregating to form micelles after which gelling occurs in two steps. Firstly, the temperature is increased in order to reach the CMT at which poloxamer monomers aggregate, forming spherical micelles and as the temperature increases further the concentration of micelles increases in solution to form a stiff gel [22]. Upon gelation, the gel adheres to the target site to resist muco-ciliary clearance and increase residence time allowing LTG to be completely absorbed [23]. In addition to increasing resi- dence time at the surface of the mucosa, hydrogels control API release [24–26]. Poloxamers may be combined to influence the viscosity of the gel at different temperatures. A solution of L127 changes to a gel due to swelling of micelles by interaction of PPO blocks [27]. The L68 grade consists of more PEO blocks than L127 as a result this results in a reduction in the viscosity of the final gel in combination with L127 as this causes a disruption to the PEO and PPO balance [28]. The PEO blocks are hydrophilic while the PPO clock is hydrophobic. This reduction in viscosity will enable convenient administration of a low viscosity hydrogel into the nasal cavity.LTG has been characterized in terms of the Biopharmaceutical Classification System (BCS) as a Class IIb com- pound as it exhibits low water solubility and high gastrointestinal permeability [29]. Low water solubility may present a challenge in incorporating an adequate amount of LTG to a hydrogel.
Preliminary studies to enhance the solubility of LTG in the hydro- gel were necessary since API loading must be high in low volumes (1=4to1=2mL per nostril) in nasal formulations and 1 ml per nostril would runoff [30].
Considering all these premises, the aim of this work was do develop and assess a poloxamer-based hydrogel for direct to brain delivery of LTGviathe intranasal route.
Prior to developing a pharmaceutical dosage forms consisting of an active pharmaceutical ingredient (API) and excipient, it is essential that compatibility studies be conducted. Compatibility studies are conducted with the primary goal of selecting dosage form components that are compatible with the API [31]. API- excipient incompatibility may change bioavailability and stability of the API in the final dosage form which may in turn affect prod- uct safety and efficacy and safety [32]. In this work compatibility studies were conducted using DSC and FTIR. In this work compati- bility studies were conducted using DSC and FTIR. DSC was used
to determine the suitability of excipients for use in dosage form development by evaluating physico-chemical interactions between API and excipients in mixtures [33]. FTIR was used to investigate the solid state behavior and as a compatibility screening tool for API and excipients. Its suitability for screening studies stems from its ability to detect vibrational changes which serve as evidence for potential intermolecular interactions among the dosage com- ponents [33].
The combinatory use of response surface methodology (RSM), Box-Behken Design (BBD) and artificial neural networks (ANN) was implemented to optimize the formulation.
Materials and methods Materials
LTG was purchased from Skyrun Industrial., Taizhou, P.R China and carbamazepine (CBZ) was purchased from Sigma AldrichVR, St.
Louis, Missouri, USA. Poloxamers 407 (L127) and 188 (L68) were donated by BASF, Ludwigshafen, Rhineland Palatinate, Germany and Carbomer 974 P NF (C974) was donated by Noveon Inc., Brecksville Road, Cleveland, United States of America. Propylene glycol (PG) was purchased from Aspen PharmcareVR, Port Elizabeth, Eastern Cape, South Africa. Polyethylene glycol 400 (PEG 400), disodium hydrogen phosphate, sodium dihydrogen phosphate and sodium chloride were purchased from MerckVR Laboratories, Wadeville, Gauteng, South Africa. All these materials were used without further purification.
Preformulation studies
Differential scanning calorimetry.Thermal analysis of LTG and 1:1 w/w binary mixtures of LTG and each excipient was conducted using a model Q100 differential scanning calorimeter (TA instru- ments, New Castle, DE, USA) coupled with a RCS (90) refrigerated cooling system (TA Instruments, New Castle, DE, USA). Samples weighing between 2 and 4 mg were weighed placed on aluminum pans and covered with an aluminum lids. The pan and an empty pan (reference) were placed on a constantan disk on a DSC Standard Cell FC. Both pans were heated from 30 to 450C at a heating rate of 10C/min under an inert nitrogen atmosphere at a flow rate ml/min. Thermograms were generated by the calorim- eter and analyzed by a TA Universal software (TA instruments, New Castle, DE, USA).
Fourier transform infrared spectroscopy. LTG and binary mixtures of LTG and excipients were analyzed using a Spectrum 100 FT-IR ATR Spectrophotometer (Perkin ElmerVR Ltd, Beaconsfield, England) to investigate interactions between the constituents. For analysis, LTG and the binary mixtures were placed on a diamond crystal and a force (approx. 100 N) was applied onto the sample.
Scanning range and resolution were set at 4000 to 650 cm-1 and 4 cm-1 respectively.
Method for hydrogel manufacture
A 1 L batch of a phosphate buffer solution consisting of 2.5 g of disodium hydrogen phosphate, 2.5 g sodium dihydrogen phos- phate and 8.2 g of sodium chloride was prepared using HPLC grade water. The solution was stirred for 10 min using a LabconVR Magnetic hotplate-stirrer (Lasec, Gauteng, South Africa) until a clear solution formed. The pH of the solution was measured using a CrisonVR pH meter (Barcelona, Catalonia, Spain) and adjusted to Figure 1. Chemical Structure of LTG [Adapted from (4)].
pH 6.31 using a 0.1 M NaOH solution. The phosphate buffer was used in the manufacture of hydrogels.
The LTG hydrogels 0.5% w/w (40 g) were manufactured using a cold production method as described by Talasaz et al. [34]. The amounts of L127, L68 and C974 as specified and defined in the BBD on Design ExpertVR Version 7.0.1 (Stat-Ease Inc., Minneapolis USA) as listed in Table 1 and Table 2 were weighed and trans- ferred to a transparent BonpakVR jar (Midrand, South Africa) sealed with a watertight lid.
The phosphate buffer solution was added to the powder blend in the jar and was mixed until the material was completely soaked in the solution. Specific amounts of PG and PEG 400 were weighed out and mixed using a Model G-560E Vortex Genie-2 mixer (Bohemia, New York, USA) in a ratio as established in the co-solvency investigation as described in § 2.2.2. LTG was trans- ferred into the PG: PEG 400 solution as determined in the co-solv- ency investigation as described in § 2.2.2 and the resultant mixture was heated to 50C and stirred until a solution was observed.
In this work, BBD was specifically selected since it is a popular template for RSM which only requires levels of each process factor with only a few runs and covers all possible combinations. In this design, the experimental region is assumed to be a cube, and experiments are performed at points corresponding to the mid- point of each edge and replicated experiments at the center of this multidimensional cube.
Artificial neural network (ANN) technology is a group of com- puter designed algorithms mimicking pattern recognition capabil- ities of the brain to process and understand information and understand the relationship between information and outcomes [35,36]. ANN was used to optimize formulation composition parameters to obtain ideal responses. The software used for build- ing an ANN model was Statistica version 13.2 software (Round
Rock, Texas, USA). The input factors were L127%, L68% and C974% and the output factors were viscosity at 22C, viscosity at 34C, sol-gel transition time, pH and LTG released at 2 h, 6 h and 12 h. Two feed-forward ANN architectures were used in this study, multi-layered perceptron (MLP) and radial basis function were trained using one hidden layer with 2 to 20 processing units. MLP and RBF were trained with Broyden-Fletcher-Goldfarb-Shano (BFGS) and radial basis function training (RBFT) algorithms, respectively using input-output data set from BBD. The data was divided into training (70%), cross-validation (15%) and test (15%) sets.
Co-solvency
Solubility in PG, PEG 400 and water. Based on a study by Soltanpour and Jouyban [37] PG, PEG 400 and/or water were indi- vidually and adjunctively (in different ratios) used to enhance the solubility of LTG. The solubility of LTG in PG, PEG 400 and water was reported as 52.3, 86.6 and 0.17 mg/mL respectively [37].
The solubility of LTG was investigated by dissolving 50 mg in 1 g of the selected solvent in a test tube and solubilization was noted. Approximately 0.1 ml of the resultant LTG solution was added using an EppendorfVR Research 100–1000mL micropipette to 0.9 ml of a hydrogel and precipitation was noted.
Lamotrigine solubility to hydrogel ratio. Approximately 50 mg of LTG were dissolved in 1 g of the selected solvent and the resultant solution was incorporated into the hydrogel at different ratios (LTG solution: hydrogel); 1:9, 2:8, 3:7, 4:6 and 5:5. The thermoset- ting behavior of the resultant hydrogel was investigated by assessing sol-gel transition time at nasal cavity temperature of
±34C [38]. Hydrogels that exhibited sol-transition time > 60 s were accepted. The accepted hydrogels were assessed for viscosity at 22C, viscosity at 34C, sol-gel transition time, pH, LTG release at 2, 6 and 12 h. Viscosity was assessed at a temperature of 22C to ensure that the optimized hydrogel exists as a liquid at room temperature to allow easy intra-nasal administration using a suit- able device. Viscosity was specifically assessed at 34C so as to investigate the gelation behavior of a poloxamer-based hydrogel in response to intranasal temperature of 34C [39]. The pH of the nasal mucosa ranges between 4.5 and 6.5 and the use of a formu- lation at a different pH may cause irritate the mucosa, therefore the pH of the hydrogel needed to be optimized [40].
Assessment of lamotrigine hydrogels
Thermosetting behavior, pH and LTG release were optimized using BBD wherein L127 (X1), L68 (X2) and C974 (X3) were the varied independent variables as listed in Tables 1, 2and the dependent variables were viscosity at 22C (Y1) and 34C (Y2), sol-gel transi- tion (Y3), pH (Y4) and LTG released at 2 (Y5), 6 (Y6) and 12 (Y7) hours.
The optimum responses were defined as Y1 10,000 cP, Y2 50,000 cP, Y3 60 s, Y4between 5.5 and 6.5 and Y530%, Y6 50% and Y7 60%.Response Y4 should be30% to ensure that sufficient LTG is released to achieve the minimum effective con- centration (1.02mg/L) [41] is released at 2 h and available for absorption to the brain. The desired outputs for responses Y5 and Y6 were selected to ensure that there was an adequate amount of LTG available for absorption to potentially achieve the minimum effective concentration throughout the first 12 h following of administration.
Table 1. Presentation of 17 experiments with coded values for factor levels for the BBD.
Formulation Run L127 X1 L68 X2 C974 X3
F13 1 0 0 0
F17 2 0 0 0
F15 3 0 0 0
F7 4 1 0 þ1
F6 5 þ1 0 1
F2 6 þ1 1 0
F16 7 0 0 0
F14 8 0 0 0
F3 9 1 þ1 0
F10 10 0 þ1 1
F9 11 0 1 1
F1 12 1 1 0
F4 13 þ1 þ1 0
F8 14 þ1 0 þ1
F5 15 1 0 1
F11 16 0 1 þ1
F12 17 0 þ1 þ1
The hydrogels were manufactured and characterized according to the order of their run number to avoid bias.
Table 2. Experimental factors and levels used in the BBD.
Independent factors Level (1) Level (0) Level (þ1)
X1: L127 10.00 % 20.00 % 30.00 %
X2: L68 10.00 % 12.50 % 15.00 %
X3: C974 0.20 % 0.40 % 0.60 %
The dependent variables for BBD were viscosity at 22C, viscosity at 34C, sol- gel transition time, pH and LTG released at 2 h, 6 h and 12 h.
Sol-gel transition
A modified inverted test tube approach was used to assess sol-gel transition of each hydrogel [42–45]. A 1 ml aliquot of each hydro- gel was transferred into test tube (7.5 cm in length and 9 mm in diameter) and the test tube was placed in a test tube rack at a 90angle. The test tube was left standing for 10 min at 34C after which the test tube was rotated through a 180 angle in the oven. Whilst at this angle, the downward motion of the hydrogel was monitored over 60 s. Hydrogels that flowed to the opening of the test tube under 60 s were not accepted for further optimiza- tion whereas hydrogels that did not flow were accepted as suit- able. These experiments were conducted in triplicate.
Viscosity of gel formulations
Viscosity was assessed (n¼3) using a Model RVDVIþBrookfieldVR DVIþviscometer (Middleborough, Massachusetts, USA) fitted to a helipath stand operating with spindle D (S94) at 5.8 rpm over a period of 10 s. Viscosity was assessed at 22C and 34C; heated using a ColoraVR Model NB-34980 Ultra-Thermostat water bath (Loch, Hesse Germany) for 10 min. Viscosity was measured in triplicate.
Ph of lamotrigine hydrogel
The pH of different LTG hydrogels was monitored in triplicates using a model GLP 21 CrisonVR Instruments pH meter (Barcelona, Catalonia, Spain). The pH meter was calibrated daily with pH 4.00 and 7.00 standard solutions. The pH electrode was inserted into 40 g of the hydrogel and the pH value was observed after 60 s,
and the electrode was rinsed with distilled and dried between readings.
In vitrorelease of lamotrigine
The release of LTG from a hydrogel was studied to describe the mechanism of its release, evaluate the effect of L127, L68 and C974 concentrations on LTG release and to compare the LTG release from different hydrogels consisting of the same excipients or from different batches of the same formulation. The selected dissolution medium was a phosphate buffer saline system (PBS) consisting of disodium hydrogen phosphate, sodium dihydrogen phosphate and sodium chloride at 0.25%, 0.25% and 0.825% w/w respectively.
There are no standard release apparatuses and methods for topical particulate delivery systems intended for mucosal applica- tion [46]. The dialysis bag diffusion technique as reported by Brodesen and Ross [28,29] was used to assess thein vitrorelease of LTG.
Approximately 0.5 g of each hydrogel was transferred into a 25 mm flat HiVR media dialysis tubing cellulose membrane bag (12000–1,40,000 Da molecular mass cut off) (Mumbai, India) sealed on one end with a thread. The dialysis bag was sealed on the opposite end and placed into a 25 ml glass tube consisting of 15 ml of the PBS. The glass tube was placed on a LabconVR Magnetic hotplate-stirrer (Lasec, Gauteng, South Africa) to main- tain the temperature of the dissolution medium at 34C and was stirred at 200 rpm with a magnetic stirrer to maintain homogen- eity in the dissolution medium. The in vitro release of LTG was monitored over 12 h with 1 ml aliquots of the medium sampled at 0.5, 1, 2, 4, 6, 8, 10 and 12 h in order to establish the release Figure 2. DSC thermogram of LTG, L127, 1:1 mixture of LTG and L127, L68, 1:1 mixture of LTG and L68, C974 and 1:1 mixture of LTG and C974.
profile of LTG. An equal volume of fresh PBS at the same tempera- ture was immediately replaced after sampling to maintain a con- stant release volume. The concentration of LTG was analyzed using a validated RP-HPLC method [47]. LTG release experiments were conducted in triplicate.
Mathematical modelling of in vitro release profiles
Mathematical models depict dissolution as a function of the char- acteristics of the dosage form of interest [48]. The mechanisms involved in controlling the release of the API are well interpreted and understood by the use of these models [49]. The models commonly used to investigate the kinetics of API release for gels are zero-order, first-order, Higuchi, Korsmeyer-Peppas and Hixson- Crowell models [50–52]. The diffusional exponent (n) relates to the release mechanism of the API from the dosage form [49]. The magnitude of n describes the diffusion mode as Fickian or non- Fickian diffusion [53,54].
Results and discussion Preformulation studies
Differential scanning calorimetry. The DSC scans for LTG and 1:1 binary mixtures of LTG and excipients are depicted in Figures 2 and3.
The sharp melting endothermic peaks at 220.94C for LTG and 218.37C for LTG: L127 indicate that LTG was present in both samples. The exothermic peaks at 59.45 and 59.95C on the scans for LTG and LTG: L127 confirm that there were no incompatibil- ities between LTG and L127. The presence of LTG in both samples was revealed by the endothermic peak at 220.94C for LTG and 217.70C for the LTG: L68 binary mixture. The melting peak of
L68 was also found in the binary mixture scan suggesting that there were no incompatibilities between LTG and L68. The endo- thermic peak at 224.05C on the C974 thermogram reveals its crystallization [55]. The binary mixture reveals that in the presence of LTG, C974 melted at 396.95C due to a reaction between LTG and C974. The melting peak of LTG was observed in the thermo- gram of LTG: C974 indicating that the constituents were compatible.
Fourier transform infrared spectroscopy. The vibrational frequen- cies for LTG are summarized inTable 3.
The absorption and frequency peaks were evaluated for LTG and excipient 1:1 binary mixtures and additional peaks were not observed. There were slight shifts in the frequencies of functional group vibration due to the occurrence of hydrogen bonding between API and excipients [56]. The FT-IR spectra of LTG, L127, L68 and C974 and binary mixtures are depicted in Figures 3–6 respectively.
Solubility in PG, PEG 400 and water. The solubility of 50 mg of LTG in 1 g of the solvent system at varying ratios and the Figure 3. FT-IR absorption spectrum of LTG.
Table 3. Assignment of vibrational frequencies for functional groups of LTG.
Functional group/Assignment Vibrational frequency (cm1)
C–Cl stretch 716.72–789.75
N–H stretch 3447.58
N–H stretch 3447.58
C¼C–C stretch 1459.56 and 1489.52
C¼N stretch 1617.44
N-H bend 1645.96
C¼C–C stretch 1584.58
C-H in plane bend 957.91–1189.84
C-N stretch 1051.99
solubility of 5 mg of LTG in 1 g of LTG solution-hydrogel mixture are listed inTable 4.
Complete solubility of 50 mg in 1 g of a PG-PEG 400 solution and subsequent miscibility with 1 g of the hydrogel was observed
with PEG 400: PG system in a ratio of 4: 1. At this ratio, LTG did not precipitate out of solution indicating that 5 mg of LTG was completely dissolved in 1 g of the hydrogel due to the use of PEG 400 and PG as cosolvents in a 4:1 ratio.
Figure 4. FT-IR absorption spectrum for a 1:1 mixture of LTG and L127.
Figure 5.FT-IR absorption spectrum for a binary mixture of LTG and L68.
Ltg solution to hydrogel ratio. To investigate the most ideal LTG solution-hydrogel mixture ratio to maintain LTG solubility and achieve sol-gel transition time60 s, sol-gel transition time of LTG hydrogels was assessed and the results are listed inTable 5.
The ideal LTG solution to hydrogel ratio was 0.9: 0.1 because existed as a clear solution and exhibited sol-gel transition time
>60 s. At this ratio, the solubility was still improved and poloxamer concentrations in the final hydrogel mixture were still sufficient to undergo sol-gel transition at 34C. Sol-gel transition improved with an increase in the proportion of hydrogel due to a corresponding increase in PPO blocks, found in the hydrogel, which interact to form necessary micelles and micellar packing required for gelation to occur. At lower proportions of the hydrogel in the final hydro- gel-co-solvency mixture no gelation was observed which may be attributed to an insufficient amount of PPO blocks necessary to form micelles for gelation to occur at the CMT.
Assessment of lamotrigine hydrogels
The experimental data for the responses are summarized in Table 6.
Viscosity at 22C.Analysis of variance (ANOVA) data for the BBD for viscosity at 22C revealed that L127 was the only independent
variable with a significant effect (p value ¼ <0.0001) on the dependent variable. Lack of fit was not significant (p value ¼ 0.9924). The final equation for viscosity at 22C is shown as Equation (1)indicating that L127 and L68 reduced the viscosity of the hydrogel as the poloxamers existed as monomers at this tem- perature [57].
Y1¼546:08–ð50849:81X1Þ–ð1705:36314X2Þ þð7152:09X3Þ–ð18:39X1X2Þ
–ð143:75X1X3Þ–ð1781:51X2X3Þ
þð1706:95X12Þ þð115:80X22Þ þð22399:84X32Þ (1)
L68 exhibits Newtonian flow in an aqueous solution and non- Newtonian flow at higher concentrations at ambient temperature [58]. The critical micelle temperature (CMT) of L68 at concentrations between 10% and 15% is between 75 and 80C and that of L127 at the used concentration is between 32–40C hence the low viscos- ity at 22C [58]. C974 slightly increased viscosity as it known to exhibit high viscosities at ambient temperature existing as a gel [59,60]. The slight viscosity increase due to C974 was ideal as it was only included for its mucoadhesive property. The effect of L127 and L68 of lowering viscosity is ideal to produce hydrogels with low viscosity for convenient administration into the nasal cavity.
Figure 6. FT-IR absorption spectrum for a binary mixture of LTG and C972.3.1 Co-solvency.
Table 4. Solubility of LTG in solvent system and in hydrogel.
Solvent system
Solubility of 50 mg of LTG per 1g of solvent system
Solubility of 5mg of LTG per 1g of hydrogel
PEG 400 (w/w) PG (w/w) Water (w/w)
1.00 0.00 0.00 Completely dissolved LTG precipitated
0.79 0.00 0.21 Completely dissolved LTG precipitated
0.80 0.10 0.10 Completely dissolved LTG precipitated
0.50 0.20 0.30 Completely dissolved LTG precipitated
0.40 0.40 0.20 Completely dissolved LTG precipitated
0.80 0.20 0.00 Completely dissolved No precipitation
Viscosity at 34C. ANOVA data for the BBD for viscosity at 34C revealed that L127 was the only independent variable with a sig- nificant effect (pvalue¼<0.0001) on viscosity at 34C. Lack of fit was not significant (p value¼ 0.8273). The final equation for vis- cosity at 34C is shown asEquation (2).
Y2¼ 348:52þð17103:45X1Þ þð10820:05X2Þ
þð53675:66X3Þ (2)
The equation suggests that C974 has the largest effect on the final viscosity of the hydrogel as it acts as a gelling agent at con- centrations lower than 1% [61]. C974 also swells up to 1000 times its original volume in a pH environment between 4 and 6 to pro- duce a gel [61]. Despite this large contribution, C974 had an insig- nificant effect at the concentrations used. Poloxamer L127 increased the viscosity of the hydrogel at 34C to ensure that gel- ation would occur in the nasal cavity. The increase in viscosity caused by L127 and L68 suggests that 34C is within the CMT range for these gelling agents at the concentrations used.
Poloxamers at these concentrations have been reported not to irritate mucosal membranes [20]. Gelation at this temperature will ensure that the hydrogel resists mucociliary clearance and that the API remains in contact with the epithelium long enough to diffuse into olfactory and trigeminal projections [20].
The effect of L127 was dependent on the concentration of L68 because L68 introduced more hydrophilic Polyethelyne Oxide (PEO) monomers which weaken the micelles formed by hydropho- bic interactions between Polyoxypropylene oxide (PPO) monomers in solution [28]. The addition of L68 results in lower viscosity because it is more hydrophilic as it possesses a higher PEO num- ber [28]. L127 possesses PEO and PPO blocks with longer chains than those found in other grades of poloxamers and is considered as the primary gelling agent and L68 therefore complements the effect of L127 [62]. The aggregation of micelles may be improved
by addition a more hydrophobic poloxamer possessing a higher PPO number so that the hydrophobic cores are strongly intact [62].
Sol-gel transition. ANOVA data for the BBD for sol-gel transition revealed that L127 was the only independent variable with a sig- nificant effect (p value ¼ 0.0015) on sol-gel transition time. Lack of fit was not significant (pvalue¼0.8503). The final equation for sol-gel transition is shown asEquation (3).
Y3¼ 98:38þð2:98X1Þ þð5:95X2Þð0:00014X3Þ (3) L127 improved gel strength and the addition of larger amounts may result in more rapid gelation and cause the hydrogel to remain in the stiff gel state for longer.
Ph of lamotrigine hydrogel. ANOVA data for the BBD for pH revealed that C974 was the only independent variable with a sig- nificant effect (p value ¼ < 0.0001) on the responses. Lack of fit was not significant (p value ¼ 0.0368) but the model was accepted based on model fit which was significant (p value ¼ 0.0006) and the R2 which was above 0.9555 indicating adequate understanding of the relationship between independent and dependent variables. The final equation for pH is shown as Equation (4).
Y4¼3:75989þ ð0:013X1Þ þ ð0:45X2Þ–ð5:47X3Þ –ð0:0060X1X2Þ þ ð0:027X1X3Þ
þð0:0017X2X3Þ þ ð0:65X12Þ–ð0:012147X22Þ þð3:76874X32Þ
(4)
Hydrogel pH was significantly reduced by the addition of C974 and therefore its concentration should be kept low in formulation.
C974 dissociates in an aqueous solution and releases Hþ ions which cause a reduction in the pH of the hydrogel [63]. The reduction in pH was accounted for by manufacturing the hydro- gels with a buffer at a pH of 6.31. Changes in the concentrations of L127 and L68 caused negligible effects on the pH of the hydrogels.
Irritation of the nasal mucosa due to hydrogel pH may induce a cascade whereby the 7thcranial nerve stimulates nasal glands to secrete mucous to dilute the irritant on the mucosa and move it to the nasopharynx. This cascade results in the swallowing of the formulation before the API is absorbed [64].
Table 5.LTG solution to hydrogel ratio properties (appearance and sol-gel tran- sition time).
LTG Hydrogel
Appearance Sol-gel transition time (s) LTG-PG-PEG 400 Hydrogel
0.5 0.5 Milky-white <60
0.4 0.6 Milky-white <60
0.3 0.7 Clear <60
0.2 0.8 Clear <60
0.1 0.9 Clear 60
Table 6. Thermosetting behavior, pH and LTG released over 12 h.
Formulation
Viscosity at 22C cP
Viscosity at 34C cP
Sol-gel
transitions pH
LTG released at 2 h %
LTG released at 6 h %
LTG released at 12 h %
F1 6092 11150 30.00 5.27 29.98 ± 0.54 34.98 ± 0.26 36.57 ± 0.85
F2 350000 350000 60.00 5.44 74.92 ± 0.35 85.63 ± 0.65 95.13 ± 1.28
F3 7931 7241 0.50 5.81 43.40 ± 0.62 53.22 ± 0.14 54.69 ± 0.36
F4 350000 350000 0.50 5.43 42.80 ± 0.13 48.92 ± 1.40 54.34 ± 1.23
F5 6781 7471 0.50 6.05 24.27 ± 0.06 25.68 ± 0.16 27.97 ± 0.05
F6 350000 350000 60.00 6.11 25.59 ± 0.15 39.88 ± 0.12 54.48 ± 0.45
F7 7931 5862 0.50 5.21 44.64 ± 0.78 48.96 ± 0.25 51.05 ± 0.99
F8 350000 350000 60.00 5.49 19.72 ± 0.32 30.73 ± 0.96 41.98 ± 0.21
F9 8046 113767 0.50 5.85 33.67 ± 0.58 42.82 ± 0.21 45.68 ± 0.80
F10 10000 161233 60.00 5.92 37.35 ± 0.56 43.96 ± 1.42 46.88 ± 0.73
F11 9195 94823 0.50 5.12 35.39 ± 0.29 41.49 ± 0.17 45.31 ± 0.45
F12 7586 267667 60.00 5.21 42.61 ± 0.26 46.06 ± 0.56 49.90 ± 0.51
F13 8391 141100 60.00 5.53 40.98 ± 0.48 57.53 ± 0.36 61.97 ± 0.16
F14 8160 153633 60.00 5.46 40.01 ± 0.26 57.75 ± 0.25 72.49 ± 0.65
F15 8736 142833 60.00 5.44 31.79 ± 0.39 50.98 ± 0.25 53.15 ± 0.30
F16 8620 141200 60.00 5.40 37.97 ± 0.19 44.19 ± 0.13 51.90 ± 0.08
F17 9080 350000 60.00 5.43 48.95 ± 0.51 60.30 ± 0.17 63.68 ± 0.45
BBD analysis derived equations to describe the relationships between the independent variables and responses.
In vitrorelease of lamotrigine. ANOVA data for the BBD for LTG at 2, 6 and 12 h revealed that L127 and L68 exhibited a significant effect (p value ¼ < 0.0001) on the responses for Y5, Y6 and Y7. The final equations for LTG release at 2, 6 and 12 h are shown as Equations (5–7).
Y5¼ þ64:17þð7:44X1Þ–ð25:06X2Þ þð275:95X3Þ –ð0:46X1X2Þ–ð3:28X1X3Þ þð1:77X2X3Þ –ð0:0043X12Þ þð1:32X22Þ–ð273:81X32Þ (5) Y6¼ 74:67þð10:17X1Þ–ð7:95X2Þ þð368:38X3Þ
–ð0:55X1X2Þ–ð4:05X1X3Þ
þð1:72X2X3Þ–ð0:029X12Þ þð0:71X22Þ–ð374:28X12Þ (6) Y7¼ 159:80þ ð10:79X1Þ þ ð5:03X2Þ þ ð376:12X3Þ
–ð0:589X1X2Þ
–ð4:45X1X3Þ þ ð1:70X2X3Þ–ð0:018X12Þ þð0:21X22Þ–ð375:07X32Þ
(7)
C974 exists in a swollen state in a hydrogel and degrades rap- idly as the dissolution medium penetrates the hydrogel eliciting more API release. The degradation of C974 results in the opening of microspores in the hydrogel matrix and the release of LTG increases [61,62]. The effect of C974 on LTG release increases throughout the dissolution process as more C974 is dissolved by the dissolution medium resulting in higher LTG release. The effect of poloxamers L27 and L68 increased over the duration of the dis- solution study due to a decrease in the number of micelles from 2 to 12 h. There was lower LTG release at 2 h due to the entrapment of LTG inside the micelles as there was a large number of micelles.
As time elapsed, more dissolution medium penetrated the hydro- gel and more micelles were disrupted hence the increase in the effect of L127 and L68 on LTG release closer to 12 h. The release of LTG was prolonged due to its entrapment in the micelles. After 12 h, some LTG was still entrapped in micelles hence 100% release
was not achieved with any of the hydrogels. LTG remained entrapped because it is lipophilic and favorably partitions toward poloxamer micelles resulting in slow and limited release [65].
The LTG content of the hydrogels was in the range of 3.846.34 mg/ml. LTG release profiles from hydrogel formulations viz, F1, F2, F3, F4, F12 and F14 that illustrate the cumulative % LTG released through an area of 31.42 cm2 are depicted inFigure 7. These were selected as they show L127, L68, and C974 at con- centrations of 1030%, 1015% and 0.20.8% respectively and they illustrate the effect of the varying concentrations on the responses.
The error bars were too small as a result of the good accuracy and precision of LTG release. Hydrogels, F1 and F3 possessed the same amount of L127 but different amounts of L68. F3 consisted of more hydrophilic L68 and released more LTG than F1 due to the formation of weaker micelles that were easily disrupted.
Hydrogels, F12 and F14 consisted of the same amount of L127 (20%) which was enough to form a large number of strongly bound micelles. Upon addition of L68 there was an increase in the micelle formation as there were more PPO chains introduced and hydrophobic interactions were made stronger. The effect of the PEO blocks introduced was negligible due to the already high concentration of PPO chains in solution. LTG release was lower in F12 as it consisted of a larger amount of L68 and LTG was more entrapped.
Hydrogels F2 and F4 were very viscous at 5C and were diffi- cult to mix homogenously using a glass rod with the LTG solution and therefore the extent of LTG release may not be a true repre- sentation. F4 released less LTG due to possessing a higher concen- tration of L68.
The mathematical model that best described the hydrogel for- mulations was evaluated using R2 values. The average R2 value suggests that LTG release data best fit the Korsmeyer-Peppas Table 7. Model dependent parameters for LTG release from thermosetting gels.
Formulation
Zero Order First Order Higuchi Korsmeyer- Peppas Hixson-Crowell
R2 K R2 K R2 K R2 K n R2 K
F1 0.6632 1.45 0.6883 0.020 0.8040 11.4 0.8780 18.6 0.28 0.6083 0.22
F2 0.5989 3.13 0.6329 0.056 0.7543 7.87 0.8597 27.9 0.38 0.5623 0.23
F3 0.6305 2.82 0.6780 0.047 0.7809 23.1 0.8530 24.5 0.39 0.5698 0.34
F4 0.7601 3.75 0.6329 0.056 0.8880 12.9 0.9260 23.8 0.45 0.6855 0.32
F5 0.6217 1.01 0.6391 0.012 0.7568 7.62 0.8342 13.5 0.28 0.5658 0.19
F6 0.9114 3.16 0.9480 0.045 0.9788 11.7 0.9742 13.0 0.55 0.8162 0.37
F7 0.5439 1.54 0.5625 0.022 0.7032 14.9 0.8075 23.0 0.27 0.5040 0.22
F8 0.7707 4.10 0.9503 0.049 0.8902 14.9 0.9431 15.5 0.61 0.7164 0.41
F9 0.6108 2.31 0.5850 0.023 0.7685 17.5 0.8550 20.6 0.39 0.5623 0.30
F10 0.6582 2.34 0.7074 0.037 0.8009 17.4 0.8542 18.8 0.34 0.4706 0.25
F11 0.6898 1.85 0.7130 0.028 0.8332 7.44 0.9160 25.0 0.26 0.6490 0.18
F12 0.6391 2.21 0.6799 0.034 0.7779 8.23 0.8581 24.3 0.32 0.5864 0.21
F13 0.7914 3.07 0.8476 0.057 0.9113 10.6 0.9522 29.7 0.33 0.7304 0.25
F14 0.8469 4.64 0.9212 0.090 0.9401 36.0 0.9526 21.6 0.52 0.7643 0.51
F15 0.6834 3.11 0.7048 0.048 0.8266 25.3 0.9095 18.7 0.48 0.6399 0.41
F16 0.7711 2.70 0.8261 0.043 0.8856 19.3 0.9212 19.1 0.36 0.4929 0.25
F17 0.6319 3.81 0.6907 0.068 0.7005 27.3 0.8567 16.1 0.50 0.5798 0.43
Reference [66] [67] [68] [65,66] [69]
Table 8. A summary of the performance and errors of active networks.
Network name Training R2 Training MSE Validation R2 Validation MSE Test R2 Test MSE
MLP 3-15-7 0.628 1701889000 0.714 13201600000 0.143 1537634000
MLP 3-15-7 0.939 195832100 1.00 11268170000 0.143 1285729000
RBF 3-8-7 0.707 3061927000 1.00 13525990000 0.714 2469156000
MLP 3-18-7 0.650 4446476000 0.714 15960670000 0.143 1721968000
RBF 3-7-7 0.701 3106071000 1.00 13160060000 0.714 2006103000
MLP 3-5-7 0.662 778474300 0.714 9708287000 1.00 369282700
MLP 3-3-7 0.691 734481900 0.714 8505199000 1.00 104723700
model ranging from 0.80750.9742 and n values ranging from 0.28 to 0.61 and these are summarized inTable 7with the values of the best fitted model shaded with a dark gray color.
Hydrogels F13F17 exhibited an averagen value of 0.44 sug- gesting that LTG release occurredviaFickian diffusion wherein gel relaxation occurs slower that the penetration of the dissolution medium into the gel matrix [70,71]. The release of LTG was ini- tially diffusion controlled and then was gel degradation controlled [72]. Hydrogel formulations, F1, F2, F3, F4, F5, F7, F9, F10, F11 and F12 also released LTG via exhibited Fickian diffusion. The release data for F6 was best fitted to the Higuchi model wherein LTG release occurredvia diffusion of the API from the gel matrix with slow degradation of the gel in the dissolution medium ]73]. The different release patterns for the hydrogels may be attributed to the composition of the hydrogels and model of LTG release as indicated by the mathematical models investigated. The difference in release patterns was due to the different extent of gelation and the aqueous phase content for each hydrogel which affected the mode of release viz, diffusion, gel erosion control.
Optimization of LTG hydrogel formulation using BBD and ANN.
ANN models were trained and the R2 and mean sum of squares error (MSE) values for select models are summarized listed in Table 8.
The best model was selected based on the lowest test MSE and an R2value above 0.95. The test MSE represents the predict- ive ability of the model and R2 represents how well data fits the model. Hence the selected model was MLP 3-3-7, marked as gray inTable 8.
The formulation for the desired final LTG hydrogel was selected based on the desired ranges for the responses and the optimiza- tion process was conducted using BBD and ANN. The relationship between the independent variables and the responses were defined and listed inTable 9.
These response values were defined on the established BBD and the generated solutions are summarized inTables 10and11.
The ANN that best described the relationship between the independent variable and responses was Multi-Layered Perceptron (MLP) 3-3-7 which generated the lowest test mean sum of errors (MSE) trained using Broyden-Fletcher-Goldfarb-Shano (BFGS) train- ing algorithm and activation functions for the hidden layer and output were both exponential functions. ANN predictions for the responses are summarized inTable 11.
The predicted responses for formulations, F13–F17 reveal that the network learnt the input-output data relationships. The formu- lation composition parameters provided by the BBD solution (Table 9) were inserted as custom inputs for the trained MLP model so as to compare the two approaches in their ability to predict the responses of the optimized hydrogel. ANN generated predicted responses as summarized inTable 12.
The mean residual sum of squares error (RSSE) for BBD was 13 448 147.71 and it was lower than the MSE of 104 723 700 for ANN revealing that BBD generally exhibited better predictive abil- ity than ANN for the responses. The optimized hydrogel was man- ufactured and assessed for thermosetting behavior, pH and LTG release and the results are summarized inTable 13.
The % LTG released at 2 and 6 h was slightly lower than the predicted responses with an 8.73% difference for 2 h and 8.8% dif- ference for 6 h. The % LTG released at 12 h was slightly higher than that predicted with a 7.06% difference. The viscosity of the hydrogel at 22C was>1,00,000 cP which was more viscous than required and the amount of L127 in the hydrogel formulation should be reduced to lower the viscosity. Lower viscosity will allow convenient administration into the nasal cavity. A reduction of L127 may increase LTG release rate and extent due to less hydrophobic interactions and less entrapment in the micelles. The optimized hydrogel successfully undergoes gelation from 22 to 34C observed from the change in viscosity and the sol-gel transi- tion time of 60 s.
The experimentally obtained pH of the optimized hydrogel was as predicted by BBD and slightly lower than that which was deter- mined by ANN with a 1.26% difference which was not significant.
LTG release data from the hydrogel were best fitted to Korsmeyere-Peppas model and ann value of 0.371 revealing that LTG release occurred via Fickian diffusion. The release profile of LTG from the optimized hydrogel is depicted inFigure 8.
0 10 20 30 40 50 60 70 80 90 100
0 2 4 6 8 10 12
cumulative LTG released, %
Time, hr
F1 F2 F3 F4 F12 F14
Figure 7. Cumulative % of LTG released from formulations manufactured following BBD (mean ± SD,n¼3).
Table 9. Summary of response upper and lower limits.
Response Lower limit Upper limit
Viscosity at 22C (cP) 7586 10000
Viscosity at 34C (cP) 141100 350000
Sol-gel transition time (s) 55 60
LTG released at 2 hours (%) 19.72 25
LTG released at 6 hours (%) 30 50
LTG released at 12 hours (%) 60 100
Conclusions
An optimized smart thermosetting LTG hydrogel was successfully manufactured with two grades of poloxamer viz,188 and 407 and a mucoadhesive agent. Using BBD, levels of L127, L68 and C974 were identified and their influence on viscosity at 22C, viscosity at 34C, sol-gel transition, pH and % LTG released at 2, 6 and 12 h was established. Polynomial equations generated for each
response were used to describe the impact the L127, L68 and C974 on the responses. ANN was used to optimize the hydrogel formulation from the relationships identified and established by BBD. The optimized hydrogel possessed ideal thermosetting behavior but its viscosity at 22C is undesirable and the amount of L127 must be reduced to lower viscosity to 10,000 cP.
Hydrogels with viscosity>10 000 at 22C are stiff gels and would be difficult to administer to the olfactory region via a suitable Table 10A. BBD predictions based on custom inputs.
Gel L127 % L68 % C974 %
Viscosity at 22C cP
Viscosity at 34C cP
Sol-gel
transition s pH
LTG released at
2 hours %
LTG released at
6 hours %
LTG released at 12 hours %
1 25.00 13.94 0.380 135785 269929 55 5.50 39.97 52.71 60.00
Table 11. ANN predictions for the responses.
Formulation
ANN prediction
Viscosity at 22C cP Viscosity at 34C cP Sol-gel transition s pH LTG released at 2 h % LTG released at 6 h % LTG released at 12 h%
F1 6092 7241 0.50 5.23 24.37 29.47 34.24
F2 291648.2 332664.1 46.4 5.49 39.87 50.87 61.30
F3 6092 8403.7 7.77 5.75 40.51 41.03 37.06
F4 387726.9 342515.9 47.2 5.64 39.93 51.18 62.52
F5 6092 7319.2 0.90 6.19 34.28 36.67 36.54
F6 373411 334085 46.3 5.66 39.90 51.13 62.50
F7 6092 7241.4 0.50 5.12 25.75 30.20 32.83
F8 313153.6 351968.6 49.2 5.47 40.01 51.02 61.26
F9 14085.4 107780.8 29.9 5.43 39.74 48.16 53.16
F10 52296.6 219787.8 70.4 5.94 42.23 51.17 55.78
F11 6895.2 61327.9 15.1 5.16 37.82 45.25 48.51
F12 31738.6 226115.5 66.7 5.35 41.80 50.30 53.38
F13 22054.9 166024 48.2 5.39 40.96 49.42 53.31
F14 22054.9 166024 48.2 5.39 40.96 49.42 53.31
F15 22054.9 166024 48.2 5.39 40.96 49.42 53.31
F16 22054.9 166024 48.2 5.39 40.96 49.42 53.31
F17 22054.9 166024 48.2 5.39 40.96 49.42 53.31
Table 12. Custom input predictions generated by MLP 3-3-7.
Gel L127 % L68 % C974 %
Viscosity at 22C cP
Viscosity
at 34C cP Sol-gel transition s pH
LTG released at 2 h %
LTG released at 6 h %
LTG released at 12 h %
1 25.00 13.94 0.380 180633.5 305593.7 54.81 5.57 36.97 50.56 61.34
Table 13. Responses for the optimized formulation.
Formulation
Viscosity at 22C cP
Viscosity
at 34C cP Sol-gel transition s pH
LTG released at 2 h %
LTG released at 6 h %
LTG released at 12 h %
Optimized formulation 129 000 >350 000 60 5.50 36.48 ± 0.33 48.07 ± 0.16 64.24 ± 0.31
−10 0 10 20 30 40 50 60 70
0 2 4 6 8 10 12 14
Cumulative LTG released, %
Opmised hydrogel BBD predicon ANN predicon
Figure 8. Cumulative % of LTG released from the optimized formulation (mean ± SD,n¼3) and BBD and ANN predictions.
