In vitro–in vivo–in silico simulation studies of anti-tubercular drugs doped with a self nanoemulsifying drug delivery system

Abstract

This study aimed to formulate a self-nanoemulsifying drug delivery system (SNEDDS) for enhanced pharmacokinetic (PK) behavior of rifampicin and isoniazid using excipients holding innate anti-mycobacterial activity followed with in vivo–in silico predictions using GastroPlus™. The optimized formulations of rifampicin (RIF-OF1) and isoniazid (INH-OF1) were characterized for drug loading efficiency, viscosity, optical clarity, particle size, zeta potential, morphological assessment and in vitro drug release. The oral bioavailability of RIF-OF1 and INH-OF1 was estimated in rats using validated UPLC MS/MS. The results of in vitro studies showed better drug loading, Newtonian rheological behavior and nanosized globular morphology of SNEDDS. In vitro drug release of both drugs was found to be higher at pH 1.2 and 6.8 as compared to their respective suspensions. The AUC and C_max values of RIF-OF1 were increased by 3.72 and 5.22 fold compared to the RIF suspension, respectively, whereas INH-OF1 has shown that these values increased by 1.604 and 2.69 times compared to the INH suspension, respectively. Parameter sensitivity analysis predicted the considerable effect of solubility and permeability on main PK profiles. GastroPlus predicted maximum compartmental absorption of RIF-OF1 from proximal and distal portions of intestine whereas INH-OF1 was mainly absorbed from the duodenum and jejunum portions followed with improved PK parameters. The MIC value of the optimized formulation was reduced as compared to the pure drug indicating drugs acting in tandem in the explored carrier. The study suggested that the explored strategy could be a suitable alternative to conventional delivery systems for improved oral bioavailability of anti-tubercular drugs working in tandem.

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1. Introduction

First-line anti-tubercular drugs (ATDs) are related to a significant degree of patient non-compliance due to prolonged treatment, emergence of drug resistance, poor permeation and toxicity.¹ Rifampicin (RIF) and isoniazid (INH) are strong first-line ATDs due to possessing efficient sterilizing activity as compared to other ATDs.² Despite having many admirable features, both drugs show several shortfalls during formulation development and treatment period. Furthermore, hepatotoxicity, flu-like syndrome, cytochrome P450 induction and inhibition of hepatic transporter leading to various drug–drug interactions are well established limitations of RIF which further complicate the therapy, especially when the patient is suffering from other infections.³ Moreover, significant reduction in oral bioavailability (BA) of rifampicin (∼32%) and its metabolite (∼28% as 25-desacetylrifampicin) is attributed to its instability (RIF) in stomach acid in the presence of INH when administered in combination dosage form.⁴ Recently, an attempt has been published to enhance oral BA of RIF by fabricating phospholipid–RIF complex in order to show improved solubility and stability in presence of INH. The C_max (from 48.5 to 54.3 μg ml⁻¹) and AUC (from 147.71 to 472.4 μg h ml⁻¹) of complex were found to be increased as compared to free drug solution.⁵ Bhandari and Kaur, studied the advantage of lipidic formulation (solid lipid nanoparticle) to circumvent the INH associated toxicity which showed six and four folds enhanced availability in the systemic blood and brain respectively, as compared to free drug at the same dose. Thus, significant improvement in relative BA, reduced hepatic toxicity and 3 folds higher LD₅₀ value were obtained.⁶ Moreover, slight aqueous solubility (∼1–2 mg ml⁻¹) and limited stability of highly permeable RIF (>2.0 × 10⁻⁶ cm s⁻¹) vary with pH owing to its amphoteric nature (isoelectronic point 4.8).^7,8 Some report has been investigated for favored and modified release of RIF from dosage form in the gastrointestinal tract at pH 6.8 leading to greater intestinal absorption and lower risk of acid degradation.⁸ On the other hand, hydrophilic INH (125 mg ml⁻¹) is highly permeable across the intestine (72 × 10⁻⁶ cm s⁻¹).⁹ In Mycobacterium cell, the complex chemical composition of Mycobacterium cell wall resulted in limited accumulation of INH due to poor permeability and efflux-pump mediated extrusion leading to extended drug resistance.¹⁰ Furthermore, poor patient compliance and drug induced severe hepatotoxicity are still the major issues during tubercular chemotherapy.

The inadequate and inefficient formulations still underline an urgent requirement of lipidic nanocarrier with enhanced oral BA and stability.¹¹ Role of nanotechnology (particularly lipid nanocarrier) is an intriguing delivery approach to improve the therapeutic efficacy of such ATDs. It is noteworthy that the idea of employing the exogeneous surfactant and lipids as excipients in carrier systems for ferrying ATDs with dual functions (delivery to the infection site and surfactant mediated alveolar stabilization) is gaining interesting support by numerous research scientists and formulators.^12–14 There is no any commercially available self-nanoemulsifying drug delivery system (SNEDDS) of RIF or INH employing medium chain glycerides (Capmul MCM C8) and surfactants (Labrasol) with inherent anti-Mycobacterium activity. To achieve this objective, we optimized SNEDDS holding innate anti-Mycobacterium activity to deliver RIF/INH with improved oral BA. Excipients (lipid and surfactant) possessing inherent anti-Mycobacterium activities have previously been reported by us.¹²

The study aimed to optimize the INH and RIF SNEDDS formulations followed with characterization for viscosity, optical clarity, particle size, zeta potential, morphological study using electron microscopy and in vitro drug release study at different pH. Furthermore, the study reported the pharmacokinetic profiles and established in vivo–in silico assessment of drug (INH and RIF) loaded SNEDDS. We evaluated pharmacokinetic parameters and simulated the in vivo absorption profile to assess the PK prediction based on the physicochemical parameters of the drugs and in vitro experimental data to simulate the in vivo absorption profiles using the in silico simulator GastroPlus™ software tool (version 9.0 simulations Plus Inc., Lancaster, CA, USA). Furthermore, it displayed regional absorption of the drug from liquid SNEDDS formulation from nine physiological compartments of the gastrointestinal tract (GIT).

2. Materials and methods

2.1 Materials

The tuberculosis strain (M. tuberculosis H37 Rv, ATCC 25618) was used in the present study (Tubercular centre, Ranchi, India). The strain was maintained in Lowenstein Jensen media (LJ media) at 37 ± 1 °C temperature and pH 7.0. Labrasol (LAB) and Cremophor® EL (CEL) were generously gifted from Gattefosse (St-Priest, Cedex, France) and BASF India Limited (Mumbai, India) respectively. The lipid Capmul MCM C8 (CMC8) was kindly gifted from Abitec Corporation (Janesville, Germany). Rifampicin (RIF) and isoniazid (INH) were provided by Unicure India Pvt. Ltd., (New Delhi, India). Milli-Q water was used in all experiments. All other reagents used were of analytical reagent (AR) grade.

2.2 Methods

2.2.1 Solubility study. To solubilize the maximum amount of RIF and INH in explored excipients (lipids, surfactants and co-surfactants), the solubility study was carried out at 40 °C following the reported method.¹⁵ The saturated solutions of the drugs (RIF and INH) were obtained by establishing the equilibrium between the dissolved and undissolved solute. To obtain the saturation solubility of drugs in various excipients, each excipient (3.0 ml) was taken in vials. Excess amount of the drugs were added into each excipient separately. Samples were equilibrated in a water bath shaker (Remi Equipments Pvt. Ltd., Mumbai, India) at 40 °C for 48 h to facilitate solubilization. After equilibrium, the samples were filtered using Sartorius filter paper (5–8 μm) to remove the undissolved drug. The filtrates were then suitably diluted with methanol and the amount of the drugs was quantified by the UV-Vis spectrophotometer. All measurements were carried out in triplicate.

2.2.2 Preparation of optimized liquid SNEDDS. SNEDDS formulations were prepared using CMC8, LAB and Cremophor-EL and optimized by the 3² full factorial experimental design technique of Design-Expert® 8.0.7.1 software (Stat-Ease, Inc., Minneapolis, MN). The CMC8 and LAB were finally selected as main excipients owing to innate anti-Mycobacterium activity as reported earlier.¹² Three levels of each factor (CMC8 and LAB concentration) in full factorial design (FFD) were selected.¹⁶ The independent variables (X₁ = LAB and X₂ = CMC8) and dependent responses (Y₁ = absorbance, Y₂ = zone of inhibition against MS-942, Y₃ = zone of inhibition against MS-995 and Y₄ = particle size) were selected to get the most optimum placebo SNEDDS formulations (OF1, OF2 and OF3).

The experimental design suggested three best optimized formulations (OF1–OF3) and these were prepared using varied amount of lipid (CMC8) and surfactant (LAB) containing constant amount of CEL (250 mg). OF1, OF2 and OF3 were composed of 500 mg, 475.25 mg and 459.1 mg of LAB respectively with constant amount of CMC8 (250 mg) and CEL (250 mg). Several drug loaded SNEDDS formulations (OF1, OF2 and OF3) were prepared using varied amount of RIF and INH individually. All excipients including the drug were accurately weighed and then subjected to manual mixing for sufficient time in designed ratio to attain isotropic blend. Finally, obtained pre-concentrate was reconstituted with distilled water (10 ml) under mild stirring to get a homogeneous drug loaded SNEDDS formulation without precipitation of the drug. Final products were stored under ambient temperature for further characterization studies.

2.3 Characterizations of liquid SNEDDS formulations

2.3.1 Dispersibility and emulsification efficiency measurements. The dispersibility and emulsification efficiency of SNEDDS were measured using a standard USP XXII dissolution apparatus II as per method.^15,17 All formulations were subjected to test the dispersibility and emulsification efficiency in Milli-Q water. One ml from each liquid SNEDDS formulations was dispersed in 500 ml Milli-Q water under constant stirring (50 rpm) using the stainless steel dissolution paddle at 37 ± 1 °C temperature. The formulations were observed visually for uniform dispersibility, presence of any particles and stable SNEDDS formation. Moreover, the formed nanoemulsions were visually assessed for complete dispersion and self-emulsification time (s).¹⁸ The test samples were graded after in vitro study based on visual observation as reported earlier.^15,18

Those formulations falling under grade-A category (rapidly forming nanoemulsion having a clear or slight bluish color within minute) with maximum drug loading efficiency were selected for further study.

2.3.2 Drug loading efficiency. The drug loading efficiency of RIF and INH in the optimized OF1–OF3 was determined by dispersing the weighed amount of formulation in a volumetric flask containing 100 ml methanol. It was then mixed followed by sonicated to extract RIF and INH completely. Insoluble excipients (if any) were then separated by the centrifugation at 5000 rpm (3500 × g) for 15 min.¹⁸ The supernatants were collected and filtered through membrane (Millipore Mumbai, India) and duly diluted (with methanol). Samples were than analyzed using UV-Vis spectrophotometer at a λ_max of 337 nm and 262 nm for RIF and INH, respectively. The study was performed in triplicate manner. The drug loading efficiency of formulations was calculated using the reported formula.¹⁹

Loading efficiency = (total amount of drug − free drug in supernatant)/total amount of drug

2.3.3 Viscosity measurement. The rheological assessment of the isotropic blend was assessed by following the method reported earlier.²⁰ The viscosity of optimized (OF1, OF2, OF3) and drug loaded formulations were carried out using the Brookfield viscometer (rotary viscometer) equipped with coaxial cone and plate (Bohlin Visco 88, Malvern, UK) at 25 ± 1 °C temperature. The viscous liquid blend (constant amount) was placed on the plate portion uniformly and the cone was set to move between the available blend for fixed period of time. The measurements were carried out in triplicate to get mean value. The values were expressed in cP unit.

2.3.4 Optical clarity (absorbance value). Placebo optimized SNEDDS (OF1–OF3) and drug loaded SNEDDS formulations (RIF-OF1, RIF-OF2, RIF-OF3, INH-OF1, INH-OF2 and INH-OF3) were subjected for optical clarity using UV-Vis spectrophotometer (UV-1800, Shimadzu, Japan) at 600 nm against distilled water as blank. Samples were measured after aqueous dilution (ten times) using Milli-Q water [Millipore, Molsheim, France]. Milli-Q water was considered as reference for 100 percent transmittance. The completely dispersed sample can be estimated for its clarity quantitatively by transmitting the light of particular wavelength (600 nm). Usually, lower the value of absorbance, higher would be the transmittance suggesting clear solution, since turbid and cloudy dispersion possesses higher absorbance owing to scattering of incident radiation.²¹

2.3.5 Particle size, size distribution and zeta potential. Freshly prepared RIF-OF1, RIF-OF2 and RIF-OF3 containing 150 mg drug were diluted 100 times with Milli-Q water under mild stirring at 25 °C temperature. Particle size analysis was based on the principle of dynamic light scattering principle using Malvern Zetasizer (Malvern Zetasizer Nano ZS-90 Worcestershire, UK). The value of polydispersity index (the width of the size distribution) is measured concurrently at the same experimental conditions (at 25 °C temperature and 90° scattering angle). In order to measure zeta potential, the formulations were diluted 100 times with Milli-Q water and then agitated well before analysis.²² The surface charge distribution on the globules was measured using the same instrument and same experimental conditions. Analysis was performed in triplicate manner to report the value in mean and standard deviation. Similarly, freshly prepared INH-OF1, INH-OF2 and INH-OF3 containing 75 mg drug were used for the same study under same experimental conditions.

2.3.6 Morphological assessment using transmission electron microscopy (TEM). The morphological architecture of developed liquid SNEDDS formulations was carried out using TEM method. The TEM analysis was performed after dilution with Milli-Q water (1 : 25) and mixed well by gentle shaking to get homogeneous mixture. A drop of diluted formulation was placed on the copper grid and stained using 1% w/v phosphotungstic acid solution.^20,23,24 The excess sample was immediately removed using filter paper and left over night to get the dried grid for clear scanning and image observation. Then, the sample was visualized for morphological characteristics of globules under transmission electron microscopy (Philips Tecnai 12, Eindhoven, Netherlands). The microscope was operated at 10.0 kV acceleration voltages and maintained at ambient temperature. Images were produced at various magnifications. The comparison between particle size obtained from TEM and Zetasizer was compared using fold error (FE) equation (FE = 10^{log(particle size,TEM/particle size,Zetasizer)}) for the first time.

2.3.7 In vitro drug release profile: comparative studies. In vitro RIF release studies were performed for optimized liquid SNEDDS (OF1–OF3) loaded with rifampicin (150 mg) in each formulation. The studies were carried out in 900 ml simulated gastric fluid (SGF, 0.1 M HCl, pH 1.2) as well as simulated intestinal fluid (SIF, phosphate buffer, pH 6.8) without any enzyme.²⁵ Release study was carried out using USP Apparatus II (Electrolab Mumbai, India) stirred at 75 rpm and temperature of 37 ± 1 °C. Pre-concentrate liquid SNEDDS formulations were filled into the hard gelatin capsule containing equivalent amount of RIF.¹⁸ After achieving experimental conditions, capsule was placed into the vessel using a sinker. Samples (5 ml) were taken out at predetermined time intervals (2, 5, 7, 10, 15, 60 and 120 min) and filtered through membrane filter (0.45 μm) before analysis. Then, the concentration of drug was analyzed using UV-Vis spectrophotometer (U-1800, Shimadzu, Japan) at 337 nm.

Similarly, in vitro INH release studies were carried out for INH-OF1, INH-OF2 and INH-OF3 containing INH (75 mg) under same sets of condition. The drug amount was analyzed using spectrophotometer at 262 nm. In vitro dissolution data such as time required to dissolve 50 and 85% of formulation were calculated and cumulative percent drug release versus time (min) were plotted. The study was performed in triplicate.

3. Estimation of RIF and INH using ultra high performance liquid chromatographic-mass spectrometry (UPLC-MS/MS)

A UPLC (Ultra High Performance Liquid Chromatographic) system (Thermo Surveyor system, City, USA) consisted of a reverse phase C18 column (Purospher Star RP-18 HPLC cartridge column) (50 mm × 4.6 mm, internal diameter of 3 μm; Merck, Germany) and a rotary vacuum pump (E2M30, Edwards High Vacuum International, West Sussex, UK) along with a nitrogen generator (Nitro Generator, Products of Technology Ltd., Killearn, UK) was employed to elute the analytes. The UPLC system was interfaced with a triple quadrupole mass spectrometer API-4000 QTrap conjugated with a turbo electrospray ionization (ESI) source (MDS SCIEX, Applied Biosystems, USA), operating in positive mode. The operating conditions were interfaced at optimum value of the spray voltage (4500 V), tube lens voltage (124 V) and the capillary temperature (275 °C). The nitrogen gas was used as the sheath and auxiliary gas at pressure of 40 psi and 25 psi respectively. Moreover, the collision energy values for RIF and INH were set at 10 and 20 eV respectively.

The mobile phase composition for RIF was acetonitrile (ACN) containing methanol and 2 mM ammonium acetate buffer (80 : 20 v/v). The mobile phase was filtered through membrane filter (0.45 μ) followed with degassing by ultrasonication method (ultrasonication bath) before use. Analysis of RIF was carried out at flow rate of 0.5 ml min⁻¹ and run time of 3.5 min after injecting 5 μl (sample volume). Moreover, INH was analyzed using water and ACN (85 : 15 v/v) combination as mobile phase. Water contained 0.1% HOAC and 2.5 mM ammonium acetate and ACN was with added amount of 0.1% HOAC. The filtered mobile phase was injected with flow rate, total run time and injection volume of 0.2 ml min⁻¹, 2.5 min and 10 μl respectively. Linear calibration curve with effective concentrations for RIF and INH were prepared in rat plasma separately keeping regression coefficient value (r²) ≥ 0.99. The standard curve concentration range of 12.27–7999.92 ng ml⁻¹ and 27.59–3595.99 ng ml⁻¹ were prepared along with their three levels of quality control (QC) samples of RIF and INH, respectively. The lower limit of detection (LLOD) and the lower limit of quantification (LLOQ) for each analyte were 0.012 μg ml⁻¹ and 0.01 μg ml⁻¹ for RIF and 0.011 μg ml⁻¹ and 0.014 μg ml⁻¹ for INH. The spiked samples of calibration curve were allowed to inter-day and intra-day subject variation analysis with a precision of less than 20% and accuracy of 80–120%. The precision and accuracy were evaluated at three concentrations of LQC, MQC and HQC at the same day and three consecutive days for intra-and inter day variation, respectively.

4. Pharmacokinetics studies

In vivo pharmacokinetics studies were performed on Sprague-Dawley rats (SD rats) issued from the Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology; Mesa Ranchi-835215. The study was performed in compliance with the CPCSEA (Committee for the purpose of control and supervision of experiments on animals, Ministry of Environment, Government of India) guidelines with subsequent approval from Institutional animal ethics committee (IAEC) for animal experimentation (approval number: BIT/PH/IAEC/25/2013). Animals were kept on fast condition 12 h before the commencement of the experiment with free access to water. They were randomly grouped consisting six rats in each. Group-I and II were administered with RIF suspension and RIF-OF1 SNEDDS formulation respectively at a dose of 24 mg kg⁻¹. Similarly, the group-III and IV received INH suspension and INH-OF1 SNEDDS formulation respectively (15 mg kg⁻¹). Blood samples were obtained from the retro-orbital sinus at the different time points as 0.5, 1, 2, 4, 8, 12 and 24 h in polypropylene tube (wrapped in aluminum foil) containing EDTA (ethylene diamine tetra acetic acid) and sodium ascorbate. Plasma was centrifuged at 4000 rpm (2240 × g) for 10 min to separate the plasma immediately and stored at −80 °C for further analysis. The samples were analyzed using validated UPLC-MS/MS techniques to estimate the pharmacokinetic parameters such as C_max (the maximum concentration reached in plasma), T_max (time to reach the C_max), area under the plasma concentration curve from time zero to the last measured concentration (AUC_0–t), K_e (elimination rate constant), T_1/2 (terminal elimination half life) and MRT (mean residence time). Moreover, the K_e, elimination half life (T_1/2) and total clearance (CL) were calculated by the slope of the termination phase (log plasma concentration time curve), dose by AUC and 0.693/K_el respectively. In addition, the area under the first moment curve (AUMC) was calculated by the area under the product of time and concentration versus time curve. The mean residence time (MRT) was the ratio of the AUMC and AUC whereas the product of MRT and CL was the steady state volume of distribution (V_ss). Relative bioavailability (F) was calculated as: F = [AUC_0–∞ (test)/AUC_0–∞ (reference)] × 100.

5. In silico simulation studies by GastroPlus™

The plasma PK parameters were determined using the PKPlus module of GastroPlus™ software version 9.0 (Simulation Plus Inc., Lancaster, USA) in non-compartmental mode. The GastroPlus™ software simulates using an advanced compartmental absorption and transit model based on physiological based oral absorption model containing several compartments (nine) representing different segments of the GIT. The software was used to simulate the in vivo absorption performance of the developed INH-SNEDDS and RIF-SNEDDS. The program provided three tabs (compound, physiological and pharmacokinetic) for data input during simulation processing. Experimental (such as in vitro dissolution profile) or literature or ADMET Predictor™ based physicochemical parameters were fed into the compound tabs. The software default rat fasted physiology with transit time (default value) in all compartment was used in the same physiology tabs and further simulated (GastroPlus™ in-built compartment model) their in vivo oral absorption profile from the micro-constant and disposition parameters. Next, the predicted parameters (C_max, T_max, AUC), cumulative amount of the drug permeated across the intestinal membrane (F_a) and oral BA were compared against the obtained experimental values assessed by the best fit model of PKPlus™ module when imported into the PK tabs. The software provided additional informative PK parameters such as the volume of the central compartment (V_c), clearance (CL), absorption rate constant (K_a), re-distribution rate constant (K₂₁, K₃₁) and elimination rate constant (K₁₀). The extent of absorption of the drug loaded in SNEDDS from different GI segments (nine physiological compartments) was also evaluated using the GastroPlus simulation tool which was prudent to correlate the regional based drug absorption from the GIT.

The prediction accuracy of the PK parameters was considered to be high when the prediction fold error fall within two fold of observed values for the PK parameters.²⁶ The best fit model was selected with the regression co-efficient (r²) and statistical tests (Akaike Information Criterion, CIA and Schwartz Criterion, SC).

6. Determination of minimum inhibitory concentration (MIC)

MIC values of pure drugs (RIF and INH) and the drug loaded optimized formulations (RIF-OF1 and INH-OF1) were estimated against the M. smegmatis cultures (MS-942 and MS-995) and M. tuberculosis. The sterilized nutrient broth (NB) was used to revive the M. smegmatis strains whereas M. tuberculosis H37 Rv was grown in Middlebrook 7H9 broth supplemented with albumin dextrose complex following the method reported earlier by us.¹² In brief, the sterilized nutrient agar (NA) medium was cooled down to the room temperature for mixing the grown culture of MS-995 (2.5 × 10⁷ CFU ml⁻¹) and MS-942 (1.8 × 10⁷ CFU ml⁻¹) with test formulation separately. The dispersed suspension was transferred to Petri dishes (30 ml) and left for solidification.

In case of M. tuberculosis, the LJ (Lowenstein-Jensen) media was inoculated (one loopful) with previously grown culture (standard dilution of 10⁻⁴) and incubated at 37 ± 1 °C for 6 weeks. Standard dilution of 10⁻⁴ was prepared to inoculate the LJ media contained in McCartney vial. The control McCartney vial test sample (formulation or drug) and vial containing test sample were incubated overnight (12 h) in a slant position with loosened cap at 37 ± 1 °C temperature. Then, the cap was tightly closed and again incubated for period of 6 weeks in upright position. The entire work was carried out taking all care of safety issues. The MIC was determined as the lowest concentration responsible for complete inhibition of the strain after incubation period.

7. Results and discussion

RIF and INH solubility were carried out in various lipids and surfactants. Peceol, Lipoxol 300MED, Capmul PG8 and CMC8 showed considerable solubility of INH amongst the lipids. INH was more solubilized in LAB, Transcutol CG and PEG-400 amongst the surfactants. Similarly, RIF was solubilized more in Acconon C8 and CMC8 amongst the lipids as well as LAB, Transcutol CG and PEG-400 amongst the surfactants. The solubility of INH and RIF in CMC8 and LAB were found to be 31.44 ± 1.26, 39.20 ± 2.49 and 64.35 ± 5.5, 36.14 ± 0.03 mg ml⁻¹, respectively (ESI Fig. S1†). Moreover, the CMC8 and LAB exhibited maximum in vitro anti-Mycobacterium activity among all explored excipients which were the basis for final selection of these potential components of SNEDDS for further investigations as reported earlier by us.¹²

7.1 Preparation of optimized liquid SNEDDS

SNEDDS formulations (OF1–OF3) were finally optimized and selected for loading the INH and RIF separately. The objective of using these optimized formulations was the application of nanoemulsion carrier with concerted anti-Mycobacterium activities which could lead to produce enhanced absorption than conventional oral dosage form. Moreover, such formulation comprising of excipients (CMC8 and LAB) holding innate anti-Mycobacterium can be transformed into SNEDDS for hosting and ferrying ATDs working in tandem if laden as reported earlier.¹² Prepared SNEDDS formulations were isotropic, clear and stable before and after loading the drug into the formulations. INH loaded SNEDDS (INH-OF1, INH-OF2 and INH-OF3) and RIF loaded SNEDDS (RIF-OF1, RIF-OF2 and RIF-OF3) were prepared and evaluated separately. Some authors reported a significant interaction of drugs (INH and RIF) on oral absorption when formulated in fixed dose combination of conventional dosage form.⁴ Therefore, INH (75 mg g⁻¹) and RIF (150 mg g⁻¹) were loaded separately to fabricate the corresponding SNEDDS. These formulations were stored and protected from light for further studies.

7.2 Drug loading efficiency

INH and RIF loading efficiency in SNEDDS were estimated from the INH-SNEDDS (INH-OF1, INH-OF2 and INH-OF3) and RIF-SNEDDS (INH-OF1, INH-OF2 and INH-OF3) formulations respectively. All developed RIF-SNEDDS and INH-SNEDDS showed RIF and INH loading efficiency in the range of 97.6–98.34% and 94.5–96.5%, suggesting the maximum loading of the drug in the formulation with minimum loss while formulation fabrication.

7.3 Selection of drug loaded SNEDDS formulations

The optimized formulations were obtained after experimental design technique against various desired responses (absorbance, zone of inhibition, particle size). Furthermore, drug was loaded in optimized formulations with increased drug concentration (40–150 mg g⁻¹ for RIF and 25–100 mg g⁻¹ for INH) and observed for homogeneous, isotropic and precipitation free SNEDDS followed with dispersibility and emulsification efficiency as shown in the ESI Table S1.† From the Table S1,† it can be observed that with increase in concentration of RIF and INH, the SNEDDS were homogeneous and precipitation free up to 150 and 75 mg, respectively which indicates maximum loading of RIF as compared to INH. This difference may be due to more lipophilic nature of RIF (log P = 3.79) as compared to hydrophilic INH (log P = −0.64). Moreover, similar trends were observed with emulsification efficiency of RIF and INH loaded SNEDDS formulations suggesting immediate release of drugs from the formulation due to increased drug solubility and difference in partition co-efficient value.

Thus, the SNEDDS of the grade A with optimum emulsification time were selected based on visual observation for uniform dispersibility after dispersion with water media.

7.4 Characterizations of SNEDDS formulations

7.4.1 In vitro characterizations of liquid SNEDDS. Liquid SNEDDS formulations with maximum drug content and passing the dispersibility test were screened for characterizations. Table 1 portrayed the characterization parameters of the selected RIF-SNEDDS (RIF-OF1, RIF-OF2, RIF-OF3) containing 150 mg and INH-SNEDDS (INH-OF1, INH-OF2 and INH-OF3) containing 75 mg drug for viscosity, absorbance, droplet size and size distribution, and zeta potential. The viscosity of RIF-SNEDDS and INH-SNEDDS were found in the range between 132.7 ± 11.9–171.4 ± 15.2 cP for RIF and 109.5 ± 9.5–137.2 ± 10.6 cP for INH respectively while the absorbance values (inverse of percent transmittance) were ranged from 0.183 ± 0.06 to 0.231 ± 0.05 and 0.101 ± 0.02 to 0.179 ± 0.08 for RIF and INH respectively (Table 1). From the results of viscosity assessment, it can be observed that the RIF loaded SNEDDS showed higher viscosity than INH loaded SNEDDS which may be due to more lipophilic nature of RIF as compared to INH. Lipophilic RIF was more viscous in blend of excipients due to lipophilic–lipophilic adhesive force. Low viscosity is one of the characteristic features of the nanoemulsion to exhibits Newtonian flow behavior.^15,27 To support the qualitative assessment obtained visually (optical measurement), spectroscopic method was used to differentiate among them quantitatively for comparison during optimization. Similar findings were reported that aqueous dispersion of SNEDDS formulations with lower value of absorbance were optically clear and globular size were considered to be in nanoscale range for stable SNEDDS.²¹ Results revealed that there is slight increase in absorbance value after drug loading in all SNEDDS formulation as compared to blank OF1 (0.125 observed value near to predicted 0.137 value) which could be due to drug molecules encapsulated into the globules.

Table 1 Evaluating parameters of optimized SNEDDS^a

Optimized liquid RIF loaded SNEDDS (150 mg) and INH loaded SNEDDS (75 mg) formulations
Code	Abs. (400 nm)†	Globular size (nm)		Charge (mV)	Viscosity (cP)	In vitro drug release (buffer pH 1.2)		In vitro drug release (buffer pH 6.8)
		Z-Average	PDI			T50% (min)	T85% (min)	T50% (min)	T85% (min)
a RIF: rifampicin, SNEDDS: self-nanoemulsifying drug delivery system, PDI: polydispersity index, † = absorbance after 30 times dilution, values in parenthesis indicate the ±standard deviation.
RIF-OF1	0.183 (0.06)	183.5 (9.0)	0.57 (0.02)	−4.27 (0.26)	132.7 (11.9)	1.56 (0.05)	5.56 (0.11)	3.42 (0.02)	6.51 (0.04)
RIF-OF2	0.207 (0.03)	208.2 (43.7)	0.55 (0.08)	−2.98 (0.12)	147.6 (9.5)	3.99 (0.12)	8.28 (0.22)	7.08 (0.05)	9.85 (0.04)
RIF-OF3	0.231 (0.05)	232.2 (14.1)	0.6 (0.04)	−3.95 (0.08)	171.4 (15.2)	4.97 (0.11)	9.76 (0.11)	8.09 (0.15)	14.7 (0.21)
INH-OF1	0.101 (0.02)	194.1 (16.62)	0.56 (0.04)	−3.63 (0.12)	109.5 (9.5)	3.56 (0.05)	5.95 (0.08)	11.25 (0.1)	12.77 (0.21)
INH-OF2	0.112 (0.01)	211.6 (3.18)	0.49 (0.01)	−6.61 (0.26)	123.1 (5.2)	5.38 (0.8)	8.68 (0.1)	11.8 (0.17)	13.75 (0.67)
INH-OF3	0.179 (0.08)	227.4 (30.69)	0.59 (0.03)	−5.01 (0.11)	137.2 (10.6)	8.31 (0.2)	12.0 (0.6)	12.0 (0.14)	15.01 (0.20)

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Globular mean size of RIF-SNEDDS and INH-SNEDDS formulations using the dynamic light scattering method were in the ranged of 183.5 ± 9.0–232.2 ± 14.1 nm and 194.1 ± 16.62–227.4 ± 30.69 nm respectively, which suggested that emulsification process caused the formation of nanoemulsion after aqueous dilution (hundred times). The lowest value of particle size may probably be owing to comparatively higher amount of surfactant LAB (500 mg, LAB) in OF1 as compared to others (OF2 and OF3) leading to efficient emulsification of drug loaded OF1 under mild agitation after dilution with Millipore water. The particle size is the deciding factor for efficient emulsification of the formulation in vitro to simulate the in vivo performance at the intestinal membrane. Generally, the smaller particle size has several advantages over larger one such as efficient emulsification, increased surface area, increased dissolution in hydrophilic mucous layer, increased drug absorption and increased intra-enterocyte endoplasmic reticulum processing for chylomicron formation. Thus, the system may yield more reproducible and increased BA of the drug loaded SNEDDS. In this investigation, we developed formulations with addition of constant amount of co-surfactant (Cremophor EL) in (250 mg) which played a vital role in efficient emulsification of nanoemulsion formulation (SNEDDS). Formulations containing mixture of oil and a single surfactant are able to form only emulsion (conventional) or microemulsion.²⁸

Furthermore, the surface charge distribution in term of zeta potential for RIF and INH loaded SNEDDS were found to be from −4.27 to −3.95 mV and −3.63 to −6.67 mV respectively, corroborating negative charge distribution over nano-globules.²⁹ Moreover, the hydrophilic nature of non-ionic LAB (HLB = 12) is required for the immediate emulsification of oil-in-water SNEDDS in aqueous medium. CMC8 is lipid and may cause phase separation with inefficient amount of LAB and CEL while SNEDDS fabrication. Similarly, lipophilic drug (RIF) may be precipitated in the gastro-intestinal tract after administration with such SNEDDS. Therefore, the amphiphilic LAB is capable to dissolve and solubilize relatively the high amount of CMC8 and prevents the lipophilic drug (RIF) from precipitation in the GIT lumen after oral administration. Thus, drug loaded lipid prolonged the existence of drug in soluble form leading to effective absorption (increased BA).²⁸ The intestinal hydrophilic mucous membrane further assists the emulsification of hydrophilic drug such as INH and presents no barrier at absorption site. However, INH loaded in SNEDDS is capable to enter across the biological lipophilic membrane (barrier) via several reported mechanisms as explained earlier in this section.

The study prepared the RIF loaded SNEDDs using CMC8 (monoglycerides), CEL and LAB (P-gp efflux pump inhibitor) to improve its absorption (oral BA) by avoiding hepatic first-pass effect, inhibiting the P-gp efflux and promoting lymphatic transport. Chemotherapeutic potential could be improved due to synergistic activity of excipient against Mycobacterium. It was reported that lipophilic drug and higher lipids avoids hepatic metabolism leading to improved oral BA.³⁰ This may be additional advantage of high drug payload capacity in CMC8 based formulation.³⁰

7.4.2 Morphological assessment using TEM method. Morphological assessment of blank and drug loaded SNEDDS formulations (OF1, RIF-OF1 and INH-OF1) were performed using TEM. The shape of the uniformly distributed nanoglobules was spherical as illustrated in the Fig. 1A–C. Furthermore, comparing the TEM analysis report (∼100 nm) with DLS findings (RIF SNEDDS: 183.5–232.2 nm; INH SNEDDS: 194.1–227.4 nm) the fold error (FE) ranged between 0.430–0.544 and 0.439–0.515 for RIF and INH SNEDDS, respectively. It is noteworthy that the particle size measured by the TEM was biased owing to the preferential adsorption of smaller particles on the grid. This may be plausible reason why TEM studies showed particle size around 100 nm in our case. The TEM sample was prepared by placing a drop on the perforated carbon grid and the dispersion passes though the pores of the same grid. The smaller globules have a higher propensity to diffuse across the streamlines and settle on the carbon film. This leads to biasness towards smaller sizes. Similar finding was also reported by J. Tuoriniemi et al., 2014.³¹

Fig. 1 TEM microphotographs of SNEDDS: blank OF1 (A), INH-OF1 (B) and RIF-OF1 (C).

This uniform and smaller size suggested that the surfactants (LAB and CEL) mixture (S_mix) was adequate in amount to emulsify the drug loaded lipid in nanoemulsion droplets which could act as dual behavior such as enhanced oral absorption and increased bacterial killing due to augmented surface area.¹² On the other hand, it is as important aspect to extract the vital role of nanoscale formulation (nanoemulsion) for antimicrobial action. Hamouda and Baker Jr reported that there are several mechanisms for bacterial killing with surfactant lipid preparation such as osmotic effect of water present in nanoemulsion leading to irregular vacuolization in cells of E. coli.³² Moreover, enhanced bacterial damage may be due to globular fusion and subsequent internalization within the cells. Conclusively, the nanocarriers could be used as novel approach for delivery of anti-tubercular drugs due to dual functions when transformed into SNEDDS.

7.4.3 In vitro drug release profile: comparative studies. In vitro drug release studies of the prepared SNEDDS were investigated at two explored pH (pH 1.2 and pH 6.8) and compared against drug suspension (RIF) and drug solution (INH). The release pattern and its parameters (T_50% and T_85%) have been displayed in the Fig. 2 and Table 1 respectively. The results revealed that the optimized RIF-OF1, RIF-OF2 and RIF-OF3 portrayed 85% release within 10 min at both explored pH. Moreover, RIF-OF1 showed 85% drug release within 5.56 ± 0.11 and 6.51 ± 0.04 min at pH 1.2 and pH 6.8 respectively suggesting rapid RIF release at both pH as compared to RIF-OF2 and RIF-OF3 (Table 1). Similarly, the INH-OF1 showed 85% drug release within 5.95 ± 0.08 and 12.77 ± 0.21 at pH 1.2 and pH 6.8 respectively suggesting rapid INH release in both pH as compared to INH-OF2 and INH-OF3 (Table 1). Slightly rapid release of both drugs from OFI may be due to large content of LAB (500 mg) as an efficient emulsifier as compared to OF3 (∼460 mg). Similar findings were observed with respect to T_50% (Table 1).

Fig. 2 In vitro drug release profile of RIF loaded in optimized formulations (RIF-OF1, RIF-OF2 and RIF-OF3) under varied pH.

7.4.4 UPLC-MS/MS analysis. RIF and INH were quantified by validated UPLC-MS/MS method. RIF and INH were eluted at retention time of 2.11 and 1.13 min respectively within total run time of 3.5 min and 2.5 min respectively. The representative images of chromatogram of blank plasma, standard RIF and RIF in 4^th h sample after oral administration of RIF-OF1 to rat have been portrayed in the ESI Fig. S2† which revealed no considerable fronting and tailing of sharp and symmetric peaks. Effective concentrations for standard calibration curves were prepared with three levels of quality control (QC) samples at low (68.45 ng ml⁻¹, LQC), medium (548.99 ng ml⁻¹, MQC) and high concentrations (4038.42 ng ml⁻¹, HQC) with a precision of less than 20% and accuracy of 80–120%. Similarly, the representative images of chromatogram of blank plasma, INH and INH in 4^th h sample have been portrayed in the ESI Fig. S3.† Linear calibration curve for INH was prepared in rat plasma, keeping r² > 0.99. The LLOD (lower limit of detection) and LLOQ (lower limit of quantification) for INH were found to be 0.012 μg ml⁻¹ and 0.015 μg ml⁻¹ respectively. Effective concentrations for standard calibration curves were prepared with three levels of quality control (QC) samples at low (450 ng ml⁻¹, LQC), medium (1800 ng ml⁻¹, MQC) and high concentrations (3600 ng ml⁻¹, HQC) with a precision of ±20%. Percent recoveries of RIF from the plasma spiked were 95.28 ± 3.08, 98.34 ± 8.6 and 99.72 ± 11.7, respectively. Percent recoveries of INH from the spiked plasma were 99.56 ± 0.20, 96.25 ± 3.42 and 99.71 ± 3.31, respectively. The mean percent recovery of RIF and INH was found to be 97.70 ± 2.16 and 98.512 ± 1.95 respectively.

7.4.5 Pharmacokinetics evaluation. The PK analysis was carried out by the validated UPLC-MS/MS methods of orally administered drug loaded formulations (INH-OF1 and RIF-OF1) and the drug suspensions (INH and RIF) in rats. The mean plasma drug-concentration time curve profiles have been portrayed in the Fig. 3. The input parameters for ACAT model based analysis have been presented in the Table 2. The compartmental and non-compartmental based calculated PK parameters using the GastroPlus™ module (PKPlus™) are illustrated in the Tables 3 and 4. The compartmental analysis was performed to get a visual presentation of the drug disposition and suggested the 2 compartment as the best fit model for INH-OF1 and RIF-OF1 based on lower values of the AIC and SC with the higher value of r² as shown in the Tables 3 and 4. The findings of some pharmacokinetic parameters such as MRT, T_1/2 and CL were found to be significantly different in various compartment models which could be due to possessed central and multiple compartment models (peripheral hypothetical model).²⁶ These variations may be owing to heterogeneous nature of the body and the drug distribution does not follow the instantaneous process after administration.²⁶

Fig. 3 Plasma concentration time curves of (A) INH-OF1 and (B) RIF-OF1 from rat plasma.

Table 2 Summary of the input parameters for INH and RIF in ACAT model simulation^a

Parameters	RIF	INH
a Note: a = literature value (Trevaskis NL, et al., (2008); Lo, Y., (2003)); b = values obtained from experiment, c = prediction from ADMET Predictor module of GastroPlus simulation.
^aMolecular weight	822.94	137.14
^alog P	3.719	−0.64
^aAqueous solubility (mg ml^−1)	1.0–2.0	125.0
^aHuman permeability (Papp cm s^−1 × 10^6)	>2.0	72.7
^bDose (mg)	8.0	5.0
^bDose volume (ml)	2.0	2.0
^cClearance (L h^−1)	0.111	1.24
^cVolume of distribution (L)	0.512	6.35
^aElimination half life (h)	2–5	2.78
^bBody weight (kg)	0.3	0.3
^cSimulation time (h)	24	24
^aProtein binding	∼83.0	—

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Table 3 Comparative pharmacokinetic parameters of RIF formulations in several compartmental models^a

Pharmacokinetic parameters	RIF suspension				RIF SNEDDS
	NC	C1	C2	C3	NC	C1	C2	C3
a Values in parentheses indicate % CV; NC: non-compartment; C1: one compartmental; C2: two compartmental; C3: three compartmental; AUC: area under curve; AUMC: area under moment curve; CL: clearance; AIC: Akaike information criterion; SC: Schwartz criterion. AIC: Akaike information criterion, AUC: area under curve, AUMC: area under mean curve, Cmax: maximum plasma concentration, Tmax: time required to reach Cmax, MRT: mean residence time, SC: Schwartz criterion, T1/2: plasma half life of drug and F: relative bioavailability; * the value in the parenthesis indicates % CV.
Cmax (ng ml^−1)	5060 (268.1)				26 400 (1385)
Tmax (h)	2.0 (0.0)	—	—	—	6.0 (0.0)	—	—	—
AUC(0–t) (μg h ml^−1)	76.59 (3.58)	—	—	—	285.5 (15.6)		—	—
AUC(0–∞) (μg h ml^−1)	77.80 (3.98)	77.8 (3.98)	—	—	287.4 (16.7)	—	—	—
AUMC (μg h^2 ml^−1)	612.9 (32.85)	331.0 (16.4)	—	—	2213.3 (13.5)	994.0 (64.7)	—	—
MRT (h)*	7.878 (54.6)	4.604 (101.8)	—	—	7.701 (59.4)	4.238 (136.9)	—	—
Kel (h^−1)	0.205		—	—	0.249	—	—	—
T1/2 (h)	—	3.19	—	2.86	—	2.937 (52.39)	7.64 × 10^5 h	4.16 × 10^5 h
CL (L h^−1)*	0.103 (29.41)	0.111 (22.91)	0.118 (18.21)	0.118 (18.21)	0.028 (45.62)	0.034 (38.02)	—	0.033 (41.63)
Vss (L)	0.810	—	—	—	0.214		—	—
Vd (L)*	—	0.512 (99.19)	—	—	—	0.145 (36.06)	—	—
Vc (L)*	—	—	0.240 (133.2)	0.240 (49.42)	—	—	0.145 (19 711)	—
Ka (h^−1)*	—	—	0.242 (571.63)	0.241 (435.6)	—	0.236 (13.53)	0.236	0.236 (9089)
K10 (h^−1)*	—	0.217 (101.8)	0.489 (134.26)	0.49 (52.69)	—	0.236 (53.39)	0.228	0.227
K12 (h^−1)*	—	—	2.052 (1765)	1.158 (1405)	—		7.8 × 10^−3	2.27 × 10^−3
K21 (h^−1)*	—	—	2.235 (2086)	2.236 (1681)	—	—	2.71 × 10^−6	1.68 × 10^−6
K13 (h^−1)*	—	—	—	0.889 (1800)	—	—	—	6.88 × 10^−3
K31 (h^−1)*	—	—	—	2.239 (3860)	—	—	—	2.12 × 10^−6
r^2	—	0.8286	0.8813	0.8812	—	0.6879	0.6876	0.6879
AIC	—	−22.49	−21.19	−17.19	—	−10.92	−6.92	−2.9235
SC	—	−22.26	−20.79	−16.63	—	−10.68	−6.52	−2.3674

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Table 4 Comparative pharmacokinetic parameters of INH formulations in several compartmental models^a

Pharmacokinetic parameters	INH suspension				INH SNEDDS
	NC	C1	C2	C3	NC	C1	C2	C3
a Values in parentheses indicate % CV; NC: non-compartment; C1: one compartmental; C2: two compartmental; C3: three compartmental; AUC: area under curve; AUMC: area under moment curve; CL: clearance; AIC: Akaike information criterion; SC: Schwartz criterion. AIC: Akaike information criterion, AUC: area under curve, AUMC: area under mean curve, Cmax: maximum plasma concentration, Tmax: time required to reach Cmax, MRT: mean residence time, SC: Schwartz criterion T1/2: plasma half life of drug and F: relative bioavailability; * the value in the parenthesis indicates % CV.
Cmax (ng ml^−1)	710 (42.7)				1910 (90.32)
Tmax (h)	2.0 (0)	—	—	—	0.5 (0)	—	—	—
AUC(0–t) (μg h ml^−1)	3.95 (0.78)	3.988 (0.2)	—	—	6.338 (0.4)	—	—	—
AUC(0–∞) (μg h ml^−1)	39.80 (1.3)	—	—	—	76.23 (4.3)	—	—	—
AUMC (μg h^2 ml^−1)	23.17 (1.1)	20.38 (1.0)	—	—	92.05 (5.2)	77.16 (3.1)	—	—
MRT (h)*	5.809 (56.83)	5.087 (60.64)	—	—	1.208 (134.7)	7.649 (69.29)	—	—
Kel (h^−1)	0.209	—	—	—	0.052	—	—	—
T1/2 (h)	—	3.526 (60.64)	3.708 (55.97)		—	5.302 (69.29)	21.42 (0.0)	—
CL (L h^−1)	4.179 (0.119)	1.248 (34.64)	1.282 (33.53)	1.185 (18.13)	0.656 (59.7)	0.496 (41.88)	—	0.456 (47.61)
Vss (L)	7.282	—	—	—	7.921	—	—	—
Vd (L)*	—	6.350 (49.78)	—	—	—	3.791 (55.2)	—	—
Vc (L)*	—	—	4.125 (59.6)	1.079 (458.24)	—	—	2.708 (43.46)	—
Ka (h^−1)*	—	1.454 (123.69)	0.937 (152.49)	0.938 (152.49)	—	2.77 × 10^4 (0.0)	24.41 (0.37)	75.40 (1.74)
K10 (h^−1)*	—	0.197 (60.64)	0.311 (68.38)	0.287 (62.29)		0.131 (69.29)	0.208 (91.05)	0.171 (47.61)
K12 (h^−1)*	—	—	0.262 (461.65)	0.261 (462.1)	—	—	0.151 (85.41)	0.088 (220.24)
K21 (h^−1)*	—	—	0.582 (467.54)	0.582 (467.99)	—	—	0.06 (351.1)	0.089 (215.7)
K13 (h^−1)*	—	—	—	0.023 (229.83)	—	—	—	0.104 (160.82)
K31 (h^−1)*	—	—	—	1.05 × 10^−6 (221.96)	—	—	—	0.020 (154.52)
r^2	—	0.7054	0.7481	0.748	—	0.5862	0.8642	0.8654
AIC	—	−13.612	−9.955	−5.955	—	−9.004	−17.67	−13.688
SC	—	−13.374	−9.558	−5.399	—	−8.765	−17.27	−13.132

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The non-compartmental analysis suggested that RIF-OF1 and RIF suspension demonstrated the AUC_0–t of 285.5 ± 15.6 μg h ml⁻¹ and 76.59 ± 3.58 μg h ml⁻¹ respectively, with the mean C_max values of 26 400.0 ± 1385 ng ml⁻¹ and 5060.0 ± 268.1 ng ml⁻¹ respectively. Thus, the AUC and C_max values of RIF loaded SNEDDS were increased by 3.72 and 5.22 folds higher as compared to RIF drug suspension demonstrating enhanced oral absorption which may be due to increased RIF solubility and in vitro drug release at pH 6.8 (Table 3, Fig. 3A, 4A and B and 5A). It was investigated that RIF is very least water soluble and its solubility along with stability changes at varied pH values owing to amphoteric nature of RIF.³³ The solubility was reported as 100 mg ml⁻¹ at pH 2 which was reduced to 4.0 and 2.8 mg ml⁻¹ at pH 5.3 and 7.5, respectively.³³ The higher HLB value of LAB (>11) and its subsequent hydrophilic nature is required for the immediate formation of oil in water (o/w) droplets and quick dispersion of the SNEDDS in the aqueous medium which provides a superior self-emulsification. Surfactants are amphiphilic and therefore dissolve to solubilize relatively higher amount of hydrophobic drug which is considered as prime importance to prevent the precipitation of lipophilic drug within the GIT lumen. The improved solubility is responsible for the extended existence of such drug candidate in soluble form for effective absorption.^34,35 The LAB is quite well established surfactant to inhibit the P-gp efflux pump at apical membrane of the intestinal cells leading to increase its further absorption to systemic circulation.^12,36 Moreover, RIF may possibly be transported back to the GI lumen through efflux pump and then reabsorbed to the enterocytes. There is interplay between the P-gp efflux pump and enterocyte CYP 3A4 enzyme wherein the micelle species prevent the co-administered lipophilic RIF from precipitation thereby stimulating the intestinal lymphatic transport pathway for enhanced absorption of nanocarrier based lipid formulation.³⁷ These possible reasons could be determining factors for enhanced oral absorption of the RIF ferried in SNEDDS formulation. Moreover, the clearance value (CL) of free drug solution (0.103 L h⁻¹) as compared to RIF-OF1 (0.028 L h⁻¹) is 3.64 folds higher than the free drug. This may be due to lipophilic nature of RIF (higher log P) greatly accessed to the lymphatic transport when complexed with lipoprotein in the enterocyte and exogenous lipid carrier rather than the free drug.³⁸

Fig. 4 Plasma concentration–time curves and percent drug absorbed to portal vein: (A) RIF suspension (DS), (B) RIF-OF1, (C) INH suspension and (D) INH-OF1 from rat plasma.

Fig. 5 Compartmental absorption of optimized formulation and free drug obtained by the GastroPlus™ simulation tool: (A) RIF-OF1 and (B) INH-OF1.

Similarly, the hydrophilic INH was comparatively less soluble than RIF in excipients which further led to reduced INH loading (ESI Table S1†). INH loaded SNEDDS showed profound augmented PK parameters as compared to the INH solution in rat model. The results suggested that INH-OF1 and INH solution demonstrated the AUC_0–t of 6.338 ± 0.4 μg h ml⁻¹ and 3.950 ± 0.78 μg h ml⁻¹ respectively, with the mean C_max values of 910.0 ± 90.32 ng ml⁻¹ and 710.0 ± 42.7 ng ml⁻¹ respectively (Table 4, Fig. 3B, 4C and D and 5B). Thus, the AUC and C_max values of INH-OF1 were augmented by 1.604 and 2.69 times higher than INH solution signifying enhanced oral absorption which may be owing to surfactant mediated enhanced INH permeation from the apical sites of intestinal membrane to the basolateral portion. INH-OF1 emulsification in the hydrophilic mucin layer over the intestinal membrane results to facilitated oral absorption at the enterocyte membrane in addition to several mechanisms such as absorption through the tight junction, lipid based delayed transit time leading to prolong availability at absorption site, optimum HLB value (10 < HLB < 17) of LAB potentially inhibits efflux P-gp pump and low molecular weight of INH.^39,40 The CL of INH-OF1 (0.646 L h⁻¹) was higher as compared to drug solution (1.254 L h⁻¹).

Thus, the plausible mechanism for improved drug absorption is attributed to nanocarrier based drug delivery to avoid the hepatic access, pre-and post absorption enterocyte drug absorption and facilitated transport to the lymphatic system.

7.4.6 GastroPlus™ simulation: in silico assessment. RIF-OF1, RIF suspension, INH-OF1 and INH suspension were further evaluated and simulated by in silico prediction for their plasma concentration time profile. In the simulation studies, various input parameters (experimental, literature, predicted from ADMET Predictor module of GastroPlus) such as log P, aqueous solubility, clearance and apparent permeability across human intestinal membrane of RIF and INH is tabulated in Table 2. The observed and simulated output parameters obtained from ADMET Predictor module of GastroPlus (single mode simulation) have been depicted in the Table 5. The observed/simulated values of C_max for RIF suspension and RIF-OF1 were 5060.0/3846.5 ng ml⁻¹ (fold error: 1.31) and 26 400/14 690.0 ng ml⁻¹ (fold error: 1.79), respectively (Table 5). Similarly, the observed and simulated C_max values of INH suspension were 710.0 and 469.06 ng ml⁻¹ (fold error: 1.51), respectively, while these values were 1910.0 (observed) and 882.40 ng ml⁻¹ (simulated) for INH-OF1 (Table 5). Similarly, the observed and simulated values for AUC_0–t and AUC_(0–∞) have been delineated for RIF and INH formulations in the Table 5. The log plasma drug concentration profiles of simulated and observed results have been illustrated in the Fig. 4A and B. The obtained curves showed a reasonable degree of superposition which is prudent to correlate the observed and simulated profiles of RIF formulations (Fig. 4A and B) and INH formulations (Fig. 4C and D). Furthermore, the validation of prediction (prediction accuracy) dictated from fold error (FE) were calculated for C_max, and AUC and found to be within range in all developed formulations (Table 5) suggesting acceptable prediction efficiency of simulation technique.⁴¹

Table 5 Results of PK parameters of the drug suspension and the drug loaded SNEDDS assessed by in silico simulation GastroPlus™ software^a

PK parameters	RIF suspension			RIF-OF1			INH suspension			INH OF1
	Observed	Simulated	FE*	Observed	Simulated	FE*	Observed	Simulated	FE*	Observed	Simulated	FE*
a Fa (%)‡ = cumulative amount of drug absorbed; F† = oral bioavailability; PK = pharmacokinetic; FE* = fold error.
Cmax (ng ml^−1)	5060.0	3846.5	1.31	26 400.0	14 690.0	1.79	710.0	469.06	1.51	1910.0	882.4	2.16
AUC0–t (μg h ml^−1)	77.8	55.99	1.79	287.4	193.3	1.48	3.9994	3.5668	1.12	7.6228	7.5074	1.01
AUC(0–∞) (μg h ml^−1)	76.59	553.570	1.51	285.5	187.5	1.52	3.950	3.4727	1.13	6.3375	5.8461	1.08
Fa (%)‡	—	77.614		—	82.23		—	90.1		—	90.01	—
F (%)	—	77.47		—	82.18		—	88.65		—	89.86	—

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The 3D PSA was performed to assess the effect of drug solubility and permeability on major PK parameters (C_max, AUC and T_max) of RIF suspension determined from the in silico GastroPlus™ simulation software. It is evident from the results that the increased RIF solubility caused considerable increase in PK parameters (AUC, C_max and T_max) as shown in the ESI Fig. S4A–C.† Composite nanoemulsion withholds several mechanical and chemical disturbances and its drug release profile in the digestive tract which was unique characteristic. These stable nanoemulsion droplets may be taken up based on a different mechanism leading to completely different PK profiles (slightly delayed T_max, increased C_max and AUC).⁴²

Similar pattern was obtained when simulated for the permeability in in silico permeation (ESI Fig. S5A–C†). In case of INH, the effect of solubility on PK parameters (C_max, AUC and T_max) evaluated by PSA analysis, was found to be significantly increased with increase in INH solubility. 3D-PSA analysis for INH loaded SNEDDS has assessed the effect of permeability on C_max, AUC and T_max (ESI Fig. S5A–C†). The GastroPlus™ simulation predicted the percent drug absorbed to the portal vein as shown in the Fig. 4 which may be result of overall absorption across the intestinal lumen and post-enterocyte absorption successfully. RIF-OF1 (∼82.0%) and INH-OF1 (∼90.0%) have exhibited profound percent drug absorbed to the portal vein as shown in the Fig. 4. It has been observed that increased permeability caused increase in PK parameters which might be owing to lipid and surfactants mediated augmented absorption from the intestinal lumen as shown in the Fig. 5.

7.4.7 Compartmental (regional) drug absorption. The regional absorption profiles of RIF-OF1 and INH-OF1 (SNEDDS) has been displayed in the Fig. 5. GIT simulation of compartmental absorption for RIF-OF1 (SNEDDS) suggested that RIF was mainly absorbed through upper segments of intestine (duodenum, jejunum 1 and jejunum 2) and proximal portion of the large intestine such as ascending curve of large intestine (29.4%) as shown in the Fig. 5A. There was very less amount of RIF absorbed from the ileum portion (0.4% of total absorbed drug) as predicted by the GastroPlus® software simulation technique. The variation in RIF absorption from different segments of GIT could be due to varied population of P-gp efflux transporter as major absorption carrier for RIF. It has been reported that the concentration order of P-gp efflux transporter is duodenum < jejunum for RIF delivery (in vitro study) which is in accordance with our in vivo findings (jejunum absorption, 26.2%; duodenum, 4.7%).⁴³ Moreover, RIF enhanced intestinal absorption may be correlated with recent report that RIF absorption is dependent on P-gp efflux inhibition by LAB present in SNEDDS formulation as well as the drug maintained in solubilized form below critical micellar concentration at explored concentration of excipients.⁴⁴ Furthermore, increased absorption of RIF in the ascending large intestine segment could be due to prolonged residence time and alkaline pH suitable for RIF availability in non-ionized form (pK_a = 7.9) for increased absorption.⁴⁵ The ascending colon showed comparatively higher value of fraction-drug absorbed, since this region has a relatively large residence time (typically takes 5–12 h) and sufficient available free water volume.⁴⁵

Emulsification process provides different structures in the diluting media such as micelle and microemulsion, and reported to penetrate across the aqueous mucin layer during absorption through various mechanisms.⁴⁶ The hydrophilic INH loaded on SNEDD was primarily absorbed from the upper portion of small intestine across the aqueous mucin layer (duodenum, jejunum 1 and jejunum 2) as shown in the Fig. 5B. It can be rationalized that the increased absorption could be due to either surfactant effect (hydrophilic LAB of SNEDDS results into increased intestinal membrane permeability or improved affinity between lipid particle and physiological membrane) or lymphatic transport of SNEDDS and P-gp efflux inhibition.⁶ It is noticeable that INH does not exhibit a dose dependent PK (as reported earlier) and shows a high oral bioavailability of 90.0% which is about same as reported earlier (91.0%).⁴⁷

Broadly speaking, SNEDDS are well established formulations to improve oral BA via several mechanisms such as (a) transcellular uptake (digestion and accumulation into the cell membrane), (b) paracellular (by opening tight junction particularly hydrophilic molecules) and (c) through the Peyer's patch (M-cell uptake at epithelial membrane). A mechanistic study of TJ (tight junction) opening by SNEDDS containing LAB has been investigated to cause significant changes in subcellular localization of the TJ proteins.⁴⁸ Moreover, LAB and lipids are well reported to interrupt the interplay between P-gp efflux transporter and intra-enterocyte metabolic barriers (cytochrome P3A4).^37,49

7.4.8 Determination of minimum inhibitory concentration (MIC). The results of MIC assay of the pure RIF, INH and optimized formulations (RIF-OF1 and INH-OF1) have been presented in the ESI Table S2.† In the preceding paper, CMC8 and LAB showed MIC value as 12.5 and 25.0 μg ml⁻¹ against the MS-995 whereas these values were found to be as 18.75 and 25.0 μg ml⁻¹ against the MS-942 respectively.¹² The MIC values were obtained as 18.4 and 30.4 μg ml⁻¹ for CMC8 and LAB against the M. tuberculosis H₃₇ Rv, respectively.¹² The results of the determined MIC showed that the MIC of drug loaded formulations (INH-OF1 and RIF-OF1) was found to be significantly low as compared to respective pure drug against the studied cultures (three strains) suggesting additive effect of excipients present in the optimized formulation.

8. Conclusion

The suitable selection of excipients (lipid and surfactant) and the optimized combination in the formulation played imperative role for enhanced drug absorption leading to increased oral bioavailability. The present study highlighted the optimized SNEDDS formulation for delivery of RIF and INH using excipients with concerted anti-Mycobacterium activities which could be a potential therapeutic approach with reduced adverse effects and enhanced oral bioavailability (BA) of ATDs. Improved solubility drugs solubility in the excipients and inherent anti-Mycobacterium activity of the CMC8 and LAB dictated to fabricate SNEDDS and further characterization parameters led to obtain the optimized OF1. RIF-OF1 and INH-OF1 were evaluated for anti-Mycobacterium and BA in rat model followed with comparison against the free drug. Thus, the study suggested that SNEDDS with potential anti-Mycobacterium activity can be employed for delivery of ATDs (RIF and INH) with aided effect safely, effectively and economically. Conclusively, the lipid based SNEDDS delivery of both INH and RIF could be considered as suitable substitute with obvious advantages over the conventional dosage form.

Declaration of interest

Authors report no declaration of interest. Authors are alone responsible for the content and writing of this research article.

Acknowledgements

Authors are highly thankful to the Department of Biotechnology (DBT), New Delhi to provide Senior Research Fellow under DBT project (No. BT/PR5653/MED/29/561/2012) for financial assistance for carrying out this work and Birla Institute of Technology, Mesra, Ranchi for providing the facilities and encouragement. The authors thank Intermediate Reference Laboratory (IRL, Jharkhand) TB Sanatorium, Itki, Ranchi for valuable extending facilities to carry out anti-tubercular activity against tubercular strains under safe condition.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c6ra14122f

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