Ribociclib Nanostructured Lipid Carrier Aimed for Breast Cancer: Formulation Optimization, Attenuating In Vitro Specification, and In Vivo Scrutinization

Abstract

Purpose. The current investigation is on the explicit development and evaluation of nanostructured lipidic carriers (NLCs) through the oral route to overcome the inherent lacuna of chemotherapeutic drug, in which Ribociclib (RBO) was used for breast cancer to diminish the bioavailability issue. Method. The RBO-NLCs were prepared using the solvent evaporation method and optimized method by the Box–Behnken design (BBD). Various assessment parameters characterized the optimized formulation and their in vivo study. Results. The prepared NLCs exhibited mean particle size of $114.23\pm 2.75\text{nm}$, mean polydispersity index of $0.649\pm 0.043$, and high entrapment efficiency of $87.7\pm 1.79\%$. The structural analysis by TEM revealed the spherical size of NLCs and uniform drug distribution. An in vitro drug release study was established through the 0.1 N HCl pH 1.2, acetate buffer pH 4.5, and phosphate buffer pH 6.8 with % cumulative drug release of $86.71\pm 8.14$, $85.82\pm 4.58$, and $70.98\pm 5.69\%$, was found respectively, compared with the RBO suspension (RBO-SUS). In vitro intestinal gut permeation studies unveiled a 1.95-fold gain in gut permeation by RBO-NLCs compared with RBO-SUS. In vitro lipolysis suggests the drug availability at the absorption site. In vitro haemolysis study suggests the compatibility of NLCs to red blood cells compared to the suspension of the pure drug. The confocal study revealed the depth of penetration of the drug into the intestine by RBO-NLCs which was enhanced compared to RBO-SUS. A cell line study was done in MCF-7 and significantly reduced the IC₅₀ value compared to the pure drug. The in vivo parameters suggested the enhanced bioavailability by 3.54 times of RBO-NLCs as compared to RBO-SUS. Conclusion. The in vitro, ex vivo, and in vivo results showed a prominent potential for bioavailability enhancement of RBO and effective breast cancer therapy.

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1. Introduction

The incidence of cancerous disease recently increased in recent years, impacting the physical, mental, and social life of humans. The incidence varies from developed countries (1 to 2%) to fewer development countries (almost 5%) yearly. The estimate also showed that more than 7 million people die from cancer disease and is predicted to be 10 to 15 million new cases added by 2020. Meanwhile, this disease is an unexceptional malignant breast cancer found in women, with more than 1 million fresh cases added yearly [1]. Breast cancer was ranked as number 1 due to the number in Indian women with an age rate as high 25.8 per 100,000 and a mortality rate of 2.7 per 100,000 women [2]. There are lots of chemotherapy drugs available for breast cancer; however, Ribociclib (RBO) is one of them that has been recently approved by the US FDA, and it is given orally of 200 mg as shown in Figure 1. The mechanism of action of RBO is to hamper the activity of cyclin-dependent kinase (CDK) at different types of cyclins like CDK4 and CDK6 of cell cycle pathways which indirectly inhibit the retinoblastoma (Rb) protein phosphorylation. The hampering of Rb again slows down the CDK-mediated G1-S phase movement. Because of this, the cell cycle is apprehended, inhibiting the cancer cell growth [3, 4]. The RBO is associated with various adverse effects, and the most common reaction, with more than 20% incidence, is neutropenia, nausea, fatigue, diarrhea, leukopenia, alopecia, vomiting, constipation, headache, and back pain. Apart from adverse effect, the drug is also associated with low solubility and permeability as it is a BCS class IV drug and undergoes immense metabolism by hepatic cells mediated via CYP3A4 in the human liver. Ribociclib is also the substrate for P-gp efflux, which leads to an increase in the dose to achieve the therapeutic level [5]. Thus, these major factors which decrease the degree of absorption of Ribociclib lead to its poor in vivo prospects. The clinical efficacy of Ribociclib is not satisfactory at the therapeutic level, which often results in an increase in dose frequency, or high dose causes adverse effects [6]. However, being a recently approved drug (RBO), not much work has been done so far in the nanocarrier system to overcome the related issue. A recent study investigated by Fei and Yoosefian on the preparation of RBO micelles to increase the aqueous solubility of hydrophobic drug carried out using dodecylphosphocholine surfactant [7]. The remaining challenge still to overcome is the bioavailability issue by inhibiting P-gp efflux and bypassing the extensive first-pass metabolism [8]. The lipidic nanocarriers are being developed in order to overcome the predicaments like improving solubility, minimization of P-gp efflux, protection of the drug from enzymatic (CYP3A4) degradation, providing metabolic stability (stability in GIT), enhancing permeability and retention in the target tissue, enhancing the bioavailability, and minimization of toxic drug effects [9]. The drug integrated into nanostructured lipidic carrier (NLCs) formulations with specific lipid (Solid and Liquid lipids) and excipients can regulate P-gp-mediated efflux movement and has the potential to change the pharmacokinetics of Ribociclib largely. In addition, lipids used in Ribociclib-loaded NLCs will promote its systemic blood circulation via the intestinal lymphatic system rather than being directly absorbed into the portal circulation and consequently prevent its significant first-pass metabolism [10]. Thus, our objective is to develop NLCs as a formulation which exhibits great potential for improving and normalizing the absorption of Ribociclib and contributing significantly in enhancing its therapeutic efficacy up to a satisfactory level.

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Based on solubility data, Labrafil M2125 CS (HLB 4), Capmul MCM C8 (HLB 5-6), Maisine 3S1 (HLB 4), and Plurol oleique (HLB 6) were showing high solubility of RBO as it was anticipated that the structure containing carboxylic acid and succinate group favors the solubility of RBO in each liquid lipid. In addition, longer triglycerides have shown more solubility than the medium-chain due to more entrapment of drugs. Similarly, Stearic acid (HLB 17) and Capmul MCM C10 (HLB 5) have shown high solubility of RBO due to similar reasons. The solubility parameters of each lipid direct reflect the encapsulation efficiency. Thus, the high solubility associated with the drug in lipids is also attributed to the high encapsulation efficiency of the NLCs formulation [29]. Bang and coworkers investigated NLCs of anticancer drug paclitaxel, and similar methods were applied for the selection of solid and liquid lipid for the NLCs preparation [30, 31].

4.1.2. Compatibility Study of Lipids

The results of compatibility studies are given in Table 3. Labrafil M 2125 CS, Capmul MCM- C8, Maisine 351, Plurol oleique were selected as liquid lipids, and Stearic acid and Capmul MCM C10 were selected as solid lipids for further compatibility/miscibility study among lipids. Negi and coworkers develop a protocol for solid and liquid lipid-based compatibility on miscibility/affinity and the physical compatibility of lipids. So based on these parameters, Capmul MCM C8 and Compritol were selected [31].

Table 3

Results of miscibility study between liquid lipids and solid lipids.

Solid lipid	Liquid lipid	Observation	Inferences
Stearic acid	Labrafil M 2125 CS	After 48 h, separate layers were observed.	Failed
	Capmul MCM-C8	Uniform distribution and no phase separation were observed.	Good compatibility
	Maisine 351	Turbidity and phase separation was found after 48 h.	Failed
	Plurol oleique
Capmul MCM C10	Labrafil M 2125 CS	No phase separation was observed.	Passed
	Capmul MCM-C8
	Maisine 351	After 48 h, all remain in the liquid phase.	Failed
	Plurol oleique

4.1.3. Thermal Inspection of a Binary Mixture by DSC

In a ratio of the binary mixture, as the % of liquid lipid increases by 10%, the enthalpy for the melting point decreases in respect of the solid lipid (100%) as shown in Figure 4. However, the crystallinity index (CI) has less variability in the ratio of 8 : 2 to 6 : 4 compared to 9 : 1. Therefore, the final ratio was selected based upon CI, i.e., 6 : 4, as shown in Figure 5 [32]. Iqbal and associates reported similar parameters for the selection of the best ratio of solid and liquid lipids for a suitable binary mixture. As the % of the liquid lipid (Sefsol 218) increases, the enthalpy of the binary mixture decreases with respect to the solid lipid (Geleol), and it was accompanied by a decrease in crystallinity index from 100.0 to 30.3% [13].

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4.1.4. Selection of Surfactant

The surfactants, namely, Cremophor RH 40, Cremophor EL, Tween 20, Tween 80, Poloxamer 188, and Solutol HS15, were used to evaluate for its emulsification property. The result of the screening is illustrated in Table 4. The higher emulsification property reflects to reduce the particle size of binary mixture lipids and increase the physical stability of lipid nanoparticles, sequentially preventing the aggregation of nanoparticles which gives higher transmittance [33]. Alam and coworkers developed isradipine NLCs. They have reported in their research about the surfactant selection criteria based on % of transmittance, which was examined by UV spectroscopy method at 510 nm [12].

Table 4

Observational study for the selection of surfactants.

Name of surfactants	% transmittance
Cremophor EL	64.23
Cremophor RH 40	91.61
Poloxamer 188	92.04
Solutol HS 15	98.28
Tween 20	45.95
Tween 80	63.69

4.2. Preparation and Optimization of NLCs

With regard to approaches to Pharmaceutical Development, the product should be designed to meet needs and the intended product performance. A researcher might select either an experimental approach, an organized approach, or both for product development. A more organized approach for product development also refers to the quality by design approach, which includes adding prior knowledge and their results using the design of experiments (DOE). Such an organized approach helps to get the final desired product with the desired quality. It also helps to understand all the regulations. With respect to the quality of the product, which is generally related to safety and efficacy, setup parameters were justified, which refers to the quality target product profile (QTPP) which gives the outlook summary of drug product characterization, which can be predetermined. The dependent variables like particle size, entrapment efficiency, and PDI are considered critical quality attributes (CQAs). For effective delivery at the targeted site, the particle size should be small; more entrapment of the drug leads to therapeutic efficacy even at a low dose and low PDI (≤0.7) [34] which is considered as a uniformly distributed formulation. These parameters of QTPP and CQAs are summarized in Tables 5 and 6, respectively [35, 36].

Table 5

Quality target product profile of the nanostructured lipidic carrier.

QTPP parameters	Target to achieve	Justification
Dosage type	Nanoformulation	Escalate the drug permeation/bioavailability
Route of administration	Oral	Easy to use/lymphatic uptake/stability/minimize side effects
Physical state	Lyophilized powder	Easy administration/physical aspect
Physiochemical characterization	Entrapment efficiency	Drug loading assurance
	Particle size	Influence the permeation and absorption
	Zeta potential	Product stability assurance
Pharmacokinetics	Absorption	Required to achieve the desired efficacy
	Distribution
	Metabolism and targeting

Table 6

List of various CQAs affecting the therapeutic efficacy of RBO-NLCs.

CQA parameters	Target to achieve	Justification
Particle size	100-200 nm	Assure the absorption, hence the increase in bioavailability
Entrapment efficiency	≥70%	To reach the optimum therapeutic efficacy
PDI	≤0.7	Uniform drug distribution, hence content uniformity

4.2.1. Risk Assessment

The profound parameters for further experiment for optimization of formulation using Box-Behnken design from preliminary assessed data were binary mixture concentration (1-3%), surfactant concentration (1-3%), and sonication time (1-5 min). The 100% equipped response surface fraction is present in the design space to signify its accuracy all over the region. Figure 6 demonstrated the relation among all factors for NLCs preparation prepared by software Minitab 19, Philadelphia, USA. Similarly, Kovacs and associates have reported for the salicylic acid-loaded NLCs in which they have investigated the risk assessment, which referred to both qualitative and quantitative estimates of the risk. An Ishikawa diagram was drawn to find out the key material and process attributes which affects the NLCs formulation preparation [37].

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4.2.2. Box-Behnken Design (BBD)

The Box-Behnken design (BBD) response surface method tested the points which are within a predetermined range unlike the central composite design (CCRD) to get the total possible runs based on the optimized NLCs formulation data, which was prepared by probe sonication technique; 17 runs were obtained using the mentioned variables in Table 7. Table 8 gives the result derived from the experimental runs. The optimized formula obtained was a binary mixture, surfactant, and sonication time which were found as 1% $w/v$, 3% $w/v$, and 3 min, respectively. The results of the dependent variable for the optimized formula were particle size ($114.23\pm 2.75\text{nm}$), entrapment efficiency ($87.7\pm 1.79\%$$w/w$), and PDI ($0.649\pm 0.043$).

Table 7

Different variables selected for Box-Behnken design.

Independent variables	Factors	Unit	Level
			Low	High
A1	Binary mixture	% $w/v$	1	3
A2	Surfactant	% $w/v$	1	3
A3	Sonication	Min	1	5

Table 8

Experimental runs and observed responses from BBD.

Std	Runs	Factor 1	Factor 2	Factor 3	Response 1	Response 2	Response 3
		Binary mixture (% $w/v$)	Surfactant (% $w/v$)	Sonication time (min)	Particle size (nm)	PDI	Entrapment efficiency (% $w/w$)
14	1	3	1	3	656	0.653	94.5
13	2	2	2	3	211.9	0.562	89.9
17	3	2	3	5	179.87	0.554	89.99
16	4	1	2	1	230.7	0.497	87.1
1	5	1	1	3	212.54	0.499	85.9
9	6	1	2	5	152.32	0.618	86.1
3	7	2	3	1	221.92	0.5	87.76
15	8	3	3	3	276.53	0.621	96.12
8	9	2	2	3	225.9	0.549	87.98
11	10	2	2	3	234.8	0.541	89.42
7	11	2	1	5	465.71	0.487	87.91
12	12	2	2	3	212.7	0.502	88.4
6	13	1	3	3	114.23	0.649	87.7
4	14	3	2	5	543.73	0.597	95.4
5	15	3	2	1	419.34	0.682	96.71
2	16	2	2	3	211.9	0.562	89.9
10	17	2	1	1	396.4	0.512	90.14

The quadratic equations obtained for different dependent variables and $p$ value were found significant, and lack of fit has been found to be insignificant, as mentioned below in Table 9.

Table 9

Interpretation of regression value of dependent variable responses B1, B2, and B3.

Dependent variables	$R^2$	$R^2$		Adequate precision	SD	% CV
		Adjusted value	Predicted value
Particle size (B1)	0.9983	0.9962	0.9908	74.6866	9.27	3.17
PDI (B2)	0.9500	0.8856	0.7640	12.2250	0.0211	3.75
EE (B3)	0.9692	0.9297	0.7403	14.2001	0.9234	1.03

Particle Size (B1) = 219.44, $X$ 148.23, $Y$ -117.26, $Z$ 9.16, $XY$ -70.29, $XZ$ 50.69, $YZ$ -27.84, $X^2$ 57.97, $Y^2$ 37.42, $Z^2$ 59.12

PDI (B2) = 0.5432, $X$ 0.0363, $Y$ 0.0216, $Z$ 0.0081, $XY$ -0.0455, $XZ$ -0.0515, $YZ$ 0.0198, $X^2$ 0.0738, $Y^2$ -0.0115, $Z^2$ -0.0185

Entrapment efficiency (B3) = 89.12, $X$ 4.49, $Y$ 0.3900, $Z$ -0.2888, $XY$ -0.0450, $XZ$ -0.0775, $YZ$ 1.11, $X^2$ 2.16, $Y^2$ -0.2213, $Z^2$ 0.0513

In all the equations, $A$ represents the binary mixture %, $B$ is the surfactant %, and $C$ depicts the sonication time (in min). The effect between each category of variables was depicted using 3-dimensional graphs in response surface analysis, as shown in (Figures 7, 8, and 9).

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4.2.3. Impact of Independent Variables on Responses

(1) Impact of the Binary Mixture on Dependent Variables. As the binary mixture concentration increases, the particle size also increases because of agglomeration of particles due to lack of emulsifying agent (surfactant) as more emulsifying agent is required if lipid concentration increases aqueous phase, and lack of it is attributed to an increase in particle size.

Entrapment efficiency was directly affected binary mixture quantity. This indicated that an increase in the lipid concentration leads to an increase in the amount of solid lipid, which can be, accommodated more drugs inside the NLCs formulation in the solid lipid [38]. Similarly, Subedi and associates investigated the Doxorubicin loaded into the lipidic carrier, which stated the factor affecting the quantity of lipid on particle size as well as encapsulation efficiency. So, the increment of the lipid content increases the encapsulation efficiency and particle size [39].

(2) Impact of Surfactant on Dependent Variables. The lipid nanoparticle particle size decreases as the concentration of surfactant increases above the critical micelle concentration due to the decrease in interfacial tension. This critical concentration of surfactant also forms a network on the surface of lipid nanoparticles which prevent its agglomeration of the small particle from forming a bigger particle size.

However, the increase in the concentration of surfactant on entrapment efficiency was found very minimal [40]. The results are in agreement with the research reported by Shtay and associates. They have studied the factorial design, which applied to variables that affecting their preparation for food application using lipid nanocarrier. They have reported the increase in concentration decrease the particle size explained by a decrease in interfacial tension [40].

(3) Impact of Sonication Time on Dependent Variables. The mechanism of probe sonication is based on the principle that high energy waves ultrasonically emitted cause the breakage of lipid nanoparticles into small nanoparticles. Thus, upon an increase in sonication time, the lipid nanoparticle size decreases and forms monodisperse globules because of the shear force generated by cavitation.

However, the impact of sonication on entrapment efficiency was observed to be very minimal with aggravation in the sonication time [41]. Ahad and coworkers formulate the lipidic nanocarrier using an experimental design technique for valsartan. They reported an inverse relationship between the sonication time and vesicle size [42].

4.2.4. Validation of Design of Experimental

The goal of the current study is to achieve minimum particle size with maximum entrapment efficiency. Design-Expert software, version 12.0.3.0 (Minneapolis, USA), was applied for the predicted value of response given in Table 10. Based on independent variable values, RBO-NLCs prepared and compared their data with a predicted response. The value obtained from the experiment was almost similar, which confirms the validity of the optimized process for preparing NLCs except for the particle size, which might be due to the wide variety of particle data obtained from a number of runs which give a broad mean value.

Table 10

Point prediction method to attain predicted and actual response (maximum entrapment efficiency, optimum PDI, and minimum particle size) [12].

	Lipid (% $w/v$)	Surfactant (% $w/v$)	Sonication time (min)	Particle size (nm)	Entrapment efficiency (%)	PDI
Predicted	1.0	3.0	3.0	219.44	89.12	0.543
Actual				117.00	87.70	0.600

4.3. Characterization of Optimized RBO-NLCs

4.3.1. Particle Size, PDI, and Surface Charge

The nanoparticle size (Z-Average) and PDI were obtained at $114.23\pm 2.75\text{nm}$ and $0.649\pm 0.043$, respectively. The zeta potential of RBO-NLCs was obtained at $2.61\pm 0.54\text{mV}$. Smaller particle size suggests good miscibility and more systemic circular time. The low PDI value states the uniformity of nanoparticle distribution. Zeta potential indicates the stability of the nanoformulation. Varshosaz and coworkers investigated the NLCs preparation in which the particle size found was smaller (103 to 127 nm) because their good miscibility of the excipient and zeta potential were positive values suggesting longer residence time and less uptake by the reticuloendothelial system in the blood circulation system [43].

4.3.2. Drug Entrapment (EE) and Drug Loading (DL)

The % drug entrapment efficiency of NLCs was calculated to be $87.7\pm 1.79\%w/w$. The lipophilic drug has the intrinsic property to get more solubilization in lipids, unlike the hydrophilic drug. So, this lipophilic property entraps them more inside the lipids.

The % DL was found to be $8.77\pm 0.18\%w/w$. Elmowafy and coworkers investigated drug-loaded NLCs to overcome the oral delivery drawback. They have found the % encapsulation efficiency varies between 76 ± 12.4% and 96.6 ± 7.1%. The high % of liquid lipid (Capryol® PGMC) causes massive crystal order defects, which lead to more space to entrap the drug molecules and improve the % EE [44].

4.3.3. Structural Analysis by TEM

The TEM image shown in Figure 10 demonstrated that the RBO-NLCs particles were uniformly distributed with no sign of any aggregation of particles, and the shape of each nanoparticle was spherical. The result indicated that the NLCs particle was dispersed homogenously. A similar outcome was evaluated by Alam and coworkers where the NLCs particles were uniform and in spherical shape [45].

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4.4. Powder X-Ray Diffraction (PXRD) Pattern Study

RBO was found to be crystalline in nature as it showed sharp, intense peaks located at 10.0, 14.8, 15.2, 15.7, 20.1, 22.6, and $23.4\pm {0.2}^{°}$; 2 thetas in the powder X-ray diffraction spectrum are shown in Figure 11(a) [46]. The prepared RBO-NLCs were lyophilized to get the powder and used for p-XRD studies to see drug entrapment in the NLCs, as shown in Figure 11(b). The absence of the sharp and intense peaks of the drug in RBO-loaded NLCs indicates that the drug is completely entrapped within the NLCs or the unentrapped drug is converted into the amorphous state [47]. The mannitol used for lyophilization was converted into the amorphous state after freeze-drying and did not show any intense and sharp peaks [48, 49]. Yang and coworkers reported the development of gypenoside-loaded NLCs for oral delivery. The result found that typical peaks of the drug alone were missing in the XRD pattern of formed NLCs, in which attributed drugs in NLCs may appear in an amorphous state [50].

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4.5. Structural Analysis by FT-IR Spectroscopy

The spectra obtained from FT-IR spectroscopy of drug alone and RBO-NLCs are demonstrated in Figures 12(a) and 12(b), respectively. The spectra of the drug alone have seen typical peaks at 3667.64 N–H stretch, 1727.66 C=O stretches, 1604.90–1458.69 C=C stretches, and 1391.78 C-N stretches. FTIR spectrum of RBO-NLCs showed a peak at 2916 C-H stretch, 2849.51 O-H stretch, and 1699.26 C=O stretch of carboxylic acid, which could be due to the existent of excipients in the NLCs formulation. In the FT-IR spectrum, the typical peak of RBO-NLCs was absent compared to the pure drug because of the complete entrapment of RBO inside the NLCs formulation [51]. Annu et al. have developed the chitosan nanoparticle. The result reported in the FT-IR study stated that the characteristic peaks of the drug in nanoparticles were absent compared to drug alone spectra, and it could be the possible reason for entrapment of the drug within the nanoformulation [52].

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4.6. In Vitro Drug Release Study

RBO-NLCs and RBO-SUS shown in Figure 13 indicated a sustained drug release at different pH 1.2, 4.5, and 6.8 from the initial time point as compared to RBO-SUS, which shows a gradual increase in release but not sustained for 24 h. The drug present inside the lipid matrix of NLCs undergoes surface erosion which is attributed to its sustained release from the formulation. Initial burst release in the NLCs was due to the unentrapped drug. The $t_{75\%}$ and $t_{50\%}$ were calculated for each drug formulation. The dissolution profile was compared in terms of % dissolution efficiency (%DE) and similarity factor (f2), as shown in Table 11. Results showed a higher %DE for NLCs formulation in pH 1.2, 4.5, and 6.8 compared with RBO-SUS.

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Table 11

Dissolution profile comparison for NLCs and suspension formulation in different dissolution media.

Parameters	Formulation	0.1 N HCL (pH 1.2)	AB (pH 4.5)	PBS (pH 6.8)
%DE	RBO-NLCs	$$83.98\pm 7.69$$	$$84.37\pm 2.97$$	$$55.98\pm 3.16$$
	RBO-SUS	$$68.30\pm 4.64$$	$$71.33\pm 3.06$$	$$43.55\pm 1.48$$
f2 similarity factor	—	43.89	43.76	48.52
$T_{50\%}$ (h)	RBO-NLCs	2.03	1.38	11.27
	RBO-SUS	2.05	1.20	—
$T_{75\%}$ (h)	RBO-NLCs	4.47	6.53	—
	RBO-SUS	4.49	3.53	—

Similarly, similarity factor, f2 was calculated. The f2 values below 50 for pH 1.2, 4.5, and 6.8 indicated the both RBO-NLCs and RBO-SUS release pattern were not similar. Sahibzada and coworkers investigated a similar comparison of drug nanoparticle dissolution parameters for the enchantment of oral bioavailability. The %DE and similarity factor f2 were calculated for two methods to prepare nanoparticles and compared for better dissolution [21].

4.7. Mechanism of Drug Release

The kinetic release model in the buffer of pH 1.2, 4.5, and 6.8 was calculated. Based on the $R^2$ value, the appropriate kinetic model was chosen for the drug release mechanism from NLCs. So, the Korsmeyer-Peppas kinetic release model was selected as the $R^2$ value was close to linearity compared to other kinetic release models. This model described release mechanisms from NLCs formulation, which described in three steps the diffusion of water, swelling, and dissolution of the matrix [53]. Duong and coworkers investigated the drug-loaded NLCs, and their drug release kinetic model was compared, and the mechanism was studied using the Korsmeyer-Peppas equation [18, 53, 54].

4.8. In Vitro Lipolysis Study

The drug should be solubilized near the absorptive membrane so that it is available for systemic absorption. Therefore, the drug should solubilize in an aqueous layer in lipolysis media, and the same will not happen in the case of the sediment layer. The percentage of drug content in a different layer of aqueous and sediment is depicted in Figure 14. The high solubilization potential of the drug in the NLCs formulation in the aqueous layer indicated higher absorption, i.e., approximately 76% after orally administering the RBO-NLCs formulation. Furthermore, drug content in the sediment phase of RBO-NLCs was also calculated and found to be $18.47\pm 8.45\%$. This is because some of the solid lipids might not be digested, so the entrapped drug remains inside the solid lipid. Thus, the result established that RBO-NLCs enhanced its solubilization in the aqueous medium, which simulates the environment of GIT and the intestine. Hence, it can be used as in vivo fate of the RBO. A similar investigation was reported by Khan et al. and Rehman et al., in which the drug-loaded NLCs formulation found high drug content available for solubilization in the aqueous phase compared to the sediment phase [18, 55].

[figure omitted; refer to PDF]

4.9. In Vitro Haemolysis Study

Haemolysis is detected in red blood cells treated with experimental agents, as shown in Figure 15. The positive control sample showed the least variability in red blood cells with respect to their structure or shape, which was almost similar to the sample treated with NLCs-placebo as the haemolysis count was significantly high in the case of Triton X100 treated sample which destabilizes erythrocytes membrane. The RBO-NLCs formulation showed well intact red blood cells, which were again similar to the NLCs placebo-treated sample (% haemolysis of 1.855%). However, slight structure modification occurred in the case of the RBO-SUS sample (% haemolysis of 2.712%) treated red blood cells, which disrupts the membrane of red blood cells. The result concluded that the NLCs formulation of RBO was safer compared to a pure drug suspension. So, the result comprises the in vivo fate of NLCs formulation of the selected drug. A similar investigation was reported by Chauhan and associates in which the curcumin nanoformulation evaluated their anticancer potential and evaluated direct nanoformulation erythrocyte interaction in which membrane disruption directly measures the toxicity of nanoformulation [56].

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4.10. In Vitro Gut Permeation Study

The intestinal permeability of RBO-NLCs and RBO-SUS is shown in Figure 16. After 2 h study setup, the flux of the drug in the rat intestine was calculated. The flux for RBO-NLCs and RBO-SUS formulations was found to be $2426.98\pm 157.77$ and $1241.77\pm 68.70\mu \text{g}/\text{c}{\text{m}}^2$, respectively. The apparent permeability coefficient was found to be $75.86\pm 2.46$ and $38.81\pm 1.07\text{cm}{\min }^{-1}$ for RBO-NLCs and RBO-SUS, respectively. The smaller particle size and permeation enhancer (lipids) of RBO-NLCs enhanced the drug’s permeability compared to the RBO-SUS. The reason can be owed to the P-gp inhibitory activity of Solutol HS 15, which inhibits the drug efflux, thereby enhancing the permeability. Almost two times of drug release were observed in RBO-NLCs in contrast to the RBO-SUS formulation [12]. Wu and coworkers investigated the repaglinide-loaded NLCs formulation which demonstrated the membrane permeability compared with their solution. Drug-loaded NLCs with small particle size easily pass the mucus layer and intestinal epithelial cell layer compared with large NLCs [57].

[figure omitted; refer to PDF]

4.11. Depth Permeation Study by Confocal Microscopy

The confocal microscopy images of rat intestine with Rhodamine B dye, as shown in Figure 17, showed the depth of penetration of RBO-NLCs and RBO-SUS, respectively, after 2 h of dose administration. The depth of penetration measured through the $z$-axis is 15 μm for both formulations. The data obtained distinctly indicated the intensified fluorescence in RBO-NLCs in contrast to RBO-SUS even after 15 μm of depth. The result signifies greater penetration of RBO-NLCs, which could be the possible reason for the small particle size of NLCs and the role of lipids and surfactants as penetration enhancers [58]. Soni and coworkers reported the sulforaphane-loaded NLCs, and the result suggested that the depth of permeation of the drug was measured in the intestinal lumen by the depth of fluorescence permeated. Drug-loaded NLCs penetrated more as compared to drug solutions [58].

[figures omitted; refer to PDF]

4.12. Cell Line Study

4.12.1. Effect of RBO on MCF-7 Breast Cancer Cells

The antitumor activity of RBO against the MCF-7 cells was investigated by MTT assay. As shown in Figure 18, RBO exhibited a broad spectrum of inhibition against cancer cell lines in a dose-dependent manner. The result from the MTT assay, the IC₅₀ value (μg/ml) of RBO post-24 hrs and 48 hrs of treatment against the MCF-7 cell line at 37°C at 5% CO₂, was found to be 39.51 and 13.36 μg/ml, respectively. After calculation of the IC₅₀ value, similarly dose-dependent toxicity of the RBO-NLCs formulation was done as shown in Figure 19. The % cytotoxicity was significantly enhanced in the case of nanoformulation with lower IC₅₀ value of 0.531 and 0.474 μg/ml post-24 hrs and 48 hrs, respectively. So, by formulating into NLCs of the drug, the cytotoxicity was enhanced and reduced their IC₅₀ value by 74 times and 28 times after 24 h and 48 h, respectively. A similar study was also conducted by Marinelli and coworkers in which RBO alone or in combination with Everolimus was investigated in breast cancer lines [59].

[figure omitted; refer to PDF][figure omitted; refer to PDF]

4.13. In Vivo Pharmacokinetic Study

In vivo pharmacokinetic study was conducted in female Wistar rats for the determination of bioavailability data, as depicted into Figure 20 after the oral administration of RBO suspension and RBO-loaded NLCs. The peak plasma concentration ($C_{\max }$) and time of occurrence of the same ($T_{\max }$) were calculated directly from the drug plasma concentration versus time profile graph. The significant parameters are provided in Table 12 calculated by the linear trapezoidal method using the PK solver add-in tools in Microsoft excel. RBO belongs to the BCS IV drug category which makes it essential to develop a novel drug delivery system so that NLCs can overcome solubility as well the permeability issue. The comparative data of RBO suspension and RBO-NLCs are summarized in Table 12 where $C_{\max }$ and $T_{\max }$ of RBO suspension and RBO-NLCs were found to be $311.90\pm 36.70\text{ng}/\text{ml}$ and 4.00 h and $897.92\pm 28.14\text{ng}/\text{ml}$ and 4.00 h, respectively. The higher $C_{\max }$ of RBO-NLCs indicated the higher absorption due to their nanosize and lipophilic characteristic of NLCs which is also responsible for micellar solubilization which enhances the lymphatic uptake through Peyer’s patches present in the small intestine [60, 61]. The higher $T_{\max }$ also suggested the prolonged and sustained drug release. The in vivo result corroborated with in vitro drug release of RBO in terms of sustained and longer period of drug release. Higher absorption is achieved due to more of the drug being entrapped inside the lipidic nanoparticles, and again, the micellar solubilization leads to conversion of nanoparticles into chylomicrons which enhance the lymphatic uptake and hence bypass the hepatic first pass metabolism. From the calculated data, a 3.54-fold increase in the bioavailability of RBO-NLCs was observed as compared to the RBO suspension. Data showed statistical difference at ${}^{\ast }p<0.001$ between RBO-SUS and RBO-NLCs.

[figure omitted; refer to PDF]

Table 12

Pharmacokinetic parameters of RBO-SUS and RBO-NLCs.

Pharmacokinetic parameters	RBO-SUS	RBO-NLCs
$C_{\max }$ (ng/mL)	$$311.90\pm {36.70}^{\ast }$$	$$897.92\pm {28.14}^{\ast }$$
$T_{\max }$ (h)	4.00	4.00
$\text{AU}{\text{C}}_{0-t}$ (ng h/mL)	$$9620.75\pm {781.21}^{\ast }$$	$$34117.67\pm {548.20}^{\ast }$$
$\text{AU}{\text{C}}_{0-\alpha }$ (ng h/mL)	$$10924.97\pm {751.39}^{\ast }$$	$$94903.96\pm {21646.64}^{\ast }$$
$t_{1/2}$ (h)	$$14.95\pm 3.85$$	$$70.53\pm 18.82$$

Data represented as $\text{mean}\pm \text{standard}\text{deviation}$ ($n=3$) with statistical difference at ${}^{\ast }\text{p}<0.001$.

4.14. Stability Study

The parameters of optimized NLCs on the stability study were evaluated as per the ICH guidelines, and change in any physical and chemical was evaluated as shown in Table 13. A freshly prepared sample was kept for stability study after determining their particle size, and PDI, which was $114.23\pm 2.75\text{nm}$ and $0.649\pm 0.043$, respectively, and % entrapment efficiency was $87.75\pm 1.79\%$ on 0 days. As the time point from 1 month to 6 months of stability, the particle size increases from 114.23 to 135.44 nm, as shown in Figure 21(a). It might be because of the swelling of NLCs nanoparticles upon a long period of storage. The entrapment efficiency decreases during the storage time, as shown in Figure 21(b). It might be because solid and liquid lipid integrity decreases and swelling of nanoparticles causes the leakage of the drug, reflecting the decrease in entrapment efficiency. Thus, the drug-loaded NLCs showed good physical and chemical stability upon long storage [45]. The changes in particle size and entrapment efficiency are shown in Figures 21(a) and 21(b), respectively, have drawn by using software Minitab 19, Philadelphia, USA. All data obtained from stability corresponded to the preceding research done by Nabi and associates in which they have formulated NLCs using the BBD and stability study done for 90 days [29]

Table 13

Result of stability study for RBO-NLCs at $25\pm 2^{°}\text{C}$/$60\pm 5\%$ RH ($n=3$).

Time (month)	Phase separation	Sedimentation	Particle size		PDI		Entrapment efficiency
0	No	No	nm	SD	PDI	SD	%EE	SD
			114.23	2.75	0.649	0.043	87.75	1.79
1	No	No	127.78	1.26	0.711	0.067	86.47	0.91
3	No	No	131.91	2.50	0.703	0.054	85.87	0.79
6	No	No	135.44	1.31	0.707	0.067	85.13	0.91

[figures omitted; refer to PDF]

5. Conclusion

RBO loaded NLCs was prepared using solvent evaporation followed by the probe sonication method. The NLCs formulation was optimized using the Box-Behnken design response surface method. The prepared NLCs exhibited mean particle size of $114.23\pm 2.75\text{nm}$, mean polydispersity index of $0.649\pm 0.043$, and high entrapment efficiency of $87.7\pm 1.79\%$. TEM images also suggested uniform size and distribution. The in vitro drug release from the NLCs nanoformulation shows a sustained release for a long time (up to 72 h), unlike drug suspension, which is only up to 24 h of drug release, and it could not maintain the sustained drug release for a longer period. The in vitro lipolysis study indicated the drug availability after released from lipid-encapsulated drug to the absorption site. The in vitro haemolysis study suggested that the NLCs formulation of the given drug was safe compared to the pure drug. The in vitro permeation study showed an increase in depth of the NLCs formulation due to the lipid used in the formulation, which enhances the permeation as compared to a drug suspension. The cell lines in the MCF-7 study which significantly reduced the dose in the case of the NLCs formulation required to produce similar cytotoxicity when pure drug was used. The findings of the pharmacokinetics study by the in vivo study in female Wistar rats of the RBO-NLCs were carried out which enhance its bioavailability by 3.54 times as compared to the RBO-SUS.

Acknowledgments

The authors would like to acknowledge the Indian Council of Medical Research, Govt. of India, New Delhi, India, for providing ICMR-SRF Research fellow to the first author (Grant Number: 45/36/2019-NAN-BMS).

Glossary

Abbreviations

RBO:Ribociclib

NLCs:Nanostructured lipid carriers

P-gp:P-Glycoprotein

BBD:Box-Behnken design

PDI:Polydispersity index

EE:Entrapment efficiency

TEM:Transmission electron microscopy

$R^2$:Regression value

CDK:Cyclin-dependent kinase

IUPAC:International Union of Pure and Applied Chemistry

HLB:Hydrophilic and lipophilic balance

rcf:Relative centrifugal force

UV:Ultraviolet

QbD:Quality by design

p-XRD:Powder X-ray diffraction

FT-IR:Fourier-transform infrared spectroscopy.

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