A suitable quantity of Bicalutamide and ß-cyclodextrin or HP- ß -CD of different ratios were mixed in mortar and pestle, and then sieving was done through a #60 sieve.

Inclusion complex of Bicalutamide and ß-cyclodextrin or HP- ß -CD in 1:1, 1:1.5, and 1:2 ratios were prepared by kneading method. The ß -CD or HP- ß -CD was kneaded like paste with a small amount of water, with continuous trituration and slurry-like consistency. The drug was included in slurry, and further triturated continuously for 1 hour until the powder was obtained. The powder was sieved in a #40 sieve and stored in a desiccator.

An excess amount of inclusion complex was added to 10 ml vials containing 5 ml of 1%Sodium Lauryl Sulphate (SLS). The vials were sealed and placed in an orbital shaker for 48 hours at room temperature. The samples were filtered, diluted and analyzed spectrophotometrically at 272 nm. 11

Various excipients were selected according to the literature search, and screening was done as per their inactive ingredient guide (IIG) limits. 12 Different binders like hydroxypropyl cellulose, starch, and PVP K30 in 2.5%,5% and 7.5%amount were screened. The fillers like Avicel 102, LMHandmannitol were screened alone and in a 1:1 ratio while keeping the amount of binder PVP K30 constant. The moisture absorbents (Avicel PH 200, Avicel PH 102, Aerosil 200, Aeroperl 300, and Neusilin US2) were also screened.¹¹ Sodium starch glycolate (SSG) in 4%, 6% and 8%,Croscarmellose sodium (CCS) in 2%, 3% and 4% and neusilin in 1.5% and 3% amount were screened as disintegrants. The preliminary screening was optimized with the design of experiments.

The Box–Behnken design was selected for optimization of the formulation. The dependent and independent variables selected are shown in Table 1. Level of the variables low, medium and high were selected based on the results from preliminary screening methods. 11, 13 In addition, second-order polynomial models with Design Expert® (Stat-Ease.v11.0.4.x64) were obtained. 12, 13

Flow properties of prepared MADG granules were evaluated by measuring the Angle of Repose, Bulk Density, Tapped Density, Carr's Index and Hausner's Ratio (HR) according to the US Pharmacopoeia methods and equations. 14

All prepared batches were evaluated for characteristics like Weight variation, Content uniformity, hardness, stability, dissolution, and disintegration time. 17 In-vitro dissolution study was performed for 30 minutes in a USP type II dissolution test apparatus (Electro lab, Mumbai, India) operated at 50 RPM and maintained at 37°C. Five ml samples were collected every 5 minutes for 35 minutes and replacing with fresh dissolution media (0.1 MHCl containing 1% SLS). 18 In-vitro parameters of optimized batch like % drug release, disintegration time and hardness were compared with the marketed formulation prepared using the wet granulation method. 19

Stability studies were carried out as per ICH stability testing guidelines. 20 For one month, the optimized formulation was stored at 40±2°C/75±5% relative humidity (RH). 21, 22 The tablets were evaluated for hardness, drug content, and dissolution study and compared with tablets evaluated immediately after manufacturing.

Bicalutamide solubility in water was 0.0061±0.000152 mg/ml. As seen in Figure 1, both HP-ß-CD and ß-CD increases solubility by 40 folds approximately, but ß-CD was in ratio of 1:2 while HP-ß-CD 1:1. The formulation became more bulky if ß-CD was used. Additionally, ß-CD in higher concentration may cause nephrotoxicity thus HP-ß-CD was selected for further studies.

Figure 1

According to pharmacopoeia, the hardness of the immediate release tablet must be 3.4 to 4.8 kg/cm², and friability must be less than 1%¹⁴. Based on hardness and friability data in preliminary trials, PVP K30 (2.5%, 5% and 7.5%) as a binder, Avicel 102 and LMH in (1:1) ratio as fillers were selected for further studies. Based on powders' flow property, Aeroperl 300 was selected as an adsorbent. Neusilin US2 (3%) and the cross-linking of CCS (4%) act synergistically, allowing the tablet to swell and absorb many times its weight in water leading to quick disintegration. Neusilin US2 acts as an adsorbent and improves flow ability, hardness, and tablet DT. However, Neusilin US2 and CCS did not affect the disintegration time when hardness and compression force increased. Therefore, all the screened excipients were used for further studies.

A three-level, three-factorial Box Behnken experimental design was used to evaluate the effects of selected independent variables on the responses, to maximize the hardness while controlling drug release and disintegration time. The speed of granulator (rpm) (X1), the concentration of binder, PVP K30 (%) (X2) and concentration of moisture absorbent, Aeroperl 300 (%)(X3) were independent variables to prepare each of the 17 formulations. The seventeen formulations with their responses are shown in Table 2. All responses were best fitted to the quadratic model.

Various pre and post compression parameters characterized the IR tablets. The results are summarized in Table 3 and Table 4.

Post-compression parameters suggested that increased Aeroperl 300 at high concentration form high-density granules, which increased hardness. Increased concentration of PVP K30 affected DT, hardness and friability. Ata very high concentration, PVP K30 formed avery hard tablet, which affected DT time. An increase in granulator speed (rpm) decreased granule size and increased hardness; thus, the cumulative effect of granulator speed, binder concentration, PVP K 30 and moisture absorbent, Aeroperl 300, is shown in Table 4.

In-vitro drug release of prepared batches using MADG technique after applying experimental design is shown in figure 2 which depicts that percent drug release of pure drug at 30 mins is 15 % while for batch F1- F12 its 58.87%, 79.75%, 69.52%, 81.73%, 71.72%, 83.13%,79.34%, 83.18%, 79.32%, 91.22%, 59.74%, 79.78%, 78.30%, 78.91%, 98.89%,94.99%, 95.69% and 91.96% respectively. These results reflect that with varying the processing parameters changed the drug release.

Figure 2

The causal factor and response variables were related using a polynomial equation with statistical analysis through Design-Expert® software. The quadratic model's approximations of response values (Disintegration, % of drug release in 30 min, hardness) were most suitable because its PRESS value was the smallest.

The design expert software suggested a quadratic model with an R² value equal to 0.9637 (p=0.0003). A high value of the correlation coefficient (0.9637) indicates a good fit between the independent variables and the first dependent variable (Disintegration time). The model is significant, with a P-value of 0.0003 (table 5). The evolved mathematical model is

Y₁ (Disintegration Time) = 194.42 -35.53X₁ -32.03X₂ -48.50X₃ -29.57X₁X₂ +1.65X₁X₃ -3.50 X₂X₃ + 89.22X₁ X ₁+ 93.22X₂ X₂+ 25.15X₃ X₃……………..equation 4

The contour plot for the Disintegration time is shown in Figure 3. The 2D and 3D response surface plot derives that as the speed of granulator, the concentration of binder, PVP K 30 and concentration of moisture absorbent, Aeroperl 300 increases, DT time decreases. The contour lines are concentric in the contour plot (Figure 3a) since the interactions of terms (X_1, X₂) were found significant for DT as the acceptable region is in a full circle. While the interaction of X1 and X3 (Figure 3b) has a positive value, thus they will increase DT. Thus utilizing these interactions, DT can be adjusted according to the factor's value.

The design expert software suggested a quadratic model with an R² value equal to 0.9860 (p <0.0001). A high value of correlation coefficient (0.9860) indicates a good fit between the independent variables and the dependent variable (% drug release). The model is significant, with a P-value of <0.0001 (Table 5). The evolved mathematical model is

Y₂ (% drug release) = 93.80 +7.06 X₁ + 4.16 X₂ + 4.17X₃ -2.17X₁ X₂+0.1050X₁ X₃ -4.86 X₂X₃ -7.07X₁X₁-14.25X₂X₂-5.36X₃X₃ ………….equation 5

Significant effect on % drug release of the tablet was shown by the speed of granulator, the concentration of binder, PVP K 30 and concentration of moisture absorbent, Aeroperl 300, as they have a positive effect on drug release. The contour plot for the % drug release is shown in Figure 4. The desired value of % drug release is NLT 85% in 30 mins. The acceptable region is shown in green, yellow and red regions. The 2D and 3D response surface plot shows the interaction effect of parameters where the interaction effect of X₁X₂ and X₂X₃ are negative while that of X₁X₃ is positive; thus, utilizing these interactions, drug release can be tailored according to the values of factors. The contour plots show that PVP K 30 in the range of 3.5-6.5, Aeroperl 300 in the concentration range of 1.2-2 and RPM in the range of 300-600maximized the % drug release.

The design expert software suggested a quadratic model with an R² value equal to 0.9944, with (< 0.0001). A high value of correlation coefficient (0.9944) indicates a good fit between the independent variables and the dependent variable (Hardness). The model is significant, with a P-value of <0.0001 (Table 5). The evolved mathematical model is

Y₃ (Hardness) = 5.12 +0.3750 X₁ + 1.20 X₂ + 0.2988 X₃ +0.1500X₁ X₂ -0.2000X₁ X₃ +0.24756 X₂X₃ -0.4328X₁X₁-0.5353X₂X₂-0.3852X₃X₃…………..equation 6

Significant effect on hardness of the tablet was shown by the speed of granulator, the concentration of binder, PVP K30 and concentration of moisture absorbent, Aeroperl 300, as they all offer a positive effect, i.e. with an increase of these parameters, hardness will be maximized. The contour plot for the hardness is shown in figure 5. The desired value of hardness is 3-6 kg/cm². The acceptable region is shown in the green, yellow and red regions. The 2D and 3D response surface plot shows the interaction effect of parameters, and from the contour plots, we found that X₁X₂ and X₂X₃ show positive interaction. In contrast, X₁X₃ shows negative interaction; thus, utilizing these interactions, hardness can be tailored according to the values of factors.

The overlay plot is generated by superimposing the contour plots of all the regions, 23 as shown in Figure 6. The range selected for the overlay plot was ± 10 as per USFDA criteria.The relative error should not be more than 5% as per USP.

Predicted value - Observed valuePredicted value x 100........................equation 7

The optimized batch was selected based on the following criteria:

Disintegration time (180-300), % CDR at 30 min should >85%, and hardness should be 4-6.

Figure 6

To verify the evolved models, the optimum formulation was prepared according to values of the factors and subjected to Disintegration time, % Drug release and hardness, as shown in Table 6. It demonstrates that the observed value of a new batch was relatively closer to the predicted value. The prediction error was less than 5%, which validated the model applied.24, 25 All batches were evaluated for different evaluation parameters, and they all are within the desired range, as shown in Table 7.

An in-vitro comparison of the optimized batch with the marketed formulation is shown in Table 8. In-vitro comparison of optimized batch prepared using MADG with marketed formulation and tablet designed with wet granulation is shown in Table 9.

Disintegration time, % Drug release and hardness of optimized batch showed better results than marketed formulation and wet granulation.In-vitro comparison of an optimized batch with marketed formulation and tablet prepared with wet granulation demonstrates that the optimized MADG formulation shows considerably similar drug release, disintegration time and hardness as that of marketed formulation and has significantly better drug release and disintegration time and hardness compared to tablet prepared via wet granulation.

The stability study of the optimized batch showed (Table 10) no significant changes in Disintegrating time, % Drug release and hardness. The DT and hardness were slightly increased while drug release was decreased somewhat, but the changes are not significant.

MADG approach increase content uniformity, which was critical parameter of the study as the selected drug was having very low dose. Energy and time were also saved in this process. As per the literature search, very less work has been done on MADG till date.In present research work Bicalutamide: HP-ß-CD complex (1: 1) has been prepared to enhance the solubility of Bicalutamide due to partial conversion of crystalline to amorphous state.The kneading method and physical mixture both were employed for solubility enhancement. 11, 26 TheΔG°tr values were negative at the treated concentrations of the polymers, which reflect the spontaneous nature of the Bicalutamide solubilization. Screening of excipients results in selection of PVP K30 (5%) as binder, Avicel102 and LMH(1:1) as diluent, Aeroperl 300 (1.5%) as absorbent, Neusilin US2 (3%) along with Croscarmellose sodium (4%) as disintegrate. NeusilinUS2 showed synergistic effect with Croscarmellose sodium and helps in achieving target disintegration time.

The CQA of prepared tablet were optimized by using Box Behnken design. The seventeen batches were prepared using different speed of granulator (rpm), concentration of binder, PVP K 30 (%) and concentration of moisture absorbent, Aeroperl 300 (%) were evaluated. The granules had good flow and compression strength while tablet had good hardness, DT and %CDR. For the preparation of granules lab scale mixer granulator was used. 19 Comparison of optimized formulation with marketed formulation and wet granulation showed that optimized formulation gave results similar to that of marketed formulation and better than that of wet granulation. Short term stability study was conducted at 40˚±2˚ 75% ±5% RH for 1 month. Disintegration time, % CDR and Hardness were measured at frequent intervals and significant difference was not found.

MADG is a novel yet simple technique for granulation, which overcomes the downsides of highly used wet granulation method. The current research explored the MADG technique for preparation of tablets of a new non-steroidal anti-androgen drug Bicalutamide for treatment of prostate cancer. The combined effect of binder, moisture absorbent, and the optimized speed of granulator were reflected in the % Cumulative drug release (CDR), which showed better drug release than the conventional wet granulation method. Simplicity of technology and FDA approved excipients used in formulation can be taken further at industry level without complicated regulatory issues. If the aforementioned formulation will scaled-up to manufacturing level, the process will be easy by minimizing waste and saving time, energy and cost.

No conflict of interest.