Evaluation of a Natural Polymer for the Development of Colon Specific Drug Delivery System

Targeted drug delivery into the colon is highly desirable for local treatment of bowel diseases such as ulcerative colitis, Chrohn’s disease, amoebiasis, colon cancer and also for systemic delivery of protein and peptide drugs because of less digestive enzymatic activity compared to stomach and small intestine. To deliver the compounds in non degraded form to lower part of the Gastrointestinal Tract (GIT), they must first of all pass through the stomach, the upper part of intestine and must use the characteristics of the colon to specifically release the drugs in this part of digestive tract [1] .Various approaches have been developed for colon targeting including pH dependent systems, Time dependent system and Microbially triggered delivery system. The pH dependent delivery system protects the formulation in the stomach and proximal part of small intestine but it may start to dissolve in the lower part of small intestine and thus it shows poor site specificity [2]. Similarly time dependent delivery systems are not able to sense any variation in upper GIT transit time [3,4]. Colonic bacteria possess ability to degrade a variety of polysaccharides present in the diet that are not degraded either in stomach or small intestine. Hence, the use of biodegradable polymers holds great promise for drug delivery to colon [1].

Gums and mucilages are used as inert pharmaceutical excipients and also as medicinal agent. They are widely used in food and pharmaceutical industry as thickening, stabilizing emulsifying and disintegrating agents [5]. The polysaccharide gums represent one of the most abundant industrial raw materials and have been the subject of intensive research over comparable synthetic materials due to their sustainability, biodegradability and safety [6]. The most of the natural polymers are obtained from trees in the forms of gums as tree exudates. Tree exudates gum are polysaccharides with high molecular weight mainly composed of monosaccharide unit, uronic acid and to some extent proteins and fibers. The purpose of this study was to evaluate novel polymer derived from the tree exudates of Anogeissus latifolia (Combretaceae, Myrtales) as a colon specific drug delivery carrier. It is a large deciduous tree found in dry areas of India. It is also known as Gum ghatti or Indian gum. This plant exudates has been in use for a long time and its name is derived from the word “Ghat” which means a mountain pass because of its ancient mountain transportation routes. It is approved as a food additive in Japan and has Generally Recognized as Safe (GRAS) in United States.

Gum ghatti is an extremely complex polysaccharide that occurs in nature as mixed calcium and magnesium salts of uronic acid and/or ghattic acids and has also been reported to contain approximately 3% protein. It consists of L-arabinose, D-galactose, D-mannose, D-xylose and D-glucuronic acid in a 48:29:10:5:10 molar ratio and < 1% of rhamnose, which is present as nonproducing end groups. Gum contains alternating 4-O-substituted and 2-O-substituted μ-D-mannopyranose units and chains of 1 → 6 linked β-D galactopyranose units with side chains of L-arabinose units. This gum has been reported to be an excellent emulsifier, thickener and binder. The gum is comprised of around 80% soluble dietary fiber, acts as a prebiotic by supplying the matrix required to sustain the bacterial flora of the human colon. This hydrocolloid is resistant to gastrointestinal enzymes and known to be degraded enzymatically only by the specific microflora of the colon such as Bifidobacterium longum [6,7,9-11]. In this investigation, gum ghatti in the form of matrix tablets have been evaluated for its ability to deliver formulation to the colon using Diclofenac Sodium (DS) as a model drug.

Materials

Characterization of drug

 

Parameter	Results
Solubility	Soluble in hot water, forming a viscous solution; practically insoluble in chloroform, Acetone, Methanol Also polymer swells in 0.1 N HCl and phosphate buffer and shows good gelling properties.
Moisture content (%)	3%
Ash Value	4%
Acid Insoluble ash	1.60%
Water soluble ash	1.40%
Viscosity 10% solution (Cps)	400
Swelling Index (%)	150
Heavy metals	Not more than 10 ppm
Ethanol soluble Extractive(%w/v)	0.8% w/v
Density (g/ml)	Bulk- 0.9 ± 0.010
	Tapped- 0.984 ± 0.011
Carr’s index (%)	8.54 ± 0.78
Hausner’s ratio	1.09 ± 0.055
Angle of repose (θ)	29.340 ± 0.53

Table 2: Characterisation of natural polymer.

The gum powder exhibited insolubility in common solvents except distilled water. The moisture content, ash value and all other parameters were within the limits as specified in official compendium. The values of angle of repose, Carr’s index, Hausner’s ratio indicated that the polymer has good flow property and compressibility.

FTIR spectrum of natural polymer: IR spectrum of natural polymer (Figure 1b) showed broad peaks at 3408.4 cm^-1 (O-H stretching of carbohydrates), 2928, 1406, 1234 cm^-1 (-CH2 asymmetric stretching, scissoring and twisting and rocking vibration of methylene groups, 1445.35 cm^-1 (-CH and -CH₂ in plane bending in carbohydrates), 1089.51cm^-1 (-C-O stretching region as complex bands resulting from C-O and C-O-C stretching vibrations) and 643.71 cm^-1 (pyranose ring).

 

Figure 1b: IR spectrum of natural polymer.

 

Drug-excipients compatibility study: IR spectra of physical mixture of drug and polymer (Figure 1c) reveals that the principal peaks of DS for NH₂ at 3387cm^-1, aromatic at 1573 cm^-1 and at 746 cm^-1 (ortho-disubstituted phenol) are present in both, the spectra of pure drug and physical mixture with the natural polymer.

 

 

 

Figure 1c: IR spectra of drug +polymer.

 

FTIR studies suggested absence of any significant interaction between the polymer and the drug in the formulation.

Physicochemical evaluation: The physicochemical evaluation of developmental batches F1-F9 showed good flow property, uniformity of weight & drug content in powder blend as well as optimum hardness and friability limit specified for tablet formulations. The results are depicted in table 3 and table 4.

 

Test Batch	Bulk Density	Tapped density	Carr’s index	Hausner’s Ratio	Angle of repose
F1	0.73±0.034	0.79±0.003	7.59±1.1	1.08±0.0023	31.36±0.21
F2	0.69±0.065	0.75±0.003	8.01±0.51	1.07±0.005	31.99±0.25
F3	0.7±0.025	0.75±0.03	6.66±1.07	1.07±0.001	31.07±0.18
F4	0.74±0.005	0.81±0.001	8.02±0.66	1.08±0.005	32.61±0.04
F5	0.74±0.005	0.84±0.01	11.9±0.72	1.08±0.007	32.64±0.37
F6	0.68±0.04	0.73±0.02	6.84±0.61	1.07±0.007	30.81±0.22
F7	0.75±0.03	0.82±0.04	8.53±0.4	1.08±0.004	32.81±0.08
F8	0.82±0.042	0.88±0.056	6.81±0.56	1.09±0.005	33.16±0.22
F9	0.81±0.005	0.87±0.041	6.89±1.07	1.076±0.011	33.62±0.05

Table 3: Evaluation of developmental batches F1-F9 (powder blend).

 

Test	Tablet weight (mg)	Hardness (Kg/cm2)	Friability (%)	Drug Content (%)
Batch
F1	300.75±3.38	4.33±0.28	0.32±0.16	102.9±1.98
F2	298.25±4.6	5.13±0.32	0.44±0.19	100.5±0.57
F3	300.7±3.04	6.01±0.5	0.58±0.13	99.26±2.50
F4	302.9±4.16	6.50±0.5	0.24±0.15	96.60±2.75
F5	300.5±4.17	6.50±0.5	0.26±0.15	96.30±1.13
F6	299.9±4.16	6.00±0.45	0.66±0.10	98.96±1.15
F7	299.6±4.07	6.33±0.5	0.20±0.10	102.0±1.26
F8	301.0±3.62	5.83±0.28	0.21±0.16	96.63±2.56
F9	301.1±4.63	6.00±0.5	0.56±0.20	97.03±1.91

Table 4: Evaluation of developmental batches F1-F9 (tablets).

The precompression parameters of all batches were found to be in acceptable range indicating good flow behaviour.

The weight variation and friability was not more than 5% and 1% respectively. Good drug content uniformity was found among different batches of the tablets.

In vitro drug release study: The result of in vitro drug release is depicted in figure 2. All formulations (F1 - F9) were able to retain tablet in intact form up to 12 hrs and also sustained drug release up to 12 hrs. All the developed batches were capable of preventing drug from being released completely in the physiological environment of stomach but showed certain drug release in the small intestine. The formulations F3 and F6 were able to minimize the drug release up to 25% in the lag time of 5 hrs. All the developed batches showed cumulative drug release more than 90% after 12 hrs.

 

Figure 2: in vitro drug release profile of developmental batches (F1-F9).

The in vitro drug release studies revealed that formulations F1 to F9 containing respectively 20, 30 and 40 % of natural polymer (Anogeissus latifolia gum) were able to sustain the drug release for 12 hrs. Hwever, the purpose of colon targeted drug delivery system was not only to sustain the drug release up to 12 hrs but also to minimize drug release in the physiological environment of the stomach and intestine. Hence, the ability of the polymers used in the formulations to retain the integrity of tablet in upper GIT was the challenge.

The developed batches were able to prevent the drug release in acidic environment of stomach due the acid resistant property of natural polymer as well as low solubility of drug in acidic medium i.e., in first 2 hrs but unable to prevent the drug release in intestinal pH. Thus minimum drug release in lag time (5 hrs) i.e., drug release in between 20-25% was the basis of selection of optimized batch. The batches with higher concentration of natural polymer with low and intermediate concentration of HPMC K100M respectively showed minimum drug release i.e., ≤ 25% in lag time of 5 hrs. This can be explained on the basis that on increase in natural polymer concentration, hardness of tablets was increased and porosity was decreased which reduced the drug release in lag time. But the batch with higher concentration of both natural polymer and HPMC K100M showed more swelling in initial hours so unable to maintain drug release below 25% in lag time.

Optimization data analysis: The data obtained after putting all values for % CDR in lag time and % CDR in 12 hrs of all 9 batches analysed to get the optimum formulation based on the desired objective. Polynomial models including interaction and quadratic terms were generated for the entire response variables using Multiple Linear Regression Analysis (MLRA) approach. The general form of the MLRA model is represented in the Equation



Whereas, the B₀ is the arithmetic average of all the quantitative outcomes of nine runs and B₁ and B₂ are the coefficients computed from the observed experimental values of Y. X₁ and X₂ are the coded levels of independent variables. The interaction terms (X₁ and X₂) shows how the response values changes when the two factors are simultaneously changed. The polynomial equations can be used to draw conclusion after considering the magnitude coefficient and the mathematical sign that the coefficient carries. A high positive or negative value in the equation represent that by making a minor change in the setting of that factor one may obtain a significant change in the dependent variable. Statistical validity of the polynomials was established on the basis of Analysis of Variance (ANOVA) provision in the Design Expert software. Level of significance was considered at p < 0.05. The best-fitting mathematical model was selected based on the comparison of several statistical parameters, including the Coefficient of Variation (CV), the multiple correlation coefficient(R2), the adjusted multiple correlation coefficient (adjusted R2) and the Predicted Residual Sum of Squares (PRESS), provided by the software. PRESS indicates how well the model fits the data, and for the chosen model, it should be small relative to the other models under consideration. The 3-D response surface graphs and the 2-D contour plots also generated by the Design Expert software. These plots are very useful to see interaction effects of the factors on responses.

Model assessment for the dependent variable: %CDR in lag time

Final equation in terms of actual factors:

%Drug release in lag time = +57.38222-0.93533(X1)-1.11092(X2)+0.036625(X1)(X2)

X1=Proportion of natural polymer (Gum Ghatti); X2=Proportion of. Of HPMC K 100

The Model F-value of 6.34 (Table 5) implies the model is significant. There is only a 3.72% chance that a “Model F-Value” this large could occur due to noise. Values of “Prob > F” less than 0.0500 indicate model terms are significant. In this case AB is significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. The 3D response and contour plot is depicted in figures 3a and 3b.

 

Source	Sum of	Df	Mean	F-value	P-value	Significance
	squares		Square		Probe>F
Model	50.07	2	25.03	18.23	0.0028	Significant
Conc. Of Natural polymer	0.13	1	0.13	0.094	0.7695	-
Conc. Of HPMC K100 M	49.94	1	49.94	36.36	0.0009	Significant
Residual	8.24	6	1.37
Core total	58.31	8

Table 5: Analysis of variance for Y1.

 

Figure 3a: 3D Response plot of %CDR in lag time.

 

Figure 3b: Contour plot of % CDR in lag time.

Model assessment for the dependent variable: % CDR in 12h

Final equation in terms of actual factors:% CDR in 12 HRS= +102.49667+0.014667(X1)-0.28850(X2)

X1=Conc. of natural polymer (Gum Ghatti); X2=Conc. of HPMC k 100 M

The Model F-value of 18.23 (Table 6) implies the model is significant. There is only a 0.28% chance that a “Model F-Value” this large could occur due to noise. Values of “Prob > F” less than 0.0500 indicate model terms are significant. In this case B is significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. The 3D response and contour plot is depicted in figures 4a and 4b.

 

source	Sum of	Df	Mean	F-value	P-value	Significance
	squares		Square		Probe>F
Model	78.43	3	26.14	6.34	0.0372	Significant
Conc. Of Natural Polymer	24.68	1	24.68	5.98	0.0582	-
Conc. HPMC K100 M	0.089	1	0.089	0.022	0.8891	-
AB	53.66	1	53.66	13.01	0.0154	Significant
Residual	20.62	5	4.12
Core total	99.05	8

Table 6: Analysis of variance for Y2.

 

 

Figure 4a: 3D Response plot of %CDR in 12h.

 

Figure 4b: Contour plot for % CDR in 12hrs

 

Solutions for optimized batch: After analysis of both independent variables (i.e. factor) and dependant variables (i.e., response) Design Expert® software gives solutions. One batch from the solutions provided by software was selected as an optimized batch based on desirability value depicted in table 7.

 

Sr. No.	Amount of natural polymer (%w/w)	Amount of HPMC K 100M	% CDR in 12 hrs	% CDR in lag time	Desirability
1	40%	10%	100.1	23.5	1

Table 7: Solution for optimized formulations.

The optimized batch was then developed and evaluated for various physicochemical properties and the results of physicochemical evaluation and in vitro drug release study for optimized formulation have been depicted in table 8 and figure 5 respectively.

 

Sr. No.	Evaluation Parameters	Result
1.	Weight Variation	300.6±2.78
2.	Hardness	5.83±0.28
3.	Friability (%)	0.46±0.13
4.	Drug content	100.26±0.5
5.	% CDR in lag time (5 h)	23.92±1.77
6.	%CDR (12h)	100.08±0.31

Table 8: Evaluation results for optimized formulation.

 

 

Figure 5: in vitro drug release profile of optimized batch.

 

Kinetic analysis of dissolution data: Drug release data of optimized formulation showed good fit into the zero order equation (r²=0.9848), partially fitted in Higuchi equation (r²=0.92) and also showed high linearity with Korsmeyer equation (r²=0.94). The Korsmeyer-Peppas equation for drug release is given below:



Where, Mt=is the amount of drug released in time t; M_∞=amount of drug release at infinite time K is constant, and n represents the release exponent indicative of mechanism of drug release.

When n=0.5 means Fickian diffusion, 0.5>n
Stability study: The stability studies were carried out for the optimized formulation. The optimized formulation did not show any significant change in hardness, friability and drug content when kept at accelerated conditions of temperature and humidity. Also no significant difference in values of in vitro drug release profile observed during the stability studies (Figure 6).

 

 

Figure 6: in vitro dissolution profile for stability batches.

 

The formulation was found to be stable under accelerated conditions of temperature and humidity showing proper hardness, optimum friability, uniform drug content and uniform in vitro drug release behaviour during 3 months accelerated stability studies.

This study exhibited that it is possible to control the release rate of Diclofenac sodium over a wide time scale using Anogeissus latifolia as a sustained release polymer. The combination of both natural and synthetic polymers can be a better choice in comparison to costly synthetic sustained release polymers to achieve desired sustained release effect of formulation. The present study provides a new alternative which is cheaper, having lesser side effects & biocompatible formulation of Diclofenac sodium in the treatment of IBD. Thus this polymer proved to be an excellent carrier for colon targeting and can be exploited commercially.

1. Jain A, Gupta Y, Jain SK (2007) Perspective of biodegradable natural polysaccharides for site-specific drug delivery to colon. J Pharm Pharm Sci 10: 86-128.
2. Ashford M, Fell JT, Attwood D, Woodhead P (1993) An in vitro investigation into the suitability of pH-dependent polymers for colonic targeting. Int J Pharm. 91: 241-245.
3. Fukui E, Miyamura N, Kobayashi M. (2001) An in vitro investigation of the suitability of press-coated tablets with hydroxypropylmethylcellulose acetate succinate (HPMCAS) and hydrophobicn additives in the outer shell for colon targeting. J Control Release 70: 97-107.
4. Ashford M, Fell JT, Attwood D, Sharma H, Woodhead P (1994) Studies on pectin formulations for colonic drug delivery. Journal Controlled Release 30: 225-232.
5. Jani GK, Shah DP, Prajapati VD, Jain VC (2009) Gums and mucilages: versatile excipients for pharmaceutical formulations. Asian J Pharm. 4: 308-322.
6. Deshmukh AS, Setty CM, Badiger AM, Muralikrishna KS (2012) Gum ghatti: A promising polysaccharide for pharmaceutical applications. Carbohydrate Polym. 87: 980-986.
7. Kaur L, Singh J, Singh H (2009) Characterisation of gum ghatti (Anogeissus latifolia): A structural and rheological approach. J Food Sci. 74: 328-332.
8. Cartensen JT, Rhodes CT (2005) Preformulation. In: Cartensen JT, Rhodes CT (eds.). Drug Stability principles and practices (3rd edn)., Marcel Dekker Inc., New York, USA.
9. Kora AJ, Beedu SR, Jayaraman A. (2012) Size controlled green synthesis of silver nanoparticles mediated by gum ghatti (Anogeissus latifolia) and its biological activity. Org Med Chem Lett 2: 17.
10. Salyers AA, Vercelotti JR, West SE, Wilkins TD (1977) Fermentation of mucin and plant polysaccharides by strains of Bacteroides from the human colon. App Environ Micro 33: 319-322.
11. Crociani F, Alessandrini A, Mucci MM, Biavati B (1994) Degradation of complex carbohydrates by Bifidobacterium spp. Int J Food Micro 24: 199-210.
12. Ministry of Health and Family Welfare (2007) Indian Pharmacopeia (5thedn). Indian Pharmacopeia Commission Ghaziabad, India.
13. Reddy KJ, Gaikwad SB (2011) Preliminary phytochemical standardisation of tree exudates from India: Gum kondagogu and gum ghatti. Res J Pharm Bio Chem Sci 2: 1023-1034.
14. British Pharmacopoeia (2009) British Pharmacopoeia (Vol III). The stationary office, London, UK.
15. United States Pharmacopeial Convention (2007) United States Pharmacopoeia. United States Pharmacopeial Convention, Rockville, USA.
16. Jain NK (2004) Response Surface optimization of drug delivery system. In: Jain NK (ed.). Progress in controlled and novel drug delivery system, CBS Publishers and Distributors, New Delhi, India.
17. Dash S, Murthy P, Nath L, Chowdhury P (2010) Kinetic modelling on drug release from controlled drug delivery systems. Acta Pol Pharm 67: 217-223.
18. Cartensen JT, Rhodes CT (2005) Preformulation. In: Cartensen JT, Rhodes CT (eds.). Drug Stability principles and practices (3rdedn.) Marcel Dekker Inc., New York, USA.