Fabrication and Characterization of Single Layer Osmotic Pump (SCOP) by Solubility Modulation Approach for Fluvoxamine Maleate

 

Ghanshyam M. Umaretiya¹, Dr. Jayant R. Chavda², Dr. Jayvadan. K. Patel³

¹Research Scholar, School of Pharmacy, RK University, Rajkot, Gujarat, India.

²B.K. Mody Government Pharmacy College, Gujarat, India.

³Nootan Pharmacy College, Gujarat, India

 

ABSTRACT:

Fluvoxamine maleate (FLV) is a sparingly water-soluble drug which is prescribed for compulsive disorder (OCD) and social anxiety disorder. Pharmacokinetics parameters of FLV urge it to be formulated into controlled release design which provides constant release. So, in the present study an attempt has been made to develop single core osmotic pump (SCOP) along with solubility modulation of FLV. Different tools of QbD were employed for risk free formulation of SCOP. Central composite design (CCD) was used defining, amount of osmogene (X1) and amount of leachable component in coating (X2) as independent variables (IVs). The quantification of FLV was done by UV method with a linearity range of 5-25μg/mL. Citric acid was found as best solubility modulator which had shown 43.12% increment in solubility of FLV. The stand error of applied CCD was less than 1. The ANOVA results of CCD proved significant effect of selected IVs on critical quality attributes of FLV osmotic pump (FLVOP). Initial drug release from SCOP was greatly affected by the amount of leachable component in coating. %Error was found to be less than 5% in check point batches confirming suitability of developed multiple linear regression (MLR) equations. Risk free control space was outlined from overlay region. The optimized batch was composed of 13.04% osmogen (Xylitab) and 12.79% leachable component in coating (HPMC E5). The SEM study helped to understand the mechanism of drug release from SCOP. The drug release data were best suited to zero order with RSQ is 0.998. The drug release profile of optimized batch was unaffected by change in pH, agitation and ionic strength. Short term stability data proved stable characteristics of developed SCOP of FLV.

 

 

 

INTRODUCTION:

Greater attention is focused on development of modified drug delivery systems due to drawbacks of conventional dosage forms and increment in expense and complications involved in marketing of new drug entities. New delivery systems become attractive due to toxicity and ineffectiveness of drugs when administered in conventional dosage forms including tablets, capsules, injectables, ointments etc.

 

Conventional dosage form shows vast fluctuation in drug concentration in the plasma and tissues with consequent unwanted toxicity and poor efficiency. Moreover, repetitive dosing frequency and unpredictable absorption led to employment of the concept of controlled drug delivery systems¹.

 

The aim of fabrication of controlled delivery systems is to reduce dosing frequency or to increase effectiveness of the drug by localization at the site of action, reducing the dose required or providing uniform drug delivery. Thus, controlled release dosage form is a design which releases one or more APIs unremittingly in a preset pattern for a fixed time, either systemically or to a specified target organ constant delivery, less side effect and dosing frequency².

 

Among all the routes that have been employed for systemic delivery of APIs through different dosage for, oral route is the most widely accepted route of administration as it is considered non-complicated, natural, convenient and safe due to self-medication, patient friendly, cost effective development process. The conventional oral dosage forms show peak and valley phenomenon (fluctuation in drug plasma concentration) when pharmacokinetics of any API is studied after oral administration. This is not desirable because such changes significantly affect pharmacodymanic profile of API. So, it is always recommended to develop optimized dosage regimen which constantly release drug at fixed rate without any considerable variation in drug plasma concentration³.

 

Significant attempts have been made in the development of drug delivery devices which can precisely control the rate of drug release for an extended period of time. Out of them, osmotic controlled drug delivery system is considered as a best approach for achieving zero order drug release pattern which is always desirable for any controlled release drug delivery systems (CRDDS). Osmotic drug delivery systems (ODDS) utilize osmotic pressure as a driving force to expel drug form device and helps to main constant drug plasma concentration with in therapeutic window at constant rate⁴. Moreover, it is not affected by change in pH and other physiological factors including gastric motility, presence of food and diseased state^5-9.

 

Many water soluble drugs are formulated in different forms of osmotic pump including (Elementary OP, Push pull OP, porosity controlled OP)^10-14. The key part in fabrication of ODDS is solubility of API and generation of osmotic pressure¹⁵. Highly water soluble drugs are solely capable to create enough osmotic pressure to expel drug in media and also with the help of osmogen this can be assisted. On other hand it is challenging to delivery poorly water soluble drugs via ODDS, as poorly water-soluble drugs cannot generate sufficient osmotic pressure and expelled out at low rates. The problem can be solved by solubility modulation of API using different approaches¹⁶. Many researchers have contributed in this line of research and successfully delivery poorly soluble APIs (Glibenclamide, Gliclazide) through ODDS^17,18.

 

Fluvoxamine is selective serotonin reuptake inhibitor and pharmacologically classified as an antidepressant. The chemical name is 5- methoxy-4‟ trifluoromethyl) valerophenone - (E)-O-(2-aminoethyl) oxime maleate and mostly used to treat obsessive-compulsive disorder¹⁹. It is marketed by GlaxoSmithKline under registered trademark of Lotronex^TM. It is sparingly soluble in water (0.00734mg/mL). Generally it is given BID (>100mg into 2 doses) in adults and (>50mg into 2 doses) in children. More change in FLV plasma concentration remarkably affects therapeutic response. So, it is justifiable to design SCOP for FLV which can deliver the drug in a constant rate.

 

Thus, in the present study, solubility of FLV was modulated using citric acid then SCOP was developed and well characterized.

 

MATERIALS AND METHODS:

Materials:

Fluvoxamine maleate (FLV) was received as a gift sample from Ramdev Chemical Pvt. Ltd. (Boisar- Maharashtra, India). Xylitab, HPMC E5 and Poloxamer 188 were received as gift samples from Zydus Research Center (Ahmedabad, India). Citric acid, Tartaric acid, PEG 4000 and mannitol were purchased from Rakesh Chemicals, India. Double distilled water was used wherever required. Other chemicals were of laboratory grade.

 

Quantification of FLV:

Quantification of FLV was done by double-beam UV spectrophotometer (Shimadzu-1800, Kyoto, Japan) in the present work. A known detectible amount of FLV (10μg/mL) was taken and dissolved in the 0.1 N HCl and subsequently diluted with distilled water. The final solution was analyzed at 246nm. Standard concentrations were prepared in the range of 5-30μg/mL and studied for 3 days for inter-day and intra-day variations. Other validation parameters were found for FLV²⁰.

 

Solubility modulation of FLV:

Solubility modulators are the components which change environmental pH and help API to solubilize at faster rate. Additionally, it also acts as wicking agent and in some cases also increases osmotic pressure. With a goal of solubility enhancement of FLV, different solubility modulators including citric acid, tartaric acid, poloxamer-18, Poly Ethylene Glycol (PGE) 4000 and mannitol were used in a conjugation with FLV. Drug and solubility modulators were physically blended with mortar and pestle and its aqueous solubility was determined.

 

Application of QbD tools:^{21, 22}

Identification of QTTP and CQAs:

Considering desirable criteria of FLVOP and different factors impacting quality of formulation, QTPP and CQAs were finalized and properly justified. 

 

Risk assessment studies:

A fishbone diagram was delineated for proper interpreting the effect of different independent variables (IVs) on quality of product (CQAs). A risk estimation matrix was outlined relating magnitude of risk on critical quality attributes (CQAs). The risk categorized into high, medium and low values and assigned to each factor accordingly.

 

Application of Central Composite Design (CCD):²³

After detail risk assessment study, the impact of risky factors on selected CQAs was done by employing CCD. The detail layout of CCD formulation batches are summarized in Table 1. The applied design was validated by Standard Error Graph (SEG) and its standard error was found. Independent variables were fixed as amount of osmogen (X₁) and amount of leachable coating component (X₂). Dependent variables were fixed as % drug release in first hour (%Q₁), Time required for 25% drug release (T₂₅), Time required for 50% drug release (T₅₀), Time required for 75% drug release (T₇₅), and Time required for 100% drug release (T₁₀₀).

 

Table 1. Layout of CCD batches

Batch	Coded values		Actual values
	X1	X2	X1	X2
F1	-1	-1	6	6
F2	1	-1	20	6
F3	-1	1	6	20
F4	1	1	20	20
F5	-α	0	3.100505	13
F6	+ α	0	22.89949	13
F7	0	-α	13	3.100505
F8	0	+ α	13	22.89949
F9	0	0	13	13
F10	0	0	13	13
F11	0	0	13	13
F12	0	0	13	13
F13	0	0	13	13
CKP1	0.003	-0.016	13.04	12.79
CKP2	0.063	-0.082	13.83	11.93

 

Also to confirm the evolved model, different check point batches (CPK1 and CPK2) were formulated. % PE was also determined to assess the accuracy of evolved model. Detail ANOVA study was performed to under the significant and non-significant impact of factors.

 

                                  Experimental value-Predicted value

Percentage error  (%PE) = -------------------------------X 100

                                       Experimental value

 

Preparation of core tablet:

The core tablets are prepared by direct compression. All the ingredients are weighed accurately on electronic balance (Lab Intelligence, India). The drug and solubility enhancer (citric acid) were mixed according to geometrical dilution method and were triturated to remove any coarse particles. After passing this mixture through 20# sieve, Osmogen (Xytilab) was added in geometric dilution and mixing continued for additional 10 min. The blend was then compressed with a hardness of 4-5kg/cm² using 10mm round flat faced punches on 12 station tablet machine (Rimek Mini Press II). Tablet of each batch contained 150mg of FLV.

 

Coating of core tablet:

The core tablet was coated by homogenous mixture of Cellulose acetate (CA) and leachable component (HPMC E5) in acetone: methanol (9:1) containing known amount of Dibutyl phthalate (DBT). Spray solution was prepared using Remi’s stirrer. Each batch of 100 convex shaped core tablets were coated in a conventional standard coating pan (Labtronik, India) with conditions (Inlet air temperature, 45°C; air flow rate, 1.4 kg/cm²; coating spray rate, 4-5ml/min and pan speed 25rpm).

 

Physical Evaluation:

The dry blend of core tablet was evaluated for various pre-compression parameters. The prepared core tablets and coated tablets were inspected manually for any sign of defects. The core tablet and coated tablet were evaluated for weight variation, drug content, thickness, diameter, hardness and friability^24-26.

 

In vitro drug release study:

In vitro release studies of different formulations were performed according to USP apparatus II, paddle method. Paddle speed was maintained at 50rpm and 900 mL of water used as the dissolution medium. Samples (10mL) were collected at predetermined time intervals (1, 2, 3, 4, 6, 8, 10, 12, 16, 20 and 24 hrs) and replaced with equal volume of fresh medium, filtered through a 0.45 µm filter and analyzed with a UV-Visible spectrophotometer at 246nm. Drug concentration was calculated from a standard calibration plot and expressed as cumulative % drug dissolved²⁷.

 

Drug release kinetics:

In vitro release profile of the optimized batch FLVOP was fitted in various in vitro release kinetics models. Amongst them best fitting model was selected on the basis of R² value, SSR value and F value. The study was assisted by DD solver.

 

Effect of variables on drug release:

With the aim to achieve independent, constant and uniform drug release, FLVOP was developed. To determine the robustness of drug release behavior from FLVOP and independent release from system, effect of different variables including effect of pH, agitation and ionic strength on dissolution was studied.

 

Surface morphology:

To understand the drug release mechanism through pore formation, it is mandatory to examine surface morphology of FLVOP surface before and after dissolution study. Scanning electron microscope (SEM) was employed to observe the density of pores after dissolution study²⁸.

 

Stability study:

The optimized batch (OB) of FLVOP was submitted to stability chambers (Model-TH 90 S, Thermolab, India) for short term stability study as per ICH guidelines (40± 2°C and 75±5% RH; 3 months). The FLVOP was packed in flint vials and sealed hermetically with rubber plugs and aluminum caps. Samples were taken out at 1, 2 and 3 months and checked for different performance and physicochemical parameters²⁹.

 

RESULT AND DISCUSSION:

Quantification of FLV:

The drug solution in 0.1 N HCl exhibited a χ_max at 246 nm. Calibration curves (5-30μg/mL) were made using freshly prepared solutions for 3 consecutive days. The coefficient of variation (CV) determined on the basis of the absorbance for six triplicate measurements were found to be 0.416% and 0.385% for intra and inter day assay precision respectively. The% recovery was found to be varying from 98.75±0.6148 to 101.19±0.4915 indicate that proposed method was accurate. A high degree of correlation was established between concentrations and respective absorbance (R² = 0.999).

 

Solubility modulation of FLV:

The results of solubility increment in FLV are presented in Figure 1. Data clearly indicate that citric acid have drastically increased solubility of FLV amongst all tried solubility modulators. The results are attributed to the change in environment pH of surroundings of FLV.  As FLV is basic in nature, citric acid favors acidic pH which fastens solubility.

 

Figure 1. % Solubility increment of FLV by different solubility modulators

 

Application of QbD tools:

QTPP for FLVOP are summarized in Table 2. All QTPPs were justified considering osmotic pump design of FLV satisfying zero order drug release pattern.

 

Risk assessment:

Fishbone diagram as shown in Figure 2 indicates list of various factors which may affect the quality of FLVOP with an intensity of minor to major.

 

 

Table 2. Quality Target Product Profile (QTPP) for FLVOP

QTPP	Target	Justification
Dosage form	Tablet (Osmotic pump)	Suitable drug delivery system which provides constant release and not affected by variables.
Route of administration	Oral	Recommended route for efficacy
Dosage strength	150 mg	Pharmaceutical equivalence
Expected drug release	Zero order	To achieve constant drug plasma level in blood without major fluctuation
Impurity	Below safety threshold	To avoid any chance of toxicity
Assay	Acceptable limit	To achieve proper pharmacological response
Content uniformity	Acceptable limit	To maintain uniformity from batch to batch and consequently uniform therapeutic response
Stability	At least 24 months	To maintain therapeutic integrity of API for stipulated storage period
Container closure system	System qualified as suitable for this drug product	Needed to achieve the targeted shelf life

 

The CQAs were identified for FLV OP considering its impact on safety and efficacy. All Quality attributes (QAs) are summarized in Table 3 and out of them, selected CQAs were studied further using DoE.

 

 

Table 3. Critical Quality Attributes (CQAs) for OZ loaded ME with justification

Quality attributes of the drug products	Target	Is this a CQA?	Justification
Physical attributes ·   Color ·   Odor ·   Appearance	Transparent No unpleasant odor Acceptable to patients	No	They are not directly associated to efficacy and safety
Assay and content uniformity	100%	No	Proper mixing and direct compression method helps to maintain desired assay and CU in acceptable range.
% Q1 (% drug released within 1h)	3.5-4.5	Yes	To maintain minimum effective concentration (MEC) as early as possible
T25 (Time required to achieve 25% drug release)	5.5-6.5	Yes	Time required to achieve 25% drug release to obtain for zero order profile
T50 (Time required to achieve 50% drug release)	11.25-12.75	Yes	Time required to achieve 50% drug release to obtain for zero order profile
T75 (Time required to achieve 75% drug release)	17-19	Yes	Time required to achieve 75% drug release to obtain for zero order profile
T100 (Time required to achieve 100% drug release)	23-25	Yes	Time required to achieve 100% drug release to obtain for zero order profile
Microbial limits	Meets relevant pharmacopoeial requirements	No	Non compliance to microbial limits will affect safety profile of formulation. Though critical care during development may reduce bio-burden in final product.
Water content	NMT 4.0% w/w	No	Generally, water content may affect stability but FLV is not moisture sensitive and so stability may not be affected.

 

Figure 2.  Fishbone diagram

 

Table 4. Risk estimation matrix

CQAs	Conc. of Osmogen	Solubility modulator	Coating Polymer	Leachable component in coating	Compression force
%Q1	Medium	High	Medium	High	Medium
T25	High	High	Low	High	Medium
T50	High	High	Low	High	Low
T75	High	High	Low	High	Low
T100	High	High	Low	High	Low

 

Moreover, the Risk Estimation Matrix (REM) was outlined (Table 4) and the factors having high risk on selected CQAs were further studied in optimization section.

 

Validation of CCD:

Figure 3 shows standard error graph (SSG) of applied CCD. This graph represents over all standard error which is less than unity proving rationalized selection of CCD for given data set in formulation of FLVOP.

 

Figure 3. SEG plot of applied CCD for FLVOP

 

Application of CCD:

The results of CCD batches are presented in Table 5. The results show that remarkable variation in data confirming sensitivity of selected independent variables (X1 and X2) on CQAs.

 

Table 5. Results of CQAs of CCD batches

Batch	%Q1	T25	T50	T75	T100
F1	2.5	10.3	15.3	23.1	32.6
F2	2.8	4	9.3	15.4	20.1
F3	6.4	5.3	9.3	12.8	16.8
F4	8.4	3.5	5.7	7.5	10.1
F5	3.1	9.7	19.3	26.1	33.9
F6	3.8	5.3	8.3	12.1	15.9
F7	1.8	8.3	15.3	20.9	27.4
F8	10.3	2.8	5.8	8.3	11.9
F9	4.3	6.2	12.3	16.6	24.3
F10	4.2	5.9	12.6	17.3	24.6
F11	4.3	6.2	12.9	17.3	25
F12	3.9	6.1	12.7	17.1	24.9
F13	4	6	12.6	17	24.3

 

The ANOVA analysis of selected dependent and independent variables is shown in Table 6. The significant and non-significant level of main, interaction and polynomial effect are denoted as ‘S’ and ‘NS’.

 

Table 6. ANOVA analysis of IVs and CQAs for FLVOP

Source	Y1		Y2		Y3		Y4		Y5
	p-value	S/ NS	p-value	S/ NS	p-value	S/ NS	p-value	S/ NS	p-value	S/ NS
Model	< 0.0001	S	< 0.0001	S	0.0017	S	0.0001	S	< 0.0001	S
A-A	0.0303	S	< 0.0001	S	0.0007	S	0.0001	S	< 0.0001	S
B-B	< 0.0001	S	< 0.0001	S	0.0012	S	< 0.0001	S	< 0.0001	S
AB	0.0884	NS	0.0056	S	0.4641	NS	0.4447	NS	0.1175	NS
A2	0.1337	NS	0.0465	S	0.9722	NS	0.4189	NS	0.4854	NS
B2	0.0004	S	0.0750	NS	0.0294	S	0.0162	S	0.0016	S

(S=Significant, NS= Non significant)

 

The detail ANOVA study reveals that the model best fits for all selected five responses (Y1-Y5). Further, factor X2 has significant effect on drug release in initial hours. Though factor X1 is considerable, but the impact of X1 is also increased when X2 is increased. The reduced MLR equations for Y1-Y5 are summarized as below.

 

Y1 (%Q1)= +4.14 +0.41*X1 +2.69*X2 +1.02*X2²

Y2 (25) =

+6.08 -1.79*X1-1.66*X2 +1.13*X1X2 +0.52* X1²

Y3 (50)  =+12.62-3.144 *X1-2.87X2+0.60*X2²

Y4 (T75) =+17.06-4.099 *X1-4.502*X2-1.76X2²

Y5 (T100)= +24.62 -5.58* X1-5.97*X2 +1.45*X1X2 -0.45*X1² -3.08*X2²

 

Furthermore, the impact of independent variables (X1 and X2) on selected CQAs (Y1-Y5) was studied by contour plots and response surface plots. The response surface plots and overlay plot of all contour plots are show in Figure 4. The curvature in surface response plot itself indicates the sensitivity of X1 and X2 on Y1-Y5. All physico-chemical parameters of CCD batches were in pharmacopoeial limit.

 

Figure 4.  Response surface plots and overlay plot

Check point batches were defined from the yellow region of overlay plot to find the validity of reduced MLR evolved models. % PE of check point batches were calculated and were found below 5% (Table 7), which proves the legitimacy of acquired models³⁰.

 

Table 7. %PE of check point batches

Check point batches	CQAs	Observed	Predicted	%PE
CPK1	Y1	4.1	4.06	0.985
	Y2	6.2	6.12	1.307
	Y3	12.3	12.68	2.997
	Y4	17.6	17.16	2.564
	Y5	24.1	24.76	3.069
CPK2	Y1	3.6	3.76	4.255
	Y2	6.3	6.09	3.448
	Y3	12.1	12.64	4.272
	Y4	18.0	17.22	4.530
	Y5	24.6	24.77	0.686

 

Based on control space (Figure 5) revised risk assessment study was performed and revised REM (Table 8) was prepared where all IVS revealed low risk on CQAs.

 

Figure 5. Derivation of Control space

 

Also the dissolution of FLVOP was performed in different variables. In all varying conditions, non-significant deviation was observed amongst all dissolution profiles. This indicates that SCOP is robust design which release drug without being affected by different variables (pH, agitation, ionic strength).

Table 8. Updated risk assessment for FLVOP

Drug product CQAs	Risk estimation matrix
	Conc. of Osmogen	Solubility modulator	Coating Polymer	Leachable component in coating	Compression force
%Q1	Low	Low	Low	Low	Low
T25	Low	Low	Low	Low	Low
T50	Low	Low	Low	Low	Low
T75	Low	Low	Low	Low	Low
T100	Low	Low	Low	Low	Low

 

Surface Morphology:

The SEM image of upper surface of FLVOP is shown in Figure 6. Figure 6 (A) shows intact structure of film which is before dissolution and Figure 6 (B) represents spongy structure after dissolution study. Significant numbers of pores are appeared on film which would facilitate drug release.

 

Figure 6.  SEM image of film after (A) and before (B) dissolution study

 

Drug release kinetics:

Drug release kinetic model fitting parameters (R², SSR and F-value) for FLVOP are enlisted

Table 9. In vitro drug release of FLVOP was best explicated by Zero order model release kinetics. This confirms the constant release from FLVOP with uniform release rate.

 

Table 9. In vitro release kinetic model fitting parameters:

Model	FLVOP (OB)
	R2	SSR	F value
Zero Order	0.999	17.49	1.59
First Order	0.931	791.37	71.94
Higuchi	0.839	1831.87	166.53
Hixson-Crowell	0.960	455.875	41.44
Weibull	0.990	89.46	9.94

 

Stability study

The results of short term stability study of FLVOP are depicted in Table 10. The data indicates that there is no any sign of instability after stipulated time of stability study. The values of all five CQAs were remained unaltered which confirms consistence performance of developed FLVOP.

 

Table 10. Result of stability study of FLVOP (OB)

Parameters	OB
	Initial	1 month	2 months	3 months
Assay (%)	99.24±0.064	99.22±0.032	100.47±0.037	99.57±0.047
Physical degradation	No	No	No	No
%Q1	4.1	3.9±0.34	3.8±0.22	4.0±0.25
T25	6.2	6.1±0.1	6.2±0.2	6.2±0.2
T50	12.3	12.1±0.3	12.4±0.3	11.9±0.2
T75	17.6	17.3±0.1	17.8±0.6	17.4±0.2
T100	24.1	23.8±0.2	24.3±0.1	24.2±0.2

 

CONCLUSION:

From the study it can be concluded that, SCOP can be a promising approach for delivering API in a controlled manner without notable fluctuation. Solubility modulation is mandatory for poorly water soluble drugs, when it is mean to develop into osmotic pump. To achieving zero order release profile, role of leachable component in coating (orifice density) and presence of osmogen in core tablet are key factors. Different principles of QbD and CCD assisted for robust development of FLVOP.

 

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Received on 19.12.2019           Modified on 17.02.2020

Accepted on 13.04.2020         © RJPT All right reserved