Helicobacter pylori (H. pylori) is a Gram-negative, spiral-shaped, microaerophilic bacterium infecting the gastric mucosa and implicated in chronic gastritis, peptic ulcer disease, mucosa-associated lymphoid tissue (MALT) lymphoma, and gastric carcinoma.

Systematic reviews show its global adult prevalence declined from approximately 52.6% before 1990 to 43.9% during 2015–2022, though rates remain elevated among adolescents (around 35.1%)¹. Current eradication therapies rely on proton pump inhibitors (PPIs) combined with antibiotics; however, increasing antimicrobial resistance, treatment side effects, and frequent relapse reduce long-term success rates^1,2.

Probiotic supplementation has emerged as a promising adjunct therapy. An umbrella meta-analysis of 534 randomized trials reported that probiotics improved eradication rates (RR ≈ 1.10) and halved the risk of side effects (RR ≈ 0.54). Furthermore, meta-analyses incorporating Limosilactobacillus reuteri or Saccharomyces boulardii demonstrated significant improvements in eradication efficacy and notable reductions in adverse events^3,4.

Multiparticulate mucoadhesive microspheres offer targeted gastric delivery, prolong residence time, improve release kinetics, and protect encapsulated agents. Sodium alginate–based systems, often augmented with Carbopol 934, are widely used for their biocompatibility, mucoadhesive properties, and ability to shield acid-labile components such as PPIs and probiotics⁵.

Optimization of such formulations through Quality by Design (QbD), particularly using Box–Behnken response surface methodology, is well supported in pharmaceutical research. This approach enables systematic fine-tuning of variables such as polymer concentration, stirring speed, and crosslinker ratios to maximize entrapment efficiency, particle size control, and manufacturability⁶.

Despite these advances, few studies have co-encapsulated a PPI (e.g., esomeprazole) together with live probiotics in a mucoadhesive microsphere while also applying systematic optimization and evaluating probiotic survival, mucoadhesion, and release performance. This study addresses that gap by developing and optimizing such a formulation to enhance H. pylori treatment outcomes⁷.

2. MATERIALS AND METHODS:

2.1 Chemicals and reagents:

Esomeprazole was kindly provided by Torrent Pharmaceuticals (Baddi, Himachal Pradesh, India). Lactobacillus acidophilus culture was obtained from the Department of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra. Carbopol 934P was purchased from Loba Chemie Pvt. Ltd. (Mumbai, India), and sodium alginate was obtained from Kurukshetra University. Calcium chloride and other analytical-grade reagents were procured from HiMedia Laboratories (Mumbai, India). All chemicals and reagents used were of analytical grade and were utilized without further purification.

2.2 Preparation of Microspheres:

Mucoadhesive microspheres containing esomeprazole and Lactobacillus acidophilus were prepared using the ionic gelation technique. Sodium alginate and Carbopol 934 were dissolved in distilled water under constant stirring to obtain a homogeneous polymeric solution. Esomeprazole and probiotic cultures were dispersed into the polymeric solution under gentle stirring to ensure uniform distribution⁸.

The resulting dispersion was extruded dropwise through a 26 G syringe, from a distance of approximately 3 cm, into a gently stirred calcium chloride solution (cross-linking agent). Microspheres were allowed to cure in the solution for 30 min to ensure complete crosslinking. The formed microspheres were collected by filtration, washed thoroughly with sodium chloride solution to remove unbound drug and probiotics, and finally dried at room temperature.

2.3 Experimental Design for Optimization (Box–Behnken):

A Box–Behnken design (BBD), a three-factor, three-level statistical design, was employed to optimize the formulation variables. The independent variables selected were:

A: Concentration of sodium alginate (% w/v)

B: Concentration of Carbopol 934 (% w/v)

C: Stirring speed (rpm)

The dependent variables (responses) were:

Y1: Entrapment efficiency (%EE)

Y2: Particle size (µm)

Y3: Practical yield (%)

Each factor was studied at three levels (low −1, medium 0, high +1). Experimental design and statistical analysis were performed using Design-Expert® software (Version 11, Stat-Ease Inc., USA). Response surface plots and contour plots were generated to visualize the influence of independent variables, while numerical optimization was applied to identify the most desirable formulation.

2.4 Calibration Curve Preparation (UV–Vis):

Stock 1 (1000µg/mL): Dissolve accurately 5mg esomeprazole in 5mL of 0.1 N HCl in a volumetric flask.

Stock 2 (100µg/mL): Dilute 1mL of Stock 1 to 10mL with 0.1 N HCl.

· Working standards: Prepare 5, 10, 15, 20, and 25 µg/mL by appropriate dilution of Stock 2 with 0.1 N HCl.

· Measurement: Record absorbance at λ_max = 282 nm using a UV–Vis spectrophotometer (200–400 nm range; 10 mm quartz cuvette) against reagent blank.

· Linearity: Plot absorbance vs concentration and obtain the regression equation for subsequent quantification.

2.5 Solubility Studies (Esomeprazole):

Evaluate qualitative solubility/dispersion of esomeprazole in water, methanol, simulated gastric fluid (SGF, pH 1.2), and phosphate buffer (pH 6.8). For each medium, add excess drug, shake at ambient temperature, allow to equilibrate, and assess clarity/dispersion.

2.6 Melting Point Determination:

Determine the melting point of esomeprazole magnesium by capillary method using a calibrated melting point apparatus. Report onset and completion temperatures⁹.

2.7 Drug–Excipient Compatibility (FTIR):

Record FTIR spectra of esomeprazole, L. acidophilus (lyophilized), sodium alginate, Carbopol 934P, and physical mixtures (drug+excipients) using KBr pellet method (Bruker Alpha; 4000–400 cm⁻¹; 4 cm⁻¹ resolution; standard scan speed). Examine spectra for characteristic peaks and potential shifts/vanishing bands suggesting interactions.

2.8 Morphological Characterization (SEM):

Mount dried microspheres on aluminum stubs with double-sided tape, sputter-coat with gold under vacuum, and image by scanning electron microscopy at suitable magnifications. Record surface features (shape, porosity) for representative batches.

2.9 Flow Properties of Microspheres:

Evaluate bulk density (BD) and tapped density (TD) using standard funnels and tap-testers. Compute:

· Carr’s index, CI (%) = [(TD − BD)/TD] × 100

· Hausner ratio, HR = TD/BD

· Angle of repose (fixed-funnel method): θ = arctan (h/r), where h = heap height, r = radius. Perform each measurement in triplicate.

2.10 Probiotic Encapsulation Efficiency (%EE, cells):

1. Accurately weigh an aliquot of microspheres and lyse in phosphate buffer (pH 7.4) with gentle agitation to release entrapped cells.

2. Perform serial dilutions and plate on MRS agar.

3. Incubate plates at 37±0.5°C for 48 h; count CFU.

4. Calculate: %EE (cells) = (N_e/N_t) × 100, where N_t is the initial viable count added and N_e is viable cells recovered post-encapsulation. Conduct in triplicate.

2.11 Stability of Encapsulated Probiotics in SGF (Acid Tolerance):

Incubate microspheres in SGF (pH 2.0) containing pepsin (3.0g/L) at 37±0.5°C. At predetermined time points, retrieve samples, neutralize, lyse, plate on MRS agar, and enumerate CFU after incubation (37°C, 48h). Express survival relative to initial count. Include free-cell controls where applicable.

2.12 Swelling Index (pH 1.2):

Immerse pre-weighed dried microspheres (W₀) in 0.1 N HCl (pH 1.2) at 37±0.5°C. At set intervals, remove, gently blot surface, and weigh (W_t). Compute: Swelling Index (%) = [(W_t − W₀) / W₀] × 100. Report the mean of triplicates.

2.13 In Vitro Mucoadhesion Test:

Use freshly excised rat gastric mucosa (ethical approval/biowaste compliance as applicable). Mount mucosa on the basket of a USP disintegration apparatus. Place a known quantity of microspheres on the mucosal surface, then subject to sequential dipping in SGF (37 °C) for a defined period/number of dips. Quantify adhered vs detached microspheres by recovery/weighing or counting. % Mucoadhesion = (Adhered/Initial) × 100.

2.14 In Vitro Drug Release (Dissolution):

Conduct dissolution using USP Apparatus II (paddle) with 900mL 0.1 N HCl (pH 1.2) at 37±0.5°C, 50rpm. Withdraw 5mL aliquots at predetermined intervals up to 12h, immediately filter, and analyze at 282nm using the calibration curve. Replace withdrawn volume with fresh medium maintained at 37°C to preserve sink conditions. Perform in triplicate.

2.15 Drug Release Kinetics (Modeling):

Fit release data to:

· Zero-order: Qt=k0tQ_t = k_0 tQt=k0t

· Higuchi: Qt=kHtQ_t = k_H \sqrt{t}Qt=kHt

· Korsmeyer–Peppas: Mt/M∞=ktnM_t/M_\infty = k t^nMt/M∞=ktn (fit first ~60% release; log–log transform to obtain n). Compute correlation coefficients (R²) and compare goodness-of-fit. Interpret n (sphere geometry): ~0.43 (Fickian), 0.43–0.85 (anomalous), ~0.85 (case-II).

2.16 Short-Term Stability of Microspheres:

Store representative batches at ambient laboratory conditions (24–28°C) for 30 days in closed containers protected from light. Evaluate physical appearance, particle size distribution, mucoadhesion, drug content, probiotic viability, and FTIR profile at baseline and end-study, following the same methods as above.

2.17 ANOVA and Model Adequacy (Design-Expert):

Analyze BBD datasets by ANOVA (α = 0.05) to assess model significance and factor effects, including linear, interaction, and quadratic terms. Evaluate lack-of-fit, residual diagnostics (normal probability plots, studentized residuals), and model adequacy metrics (R², adjusted R², predicted R², Adequate Precision). Apply Box-Cox transformation if required to stabilize variance and improve normality.

2.18 Response Surface Mapping and Overlay Plot:

Generate 3D response surface and 2D contour plots to visualize factor interactions on Y1–Y3 while holding one factor constant. Conduct numerical and graphical optimization; produce an overlay plot with constraints to identify the design space and select optimal formulations for confirmatory runs.

3. RESULTS AND DISCUSSION:

3.1 Optimization Results of Microspheres (OM1 and OM2):

The Box–Behnken design generated 17 experimental runs with varied concentrations of sodium alginate, Carbopol 934P, and stirring speed. The observed responses included entrapment efficiency, particle size, and practical yield. Statistical analysis revealed that polymer concentration and stirring speed significantly influenced microsphere characteristics.

Formulations R3 and R9 exhibited superior performance with high entrapment efficiency, favorable particle size, and acceptable yield.

Figure 6. SEM results shows (a) perforated microsphere with surface morphology (b) Surface of Microspheres varying in size, (c) Pores in microspheres.

3.6 Scanning Electron Microscopy (SEM) Analysis:

SEM micrographs of the optimized microspheres revealed well-formed, spherical particles with a relatively smooth external surface. At higher magnifications, pores were observed on the surface, which may facilitate controlled drug release by enabling diffusion pathways. The uniform spherical shape indicated efficient ionic gelation, while the porous morphology was attributed to the polymer blend of sodium alginate and Carbopol 934P. These morphological features are desirable for gastro-retentive systems, as they enhance both mucoadhesion and sustained release behavior.

3.7 Flow Properties of Microspheres:

The flowability of microspheres was evaluated using standard pharmacopeial parameters. Both OM1 and OM2 exhibited good flow, with bulk density and tapped density values leading to low Carr’s indices (3–4%) and Hausner’s ratios close to 1.1. The angle of repose values (22–26°) fell within the range of excellent flowability. These findings suggest that the microspheres can be handled and processed easily during large-scale manufacturing without risk of aggregation or poor flow.

Table 4. Flow properties of microspheres

Formulation code

Bulk density

(g/cm³)

Tapped density

(g/cm³)

Carr’s index (%)

Hausner’s ratio

Angle of repose

OM1

0.89

0.98

4.0

1.19

26.57

OM2

0.82

0.92

3.1

1.14

22.17

3.8 Probiotic Encapsulation Efficiency:

Encapsulation efficiency for L. acidophilus was found to be high, with OM1 achieving 95.56% and OM2 achieving 94.6%. Such high values confirm the effectiveness of the alginate–Carbopol matrix in entrapping viable probiotic cells. Efficient encapsulation is critical for ensuring that probiotics survive the harsh gastric environment and are delivered intact to the site of action.

Table 5. Probiotics encapsulation efficiency of OM1 and OM2.

Formulation Code	Probiotic Encapsulation efficiency
OM1	95.56%
OM2	94.6%

3.9 Stability of Encapsulated Probiotics in Simulated Gastric Fluid (SGF):

When exposed to SGF (pH 2.0 with pepsin), free probiotics showed rapid loss of viability, whereas encapsulated cells retained significant stability. After incubation, OM1 demonstrated a survival rate of 73.9%, while OM2 retained 79% of viable cells. This confirms that the mucoadhesive microspheres provided effective protection against acidic degradation, thus ensuring probiotic delivery to the gastric mucosa where H. pylori resides.

3.10 Swelling Index Studies:

Swelling behavior of microspheres in acidic medium (pH 1.2) was time-dependent, with OM1 exhibiting higher swelling compared to OM2. After 5 hours, OM1 showed a swelling index of approximately 40%, while OM2 reached 34%. The greater swelling observed in OM1 is likely due to the higher proportion of Carbopol 934P, which absorbs water and undergoes matrix expansion. This enhanced swelling contributes to prolonged gastric residence time and stronger mucoadhesion, ultimately improving localized drug delivery.

Table 6. Swelling index of selected Optimized formulations

Time (hours)	OM1	OM2
0.5	2	1.9
1	4.8	3.5
2	11	6.3
3	14.5	12.5
4	31.58	19
5	40	34.28

3.11 In Vitro Mucoadhesion Test:

The mucoadhesion study using excised rat gastric mucosa demonstrated that both optimized microsphere formulations adhered strongly to the gastric lining. OM1 showed superior mucoadhesion (76.36%) compared to OM2 (67.27%). The higher mucoadhesive strength of OM1 can be attributed to the greater hydrogen-bonding potential of Carbopol 934P, which forms strong interactions with mucin glycoproteins. Effective mucoadhesion is a desirable property, as it ensures prolonged gastric retention, localized action, and enhanced therapeutic efficiency against H. pylori infection.

Figure 7. USP Disintegration apparatus for invitro muco-adhesion test using rat mucosa

Table 7. Percent Muco-adhesion of OM1 and OM2

Formulation Code	Percent Muco-adhesion
OM1	76.36
OM2	67.27

Figure 8. Graph representing Percent muco-adhesion of OM1 and OM2

3.12 In Vitro Drug Release:

Dissolution studies in 0.1 N HCl (pH 1.2) revealed sustained drug release from both formulations for up to 12hours. OM1 exhibited a gradual release pattern, reaching 93.3% cumulative release at 12h, while OM2 released 87.6% over the same period. The controlled release behavior was attributed to the polymer matrix, which regulated diffusion of esomeprazole through the swollen microsphere structure. These results indicate that the microspheres are capable of maintaining prolonged therapeutic drug concentrations in the gastric environment, which is essential for effective H. pylori eradication.

Table 8. Percentage Drug release of OM1 and OM2

S. No	Time	Percentage Drug release of OM1	Percentage Drug release of OM2
1	0	0	0
2	0.5	4.839344	7.726232
3	1	14.58934	12.62916
4	2	22.18984	19.46016
5	3	34.51684	28.82916
6	4	38.50009	33.4386
7	5	41.22184	44.41512
8	6	50.01184	45.98796
9	7	57.75559	56.04036
10	8	63.33334	66.24816
11	9	68.49409	68.14056
12	10	73.65259	73.11876
13	11	83.40109	84.91836
14	12	93.31009	87.68376

3.13 Drug Release Kinetics:

Release data were fitted to different mathematical models to determine the mechanism of drug release. OM1 and OM2 both followed zero-order kinetics (R² > 0.99), suggesting a constant release rate independent of drug concentration. Additionally, good correlation was observed with the Korsmeyer–Peppas model (n ≈ 0.82), indicating a non-Fickian, anomalous diffusion mechanism involving both drug diffusion and polymer relaxation. The Higuchi model also showed acceptable fit, supporting the role of diffusion through the hydrated polymer matrix. Collectively, these results confirm that the formulations achieved sustained and controlled release, a crucial attribute for gastric-targeted delivery systems.

Table 9. Release kinetics

Formulation	Zero Order		Higuchi Equation		Peppa’s Equation
Formulation	_r2	K₀	_r2	K_H	_r2	n
OM1	0.9936	7.883	0.9852	29.85	0.9952	0.824
OM2	0.9958	7.730	0.995	22.51	0.9976	0.820

3.14 Stability Studies:

Stability testing over one month at ambient laboratory conditions (24–28°C) showed no significant changes in the physical appearance, particle size, mucoadhesive properties, or drug content of the microspheres. FTIR spectra remained unchanged, indicating the absence of chemical degradation or polymer–drug interaction. Furthermore, probiotic viability remained stable within acceptable limits, confirming that the microsphere matrix provided adequate protection during storage. These results suggest that the optimized formulations possess good short-term stability and are suitable for further preclinical evaluation.

3.15 ANOVA Results:

Statistical analysis of the Box–Behnken design confirmed the significance of the selected models for all three responses (entrapment efficiency, particle size, and practical yield). For entrapment efficiency (Y1), the model F-value indicated strong influence of polymer interactions. Particle size (Y2) was significantly affected by both sodium alginate concentration and stirring speed, whereas practical yield (Y3) was largely governed by combined effects of polymer concentrations and stirring conditions. In all cases, the lack-of-fit was non-significant, validating the adequacy of the models. These results confirm the reliability of the experimental design for formulation optimization.

Table 10. ANOVA results for the response variable Y1 (entrapment efficiency).

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	731.88	9	81.32	10.10	0.0030
A-Polymer Alginate	2.00	1	2.00	0.2483	0.6335
B-Polymer Carbopol934	17.40	1	17.40	2.16	0.1850
C-Stirring Speed	0.4050	1	0.4050	0.0503	0.8290
AB	90.25	1	90.25	11.21	0.0123
AC	90.25	1	90.25	11.21	0.0123
BC	0.3600	1	0.3600	0.0447	0.8386
A²	46.55	1	46.55	5.78	0.0472
B²	484.32	1	484.32	60.13	0.0001
C²	21.79	1	21.79	2.71	0.1440
Residual	56.38	7	8.05
Lack of Fit	10.51	3	3.50	0.3055	0.8213
Pure Error	45.87	4	11.47
Cor Total	788.26	16

3.16 Response Surface Mapping and Overlay Plot:

Three-dimensional response surface plots and two-dimensional contour plots illustrated the interactive effects of sodium alginate, Carbopol 934P, and stirring speed on formulation responses. Entrapment efficiency increased with higher polymer concentrations, while particle size was positively correlated with sodium alginate levels and stirring speed. Practical yield also improved with balanced polymer ratios.

The overlay plot highlighted a well-defined design space, with the yellow-shaded region representing optimal conditions. OM1 and OM2 formulations fell within this space, confirming their desirability. This optimization approach provided clear guidance on the critical process parameters necessary to achieve robust, reproducible, and clinically relevant formulations.

Table 11. ANOVA results for the response variable Y2 (Particle size)

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	3.04	9	0.3375	74.23	< 0.0001	significant
A-Polymer Alginate	0.8070	1	0.8070	177.50	< 0.0001
B-Polymer Carbopol 934	0.1141	1	0.1141	25.08	0.0016
C-Stirring Speed	0.1992	1	0.1992	43.81	0.0003
AB	0.0349	1	0.0349	7.67	0.0277
AC	0.8310	1	0.8310	182.77	< 0.0001
BC	0.0403	1	0.0403	8.85	0.0206
A²	0.9642	1	0.9642	212.06	< 0.0001
B²	0.0264	1	0.0264	5.82	0.0466
C²	0.0086	1	0.0086	1.89	0.2116
Residual	0.0318	7	0.0045
Lack of Fit	0.0229	3	0.0076	3.41	0.1337	not significant
Pure Error	0.0090	4	0.0022
Cor Total	3.07	16

Table 12. ANOVA results for the response variable Y3 (Practical Yield)

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	600.01	9	66.67	313.49	< 0.0001	significant
A-Polymer Alginate	22.88	1	22.88	107.60	< 0.0001
B-Polymer Carbopol 934	39.60	1	39.60	186.23	< 0.0001
C-Stirring Speed	130.98	1	130.98	615.89	< 0.0001
AB	92.16	1	92.16	433.36	< 0.0001
AC	3.01	1	3.01	14.15	0.0071
BC	56.25	1	56.25	264.50	< 0.0001
A²	96.44	1	96.44	453.46	< 0.0001
B²	130.71	1	130.71	614.65	< 0.0001
C²	40.09	1	40.09	188.52	< 0.0001
Residual	1.49	7	0.2127
Lack of Fit	0.0227	3	0.0076	0.0207	0.9953	not significant
Pure Error	1.47	4	0.3665
Cor Total	601.50	16

Figure 9. 2D and 3D response surface plot showing the relationship between various levels of Sodium alginate Concentration and Carbopol 934 Concentration on entrapment efficiency

Figure 10. 2D and 3D response surface plot showing the relationship between various levels of Sodium alginate Concentration and Carbopol 934 Concentration on particle size

Figure 11. 2D and 3D response surface plot showing the relationship between various levels of Sodium alginate Concentration and Carbopol 934 Concentration on Practical Yield

4.16.1 Overlay Plot of the selected model:

The desirable region was also selected using overlay plotting, wherein the constraints for choosing an optimum formulation were further narrowed down, as indicated in Fig.12

Figure 12. Overview plot design space for the optimized formulations in two-dimensional regions

The optimized formulations were identified through graphical optimization. In the overlay plot (Fig. 12), the yellow-shaded region represents the design space, indicating the combination of factor levels that satisfy the desired criteria. The grey area corresponds to non-optimal experimental regions. The contour lines illustrate the boundary limits for each response variable. Within the design space, the selected polymer concentrations yielded microspheres with reduced particle size, high entrapment efficiency, and satisfactory practical yield, confirming the robustness of the optimization approach.

5. CONCLUSION:

The present study successfully developed and optimized mucoadhesive microspheres co-encapsulating esomeprazole and Lactobacillus acidophilus using a sodium alginate–Carbopol 934P matrix. Application of a Box–Behnken design enabled systematic optimization of formulation variables, leading to two robust formulations, OM1 and OM2, with high entrapment efficiency (>94%), excellent flow properties, and reproducible yields.

The microspheres demonstrated sustained drug release for up to 12 hours, following zero-order and non-Fickian diffusion kinetics, while maintaining strong mucoadhesion and significant probiotic protection in simulated gastric fluid. SEM confirmed a spherical porous morphology, and FTIR studies indicated compatibility among drug, probiotic, and excipients. Short-term stability evaluation confirmed that the formulations remained physically and chemically stable during storage.

Overall, the findings highlight the potential of probiotic-loaded mucoadhesive microspheres as a promising alternative strategy for the management of Helicobacter pylori–associated gastric disorders. By combining a proton pump inhibitor with probiotics in a controlled-release gastroretentive system, this approach addresses the limitations of conventional therapy, including poor stability of probiotics and frequent relapse due to incomplete eradication.

Future work should include in vivo studies to evaluate pharmacokinetics, colonization efficiency, and therapeutic efficacy, followed by clinical validation to establish translational potential.

Abbreviations

H. pylori Helicobacter pylori

SGF Simulated Gastric Fluid

FTIR Fourier Transform Infrared
Spectroscopy

SEM Scanning Electron Microscopy

UV Ultraviolet

ANOVA Analysis of Variance

rpm Revolutions Per Minute

µg/ml Micrograms per Milliliter

μm Micrometer

%EE Percent Entrapment Efficiency

sIgA Secretory Immunoglobulin A

IgG Immunoglobulin G

6. ACKNOWLEDGEMENTS:

Authors are thankful to the Department of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra for the support provided.

7. AUTHORS INFORMATION:

Authors and Affiliations”

Department of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra-136119, Haryana, India

Shubham Gautam, Rimpy Dahiya, Jaishree Sharma , Deepak Ranga & Surender Verma

8. CONTRIBUTIONS:

SB, RD, JS, DR and SV have equally contributed to this work. The authors read and approved the final manuscript.

9.COMPETING INTERESTS:

The authors declare that they have no competing interests.

10. REFERENCES:

1. Shirani M, Pakzad R, Haddadi MH, Akrami S, Asadi A, Kazemian H, et al. The global prevalence of gastric cancer in Helicobacter pylori-infected individuals: a systematic review and meta-analysis. BMC Infect Dis 2023; 23:543. https://doi.org/10.1186/s12879-023-08504-5.

2. Thulluru A, Basha SS, Rao CB, Kumar ChSP, Mahammed N, Kumar KS. Optimization of HPMC K100M and Sodium Alginate Ratio in Metronidazole Floating Tablets for the Effective Eradication of Helicobacter pylori. Asian Journal of Pharmacy and Technology 2019; 9:195. https://doi.org/10.5958/2231-5713.2019.00033.3.

3. Yang Z, Zhou Y, Han Z, He K, Zhang Y, Wu D, et al. The effects of probiotics supplementation on Helicobacter pylori standard treatment: an umbrella review of systematic reviews with meta-analyses. Sci Rep 2024; 14:10069. https://doi.org/10.1038/s41598-024-59399-4.

4. Lokhande S, More S, Raje V. A Systematic Study of Probiotics-An Update Review. Asian Journal of Pharmacy and Technology 2018; 8:149. https://doi.org/10.5958/2231-5713.2018.00024.7.

5. Ali M, Pandit V, Jain M, Dhar K. Mucoadhesive microparticulate drug delivery system of curcumin against Helicobacter pylori infection: Design, development and optimization. J Adv Pharm Technol Res 2014; 5:48. https://doi.org/10.4103/2231-4040.126996.

6. Neelam S, Meenakshi B. Formulation And Evaluation Of Polymeric Microspheres Using Box–Behnken Design. Asian Journal of Pharmaceutical and Clinical Research 2022:47–55. https://doi.org/10.22159/ajpcr.2022.v15i10.45250.

7. Mohanty D, Zafar A, Jafar M, Upadhyay AK, Haque MA, Gupta JK, et al. Development, In-Vitro Characterization and Preclinical Evaluation of Esomeprazole-Encapsulated Proniosomal Formulation for the Enhancement of Anti-Ulcer Activity. Molecules 2022; 27:2748. https://doi.org/10.3390/molecules27092748.

8. Verma S, Kumar Singh P, Panwar J, Kumar Shukla V, Easwari TS. Design and Characterisation of Gentamicin Floating Microspheres as Potential Drug Carrier for the treatment of Intra-Abdominal Infection. Asian Journal of Pharmaceutical Research 2024:133–40. https://doi.org/10.52711/2231-5691.2024.00023.

9. Mahurkar N, Sayeed Ul Hasan SM. Synergistic Antiulcer Effect of Melatonin and Esomeprazole Combination in Pylorus Ligation, Ethanol, Aspirin induced Peptic Ulcers. Asian Journal of Pharmaceutical Research 2015; 5:10. https://doi.org/10.5958/2231-5691.2015.00002.7.

Received on 12.07.2025 Revised on 16.08.2025

Accepted on 17.09.2025 Published on 20.01.2026

Available online from January 27, 2026

Asian J. Pharm. Tech. 2026; 16(1):81-90.

DOI: 10.52711/2231-5713.2026.00012

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

S. No	Conc. (µg/ml)	Absorbance
1	0	0
2	5	0.146
3	10	0.304
4	15	0.462
5	20	0.617
6	25	0.753

Sr. No.	Solvents	Lactobacillus acidophilus
1.	Water	++
2.	Methanol	+++
3.	pH 1.2	+++
4.	pH 6.8	+++

Std	Run	Factor 1	Factor 2	Factor 3	Response 1 (Y1)	Response 2 (Y2)	Response 3 (Y3)
Std	Run	A: Polymer Sodium Alginate	B: Polymer Carbopol934	C: Stirring Speed	Entrapment efficiency	Particle size	Practical Yield
		%	%	RPM	%	(µm)	%
9	1	2	1	1000	85	0.9435	85
15	2	2	1.5	1250	75	0.844	79
10	3	2	2	1000	90	0.578	87
5	4	1	1.5	1000	69	1.22	70
14	5	2	1.5	1250	87	0.855	87
13	6	2	1.5	1250	76	0.92	82
4	7	3	2	1250	78	1.4705	71
12	8	2	2	1500	88	1.017	75
11	9	2	1	1500	85	0.9812	87
6	10	3	1.5	1000	71	0.9456	75
7	11	1	1.5	1500	77	0.7012	61
1	12	1	1	1250	80	1.15	73
2	13	3	1	1250	79	1.97	89
16	14	2	1.5	1250	71	0.81	77
3	15	1	2	1250	83	1.024	82
17	16	2	1.5	1250	78	0.8002	87
8	17	3	1.5	1500	61	2.25	73