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Understanding the Effects of Associated Factors in the Development of Microsponge-Based Drug Delivery: a Statistical Quality by Design (QbD) Approach Towards Optimization

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Abstract

The investigation aims to prepare, identify, analyse, and understand the effects of different variables and constant factors associated with developing drug-loaded microsponge formulation by altering variables using the experiment’s design. A series of drug formulations were prepared by alteration of variables using the design of experiment (DoE). Shape factors were kept constant. Response surface methodology (RSM) was utilized to optimize the preparation and analyse factors and variables. The RSM and QbD make the process easy to scale up and reproducible to minimize batch-to-batch variation. Critical process attributes (CPAs), such as particle size, yield, and drug entrapment, were analysed and comprehended in the development process to estimate the risk of microsponge-based formulation and method stability. Critical process parameters (CPPs) were identified by trial and error. QbD-driven quasi-emulsion solvent evaporation method was adopted to emulsify the dispersed phase within a continuous aqueous phase to develop the microsponges. The investigation confirmed that the effects of changes in controlling factors were most prominent on response variables. Each response was found in a broad range in terms of average particle diameter (337–461 µm), entrapment efficiency (77.69–94.38%) of the drug, and product yield (76.91–96.38%). The optimum results are a yield of ~ 96%, an average particle size of 347 µm, and entrapment efficiency of ~ 93.55%. An analysis of ANOVA (P value < 0.05) and models were validated. A constant rate of drug release from the optimized product was observed for a period (8 h) with a drug release of 75%. The developed method is reproducible, stable, and reliable.

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Data Availability

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Abbreviations

QbD:

Quality by design

CPPs:

Critical process parameters

CPAs:

Critical process attributes

RSM:

Response surface methodology

NDDS:

Novel drug delivery systems

EC-46:

Ethyl cellulose 46cp

ERS-100:

Eudragit RS 100

DCM:

Dichloromethane

EA:

Ethyl alcohol

RPM:

Rotation per minute

API:

Active pharmaceutical ingredient

Np:

Power number

PB:

Phosphate buffer

UV:

Ultraviolet

DSC:

Differential scanning calorimetry

FTIR:

Fourier transformed infrared spectroscopy

Da:

Diameter of impeller

Dt:

Diameter of the tank

E:

Clearance of tank

H:

Height of the liquid

L:

Length of impeller blade

W:

Width of impeller blade

w/v:

Weight per volume

cP:

Centipoises

EE:

Entrapment efficiency

PSD:

Particle size distribution

CCD:

Central composite design

ANOVA:

Analysis of variance

CPF:

Checkpoint formulation

CPR:

Cumulative percent release

FESEM:

Field emission scanning electron microscope

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Acknowledgements

We want to give our heartiest thanks and gratitude to the Department of Pharmaceutical Technology, Jadavpur University and the Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu. We would also like to thank Mr. Debaldeb Dutta, Mr. Sahajaman Haldar, and Dr. Ankit Jain for assisting during the experimental procedure and manuscript preparation. We would also like to acknowledge the Vice-Chancellor Prof. Dr. S. Das of Jadavpur University and Director Prof. Dr. G. Aghila, and the administration of the National Institute of Technology, Tiruchirappalli, Tamil Nadu, for helping us with immense support.

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Authors and Affiliations

  1. Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

    Shibam Karmakar & Jasmina Khanam

  2. Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, India

    Sourav Poddar

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Contributions

Shibam Karmakar: conception, outcome curation, proper investigation, software utilization analysis, initiation and completion of the draft, and final manuscript. Sourav Poddar: conceptualization, data curation, formal analysis, investigation, software utilization, validation, visualization, and writing, review, and editing — original and final manuscript. Jasmina Khanam: conceptualization, data curation, formal analysis, investigation, software utilization, validation, visualization, and writing, review, and editing — original and final manuscript.

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Correspondence to Sourav Poddar or Jasmina Khanam.

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This article does not involve human participants, so it is not applicable. All the experimental methods were carried out according to the guidelines of the Jadavpur University, West Bengal, India. The article also follows the National Institute of Technology guidelines, Tiruchirappalli, Tamil Nadu, India.

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Highlights

1. Statistically integrated development process with the help of design of experiment (DoE). Adoption of optimization leads to ease of scale-up and industrialization.

2. Impact assessment of the dependent and independent variables, multiple factors (shape, physical, and chemical) aggregated with the development of microsponge formulation.

3. A QbD-driven development approach for microsponge formulation associated with critical process parameters (CPPs) and critical process attributes (CPAs).

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Karmakar, S., Poddar, S. & Khanam, J. Understanding the Effects of Associated Factors in the Development of Microsponge-Based Drug Delivery: a Statistical Quality by Design (QbD) Approach Towards Optimization. AAPS PharmSciTech 23, 256 (2022). https://doi.org/10.1208/s12249-022-02409-3

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