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TarakaRamarao Challa, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIAFollow
Krishnaveni Akula, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Kiranmai Arasavilli, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Manisha Baratam, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Jayasri Guntamukkala, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Narendra Malluri, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Manikantha Patnana, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Tulasi Chintala, UG Research Scholar, Department of Pharmaceutical Technology, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh- 532410, INDIA.Follow
Raghunadha Gupta C, Senior Manager-FRD, Pellets Pharma Limited, Hyderabad, Telangana-INDIA.Follow

Abstract

Background: Mirtazapine (MTZ) is delivered via a self-emulsifying system (SEDDS) to treat depression by acting as an antagonist at multiple serotonin and adrenergic receptors. Aim: The goal of SEDDS formulation preparation is a 2-level factorial design using a selected combination of three components such as X1- surfactant and co-solvent (Smix) (Tween80&PEG400) at upper level 1:5 and lower level 1:1 ratio, X2- stirrer speed (rpm), X3- stirring time (min), and to evaluate the produced SEDDS. Materials and methods: The two-level factorial design with a Design Expert used in formulation assessed physicochemical features such as pseudo-ternary phase design, emulsification, phase separation, pH, percent transmittance, permeability studies, ex vivo drug release, liquid (LSDDS) to solid SEDDS conversion, flow properties, entrapment efficiency, cloud point, drug excipient compatibility studies, stability studies, and optimization. Results: The Neural Network Start (NNS) was used in the optimization, feed-forward back propagation Levenberg-Marqardt Algorithm, and performance was measured using the mean square error (MSE). NNS with ten units of layer size provided a better fit for all responses (R2 = 0.99996, 0.999, and 0.98 for T100, T50, and PD 20) than multiple linear regression (MLR) (0.9517, 0.9998, and 0.7942 for T100 (time required for 100% drug release), T50 (time required for 50% drug release), and PD 20 (percentage drug release 20 minutes), respectively). Conclusion: The dissolution of drug release in LSEDDS and SSEDDD is substantially better than in pure MTZ. LSEEDS and SSEDDS formulations demonstrated appropriate stability for 90 days according to ICH stability quality requirements, including emulsification time, phase separation, angle of repose, and drug content. The SEDDS were successfully designed to increase the oral bioavailability of MTZ, allowing for larger therapeutic applications.

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