The goal of nanotechnology is to develop new nanoscale components by designing, fabricating, and using materials that are atomically, molecularly, and macromolecular organized. For several decades, there has been an abundance of scientific curiosity in the administration of medicines using particle delivery systems as carriers for small and big molecules. Particulate systems, such as nanoparticles, have been utilized as a physical method to modify and improve the pharmacokinetic and pharmacodynamics aspects of numerous pharmaceutical molecules. A typical nanoparticle is between 1 and 100 nm in size and has one or more dimensions. Nanoparticles are usually categorized as inorganic, organic, or carbon-based particles according to their superior characteristics in comparison to larger sizes of the corresponding materials. They have been utilized in vivo to protect the drug entity in the systemic circulation, limiting drug distribution to the targeted areas, and to transport the drug at a controlled and sustained rate to its site of action. The most innovative and promising medication delivery technique at the moment is nanoparticle technology. This methodical research examines the categorization, characteristics, techniques, characterizations, and applications of nanoparticles in the delivery of drug molecules.

Background: Conventional approach of formulating a new dosage form is a comprehensive task and uses various sources like man, money, time and experimental efforts. The use of AI can help to obtain optimized pharmaceutical formulation with desired (best) attributes. AI minimizes the use of resources and increases the understanding of impact, of independent variable over desired dependent responses/variables. Objective: Thus, the aim of present work is to explore the use of Artificial intelligence in designing pharmaceutical products as well as the manufacturing process to get the pharmaceutical product of desired attributes with ease. The review is presenting various aspects of Artificial intelligence like Quality by Design (QbD) & Design of Experiment (DoE) to confirm the quality profile of drug product, reduce interactions among the input variables for the optimization, modelization and various simulation tools used in pharmaceutical manufacturing (scale up and production). Conclusion: Hence, the use of QbD approach in Artificial intelligence is not only useful in understanding the products or process but also helps in building an excellent and economical pharmaceutical product.

Aim of this research work was to develop mouth dissolving tablet that disintegrates rapidly in mouth by using tasteless complex of Levocetirizine and Tulsion-335. Effect of different parameters such as swelling time, resin activation, drug resin ratio as well as stirring time was optimized by taste and percentage drug loading. Formulated DRC (Drug Resin Complex) was characterized by infrared spectroscopy, thermal analysis and X-ray diffraction pattern. Tablets were formulated by wet granulation with PVP as binder, Sodium Starch Glycolate (SSG) and Crospovidone as super disintegrants. In these batches optimum hardness was achieved but disintegration time was found to be very high as ≥ 70 second, so further trials were planned by using different superdisintegrants such as Croscarmellose sodium, Sodium Starch Glycolate (SSG) as well as Crospovidone by wet granulation method. Tablets formulated with 7.5% crospovidone showed comparatively low disintegration time (25 sec), wetting time (20 sec) and friability (0.60 %) than the other batches. In present study we optimized the conditions required for maximum drug loading of Levocetirizine with Tulsion-335. Among different superdisintergants, crospovidone was found suitable with drug-resin complex to get the low disintegration time, wetting time and friability of tablets.

Purpose: To formulate an optimized gastric floating drug delivery system (GFDDS) containing glipizide with carbomers and cellulosic polymers. Method: Central composite design (CCD) was employed in formulating the GFDDS using hydroxypropyl methylcellulose K4M (HPMC K4M) (A) and Carbopol 934P (CP934P) (B), as independent variables. Floating lag time (FLT), total floating time (TFT) and time required to release 50 % of the drug (T₅₀) were selected as dependent variables. The dissolution data obtained were fitted to various release models and the floating profiles of the formulations analyzed. Results: HPMC K4M loading clearly enhanced floating properties while CP934P showed negative effect on floating properties but was helpful in controlling drug release. The quadratic mathematical model developed was used to predict optimum formulations. The computer optimization process, contour plots and response surface plots predicted the concentration of independent variables A and B to be 47.32 and 8.4 mg, respectively, for maximum TFT and T50 at the same time for least FLT. Predicted concentration of independent variables showed the same results experimentally, with -0.75 - 1.47 percentage errors. Conclusion: CCD demonstrated the role of the derived equations, contour plots and response surface plots in predicting the values of independent variables for the preparation and optimization of glipizide gastric floating matrix tablet. Keywords: Effervescent, Floating tablet, Design of Experiment, Release kinetics, Central composite design, Optimization.

Evaporation of the solvent was utilized in this study to produce and characterize nanoparticles that were loaded with ciprofloxacin. Nine different batches of nanoparticles were manufactured, each of which included a different proportion of ethyl cellulose and polyvinyl alcohol. An investigation of the effects of E.C. and P.V.A. on one to nine formulations was carried out using a design that included 32 different factors. In order to produce the nanoparticles, E.C. and P.V.A. polymers were mixed in a variety of other combinations during the course of the manufacturing process. There were a number of elements that were analyzed in the description, including but not limited to zeta potential, morphology, drug content, Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), differential scanning calorimetry (D.S.C.), and particle size. The outcomes of the study are extremely important, particularly the astounding yield of 88.33%. The result is indicative of the effectiveness of the manufacturing process, which emphasizes reduced waste and a production method that is well-monitored and provides unaltered quality and quantity in the end formulation. One of the most important discoveries made by the inquiry is that the greatest value of the percentage cumulative drug release was 63.4%. The outcome of this study reveals that the formulation can deliver a drug release that is both monitored and sustained over a prolonged time. It is essential to have this controlled release mechanism in place in order to maintain a constant concentration of the drug throughout the body. Formulation F7 is a promising contender for applications of ineffective and controlled drug delivery because of its exceptional characteristics, which include its small particle size, substantial drug content, high encapsulation efficiency, efficient drug loading, impressive yield, and significant cumulative drug release. In a nutshell, these characteristics position it as a promising contender. The findings shed light on the ways in which these features interact with one another to make F7 a viable alternative for drug delivery systems.