Curcumin is one of the most promising natural anti-cancer agents and hence been much investigated for the past few decades [1, 2]. Several phase I and phase II clinical trials indicate that curcumin is quite safe and may exhibit therapeutic efficacy [3–5]. A purified form of curcumin which consists of three main components: curcumin (76.07%); bisdemethoxy curcumin (3.63%); and demethoxy curcumin (20.28%) is defined as curcumin C3 complex . Henceforth, curcumin C3 complex will be referred to as curcumin in this paper. Poor water solubility, poor physiochemical properties and low bioavailability continue to pose major challenges in developing a curcumin formulation for clinical efficacy. Lower serum and tissue levels of curcumin are observed irrespective of the route of administration due to extensive intestinal and hepatic metabolism and rapid elimination, thus restraining bioavailability of curcumin [7–10]. To improve its potential application in the clinical arena, several formulation strategies like nanoparticles, liposomes, complex with phospholipids, cyclodextrins and solid dispersions are being developed to improve bioavailability of curcumin and increasing its therapeutic efficacy [10–17]. Among these approaches, biodegradable polymeric nanoparticle based delivery systems offer significant advantage over other nanocarrier platforms as there is tremendous versatility in the choice of polymer matrices that can be used for tailoring nanoparticle properties to meet various drug delivery needs.
Although much research emphasis are presently being dedicated to various nanoparticle formulations in the pharmaceutical industry, especially towards particle design and targeting, very few results have ever been published on process scale-up. Scaling up of the formulation process is essential for clinical use. In this paper, we have made an effort towards optimizing and scaling up PLGA nanoparticles encapsulating curcumin (PLGA-CURC) by using Solid-Oil/Water (S-O/W) an emulsification-solvent-evaporation/diffusion technique. The major goals in designing polymeric nanoparticles as a delivery system are to control particle size and polydispersity, maximize drug encapsulation efficiency and drug loading, optimize surface properties and tailor release of pharmacologically active agents to achieve a site specific action of the drug at the therapeutically optimal desired rate and dose regimen [18, 19]. Optimization becomes especially important when the formulation needs to be scaled up for industrial production. The organic solvent used in the formulation becomes critical for pilot and industrial scale production and hence only class 3 solvents are preferred for formulation while scaling up. In our formulation, we used ethyl acetate as the organic solvent. Partially hydrolyzed PVA was used as emulsion stabilizer as it prevents redispersibility problems .
For the optimization process, our aim was to use Response Surface Methodology (RSM) in conjunction with Central Composite Design (CCD) to establish the functional relationships between three chosen operating variables: polymer (PLGA) concentration, stabilizer (PVA) concentration and volume of organic phase (ethyl acetate). Four responses were identified namely, mean particle size, polydispersity, encapsulation efficiency (EE) and drug loading (DL) of PLGA-CURC for this study. The optimization procedure involved systematic formulation designs to minimize the number of trials, and analyze the response surfaces in order to realize the effects of factors and to obtain the appropriate formulations with target goals [21, 22]. Further, for analyzing the responses to the variables, mathematical model equations were derived by using Design-Expert® 5.0 software. For a better understanding of the three variables or the optimal PLGA-CURC performance, the models were presented as three-dimensional contour response surface graphs.
Once the optimized batch was determined, classical scale up was followed to produce gram amounts of nanoparticle formulation. The nanoparticles obtained from the scale up were then characterized for particle size, polydispersity, drug loading and morphology and compared with non-scaled up optimized batch, thereby establishing successful process scale-up. Nanoparticles from the scaled up batch were further evaluated for percentage cumulative release, functional assays, cellular uptake in different cancer cell lines and storage stability.