For decades, multi-drug resistance (MDR) to chemotherapeutic drugs has been a serious challenge for researchers and has limited the use of anticancer drugs in malignancy treatment. Combination therapy has been considered as one of the most promising methods to address this problem. In the current study, we optimized niosome nanoparticles containing chemotherapeutic agent doxorubicin and chemosensitizer curcumin in term of surfactant content. Then, a new biocompatible structure (LipoNiosome, combination of niosome and liposome) containing Tween 60: cholesterol: DPPC (at 55 : 30 : 15 : 3) with 3% DSPE-mPEG was designed and developed to serve as a model for selective co-delivery of hydrophilic and hydrophobic drugs to cancerous cells. The proposed formulation provided potential benefits, including pH-sensitive sustained release, smooth globular surface morphology, high entrapment efficiency (∼80% for both therapeutic agents) and small diameter (42 nm). Exposure of cancer cells to LipoNiosome-doxorubicin–curcumin has shown an excellent performance of specific cellular internalization and synergistic toxic effect (>40%; as compared to free drugs and >23% when compared to single doxorubicin delivery) against Saos-2, MG-63 and KG-1 cell lines. A new cationic formulation (zeta potential: +35.26 mV; diameter: 52.2 nm) was also designed for co-delivery of above-mentioned drugs and gene as well. Finely, we suggested a kinetic model (Korsmeyer–Peppa with R² = 93% near cancer cells) for in vitro drug release of the co-delivery system. The presently formulated nano-based systems would provide researchers with a more obvious understanding of new LipoNiosome formulation as a successful lipid-based nano-carriers for co-delivery of doxorubicin, curcumin and other anticancer agents.

This study focuses on the development of a universal mathematical model for drug release kinetics from liposomes to allow in silico prediction of optimal conditions for fine-tuned controlled drug release. As a prelude for combined siRNA-drug delivery, nanoliposome formulations were optimized using various mole percentages of a cationic lipid (1,2-dioleoyl-3-trimethylammonium-propane, DOTAP) in the presence or absence of 3 mol% distearoyl phosphoethanolamine, polyethylene glycol (PEG–2000mDSPE). Outcome parameters were particle size, zeta potential, entrapment efficiency, in vitro drug release, and tumor cell kill efficiency. The optimized formula (containing 20% DOTAP with 3% DSPE-mPEG(2000) was found to be stable for six months, with round-shaped particles without aggregate formation, an average diameter of 71 nm, a suitable positive charge, and 89% drug encapsulation efficiency (EE). The 41% drug release during 6 h confirmed controlled release. Furthermore, the release profiles as functions of pH and temperature were investigated and the kinetics of the drug release could adequately be fitted to Korsmeyer–Peppas’ model by multiple regression analysis. The statistical parameters confirmed good conformity of final models. Functionality of the novel cationic liposome formulations (± DOX) was tested on osteosarcoma (OS) cell lines. Increased OS cell toxicity (1.3-fold) was observed by the DOX-loaded vs. the free DOX. A feasibility pilot showed that siRNA could be loaded efficiently as well. In conclusion, we have established a predictive mathematical model for the fine-tuning of controlled drug release from liposomal formulations, while creating functional drug-delivery liposomes with potential for siRNA co-delivery to increase specificity and efficacy.

Bioreactors are important inevitable part of any tissue engineering (TE) strategy as they aid the construction of three-dimensional functional tissues. Since the ultimate aim of a bioreactor is to create a biological product, the engineering parameters, for example, internal and external mass transfer, fluid velocity, shear stress, electrical current distribution, and so forth, are worth to be thoroughly investigated. The effects of such engineering parameters on biological cultures have been addressed in only a few preceding studies. Furthermore, it would be highly inefficient to determine the optimal engineering parameters by trial and error method. A solution is provided by emerging modeling and computational tools and by analyzing oxygen, carbon dioxide, and nutrient and metabolism waste material transports, which can simulate and predict the experimental results. Discovering the optimal engineering parameters is crucial not only to reduce the cost and time of experiments, but also to enhance efficacy and functionality of the tissue construct. This review intends to provide an inclusive package of the engineering parameters together with their calculation procedure in addition to the modeling techniques in TE bioreactors.