Anabolic Peptide-Enriched Stealth Nanoliposomes for Effective Anti-Osteoporotic Therapy.
Sagar SalaveDhwani RanaHemant KumarNagavendra KommineniDerajram BenivalPublished in: Pharmaceutics (2022)
The objective of the present work was to develop PTH (1-34)-loaded stealth nanoliposomes (PTH-LPs) by employing the use of the Quality by Design (QbD) approach. Risk identification was carried out using the Ishikawa fishbone diagram. PTH-LPs were optimized using Box Behnken Design, a type of response surface methodology to examine the effect of independent variables on dependent variables such as particle size and percentage entrapment efficiency (%EE). Design space was generated for PTH-LPs to reduce interbatch variability during the formulation development process. Furthermore, a cytotoxicity assay, cell proliferation assay, calcium calorimetric assay, mineralized nodule formation, and cellular uptake assay were carried out on MG-63 osteoblast-like cells. The results obtained from these procedures demonstrated that lipid concentration had a significant positive impact on particle size and %EE, whereas cholesterol concentration showed a reduction in %EE. The particle size and %EE of optimized formulation were found to be 147.76 ± 2.14 nm and 69.18 ± 3.62%, respectively. Optimized PTH-LPs showed the sustained release profile of the drug. In vitro cell evaluation studies showed PTH-LPs have good biocompatibility with MG-63 cells. The cell proliferation study revealed that PTH-LPs induced osteoblast differentiation which improved the formation of mineralized nodules in MG-63 cells. The outcome of the present study conclusively demonstrated the potential of the QbD concept to build quality in PTH-LPs with improved osteoanabolic therapy in osteoporosis.
Keyphrases
- inflammatory response
- lps induced
- cell proliferation
- anti inflammatory
- high throughput
- induced apoptosis
- drug delivery
- cell cycle arrest
- bone regeneration
- postmenopausal women
- cell therapy
- photodynamic therapy
- fatty acid
- cell death
- cell cycle
- quality improvement
- risk assessment
- signaling pathway
- low density lipoprotein
- climate change
- bioinformatics analysis