A Quality by Design Approach for Optimizing Solid Lipid Nanoparticles of Bedaquiline for Improved Product Performance.
Mercy A OkezueChidi UcheAdekoya AdebolaStephen R ByrnPublished in: AAPS PharmSciTech (2024)
Bedaquiline (BQ) solid lipid nanoparticles (SLNs), which have previously been formulated for parenteral administration, have a risk of patient non-compliance in treating tuberculosis. This research presents a strategy to develop BQ SLNs for oral delivery to improve patient adherence, The upper and lower levels for the formulation excipients were generated from screening experiments. Using 4 input factors (BQ, lecithin, Tween 80, and PEG), a full factorial design from 3 × 2x2 × 2 experiments was randomly arranged to investigate 3 response variables: Particle size distribution (PSD), polydispersity index (PdI), and zeta potential (ZP). High shear homogenization was used to mix the solvent and aqueous phases, with 15% sucrose as a cryoprotectant. The response variables were assessed using a zeta sizer while TEM micrographs confirmed the PSD data. Solid-state assessments were conducted using powdered X-ray diffraction and scanning electron microscopy (SEM) imaging. A comparative invitro assessment was used to determine drug release from an equivalent dose of BQ free base powder and BQ-SLN, both packed in hard gelatin capsules. The sonicated formulations obtained significant effects for PSD, PdI, and ZP. The p-values (0.0001 for PdI, 0.0091 for PSD) for BQ as an independent variable in the sonicated formulation were notably higher than those in the unsonicated formulation (0.1336 for PdI, 0.0117 for PSD). The SEM images were between 100 - 400 nm and delineated nanocrystals of BQ embedded in the lipid matrix. The SLN formulation provides higher drug levels over the drug's free base; a similarity factor (f2 = 18.3) was estimated from the dissolution profiles.
Keyphrases
- electron microscopy
- drug delivery
- high resolution
- solid state
- multidrug resistant
- drug resistant
- adverse drug
- mycobacterium tuberculosis
- fatty acid
- electronic health record
- ionic liquid
- deep learning
- computed tomography
- squamous cell carcinoma
- sentinel lymph node
- drug induced
- magnetic resonance imaging
- adipose tissue
- metabolic syndrome
- radiation therapy
- emergency department
- photodynamic therapy
- skeletal muscle
- big data
- machine learning
- human immunodeficiency virus
- convolutional neural network
- insulin resistance
- magnetic resonance
- hyaluronic acid
- neoadjuvant chemotherapy
- climate change
- artificial intelligence
- crystal structure
- contrast enhanced
- tissue engineering