Investigating Key Molecular Descriptors Affecting Particle Size: A Predictive Exemplary Approach for Self-Emulsifying...

Area of Science:

• Pharmaceutical Sciences
• Drug Delivery Systems
• Physical Chemistry

Background:

• Self-nanoemulsifying drug delivery systems (SNEDDS) enhance solubility for poorly water-soluble drugs.
• Formulation parameters like oil:surfactant:cosolvent ratios influence SNEDDS globule size.
• The specific impact of drug molecules on SNEDDS particle size remains under-investigated.

Purpose of the Study:

• To investigate the correlation between drug molecular descriptors and the particle size of nanoemulsion droplets formed by SNEDDS.
• To identify specific molecular attributes that influence globule size upon drug incorporation into SNEDDS.

Main Methods:

• Prepared SNEDDS preconcentrates with 40 diverse drug molecules using medium chain triglycerides (oil), dimethylacetamide (DMA, cosolvent), and Kolliphor EL (surfactant).
• Analyzed globule size using dynamic light scattering after dispersing preconcentrates in water.
• Correlated particle size data with over 700 molecular descriptors using the PaDEL toolkit and SIMCA14 software.
• Employed genetic algorithms for descriptor screening and PLS-DA for data classification.

Main Results:

• Most drugs increased globule size in SNEDDS compared to blank formulations; some drugs caused a significant reduction.
• A panel of 5 molecular descriptors (SpMiSpMin2_Bhe, RNCS, TDB9i, JG17, ETA_Shape) were identified as significantly correlated with particle size.
• These descriptors effectively classified drug molecules based on their tendency to increase or decrease particle size.

Conclusions:

• Drug molecular properties are critical determinants of SNEDDS globule size, beyond traditional formulation ratios.
• The identified molecular descriptors offer valuable insights for predicting and controlling particle size in SNEDDS.
• This systematic approach aids in rational design of SNEDDS for improved drug solubility and delivery.