# Advanced Optimization of Clonazepam-Loaded Solid Self-Emulsifying Drug Delivery Systems: Comparison of Weighted Goal Programming and Desirability Function in a Quality by Design Framework

## TL;DR

This paper compares two optimization methods for improving clonazepam drug delivery systems, aiming to enhance solubility and manufacturing quality.

## Contribution

The study introduces a novel comparison of Weighted Goal Programming and Desirability Function in optimizing solid self-emulsifying drug delivery systems.

## Key findings

- Weighted Goal Programming achieved better compromise in optimizing powder flowability, blending efficiency, and drug recovery.
- The optimized system showed nanometric droplet sizes and pH-independent drug release.
- WGP integration in QbD offers more precise optimization for pharmaceutical systems.

## Abstract

Background/Objectives: Clonazepam (CLZ), a BCS Class II drug, presents significant oral delivery challenges due to its low aqueous solubility. This study explores the systematic development of solid self-emulsifying drug delivery systems (S-SEDDS) using Quality by Design (QbD). The primary objective was to evaluate and compare advanced mathematical optimization frameworks, specifically Derringer’s Desirability Function (D) and Weighted Goal Programming (WGP), to identify a robust formulation that enhances drug solubilization while ensuring superior processability and flowability. Methods: Liquid SEDDS were solidified by adsorption onto a porous matrix (Aerosil® 200/Lactose). A multi-objective optimization was conducted to define a robust Design Space (DS), comparing D against WGP. The trade-offs between competing Critical Quality Attributes (CQAs), specifically powder flowability (angle of repose, AR), blending efficiency (BE), and CLZ recovery (CR), were evaluated. Characterization included morphology from Environmental Scanning Electron Microscopy (ESEM), droplet size analysis, and pH-dependent dissolution studies. Results: D provided a highly robust baseline, yielding constant optimal coordinates (F2, F3 = +1; F4 = 0) across all sensitivity levels, with a predicted AR of 40.46°, BE of 0.12 and CR of 90.0%. However, WGP successfully refined this solution by allowing a more flexible weighting of goals, achieving a more favorable compromise with an AR of 38.96°, a BE of 0.11, and a CR of 90.23%. The optimized system maintained nanometric droplet sizes (<200 nm) and showed a controlled, pH-independent release profile, reaching 80% drug solubilization at 6 h. Conclusions: Integrating WGP into the QbD framework offers a more versatile and precise optimization than the traditional D for complex pharmaceutical systems. This approach ensures the production of high-quality S-SEDDS, bridging the gap between mathematical modeling and the stringent requirements of industrial solid dosage manufacturing.