Computational Intelligence Modeling of Pharmaceutical Roll Compaction. Bio-inspired optimization algorithms for feature selection

      Аннотация: In this study, I have developed new variants of bio-inspired optimization algorithms such as chaotic antlion optimization (CALO), binary grey wolf optimization (BGWO), and much more. With the big data captured in the pharmaceutical product development practice, computational intelligence (CI) models based on machine learning and bio-inspired optimization algorithms could potentially be used to identify critical quality attributes (CQA) and critical process parameters (CPP) for the formulations and manufacturing processes. The primary objective is to evaluate the robustness of machine learning techniques combined with bio-inspired optimization algorithms in modeling tablet manufacturing processes. More precisely, our effort is focused on the prediction of tablet properties such as porosity and tensile strength from powder and ribbons characteristics.

Ключевые слова: computational intelligence, Feature Selection, genetic algorithm, Bio-inspired optimization, Pharmaceutical roll compaction, Antlion optimization, Moth-flame optimization, Grey wolf optimization, Social spider optimization, particle swarm optimization