Artificial neural networks to optimize formulation components of a fixed-dose combination of rifampicin, isoniazid and pyrazinamide in a microemulsion

Current Drug Discovery Technologies

Volumn 2, Issue 3, 2005, Pages 195-201

  Glass, B D ^a   Agatonovic Kustrin, S ^b   Wisch, M H ^c  

^a JAMES COOK UNIVERSITY   (Australia)

^b UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^c RHODES UNIVERSITY   (South Africa)

Author keywords

Artificial neural network (ANN); Fixed dose combination; Isoniazid; Microemulsion; Paediatric liquid dosage form; Pyrazinamide; Rifampicin

Indexed keywords

FAT DROPLET; ISONIAZID; PYRAZINAMIDE; RIFAMPICIN; SOLUBILIZER; SOLVENT; SURFACTANT;

AQUEOUS SOLUTION; ARTICLE; ARTIFICIAL NEURAL NETWORK; DRUG COST; DRUG DELIVERY SYSTEM; DRUG DESIGN; DRUG FORMULATION; DRUG SOLUBILITY; DRUG SPECIFICITY; DRUG STABILITY; LIPOPHILICITY; MICROEMULSION; OXIDATION; PRIORITY JOURNAL; SENSITIVITY ANALYSIS;

ANTIBIOTICS, ANTITUBERCULAR; ANTITUBERCULAR AGENTS; CAPRYLATES; CHEMISTRY, PHARMACEUTICAL; CHILD; DRUG COMBINATIONS; DRUG STABILITY; EMULSIONS; HUMANS; ISONIAZID; NEURAL NETWORKS (COMPUTER); POLYETHYLENE GLYCOLS; POLYSORBATES; PYRAZINAMIDE; RIFAMPIN; SOLUBILITY; SORBITOL; TRIGLYCERIDES;

EID: 24144446709     PISSN: 15701638     EISSN: None     Source Type: Journal    
DOI: 10.2174/1570163054866864     Document Type: Article

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