Prediction of drug content and hardness of intact tablets using artificial neural network and near-infrared spectroscopy

Drug Development and Industrial Pharmacy

Volumn 27, Issue 7, 2001, Pages 623-631

  Chen, Yixin ^a   Thosar, Shilpa S ^b   Forbess, Reba A ^b   Kemper, Mark S ^c   Rubinovitz, Ronald L ^c   Shukla, Atul J ^b  

^a BOEHRINGER INGELHEIM VETMEDICA INC   (United States)

^b UNIVERSITY OF TENNESSEE HEALTH SCIENCE CENTER   (United States)

^c Foss   (United States)

Author keywords

Artificial neural network; Drug content; Hardness; Near infrared spectroscopy; Tablets

Indexed keywords

CELLULOSE; MAGNESIUM STEARATE; MICROCRYSTALLINE CELLULOSE; THEOPHYLLINE;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CALIBRATION; CHEMICAL COMPOSITION; COMPRESSIVE STRENGTH; COMPUTER MODEL; COMPUTER PROGRAM; DIAGNOSTIC ACCURACY; DRUG DETERMINATION; DRUG MIXTURE; INFRARED SPECTROSCOPY; PREDICTION; RANDOMIZATION; SPECTRAL SENSITIVITY; SPECTROMETRY; TABLET COMPRESSION; TABLET HARDNESS;

CALIBRATION; CHEMISTRY, PHARMACEUTICAL; HARDNESS TESTS; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PHARMACEUTICAL PREPARATIONS; PREDICTIVE VALUE OF TESTS; SPECTROSCOPY, NEAR-INFRARED; TABLETS;

EID: 0035149710     PISSN: 03639045     EISSN: None     Source Type: Journal    
DOI: 10.1081/DDC-100107318     Document Type: Article

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