00000ctm a22000003a 4500 UP-1685523046126318428 Buklod 20170814173749.0 m |o d | ta 170814s2017 xx d r |||| u| (iLib)UPMNL-00015498145 UPM PHARM rda eng LG 993.5 2017 P5 L44 Legaspi, Donato Jr. D. author. Development of predictive PBPK model for extended-release metformin tablets through Simcyp software Donato D. Legaspi Jr., Frances Lois U. Ngo, Imma Coney P. Olayan ; adviser, Bryan Paul I. Bulatao. ​​​​​​​​​​Manila: Department of Industrial Pharmacy, College of Pharmacy, University of the Philippines Manila 2017. ​​ vii, 71 leaves 28 cm. ​​​​text rdacontent unmediated rdamedia volume rdacarrier Available to the general public. ​​​​​​Thesis (Bachelor of Science in Industrial Pharmacy)--University of the Philippines Manila, June 2017. Physiologically Based Pharmacokinetic (PBPK) models integrate the physiological, physicochemical and biochemical processes that determine the pharmacokinetic behavior of a compound such as metformin. PBPK Modelling using the Simcyp software can be applied as a method for requesting biowaivers. Modelling can be expanded to extended release formulations requiring expensive and tedious in vivo studies. Modelling using in vivo data from literature instead is another application of Simcyp. The objective of the study was to develop a drug-specific PBPK model that can be used to correlate in-vivo in-vitro performance of metformin ER tablets. Metformin specific PBPK model was developed from pharmacokinetic parameters from literature and in vivo data from Balan et al. (2001). Dissolution was performed to two brands of 500 mg metformin ER tablets available in the Philippines to examine the internal validity of the model. Point-to-point relationship was evaluated to determine if the model achieved level A correlation by computing for the prediction error (%PE). Resulting %PE of the model were greater than the 10% criteria indicative of a Level A correlation. Therefore, the model developed has poor internal predictability and must be further refined. Additional pharmacokinetic parameters such as data on the OCT1 and OCT3 protein transporters crucial in metformin absorption is recommended to be included in the input parameters. The use of clinical in vivo data from literature with subjects closest to the genetic makeup of a Filipino can simulate a more appropriate data for the purpose of products in the count. Metformin. Ngo, Frances Lois U. author. Olayan, Imma Coney P. author. Bulatao, Bryan Paul I. thesis adviser. FI UP UPMNL PHARM LG 993.5 2017 P5 L44 Thesis