LIMITED SAMPLING STRATEGY IN ORDER TO CONDUCT BIOEQUIVALENCE STUDIES

• Main Author: Akbar Emberik, Muhammad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/78935
• Institution: Institut Teknologi Bandung

Generic drugs uses have increased in several years especially as cost saving measurement in health care provision. Generic drugs is the drug that generally intended as equivalent drug to the innovator product, produced without a license from the innovator company, and marketed after expire date or other privilege. The successful application of generic drugs is based on the bioequivalence establisment to their innovator drug because it can bridge the related preclinical and clinical data. By comparing the area under the curve (AUC) of concentration time course and maximum concentration (Cmax) form drug compound in blood, two formula can be considered bioequivalent if meets the bioequivalence criteria. AUC calculation is obtained from abundance of sample collection and it can be burdensome to the patient or volunteers because it is uncomfortable and painful when the sample collections occur. Limited strategy (LSS) can be used to decrease the amount of sample collections so it can be relieve the pain in the patient and cut down the job analysis. LSS has been proven to give robust and accurate result in estimation of individual pharmacokinetics. The objective of this study is to generate the LSS models in order to bioequivalence study purposes of several products with different pharmacokinetics profiles and to examine the effect of pharmacokinetics profile type to generated LSS. The study consist of data collection from bioequivalence study, compartment determination, LSS models development, selection of LSS models, validation ofLSS models, analysis and interpretation of results. LSS for prediction of three pharmacokinetics parameters (Cmas, AUCo-t, AUCo-m) is done by using multiple regression with the criteria is R2 0.9. Validation of LSS models is done by using jackknife method. Validation parameters are bias and precision with criteria +15%. LSS be tested to several products with different pharmacokinetics profile that is immediate release one-compartment type (IROC) use metformin as drug compound, immediate release two-compartment type (IRTC) use azithromycin as drug compound, sustained release one-compartment type (SROC) use metformin as drug compound, and delay release one-compartment type (DROC) use lansoprazole as drug compound. Regression analysis is done by software using Minitab@ 17.2.1 version. The study results shown that LSS models can be applied to all of type of tested profile. The ROC, SROC, DROC type are generate the LSS models which is meets the criteria for all parameters using three sampling point, while IRTC generate the LSS model which is meets the criteria for only AUCo-t and using four sampling point. Selected models to determine the three parameters together in metformin drug compound with IROC profile is using sampling time in 1, 2, and 12 hours with bias value is 0.62% and precision is 8.26% for Cmax parameter, bias is 1.92% and precision is 5.85% for AUCo-t parameter, bias is 2.52% and precision is 5.97% for Models to determine three parameters together is l, 3, 6, and 24 hours for metformin drug compound with SROC profile with bias value 4.05% and precision 8.80% for Cmæx parameter, bias is -0.24% and precision is 4.40% for AUCo-t parameter, bias is 0.08% and precision 4.72% for AUCo-Ø parameter. Models to determine three parameters together is 1.5, 2,5, and 6 hours for lansoprazole drug compound with DROC profile with bias value-0.32% and precision is 12.79% for Cmax parameter, bias is 1.30% and precision is 9.76% for AUCo-t parameter, bias is l. 16% and precision is 9.03% for parameter. Models to determine AUCo-t and parameters in azithromycin drug compound with IRTC profile is using 1.5, 8, 12 and 24 hours sampling time with bias value is 0.34% and precision is 5.32% for AUCo-t parameter, bias is 0.49% and precision is 6.22% for AUCo-T parameter.