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Optimal experimental design for assessment of enzyme kinetics in a drug discovery screening environment
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy. (Biofarmaci)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy. (Biofarmaci)
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2011 (English)In: Drug Metabolism And Disposition, ISSN 0090-9556, E-ISSN 1521-009X, Vol. 39, no 5, 858-863 p.Article in journal (Refereed) Published
Abstract [en]

A penalized ED-optimal design with a discrete parameter distribution was used to find an optimal experimental design for assessment of enzyme kinetics in a screening environment. A data set for enzyme kinetic data (Vmax and Km) was collected from previously reported studies and every Vmax/Km pair (n=76) was taken to represent a unique drug compound. The design was restricted to 15 samples, an incubation time of up to 40 min and starting concentrations (C0) for the incubation between 0.01 and 100 µM. The optimization was performed by finding the sample times and C0 returning the lowest uncertainty (SE) of the model parameter estimates. Individual optimal designs (I-OD), one general optimal design (G-OD) and one for laboratory practice pragmatically modified design (OD) were obtained. In addition, a standard design (STD-D), representing a commonly applied approach for metabolic stability investigations, was constructed. Simulations were performed for OD and STD-D using the Michaelis-Menten (MM) equation and enzyme kinetic parameters were estimated both with MM and a mono exponential (EXP) decay. OD generated a better result (RSE) for 99% of the compounds and an equal or better result (RMSE) for 78% of the compounds. Furthermore, high-quality estimates (RMSE <30%) of both Vmax and Km could be obtained for a considerable number (26%) of the investigated compounds. The results presented in this study demonstrate that the output could generally be improved when compared to that obtained from the standard approaches used today.

Place, publisher, year, edition, pages
2011. Vol. 39, no 5, 858-863 p.
Keyword [en]
enzyme kinetics, drug discovery screen, optimal experimental design, CLint, Vmax, Km
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-132347DOI: 10.1124/dmd.110.037309ISI: 000289619600017PubMedID: 21289074OAI: oai:DiVA.org:uu-132347DiVA: diva2:358255
Available from: 2010-10-21 Created: 2010-10-18 Last updated: 2017-12-12Bibliographically approved
In thesis
1. Hepatic Disposition of Drugs and the Utility of Mechanistic Modelling and Simulation
Open this publication in new window or tab >>Hepatic Disposition of Drugs and the Utility of Mechanistic Modelling and Simulation
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The elimination of drugs from the body is in many cases performed by the liver. Much could be gained if an accurate prediction of this process could be made early in the development of new drugs. However, for the elimination to occur, the drug molecule needs first to get inside the liver cell.

Disposition is the expression used to encapsulate both elimination and distribution. This thesis presents novel approaches and models based on simple in vitro systems for the investigation of processes involved in the hepatic drug disposition.

An approach to the estimation of enzyme kinetics based on substrate depletion data from cell fractions was thoroughly evaluated through experiments and simulations. The results that it provided were confirmed to be accurate and robust. In addition, a new experimental setup suitable for a screening environment, i.e., for a reduced number of samples, was generated through optimal experimental design. The optimization suggested that sampling at late time points over a wide range of concentration was the most advantageous.

A model, based on data from primary hepatocytes in suspension, for the investigation of cellular disposition of metabolized drugs was developed. Information on the relative importance of metabolism and membrane protein related distribution was obtained by analysis of changes in the kinetics by specific inhibition of the various processes. The model was evaluated by comparing the results to those obtained from an in vivo study analyzed with an especially constructed mechanistic PBPK model. These investigations showed that the suggested model produced good predictions of the relative importance of metabolism and carrier mediated membrane transport for hepatic disposition.

In conclusion, new approaches for the investigation of processes involved in hepatic disposition were developed. These methods were shown to be robust and increased the output of information from already commonly implemented in vitro systems.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2010. 72 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 132
Keyword
Hepatic disposition, pharmacokinetics, mechanistic modelling, drug-drug interactions, enzyme kinetics, Vmax, Km, CLint, carrier-mediated transport, active transport, modelling, in vitro-in vivo extrapolation, physiologically based pharmacokinetic model, optimal experimental design, experimental optimization, data analysis optimization
National Category
Pharmaceutical Sciences Pharmaceutical Sciences
Research subject
Biopharmaceutics
Identifiers
urn:nbn:se:uu:diva-132571 (URN)978-91-554-7934-3 (ISBN)
Public defence
2010-12-10, B:21, Uppsala Biomedicinska Centrum - BMC, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2010-11-18 Created: 2010-10-21 Last updated: 2011-01-13Bibliographically approved
2. Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models
Open this publication in new window or tab >>Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The cost of releasing a new drug on the market has increased rapidly in the last decade. The reasons for this increase vary with the drug, but the need to make correct decisions earlier in the drug development process and to maximize the information gained throughout the process is evident.

Optimal experimental design (OD) describes the procedure of maximizing relevant information in drug development and drug treatment processes. While various optimization criteria can be considered in OD, the most common is to optimize the unknown model parameters for an upcoming study. To date, OD has mainly been used to optimize the independent variables, e.g. sample times, but it can be used for any design variable in a study.

This thesis addresses the OD of multiple continuous or discrete design variables for nonlinear mixed effects models. The methodology for optimizing and the optimization of different types of models with either continuous or discrete data are presented and the benefits of OD for such models are shown. A software tool for optimizing these models in parallel is developed and three OD examples are demonstrated: 1) optimization of an intravenous glucose tolerance test resulting in a reduction in the number of samples by a third, 2) optimization of drug compound screening experiments resulting in the estimation of nonlinear kinetics and 3) an individual dose-finding study for the treatment of children with ciclosporin before kidney transplantation resulting in a reduction in the number of blood samples to ~27% of the original number and an 83% reduction in the study duration.

This thesis uses examples and methodology to show that studies in drug development and drug treatment can be optimized using nonlinear mixed effects OD. This provides a tool than can lower the cost and increase the overall efficiency of drug development and drug treatment.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2011. 74 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 149
Keyword
Pharmacometrics, optimal design, nonlinear mixed effects models, robust design, optimizing drug development, population models
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
urn:nbn:se:uu:diva-160481 (URN)978-91-554-8202-2 (ISBN)
Public defence
2011-12-09, B21, Biomedicinskt Centrum, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2011-11-18 Created: 2011-10-24 Last updated: 2011-11-23Bibliographically approved

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