The virtual laboratory approach to pharmacokinetics: design principles and concepts

Abstract

SUMMARYModeling and simulation in pharmacokinetics has has turned into the focus of pharmaceutical companies, driven by the emerging consensus that in silico predictions combined with in vitro data have the potential of significantly increasing insight into pharmacokinetic processes. To adequately support in silico methodology, software tools need to be user-friendly and, at the same time, flexible. In brief, the software has to allow the realization of modeling ideas that are beyond current knowledge -in the form of a virtual lab. We present and discuss the necessary design principles and concepts. These have been implemented in the software package MEDICI-PK to demonstrate its feasibility and advantages. PHARMACOKINETICS IN DRUG DISCOVERYThe medical benefits of a drug depend not only on its biological effect at the target protein, but also on its "life cycle" within the organism -from its absorption into the blood, distribution to tissue and its eventual breakdown or excretion by the liver and kidneys. Pharmacokinetics is the study of the drug-organism interaction, in particular the investigation of absorption, distribution, metabolism, and excretion (ADME) processes [1,2]. Studying ADME profiles is widely used in drug discovery to understand the properties necessary to convert leads into good medicines [3,4].As a result of studies in the late 1990s, indicating that poor pharmacokinetics (PK) and toxicity were important causes of costly late-stage failures in drug development, it has

Improved biological properties and hypouricemic effects of uricase from Candida utilis loaded in novel alkaline enzymosomes

“…20 The pharmacokinetic parameters were estimated by statistical moment analysis. 21 Pharmacodynamic study Establishment of the hyperuricemia rat model Male Sprague Dawley rats (weighing 250-300 g) were intragastrically administered 500 mg/kg of hypoxanthine in a 3% soluble starch solution and 100 mg/kg of oxonic acid potassium salt in a mixed solvent of lanolin-liquid paraffin (volume ratio of 3:2) subcutaneously. In this hyperuricemia rat model, the plasma uric acid level elevated quickly and lasted for more than 12 hours (the mean uric acid level was determined in hyperuricemia rats within 24 hours and was 343.94 µmol/L, n = 30).…”

Prediction of Pharmacokinetic Parameters

“…There is gradually emerging consensus that in silico predictions are no less predictive to what occurs in vivo than are in vitro tests, with the distinct advantage that far less investment in technology, resources, and time is needed (17). An amalgamation of in vitro experiments and in silico modeling will dramatically increase the insight and knowledge about the relevant physiological and pharmacological processes in drug discovery (3). The linkage between data generation and model building has been illustrated in Fig.…”

“…In addition, other groups such as ECVAM (The European Centre for the Validation of Alternative Methods) have identified predictive pharmacokinetic modeling as a beneficial tool for reduction in the use of animals in drug discovery and development (5). As a result of studies in the late 1990s, indicating that the poor pharmacokinetics and toxicity were major causes of costly late-stage failures in drug development, there is increasing realization to consider these areas as early as possible in the drug discovery process (3).…”

“…The in silico approaches are being widely used today to assess the absorption, distribution, metabolism, and excretion (ADME) properties of compounds at the early stages of drug discovery process (2). Study of ADME profiles is being widely used in drug discovery to understand the properties necessary to convert lead structures into good medicines (3). Early consideration of ADME properties is also becoming increasingly important due to the implementation of combinatorial chemistry and high-throughput screening so as to generate vast number of potential lead compounds (4).…”

Explicit reformulations of the Lambert W-omega function for calculations of the solutions to one-compartment pharmacokinetic models with Michaelis–Menten elimination kinetics

“…Valuable tools for our understanding of the interplay between various pharmacokinetic parameters include either the simulation of drug time-course profiles within the framework of specific body models that are described through solving systems of differential equations, or the fitting of the corresponding equations to experimental concentration-time data (Huisinga et al 2006;von Kleist and Huisinga 2007). Here, both simulation and modeling are required to address a number of key questions at the various stages of the drug-development process (Bonate 2006;Lave et al 2007).…”