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| About Judith Madden (Liverpool John Moores University) |
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Judith Madden has many years’ experience in the development of in silico models to predict biological activity of drugs and drug-like molecules. She has worked in the School of Pharmacy and Chemistry at Liverpool John Moores University, England, since 1998, where she is currently employed as a Senior Lecturer in Pharmaceutical and Chemical Sciences. Her research interests are centred around the use of in silico models, in particular (Quantitative) Structure Activity Relationships ((Q)SARs), to predict pharmacokinetic, pharmacodynamic and toxicological properties of drugs from chemical structure. She is involved in several multinational European Union Framework Projects in the area of predictive (reproductive) toxicology (ReProTect Integrated Project) and the use of QSARs and in silico methods to predict harmful effects of chemicals, of relevance to the forthcoming REACH legislation (CAESAR Scientific Support Action and OSIRIS Integrated Project). She has a number of publications in the area of in silico ADMET, including recent review papers on the structure-based prediction of drug metabolism and in silico ADMET approaches. Before obtaining her tenured academic position she was awarded a post-doctoral research fellowship at the University of Manchester, England (1995-1998) in the field of developing physiologically-based pharmacokinetic models. Prior to that she obtained her PhD in QSAR for Drug Design from Liverpool John Moores University in 1995 and a B.Sc. (Dual Hons) in Pharmacology and Chemistry from the University of Sheffield, England in 1991.
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Application of Global and Local In Silico Models to Predict Pharmacokinetic Properties
Judith Madden, School of Pharmacy and Chemistry, Liverpool John Moores University, Byrom St, Liverpool, L3 3AF, UK
Recent advances in in silico modelling and an increasing recognition that it is essential to optimise drug candidates for pharmacokinetic acceptability alongside pharmacodynamic activity, has led to a reduced rate of attrition in drug development. However, it is unfortunate that a high number of potential drug candidates still fail the latter stages of drug development due to unacceptable pharmacokinetic properties. There is, therefore, a clear need to predict these properties as early as possible in the drug development process. Different stages of this process require different approaches. Initially global models that can be used to screen large numbers of candidates are most pertinent. Such models can be used to indicate a simple yes or no response, or provide categorisation of candidates into their suitability for continuation in the programme. Once a smaller, less diverse, series of candidates has been selected, localised models become more appropriate for lead selection and optimisation purposes.
Prediction of the overall pharmacokinetic profile of a compound is problematic due to the multifactorial and complex nature of individual pharmacokinetic parameters. Deconstructing this problem, to developing models for the constituent parameters, is a potential method of resolving this issue. Consequently models to predict parameters such as absorption, protein binding, volume of distribution, clearance etc can be used to gradually build up a complete profile of candidate structures, from which key composite parameters, such as bioavailability and half-life, can be predicted.
Work has been undertaken in this laboratory to develop models for the prediction of fundamental pharmacokinetic properties, including renal clearance, plasma protein binding and volume of distribution. The development of both global models for initial screening and subsequent refinement to produce local models for subsets of the compounds will be presented. The importance of tailoring the approach to a specific query within the drug development process will be discussed in terms of the applicability of global versus local models.
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