Population pharmacokinetics and pharmacodynamics: An underutilized resource

A meeting was convened in Canberra, Australia, at the request of the Australian Drug Evaluation Committee (ADEC), on December 3-4, 1997 to discuss the role of population pharmacokinetics and pharmacodynamics in drug evaluation and development. The ADEC was particularly concerned about registration of drugs in the pediatric age group. The population approach could be used more often than is currently the case in pharmacokinetic and pharmacodynamic studies to provide valuable information for the safe and effective use of drugs in neonates, infants, and children. The meeting ultimately broadened to include discussion about other subgroups. The main conclusions of the meeting were: 1. The population approach, pharmacokinetic and pharmacodynamic analysis, is a valuable tool both for drug registration purposes and for optimal dosing of drugs in specific groups of patients, 2. Population pharmacokinetic and pharmacodynamic studies are able to fill in the gaps' in registration of drugs, for example, to provide information on optimal pediatric dosing. Such studies provide a basis for enhancing product information to improve rational prescribing, 3. Expertise is required to perform the population studies and expertise, with a clinical perspective, is also required to evaluate such studies if they are to be submitted as part of a drug registration dossier Such expertise is available in the Australasian region and is increasing. Centers of excellence with the appropriate expertise to advise and assist should be encouraged to develop and grow in the region, 4. The use of the population approach by the pharmaceutical industry needs to be encouraged to provide valuable information not obtainable by other techniques. The acceptance of population pharmacokinetic and pharmacodynamic analyses by regulatory agencies also needs to be encouraged, and 5. Development of the population approach to pharmacokinetics and pharmacodynamics is needed from a public health perspective to ensure that all available information is collected and used to improve the way drugs are used. This important endeavor needs funding and support at the local and international levels.

Computational binding assays of antigenic peptides

Computer models can be combined with laboratory experiments for the efficient determination of (i) peptides that bind MHC molecules and (ii) T-cell epitopes. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures. This requires the definition of standards and experimental protocols for model application. We describe the requirements for validation and assessment of computer models. The utility of combining accurate predictions with a limited number of laboratory experiments is illustrated by practical examples. These include the identification of T-cell epitopes from IDDM-, melanoma- and malaria-related antigens by combining computational and conventional laboratory assays. The success rate in determining antigenic peptides, each in the context of a specific HLA molecule, ranged from 27 to 71%, while the natural prevalence of MHC-binding peptides is 0.1-5%.

Grazers and diggers: Exploitation competition and coexistence among foragers with different feeding strategies on a single resource

A mathematical model is presented that describes a system where two consumer species compete exploitatively for a single renewable resource. The resource is distributed in a patchy but homogeneous environment; that is, all patches are intrinsically identical. The two consumer species are referred to as diggers and grazers, where diggers deplete the resource within a patch to lower densities than grazers. We show that the two distinct feeding strategies can produce a heterogeneous resource distribution that enables their coexistence. Coexistence requires that grazers must either move faster than diggers between patches or convert the resources to population growth much more efficiently than diggers. The model shows that the functional form of resource renewal within a patch is also important for coexistence. These results contrast with theory that considers exploitation competition for a single resource when the resource is assumed to be well mixed throughout the system.

Molecular immunology databases and data repositories

Over recent years databases have become an extremely important resource for biomedical research. Immunology research is increasingly dependent on access to extensive biological databases to extract existing information, plan experiments, and analyse experimental results. This review describes 15 immunological databases that have appeared over the last 30 years. In addition, important issues regarding database design and the potential for misuse of information contained within these databases are discussed. Access pointers are provided for the major immunological databases and also for a number of other immunological resources accessible over the World Wide Web (WWW). (C) 2000 Elsevier Science B.V. All rights reserved.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

A computational analysis of substrate binding strength by phosphorylase kinase and protein kinase A

Protein kinases exhibit various degrees of substrate specificity. The large number of different protein kinases in the eukaryotic proteomes makes it impractical to determine the specificity of each enzyme experimentally. To test if it were possible to discriminate potential substrates from non-substrates by simple computational techniques, we analysed the binding enthalpies of modelled enzyme-substrate complexes and attempted to correlate it with experimental enzyme kinetics measurements. The crystal structures of phosphorylase kinase and cAMP-dependent protein kinase were used to generate models of the enzyme with a series of known peptide substrates and non-substrates, and the approximate enthalpy of binding assessed following energy minimization. We show that the computed enthalpies do not correlate closely with kinetic measurements, but the method can distinguish good substrates from weak substrates and non-substrates. Copyright (C) 2002 John Wiley Sons, Ltd.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advancesin information technology has the potential to radically transformimmunology in the postgenomics era. Not only do we now have readyaccess to vast quantities of existing data, but new data with relevanceto immunology are being accumulated at an exponential rate. Resourcesfor computational immunology include biological databases and methodsfor data extraction, comparison, analysis and interpretation. Publiclyaccessible biological databases of relevance to immunologists numberin the hundreds and are growing daily. The ability to efficientlyextract and analyse information from these databases is vital forefficient immunology research. Most importantly, a new generationof computational immunology tools enables modelling of peptide transportby the transporter associated with antigen processing (TAP), modellingof antibody binding sites, identification of allergenic motifs andmodelling of T-cell receptor serial triggering.

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.