Application of Artificial Neural Networks in Pharmacokinetics

Drug development is a long and expensive process. It is often not until potential drug candidates are administered to humans that accurate quantification of their pharmacokinetic characteristics is achieved. The goal of developing quantitative structure-pharmacokinetic relationships (QSPkRs) is to relate the molecular structure of a chemical entity with its pharmacokinetic characteristics. In this thesis artificial neural networks (ANNs) were used to construct in silico predictive QSPkRs for various pharmacokinetic parameters using different drug data sets. Drug pharmacokinetic data for all studies were taken from the literature. Information for model construction was extracted from drug molecular structure. Numerous theoretical descriptors were generated from drug structure ranging from simple constitutional and functional group counts to complex 3D quantum chemical numbers. Subsets of descriptors were selected which best modeled the target pharmacokinetic parameter(s). Using manual selective pruning, QSPkRs for physiological clearances, volumes of distribution, and fraction bound to plasma proteins were developed for a series of beta-adrenoceptor antagonists. All optimum ANN models had training and cross-validation correlations close to unity, while testing was performed with an independent set of compounds. In most cases the ANN models developed performed better than other published ANN models for the same drug data set. The ability of ANNs to develop QSPkRs with multiple target outputs was investigated for a series of cephalosporins. Multilayer perceptron ANN models were constructed for prediction of half life, volume of distribution, clearances (whole body and renal), fraction excreted in the urine, and fraction bound to plasma proteins. The optimum model was well able to differentiate compounds in a qualitative manner while quantitative predictions were mostly in agreement with observed literature values. The ability to make simultaneous predictions of important pharmacokinetic properties of a compound made this a valuable model. A radial-basis function ANN was employed to construct a quantitative structure-bioavailability relationship for a large, structurally diverse series of compounds. The optimum model contained descriptors encoding constitutional through to conformation dependent solubility characteristics. Prediction of bioavailability for the independent testing set were generally close to observed values. Furthermore, the optimum model provided a good qualitative tool for differentiating between drugs with either low or high experimental bioavailability. QSPkR models constructed with ANNs were compared with multilinear regression models. ANN models were shown to be more effective at selecting a suitable subset of descriptors to model a given pharmacokinetic parameter. They also gave more accurate predictions than multilinear regression equations. This thesis presents work which supports the use of ANNs in pharmacokinetic modeling. Successful QSPkRs were constructed using different combinations of theoretically-derived descriptors and model optimisation techniques. The results demonstrate that ANNs provide a valuable modeling tool that may be useful in drug discovery and development

Systemische netwerken van organisaties

TNO ArbeidSocial decision makin

In search of a novel way to analyze early communicative behavior

The aim of this study was to develop a coding scheme that enables researchers and practitioners to conduct a detailed analysis of the communicative behavior of young children with significant cognitive and motor developmental delays. Currently, there is a paucity of methods to do conduct such an analysis. For the study, video observations of three different scenarios from 38 children with significant cognitive and motor developmental delays aged between 12 and 54 months, were used. Findings from the video observations served as the primary means for development of the coding scheme, which comprises three main categories – context, partner behavior, and individual behavior – and several subcategories. The coding scheme was used to document the early expressive communicative behavior of persons with significant cognitive and motor developmental delays in a detailed manner. This fine-grained information is necessary to differentiate children based on their communicative abilities, to monitor their communicative development longitudinally, and to inform person-centered communicative interventions

Workplace innovation : Europe's competitive edge : a manifesto for enhanced performance and working lives

Why a manifesto? Workplace innovation is an increasingly influential global movement. With strong European origins, it is increasingly recognised by policymakers and other stakeholders in countries across the world as a powerful tool in helping to achieve diverse economic and social policy goals, from inclusive growth and productivity to mental health and wellbeing in the workplace. For enterprise leaders, managers and employee representatives, it provides an actionable framework for effective, sustainable and win-win organisational change, one solidly grounded in research evidence as well as practical experience. Yet we know from successive EU-wide surveys (most recently the 2019 European Company Survey) that there is a long tail between the less than 20% of European companies using workplace innovation practices systematically throughout their organisations and the majority. The EU misses out on potential gains in business performance, workforce skills and health. Several European governments have recognised the importance of workplace innovation within their economic policy platforms and actively implement measures to enhance awareness, promote dissemination and stimulate research. The European Commission itself adopted workplace innovation as part of its policy portfolio, creating the European Workplace Innovation Network (EUWIN) in 2013. Since 2013, EUWIN has been a consistent advocate for the broader adoption of workplace innovation policies and programmes at regional, national and EU levels. Now supported solely by its partners in ten European countries, EUWIN welcomes the European Commission's continuing recognition of workplace innovation but argues strongly for expanding related measures in its industry, employment and research policy fields. EUWIN also argues for the expansion of national and regional policy measures throughout Europe, and enhancing awareness amongst social partners and other stakeholder bodies. This manifesto addresses the European Social Pillar agenda as well as the broader policy priorities of DG EMPL and DG GROW. It summarises the nature, origins and policy significance of workplace innovation, making a case for enhanced recognition throughout Europe's policy eco-system

Identification of plastic constitutive parameters at large deformations from three dimensional displacement fields

The aim of this paper is to provide a general procedure to extract the constitutive parameters of a plasticity model starting from displacement measurements and using the Virtual Fields Method. This is a classical inverse problem which has been already investigated in the literature, however several new features are developed here. First of all the procedure applies to a general three-dimensional displacement field which leads to large plastic deformations, no assumptions are made such as plane stress or plane strain although only pressure-independent plasticity is considered. Moreover the equilibrium equation is written in terms of the deviatoric stress tensor that can be directly computed from the strain field without iterations. Thanks to this, the identification routine is much faster compared to other inverse methods such as finite element updating. The proposed method can be a valid tool to study complex phenomena which involve severe plastic deformation and where the state of stress is completely triaxial, e.g. strain localization or necking occurrence. The procedure has been validated using a three dimensional displacement field obtained from a simulated experiment. The main potentialities as well as a first sensitivity study on the influence of measurement errors are illustrated

Sphingolipids: towards an integrated view of metabolism during the plant stress response

Plants exist in an environment of changing abiotic and biotic stresses. They have developed a complex set of strategies to respond to these stresses and over recent years it has become clear that sphingolipids are a key player in these responses. Sphingolipids are not universally present in all three domains of life. Many bacteria and archaea do not produce sphingolipids but they are ubiquitous in eukaryotes and have been intensively studied in yeast and mammals. During the last decade there has been a steadily increasing interest in plant sphingolipids. Plant sphingolipids exhibit structural differences when compared to their mammalian counterparts and it is now clear that they perform some unique functions. Sphingolipids are recognized as critical components of the plant plasma membrane and endomembrane system. Besides being important structural elements of plant membranes, their particular structure contributes to the fluidity and biophysical order. Sphingolipids are also involved in multiple cellular and regulatory processes including vesicle trafficking, plant development and defense. This review will focus on our current knowledge as to the function of sphingolipids during plant stress responses, not only as structural components of biological membranes, but also as signaling mediators

Testing for effects of climate change on competitive relationships and coexistence between two bird species

Nils Christian Stenseth et al.© 2015 The Author(s) Published by the Royal Society. Climate change is expected to have profound ecological effects, yet shifts in competitive abilities among species are rarely studied in this context. Blue tits (Cyanistes caeruleus) and great tits (Parus major) compete for food and roosting sites, yet coexist across much of their range. Climate change might thus change the competitive relationships and coexistence between these two species. Analysing four of the highest-quality, long-term datasets available on these species across Europe, we extend the textbook example of coexistence between competing species to include the dynamic effects of long-term climate variation. Using threshold time-series statistical modelling, we demonstrate that long-term climate variation affects species demography through different influences on density-dependent and density-independent processes. The competitive interaction between blue tits and great tits has shifted in one of the studied sites, creating conditions that alter the relative equilibrium densities between the two species, potentially disrupting longterm coexistence. Our analyses show that long-term climate change can, but does not always, generate local differences in the equilibrium conditions of spatially structured species assemblages. We demonstrate how long-term data can be used to better understand whether (and how), for instance, climate change might change the relationships between coexisting species. However, the studied populations are rather robust against competitive exclusion.Peer Reviewe

Contextualizing Statelessness in the Indian Legal Framework: Illegal Immigration in Assam

With the publication of the National Register of Citizens (NRC) in Assam, the indispensable question regarding the legal status of individuals who would be excluded from the final version arises. This paper critically analyzes the legal framework that addresses and governs statelessness, by taking into consideration, both the domestic laws, and the international treaties which India is a party to, and argues that the contemporary legal system does not address the issue of statelessness effectively and requires an overhaul. The lack of a comprehensive legislative policy to address statelessness will prevent uniformity in the expulsion methods that is employed by the state. In the light of forced deportation and the subsequent expulsion, this paper highlights the significance of formulating a uniform policy that operates on established humanitarian principles that does not vary from one instance to another

Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at √s = 8 TeV

A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from Hγγ decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events