Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Predicting diffusion of innovations with self-organisation and machine learning

The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.

Predicting the outcome of post-anoxic comatose patients based on single-trial EEG analysis

Les maladies cardio-vasculaires représentent la première cause de mortalité en Suisse. Après un arrêt cardio-respiratoire, une minorité des patients survit sans ou avec peu de séquelles fonctionnelles. L'évaluation du pronostic se fait classiquement selon des critères établis par l'Académie Américaine de Neurologie (AAN) en 2006, soit précédant l'introduction de l'hypothermie thérapeutique. Depuis, ces critères semblent insuffisants, et de nouveaux examens para-cliniques sont nécessaires afin d'identifier les patients ayant un pronostic favorable. La détection d'irrégularités auditives, et plus particulièrement l'évolution de cette détection sur plusieurs jours, pourrait être un indicateur du pronostic de patients comateux suite à une anoxie cérébrale. En effet, lors d'une violation de la régularité établie par des séries de sons identiques, deux signaux sont détectables à l'électro- encéphalographie (EEG). Le premier, dénommé «Mismatch negativity» (MMN), peut être enregistré après une violation locale d'une régularité établie au niveau de chaque son. Il reflète un processus inconscient et ne demandant pas de ressources attentionnelles. Le deuxième, dénommé « complexe P300 » survient par contre après une violation globale d'une régularité établie au niveau de groupes de sons. La littérature actuelle indique que ce deuxième phénomène requerrait la présence de capacités attentionnelles. Dans notre étude, nous avons testé l'existence de cette détection d'irrégularités auditives globales chez des patients dans une phase précoce de coma post-anoxique, sous hypothermie thérapeutique. Nous avons enregistré la réponse électro-encéphalographique lors de violations de régularités auditives globales, à l'aide d'un protocole expérimental qui intégrait en plus un paradigme de MMN classique, afin de tester la détection d'irrégularités auditives locales également. Notre analyse finale inclut 24 patients comateux ayant subi un arrêt cardio-respiratoire, et bénéficié du protocole hypothermie du Centre Hospitalier Universitaire Vaudois (CHUV) à Lausanne. Après une analyse multivariée des réponses électro-encéphalographiques de chaque tracé individuellement (« single-trial »), nous avons trouvé que 8 patients sur 24 pouvaient discriminer une irrégularité globale, alors qu'étant définis comateux selon l'échelle de Glasgow (GCS). De plus, l'amélioration de la détection d' irrégularités auditives entre deux EEG consécutifs (en hypo- puis normothermie), était un facteur de bon pronostic. Notre test pourrait ainsi être un complément para-clinique dans l'évaluation du pronostic de patients en coma post- anoxique.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: The square gradient theory and the capillary approach

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which shows the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.

Septic Tenosynovitis of the Hand: Factors Predicting Need for Subsequent Débridement.

BACKGROUND: Treatment of septic hand tenosynovitis is complex, and often requires multiple débridements and prolonged antibiotic therapy. The authors undertook this study to identify factors that might be associated with the need for subsequent débridement (after the initial one) because of persistence or secondary worsening of infection. METHODS: In this retrospective single-center study, the authors included all adult patients who presented to their emergency department from 2007 to 2010 with septic tenosynovitis of the hand. RESULTS: The authors identified 126 adult patients (55 men; median age, 45 years), nine of whom were immunosuppressed. All had community-acquired infection; 34 (27 percent) had a subcutaneous abscess and eight (6 percent) were febrile. All underwent at least one surgical débridement and had concomitant antibiotic therapy (median, 15 days; range, 7 to 82 days). At least one additional surgical intervention was required in 18 cases (median, 1.13 interventions; range, one to five interventions). All but four episodes (97 percent) were cured of infection on the first attempt after a median follow-up of 27 months. By multivariate analysis, only two factors were significantly associated with the outcome "subsequent surgical débridement": abscess (OR, 4.6; 95 percent CI, 1.5 to 14.0) and longer duration of antibiotic therapy (OR, 1.2; 95 percent CI, 1.1 to 1.2). CONCLUSION: In septic tenosynovitis of the hand, the only presenting factor that was statistically predictive of an increased risk of needing a second débridement was the presence of a subcutaneous abscess. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework

Aim The aim of this study was to test different modelling approaches, including a new framework, for predicting the spatial distribution of richness and composition of two insect groups. Location The western Swiss Alps. Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained fromindividual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly process in a unique modelling procedure. We used: (1) five methods to create bS-SDM predictions; (2) two approaches for predicting species richness, by summing individual SDM probabilities or by modelling the number of species (i.e. richness) directly; and (3) five different biotic rules based either on ranking probabilities from SDMs or on community co-occurrence patterns. Combining these various options resulted in 47 implementations for each taxon. Results Species richness of the two taxonomic groups was predicted with good accuracy overall, and in most cases bS-SDM did not produce a biased prediction exceeding the actual number of species in each unit. In the prediction of community composition bS-SDM often also yielded the best evaluation score. In the case of poor performance of bS-SDM (i.e. when bS-SDM overestimated the prediction of richness) the SESAM framework improved predictions of species composition. Main conclusions Our results differed from previous findings using community-level models. First, we show that overprediction of richness by bS-SDM is not a general rule, thus highlighting the relevance of producing good individual SDMs to capture the ecological filters that are important for the assembly process. Second, we confirm the potential of SESAM when richness is overpredicted by bS-SDM; limiting the number of species for each unit and applying biotic rules (here using the ranking of SDM probabilities) can improve predictions of species composition

Predicting recurrence after unprovoked venous thromboembolism: prospective validation of the updated Vienna Prediction Model.

The updated Vienna Prediction Model for estimating recurrence risk after an unprovoked venous thromboembolism (VTE) has been developed to identify individuals at low risk for VTE recurrence in whom anticoagulation (AC) therapy may be stopped after 3 months. We externally validated the accuracy of the model to predict recurrent VTE in a prospective multicenter cohort of 156 patients aged ≥65 years with acute symptomatic unprovoked VTE who had received 3 to 12 months of AC. Patients with a predicted 12-month risk within the lowest quartile based on the updated Vienna Prediction Model were classified as low risk. The risk of recurrent VTE did not differ between low- vs higher-risk patients at 12 months (13% vs 10%; P = .77) and 24 months (15% vs 17%; P = 1.0). The area under the receiver operating characteristic curve for predicting VTE recurrence was 0.39 (95% confidence interval [CI], 0.25-0.52) at 12 months and 0.43 (95% CI, 0.31-0.54) at 24 months. In conclusion, in elderly patients with unprovoked VTE who have stopped AC, the updated Vienna Prediction Model does not discriminate between patients who develop recurrent VTE and those who do not. This study was registered at www.clinicaltrials.gov as #NCT00973596.

External Validation of the Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) Score for Predicting Stroke-Associated Pneumonia in the Athens Stroke Registry.

BACKGROUND AND PURPOSE: The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) score was developed recently for predicting stroke-associated pneumonia (SAP), one of the most common complications after stroke. The aim of the present study was to externally validate the ISAN score. METHODS: Data included in the Athens Stroke Registry between June 1992 and December 2011 were used for this analysis. Inclusion criteria were the availability of all ISAN score variables (prestroke independence, sex, age, National Institutes of Health Stroke Scale score). Receiver operating characteristic curves and linear regression analyses were used to determine the discriminatory power of the score and to assess the correlation between actual and predicted pneumonia in the study population. Separate analyses were performed for patients with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH). RESULTS: The analysis included 3204 patients (AIS: 2732, ICH: 472). The ISAN score demonstrated excellent discrimination in patients with AIS (area under the curve [AUC]: .83 [95% confidence interval {CI}: .81-.85]). In the ICH group, the score was less effective (AUC: .69 [95% CI: .63-.74]). Higher-risk groups of ISAN score were associated with an increased relative risk of SAP; risk increase was more prominent in the AIS population. Predicted pneumonia correlated very well with actual pneumonia (AIS group: R(2) = .885; β-coefficient = .941, P < .001; ICH group: R(2) = .880, β-coefficient = .938, P < .001). CONCLUSIONS: In our external validation in the Athens Stroke Registry cohort, the ISAN score predicted SAP very accurately in AIS patients and demonstrated good discriminatory power in the ICH group. Further validation and assessment of clinical usefulness would strengthen the score's utility further.

Predicting the future effectiveness of protected areas for bird conservation in Mediterranean ecosystems under climate change and novel fire regime scenarios

AimGlobal environmental changes challenge traditional conservation approaches based on the selection of static protected areas due to their limited ability to deal with the dynamic nature of driving forces relevant to biodiversity. The Natura 2000 network (N2000) constitutes a major milestone in biodiversity conservation in Europe, but the degree to which this static network will be able to reach its long-term conservation objectives raises concern. We assessed the changes in the effectiveness of N2000 in a Mediterranean ecosystem between 2000 and 2050 under different combinations of climate and land cover change scenarios. LocationCatalonia, Spain. MethodsPotential distribution changes of several terrestrial bird species of conservation interest included in the European Union's Birds Directive were predicted within an ensemble-forecasting framework that hierarchically integrated climate change and land cover change scenarios. Land cover changes were simulated using a spatially explicit fire-succession model that integrates fire management strategies and vegetation encroachment after the abandonment of cultivated areas as the main drivers of landscape dynamics in Mediterranean ecosystems. ResultsOur results suggest that the amount of suitable habitats for the target species will strongly decrease both inside and outside N2000. However, the effectiveness of N2000 is expected to increase in the next decades because the amount of suitable habitats is predicted to decrease less inside than outside this network. Main conclusionsSuch predictions shed light on the key role that the current N2000may play in the near future and emphasize the need for an integrative conservation perspective wherein agricultural, forest and fire management policies should be considered to effectively preserve key habitats for threatened birds in fire-prone, highly dynamic Mediterranean ecosystems. Results also show the importance of considering landscape dynamics and the synergies between different driving forces when assessing the long-term effectiveness of protected areas for biodiversity conservation.

Predicting overall service quality: a structural equation modelling approach

In this article, the results of a modified SERVQUAL questionnaire (Parasuraman et al., 1991) are reported. The modifications consisted in substituting questionnaire items particularly suited to a specific service (banking) and context (county of Girona, Spain) for the original rather general and abstract items. These modifications led to more interpretable factors which accounted for a higher percentage of item variance. The data were submitted to various structural equation models which made it possible to conclude that the questionnaire contains items with a high measurement quality with respect to five identified dimensions of service quality which differ from those specified by Parasuraman et al. And are specific to the banking service. The two dimensions relating to the behaviour of employees have the greatest predictive power on overall quality and satisfaction ratings, which enables managers to use a low-cost reduced version of the questionnaire to monitor quality on a regular basis. It was also found that satisfaction and overall quality were perfectly correlated thus showing that customers do not perceive these concepts as being distinct

On the Rule of Mixtures for Predicting Stress-Softening and Residual Strain Effects in Biological Tissues and Biocompatible Materials

In this work, we use the rule of mixtures to develop an equivalent material model in which the total strain energy density is split into the isotropic part related to the matrix component and the anisotropic energy contribution related to the fiber effects. For the isotropic energy part, we select the amended non-Gaussian strain energy density model, while the energy fiber effects are added by considering the equivalent anisotropic volumetric fraction contribution, as well as the isotropized representation form of the eight-chain energy model that accounts for the material anisotropic effects. Furthermore, our proposed material model uses a phenomenological non-monotonous softening function that predicts stress softening effects and has an energy term, derived from the pseudo-elasticity theory, that accounts for residual strain deformations. The model’s theoretical predictions are compared with experimental data collected from human vaginal tissues, mice skin, poly(glycolide-co-caprolactone) (PGC25 3-0) and polypropylene suture materials and tracheal and brain human tissues. In all cases examined here, our equivalent material model closely follows stress-softening and residual strain effects exhibited by experimental data

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.