Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection.

As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and outlier detection for epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterize the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggests ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. As such, our method could be of wider use for infectious disease surveillance. We illustrate ASMODEE using publicly available data of National Health Service (NHS) Pathways reporting potential COVID-19 cases in England at a fine spatial scale, showing that the method would have enabled the early detection of the flare-ups in Leicester and Blackburn with Darwen, two to three weeks before their respective lockdown. ASMODEE is implemented in the free R package trendbreaker. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Fostering Engagement With Health and Housing Innovation: Development of Participant Personas in a Social Housing Cohort.

BACKGROUND: Personas, based on customer or population data, are widely used to inform design decisions in the commercial sector. The variety of methods available means that personas can be produced from projects of different types and scale. OBJECTIVE: This study aims to experiment with the use of personas that bring together data from a survey, household air measurements and electricity usage sensors, and an interview within a research and innovation project, with the aim of supporting eHealth and eWell-being product, process, and service development through broadening the engagement with and understanding of the data about the local community. METHODS: The project participants were social housing residents (adults only) living in central Cornwall, a rural unitary authority in the United Kingdom. A total of 329 households were recruited between September 2017 and November 2018, with 235 (71.4%) providing complete baseline survey data on demographics, socioeconomic position, household composition, home environment, technology ownership, pet ownership, smoking, social cohesion, volunteering, caring, mental well-being, physical and mental health-related quality of life, and activity. K-prototype cluster analysis was used to identify 8 clusters among the baseline survey responses. The sensor and interview data were subsequently analyzed by cluster and the insights from all 3 data sources were brought together to produce the personas, known as the Smartline Archetypes. RESULTS: The Smartline Archetypes proved to be an engaging way of presenting data, accessible to a broader group of stakeholders than those who accessed the raw anonymized data, thereby providing a vehicle for greater research engagement, innovation, and impact. CONCLUSIONS: Through the adoption of a tool widely used in practice, research projects could generate greater policy and practical impact, while also becoming more transparent and open to the public.

Population Pharmacokinetic Analysis of Bortezomib in Pediatric Leukemia Patients: Model-Based Support for Body Surface Area-Based Dosing Over the 2- to 16-Year Age Range.

This population analysis described the pharmacokinetics of bortezomib after twice-weekly, repeat-dose, intravenous administration in pediatric patients participating in 2 clinical trials: the phase 2 AALL07P1 (NCT00873093) trial in relapsed acute lymphoblastic leukemia and the phase 3 AAML1031 (NCT01371981) trial in de novo acute myelogenous leukemia. The sources of variability in the pharmacokinetic parameters were characterized and quantified to support dosing recommendations. Patients received intravenous bortezomib 1.3 mg/m2 twice-weekly, on days 1, 4, and 8 during specific blocks or cycles of both trials and on day 11 of block 1 of study AALL07P1, in combination with multiagent chemotherapy. Blood samples were obtained and the plasma was harvested on day 8 over 0-72 hours postdose to measure bortezomib concentrations by liquid chromatography-tandem mass spectrometry. Concentration-time data were analyzed by nonlinear mixed-effects modeling. Covariates were examined using forward addition (P < .01)/backward elimination (P < .001). Data were included from 104 patients (49%/51% acute lymphoblastic leukemia/acute myelogenous leukemia; 60%/40% aged 2-11 years/12-16 years). Bortezomib pharmacokinetics were described by a 3-compartment model with linear elimination. Body surface area adequately accounted for variability in clearance (exponent 0.97), supporting body surface area-based dosing. Stratified visual predictive check simulations verified that neither age group nor patient population represented sources of meaningful pharmacokinetic heterogeneity not accounted for by the final population pharmacokinetic model. Following administration of 1.3 mg/m2 intravenous bortezomib doses, body surface area-normalized clearance in pediatric patients was similar to that observed in adult patients, thereby indicating that this dose achieves similar systemic exposures in pediatric patients.

Identification of Criticality in Neuronal Avalanches: II. A Theoretical and Empirical Investigation of the Driven Case.

The observation of apparent power laws in neuronal systems has led to the suggestion that the brain is at, or close to, a critical state and may be a self-organised critical system. Within the framework of self-organised criticality a separation of timescales is thought to be crucial for the observation of power-law dynamics and computational models are often constructed with this property. However, this is not necessarily a characteristic of physiological neural networks-external input does not only occur when the network is at rest/a steady state. In this paper we study a simple neuronal network model driven by a continuous external input (i.e. the model does not have an explicit separation of timescales from seeding the system only when in the quiescent state) and analytically tuned to operate in the region of a critical state (it reaches the critical regime exactly in the absence of input-the case studied in the companion paper to this article). The system displays avalanche dynamics in the form of cascades of neuronal firing separated by periods of silence. We observe partial scale-free behaviour in the distribution of avalanche size for low levels of external input. We analytically derive the distributions of waiting times and investigate their temporal behaviour in relation to different levels of external input, showing that the system's dynamics can exhibit partial long-range temporal correlations. We further show that as the system approaches the critical state by two alternative 'routes', different markers of criticality (partial scale-free behaviour and long-range temporal correlations) are displayed. This suggests that signatures of criticality exhibited by a particular system in close proximity to a critical state are dependent on the region in parameter space at which the system (currently) resides.

Interdependency and hierarchy of exact and approximate epidemic models on networks.

Over the years numerous models of S I S (susceptible --> infected --> susceptible) disease dynamics unfolding on networks have been proposed. Here, we discuss the links between many of these models and how they can be viewed as more general motif-based models. We illustrate how the different models can be derived from one another and, where this is not possible, discuss extensions to established models that enables this derivation. We also derive a general result for the exact differential equations for the expected number of an arbitrary motif directly from the Kolmogorov/master equations and conclude with a comparison of the performance of the different closed systems of equations on networks of varying structure.

Identification of Criticality in Neuronal Avalanches: I. A Theoretical Investigation of the Non-driven Case.

In this paper, we study a simple model of a purely excitatory neural network that, by construction, operates at a critical point. This model allows us to consider various markers of criticality and illustrate how they should perform in a finite-size system. By calculating the exact distribution of avalanche sizes, we are able to show that, over a limited range of avalanche sizes which we precisely identify, the distribution has scale free properties but is not a power law. This suggests that it would be inappropriate to dismiss a system as not being critical purely based on an inability to rigorously fit a power law distribution as has been recently advocated. In assessing whether a system, especially a finite-size one, is critical it is thus important to consider other possible markers. We illustrate one of these by showing the divergence of susceptibility as the critical point of the system is approached. Finally, we provide evidence that power laws may underlie other observables of the system that may be more amenable to robust experimental assessment.

Mainstreaming carbon management in healthcare systems: a bottom-up modeling approach.

Increasing greenhouse gas emissions threaten human health and the environment. In response, healthcare managers face significant challenges in balancing operational decisions about patient care with carbon mitigation targets. We explore a bottom-up modeling framework to aid in the decision-making for both carbon and cost in healthcare, using data from a case study in Cornwall, UK. A model was built and run for secondary healthcare, specifically outpatient clinics, theater lists, beds, and diagnostic facilities. Five scenarios were tested: business-as-usual; service expansion; site closure; water temperature reduction; and theater optimization. The estimated emissions from secondary healthcare in Cornwall ran to 5787 T CO(2)eq with patient travel adding 2215 T CO(2)eq. Closing selected sites would have reduced this by 4% (261 T CO(2)eq), a reduction less than the resulting increases in patient transport emissions. Reducing hot water temperatures by 5 °C and improving theater usage would lower the footprint by 0.7% (44 T CO(2)eq) and 0.08% (5 T CO(2)eq), respectively. We consider bottom-up models important tools in the process of estimating and modeling the carbon footprint of healthcare. For the carbon reduction targets of the healthcare sector to be met, the use of these bottom-up models in decision making and forward planning is pivotal.

Epidemic threshold and control in a dynamic network.

In this paper we present a model describing susceptible-infected-susceptible-type epidemics spreading on a dynamic contact network with random link activation and deletion where link activation can be locally constrained. We use and adapt an improved effective degree compartmental modeling framework recently proposed by Lindquist et al. [J. Math Biol. 62, 143 (2010)] and Marceau et al. [Phys. Rev. E 82, 036116 (2010)]. The resulting set of ordinary differential equations (ODEs) is solved numerically, and results are compared to those obtained using individual-based stochastic network simulation. We show that the ODEs display excellent agreement with simulation for the evolution of both the disease and the network and are able to accurately capture the epidemic threshold for a wide range of parameters. We also present an analytical R0 calculation for the dynamic network model and show that, depending on the relative time scales of the network evolution and disease transmission, two limiting cases are recovered: (i) the static network case when network evolution is slow and (ii) homogeneous random mixing when the network evolution is rapid. We also use our threshold calculation to highlight the dangers of relying on local stability analysis when predicting epidemic outbreaks on evolving networks.

Water quality characteristics of discharge from reforested loose-dumped mine spoil in eastern Kentucky.

Surface mining is a common method for extracting coal in the coal fields of eastern Kentucky. Using the Forestry Reclamation Approach (FRA), which emphasizes the use of minimally compacted or loose-dumped spoil as a growth medium for trees, reclamation practitioners are successfully reestablishing forests. Yet, questions remain regarding the effects FRA has on the quality of waters discharged to receiving streams. To examine the effect of FRA on water quality, this study compared waters that were discharged from three types of spoils: predominantly brown, weathered sandstone (BROWN); predominantly gray, unweathered sandstone (GRAY); and an equal mixture of both aforementioned sandstones and shale (MIXED). The water quality parameters pH, EC, Ca, K, Mg, Na, NO-N, NH-N, SO, Cl, TC, suspended sediment concentration (SSC), settleable solids (SS), and turbidity were monitored over a 2-yr period on six 0.4-ha plots (two replications per spoil type). Generally, levels of Cl, SO, Ca, NO-N, NH-N, SS, SSC, and turbidity decreased over time. The pH for all spoils increased from about 7.5 to 8.5. The EC remained relatively level in the BROWN spoil, whereas the GRAY and MIXED spoils had downward trajectories that were approaching 500 µS cm. The value of 500 µS cm has been reported as the apparent threshold at which certain taxa such as Ephemeroptera (e.g., Mayfly) recolonize disturbed headwater streams of eastern Kentucky and adjacent coal-producing Appalachian states.

Optimization of the physicochemical and pharmacokinetic attributes in a 6-azauracil series of P2X7 receptor antagonists leading to the discovery of the clinical candidate CE-224,535.

High throughput screening (HTS) of our compound file provided an attractive lead compound with modest P2X(7) receptor antagonist potency and high selectivity against a panel of receptors and channels, but also with high human plasma protein binding and a predicted short half-life in humans. Multi-parameter optimization was used to address the potency, physicochemical and pharmacokinetic properties which led to potent P2X(7)R antagonists with good disposition properties. Compound 33 (CE-224,535) was advanced to clinical studies for the treatment of rheumatoid arthritis.

Preclinical pharmacokinetics and metabolism of 6-(4-(2,5-difluorophenyl)oxazol-5-yl)-3-isopropyl-[1,2,4]-triazolo[4,3-a]pyridine, a novel and selective p38alpha inhibitor: identification of an active metabolite in preclinical species and human liver microsomes.

The disposition of 6-(4-(2,5-difluorophenyl)oxazol-5-yl)-3-isopropyl-[1,2,4]-triazolo[4,3-a]pyridine (1), a potent and selective inhibitor of mitogen activated protein (MAP) kinase p38alpha, was characterized in several animal species in support of its selection for preclinical safety studies and potential clinical development. 1 demonstrated generally favorable pharmacokinetic properties in all species examined. Following intravenous (i.v.) administration, 1 exhibited low volumes of distribution at steady state (Vd(ss)) ranging from 0.4-1.3 l/kg (2.4-26 l/m(2)) in the rat, dog and monkey. Systemic plasma clearance was low in cynomolgus monkeys (6.00 ml/min/kg, 72.0 ml/min/m(2)) and Sprague-Dawley rats (7.65+/-1.08 ml/min/kg, 45.9+/-6.48 ml/min/m(2) in male rats and 3.15+/-0.27 ml/min/kg, 18.9+/-1.62 ml/min/m(2) in female rats) and moderate in beagle dogs (12.3+/-5.1 ml/min/kg, 246+/-102 ml/min/m(2)) resulting in plasma half-lives ranging from 1 to 5 h in preclinical species. Moderate to high bioavailability of 1 was observed in rats (30-65%), dogs (87%) and monkeys (40%) after oral (p.o.) dosing consistent with the in vitro absorption profile of 1 in the Caco-2 permeability assay. In rats, the oral pharmacokinetics were dose dependent over the dose range studied (5, 50 and 100 mg/kg). The principal route of clearance of 1 in rat, dog, monkey and human liver microsomes and in vivo in preclinical species involved oxidative metabolism mediated by cytochrome P450 enzymes. The major metabolic fate of 1 in preclinical species and humans involved hydroxylation on the isopropyl group to yield the tertiary alcohol metabolite 2. In human liver microsomes, this transformation was catalysed by CYP3A4 as judged from reaction phenotyping analysis using isozyme-specific inhibitors and recombinant CYP enzymes. Metabolite 2 was also shown to possess inhibitory potency against p38alpha in a variety of in vitro assays. 1 as well as the active metabolite 2 were moderately to highly bound to plasma proteins (f(u) approximately 0.1-0.33) in rat, mouse, dog, monkey and human. 1 as well as the active metabolite 2 did not exhibit competitive inhibition of the five major cytochrome P450 enzymes namely CYP1A2, 2C9, 2C19, 2D6 and 3A4 (IC(50)>50 microM). Overall, these results indicate that the absorption, distribution, metabolism and excretion (ADME) profile of 1 is relatively consistent across preclinical species and predict potentially favorable pharmacokinetic properties in humans, supporting its selection for toxicity/safety assessment studies and possible investigations in humans as an anti-inflammatory agent.

Absolute oral bioavailability of traxoprodil in cytochrome P450 2D6 extensive and poor metabolisers.

BACKGROUND: Traxoprodil, a substituted 4-phenylpiperidine, is an N-methyl-D-aspartate (NMDA) receptor antagonist that is selective for receptors containing the NR2B subunit. In vivo and in vitro studies examining the disposition of traxoprodil have demonstrated that it is mainly metabolised by cytochrome P450 (CYP) 2D6, a major drug-metabolising enzyme that exhibits a genetic polymorphism. OBJECTIVE: To assess the single-dose absolute oral bioavailability of traxoprodil in healthy male volunteers phenotyped as either CYP2D6 extensive or poor metabolisers. METHODS: This was an open-label, three-way crossover study. Traxoprodil was administered as a single dose orally in solution of 50, 100 and 300mg and intravenously as a constant rate 2-hour infusion of 50 and 100mg. CYP2D6 phenotype was assigned following single-dose dextromethorphan administration. RESULTS: In poor metabolisers (n = 6), oral bioavailability was approximately 80% and was consistent with a liver extraction ratio of approximately 20% (plasma clearance of approximately 4 mL/min/kg) indicating near complete absorption. Following intravenous administration, the mean volume of distribution at steady state (V(ss)) was moderate (approximately 6.5 L/kg) and the mean elimination half-life (t((1/2))) was approximately 20 hours. Following oral administration the mean maximum plasma concentration (C(max)) and area under the plasma concentration-time curve from time zero to infinity (AUC(infinity)) increased approximately proportionally with dose. In extensive metabolisers (n = 11), oral bioavailability was dose-dependent and nonlinear. At the 100mg dose, the absolute oral bioavailability was approximately 39.5%. Overall, the oral bioavailability ranged from 22.8% to 62.1% and its estimation was confounded by large differences in plasma concentrations at oral doses without equivalent intravenous doses. Following intravenous administration, plasma clearance was high (approximately 27 mL/min/kg), the V(ss) was moderate (approximately 4 L/Kg) and the t((1/2)) was approximately 2-4 hours. Following oral administration the C(max) and AUC(infinity) increased more than proportionally with dose. Apparent oral clearance decreased with increasing oral dose. However, t((1/2)) was approximately the same at all doses (approximately 4 hours). CONCLUSION: The pharmacokinetics of traxoprodil were quite different in the two phenotypes. In extensive metabolisers, the oral bioavailability was nonlinear and dose-dependent, while in poor metabolisers, oral bioavailability appeared to be linear and dose-independent. Based on the pharmacokinetics in extensive and poor metabolisers, the nonlinear oral bioavailability in extensive metabolisers may be attributed to saturation of hepatic first-pass CYP2D6 metabolism. Thus, at a high oral dose, the impact of CYP2D6 metabolism on traxoprodil pharmacokinetics is minimal.

Structure-activity relationships of triazolopyridine oxazole p38 inhibitors: identification of candidates for clinical development.

The synthesis, structure-activity relationship, in vivo activity, and metabolic profile for a series of triazolopyridine-oxazole based p38 inhibitors are described. The deficiencies of the lead structure in the series, CP-808844, were overcome by changes to the C4 aryl group and the triazole side-chain culminating in the identification of several potential clinical candidates.

Influence of lipophilicity on the interactions of N-alkyl-4-phenyl-1,2,3,6-tetrahydropyridines and their positively charged N-alkyl-4-phenylpyridinium metabolites with cytochrome P450 2D6.

The relationship between lipophilicity and CYP2D6 affinity of cyclic tertiary (N-alkyl-4-phenyl-1,2,3,6-tetrahydropyridines) and quaternary (N-alkyl-4-phenylpyridinium) amines was examined. The 1,2,3,6-tetrahydropyridine scaffold was chosen due to its common occurrence in the structures of CYP2D6 ligands such as the Parkinsonian neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and the dehydrated haloperidol metabolite N-[4-(4-fluorophenyl)-4-oxobutyl]-4-(4-chlorophenyl)-1,2,3,6-tetrahydropyridine (HPTP). Likewise, the pyridinium framework is found in and 4-(4-chlorophenyl)-1-[4-(4-fluorophenyl)-4-oxobutyl]pyridinium and N-methyl-4-phenylpyridinium (MPP(+)), the positively charged metabolites of MPTP and haloperidol. The lack of CYP2D6 inhibition by MPTP and its pyridinium metabolite MPP(+) was due to their hydrophilic nature since higher N-alkyl homologs revealed substantial increases in inhibitory potency against recombinant CYP2D6-mediated bufuralol-1'-hydroxylation. The reasonable correlation between lipophilicity and CYP2D6 inhibition by pyridiniums and 1,2,3,6-tetrahydropyridines was only limited to straight chain N-alkyl analogs, since certain N-alkylaryl analogs of lower lipophilicity were better CYP2D6 inhibitors. CYP2D6 substrate properties of straight chain N-alkyltetrahydropyridines were also governed by lipophilicity, and N-heptyl-4-phenyl-1,2,3,6-tetrahydropyridine was the optimal substrate (K(mapp) = 0.63 microM). Metabolism studies indicated that the N-heptyl analog underwent monohydroxylation on the aromatic ring and on the N-heptyl group suggesting that 1,2,3,6-tetrahydropyridines can bind in more than one conformation in the CYP2D6 active site. Increased lipophilicity of haloperidol metabolites did not correlate with inhibitory potency since the more lipophilic HPTP metabolite was less potent as an inhibitor than reduced-haloperidol and reduced-HPTP. Furthermore, HPTP and reduced-HPTP, of comparable lipophilicity to the N-heptyltetrahydropyridine analog were inactive as CYP2D6 substrates. This observation suggests that steric constraints rather than lipophilicity are responsible for the lack of CYP2D6 substrate properties of cyclic tertiary amines tethered to bulky N-substituents. This phenomenon appears to be a common theme among several cyclic tertiary amine-containing anti-depressants and should be taken into consideration when designing central nervous system agents devoid of CYP2D6 substrate properties.

Assessment of the contributions of CYP3A4 and CYP3A5 in the metabolism of the antipsychotic agent haloperidol to its potentially neurotoxic pyridinium metabolite and effect of antidepressants on the bioactivation pathway.

As a plausible explanation for the large interindividual variability in the pharmacokinetics of the neuroleptic agent haloperidol, the contributions of CYP3A isozymes (CYP3A4 and the polymorphic CYP3A5) predominantly involved in haloperidol bioactivation to the neurotoxic pyridinium species 4-(4-Chlorophenyl)-1-[4-(4-fluorophenyl)-4-oxobutyl]-pyridinium (HPP(+)) were assessed in human liver microsomes and heterologously expressed enzymes. Based on recent reports on drug-drug interactions between haloperidol and antidepressants including selective serotonin reuptake inhibitors, the inhibitory effects of antidepressants on the CYP3A4/5-mediated haloperidol bioactivation were also evaluated. HPP(+) formation followed Michaelis-Menten kinetics in microsomes, recombinant CYP3A4, and CYP3A5 with K(m) values of 24.4 +/- 8.9 microM, 18.3 +/- 4.9 microM, and 200.2 +/- 47.6 microM, respectively, and V(max) values of 157.6 +/- 13.2 pmol/min/mg of protein, 10.4 +/- 0.6 pmol/min/pmol P450, and 5.16 +/- 0.6 pmol/min/pmol P450, respectively. The similarity in K(m) values between human liver microsomal and recombinant CYP3A4 incubations suggests that polymorphic CYP3A5 may not be an important genetic contributor to the interindividual variability in CYP3A-mediated haloperidol clearance pathways. Besides HPP(+), a novel 4-fluorophenyl-ring-hydroxylated metabolite of haloperidol in microsomes/CYP3A enzymes was also detected. Its formation was consistent with previous reports on the detection of O-sulfate and -glucuronide conjugates of a fluorophenyl ring-hydroxylated metabolite of haloperidol in human urine. Finally, all antidepressants except buspirone inhibited the CYP3A4/5-catalyzed oxidation of haloperidol to HPP(+) in a concentration-dependent manner. Based on the estimated IC(50) values for inhibition of HPP(+) formation in microsomes, the antidepressants were ranked in the following order: fluoxetine, nefazodone, norfluoxetine, trazodone, and fluvoxamine. These inhibition results suggest that clinically observed drug-drug interactions between haloperidol and antidepressants may arise via the attenuation of CYP3A4/5-mediated 4-(4-chlorophenyl)-1-[4-(4-fluorophenyl)-4-oxobutyl]-4-piperidinol biotransformation pathways.

On the diversity of oxidative bioactivation reactions on nitrogen-containing xenobiotics.

The unexpected occurrence of idiosyncratic drug reactions during late clinical trials or after a drug has been released can lead to a severe restriction in its use or failure to release/withdrawal. This leads to considerable uncertainty in drug development and has led to attempts to try to predict a drug's potential to cause such reactions. The biotransformation of relatively inert drugs to highly reactive metabolites, commonly referred to as "bioactivation", is now recognized to be an obligatory step in several kinds of drug-induced adverse reactions. Reactive metabolites can be formed by most, if not all, of the enzymes that are involved in drug metabolism. A major theme explored in this review includes the diversity of oxidative bioactivation reactions on nitrogen-containing xenobiotics including drugs. A variety of Phase I enzymes including P450, MAO, and peroxidases bioactivate nitrogen-containing xenobiotics via direct oxidations on the nitrogen atom leading to reactive intermediates or by oxidation at an alternate site in the molecule; for the metabolite to be reactive via the latter sequence nitrogen participation in required. Examples of direct oxidations on nitrogen include the N-oxidation of aromatic amines (e.g. procainamide), single electron N-oxidation of imides (e.g. phenytoin), or alpha-carbon oxidations of arylalkyl- or alkylamines (e.g. mianserin), to reactive nitroso, nitrogen free radical and iminium species, respectively. Examples of indirect bioactivation are highlighted with aromatic amines (e.g. diclofenac) that undergo p-hydroxylation resulting in the formation of p-aminophenols, two-electron oxidation of which results in the formation of reactive quinoneimines. Potential strategies that could be utilized in the screening of novel bioactivation pathways are also discussed.