Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

Prediction of Infant Drug Exposure Through Breastfeeding: Population PK Modeling and Simulation of Fluoxetine Exposure.

The likelihood of significant exposure to drugs in infants through breast milk is poorly defined, given the difficulties of conducting pharmacokinetics (PK) studies. Using fluoxetine (FX) as an example, we conducted a proof-of-principle study applying population PK (popPK) modeling and simulation to estimate drug exposure in infants through breast milk. We simulated data for 1,000 mother-infant pairs, assuming conservatively that the FX clearance in an infant is 20% of the allometrically adjusted value in adults. The model-generated estimate of the milk-to-plasma ratio for FX (mean: 0.59) was consistent with those reported in other studies. The median infant-to-mother ratio of FX steady-state plasma concentrations predicted by the simulation was 8.5%. Although the disposition of the active metabolite, norfluoxetine, could not be modeled, popPK-informed simulation may be valid for other drugs, particularly those without active metabolites, thereby providing a practical alternative to conventional PK studies for exposure risk assessment in this population.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Intermittent hemodialysis treatment in cefepime-induced neurotoxicity: Case report, pharmacokinetic modeling, and review of the literature.

Cefepime is a broad-spectrum cephalosporin indicated for in-hospital treatment of severe infections. Acute neurotoxicity, an increasingly recognized adverse effect of this drug in an overdose, predominantly affects patients with reduced renal function. Although dialytic approaches have been advocated to treat this condition, their role in this indication remains unclear. We report the case of an 88-year-old female patient with impaired renal function who developed life-threatening neurologic symptoms during cefepime therapy. She was treated with two intermittent 3-hour high-flux, high-efficiency hemodialysis sessions. Serial pre-, post-, and peridialytic (pre- and postfilter) serum cefepime concentrations were measured. Pharmacokinetic modeling showed that this dialytic strategy allowed for serum cefepime concentrations to return to the estimated nontoxic range 15 hours earlier than would have been the case without an intervention. The patient made a full clinical recovery over the next 48 hours. We conclude that at least 1 session of intermittent hemodialysis may shorten the time to return to the nontoxic range in severe clinically patent intoxication. It should be considered early in its clinical course pending chemical confirmation, even in frail elderly patients. Careful dosage adjustment and a high index of suspicion are essential in this population.

Ecological niche overlap in sister species: how do oil-collecting bees Macropis europaea and M. fulvipes (Hymenoptera: Melittidae) avoid competition and hybridization?

Oil-collecting bees are found worldwide and always in association with particular oil-producing flowers. In the Western Palearctic, three oil-collecting bee species within the genus Macropis (Hymenoptera, Melittidae) interact in a tight pollination mutualism with species of the only European oil-producing plant genus Lysimachia L. (Myrsinaceae). Two of these oil-collecting bees (Macropis europaea and Macropis fulvipes) show overlapping geographic distributions, comparable morphologies, and similar ecological characteristics (e.g., habitat type, floral preferences). In view of these similarities, we presume that hybridization should occur between the two species unless potential variation among the species' ecological niches prevents it, simultaneously decreasing competition for resources. Using modern genetic analyses and ecological niche modeling on a large bee sampling throughout Europe, we discuss new perspectives on the ecology and evolutionary history of this mutualism.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.

Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.

Plasma Level of Mmp-9 as Predictive Factor for Response and Progression Free Survival in Patients Treated with Bevacizumab (Bev) and Pegylated Liposomal Doxorubicin (Pld): Sakk 24/06

Background: There is currently no identified marker predicting benefit from Bev in patients with breast cancer (pts). We monitored prospectively 6 angiogenesis-related factors in the blood of advanced stage pts treated with a combination of Bev and PLD in a phase II trial of the Swiss Group for Clinical Cancer Research, SAKK.Methods: Pts received PLD (20 mg/m2) and Bev (10 mg/kg) every 2 weeks for a maximum of 12 administrations, followed by Bev monotherapy until progression or severe toxicity. Blood samples were collected at baseline, during treatment and at treatment discontinuation. Enzyme-linked immunosorbent assays (Quantikine, R&DSystems and Reliatech) were used to measure vascular endothelial growth factor (VEGF), placental growth factor (PlGF), matrix metalloproteinase 9 (MMP-9) and soluble VEGF receptors -1, -2 and -3. The natural log-transformed (ln) data for each factor was analyzed by analysis of variance (ANOVA) model to investigate differences between the mean values of the subgroups of interest (where a = 0.05), based on the best tumor response by RECIST.Results: 132 samples were collected in 41 pts. The mean of baseline ln MMP-9 levels was significantly lower in pts with tumor progression than those with tumor response (p=0.0202, log fold change=0.8786) or disease control (p=0.0035, log fold change=0.8427). Higher MMP-9 level was a significant predictor of superior progression free survival (PFS): p=0.0417, hazard ratio=0.574, 95% CI=0.336-0.979. In a multivariate cox proportional hazards model, containing performance status, disease free interval, number of tumor sites, visceral involvement and prior adjuvant chemotherapy, using stepwise regression baseline MMP-9 was still a statistically 117P Table 1. SOLTI-0701* AC01B07* NU07B1* SOR+CAP N=20 PL+CAP N=33 SOR+ GEM/CAP N=23 PL+ GEM/CAP N=27 SOR+PAC N=48 PL+PAC N=46 Baseline characteristics Age, median (range), y 49 (32-72) 53 (30-78 54 (32-69) 57 (31-82) 50 (27-80) 52 (23-74) AJCC stage, n (%) IIIB/IIIC 3 (15) 6 (18) 0 (0) 3 (11) 8 (17) 9 (20) IV 17 (85) 27 (82) 23 (100) 24 (89) 40 (83) 37 (80) Metastatic site, n (%) Non-visceral 3 (15) 6 (18) 7 (30) 6 (22) 9 (19) 17 (37) Visceral 17 (85) 27 (82) 16 (70) 21 (78) 39 (81) 29 (63) Prior metastatic chemo, n (%) 8 (40) 15 (45) 21 (91) 25 (93) - - Efficacy PFS, median, mo 4.3 2.5 3.1 2.6 5.6 5.5 HR (95% CI)_ 0.60 (0.31, 1.14) 0.57 (0.30, 1.09) 0.86 (0.50, 1.45) 1-sided P value_ 0.055 0.044 0.281 Overall survival, median, mo 17.5 16.1 Pending 14.7 18.2 HR (95% CI)_ 0.98 (0.50, 1.89) 1.11 (0.64, 1.94) 1-sided P value_ 0.476 0.352 Safety N=20 N=33 N=22 N=27 N=46 N=46 Tx-emergent Grade 3/4, n (%) 15 (75) 16 (48) 20 (91) 17 (63) 36 (78) 16 (35) Grade 3§ hand-foot skin reaction/ syndrome 8 (40) 5 (15) 8 (36) 0 (0) 14 (30) 2 (4) *Efficacy results based on intent-to-treat population and safety results based on safety population (pts who received study drug[s]); _Cox regression within each subgroup; _log-rank test within each subgroup; §maximum toxicity grade for hand-foot skin reaction/syndrome; AJCC, American Joint Committee on Cancer mittedabstractsª The Author 2011. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com Downloaded from annonc.oxfordjournals.org at Bibliotheque Cantonale et Universitaire on June 6, 2011 significant factor (p=0.0266). The results of the other measured factors were presented elsewhere.Conclusions: Higher levels of MMP-9 could predict tumor response and superior PFSin pts treated with a combination of Bev and PLD. These exploratory results justify further investigations of MMP-9 in pts treated with Bev combinations in order to assess its role as a prognostic and predictive factor.Disclosure: K. Zaman: Participation in advisory board of Roche; partial sponsoring ofthe study by Roche (the main sponsor was the Swiss Federation against Cancer (Oncosuisse)). B. Thu¨rlimann: stock of Roche; Research grants from Roche. R. vonMoos: Participant of Advisory Board and Speaker honoraria

MMP-9 as predictive factor for response and progression free survival in breast cancer patients treated with bevacizumab and pegylated liposomal doxorubicin. A multicenter, single-arm phase II trial (SAKK24/06). On behalf of the Swiss Group for Clinical Cancer Research (SAKK).

The benefit of bevacizumab (Bv) has been shown in different tumors including colorectal cancer, renal cancer, pulmonary non-small cell cancer and also breast cancer. However to date, there is no established test evaluating the angiogenic status of a patient and monitoring the effects of anti-angiogenic treatments. Tumor angiogenesis is the result of a balance between multiple pro- and anti¬angiogenic molecules. There is very little published clinical data exploring the impact of the anti-angiogenic therapy on the different angiogenesis-related molecules and the potential role of these molecules as prognostic or predictive factors.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

The Identity Style Inventory (ISI-3) and the Utrecht-Management of Identity Commitments Scale (U-MICS): Factor structure, reliability, and convergent validity in French-speaking college students

The purpose of this study was to evaluate the factor structure and the reliability of the French versions of the Identity Style Inventory (ISI-3) and the Utrecht-Management of Identity Commitments Scale (U-MICS) in a sample of college students (N = 457, 18 to 25 years old). Confirmatory factor analyses confirmed the hypothesized three-factor solution of the ISI-3 identity styles (i.e. informational, normative, and diffuse-avoidant styles), the one-factor solution of the ISI-3 identity commitment, and the three-factor structure of the U-MICS (i.e. commitment, in-depth exploration, and reconsideration of commitment). Additionally, theoretically consistent and meaningful associations among the ISI-3, U-MICS, and Ego Identity Process Questionnaire (EIPQ) confirmed convergent validity. Overall, the results of the present study indicate that the French versions of the ISI-3 and UMICS are useful instruments for assessing identity styles and processes, and provide additional support to the cross-cultural validity of these tools.

Decoupled post-glacial history in mutualistic plant-insect interactions: insights from the yellow loosestrife (Lysimachia vulgaris) and its associated oil-collecting bees (Macropis europaea and M-fulvipes)

AimWe take a comparative phylogeographical approach to assess whether three species involved in a specialized oil-rewarding pollination system (i.e. Lysimachia vulgaris and two oil-collecting bees within the genus Macropis) show congruent phylogeographical trajectories during post-glacial colonization processes. Our working hypothesis is that within specialized mutualistic interactions, where each species relies on the co-occurrence of the other for survival and/or reproduction, partners are expected to show congruent evolutionary trajectories, because they are likely to have followed parallel migration routes and to have shared glacial refugia. LocationWestern Palaearctic. MethodsOur analysis relies on the extensive sampling of 104 Western Palaearctic populations (totalling 434, 159 and 74 specimens of Lysimachiavulgaris, Macropiseuropaea and Macropisfulvipes, respectively), genotyped with amplified fragment length polymorphism. Based on this, we evaluated the regional genetic diversity (Shannon diversity and allele rarity index) and genetic structure (assessed using structure, population networks, isolation-by-distance and spatial autocorrelation metrics) of each species. Finally, we compared the general phylogeographical patterns obtained. ResultsContrary to our expectations, the analyses revealed phylogeographical signals suggesting that the investigated organisms demonstrate independent post-glacial trajectories as well as distinct contemporaneous demographic parameters, despite their mutualistic interaction. Main conclusionsThe mutualistic partners investigated here are likely to be experiencing distinct and independent evolutionary dynamics because of their contrasting life-history traits (e.g. dispersal abilities), as well as distinct hubs and migration routes. Such conditions would prevent and/or erase any signature of co-structuring of lineages in space and time. As a result, the lack of phylogeographical congruence driven by differences in life-history traits might have arisen irrespective of the three species having shared similar Pleistocene glacial refugia.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.