21 resultados para Mixed integer non-linear programming (MINLP)
em Université de Lausanne, Switzerland
Resumo:
Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions
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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.
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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.
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Besides CYP2B6, other polymorphic enzymes contribute to efavirenz (EFV) interindividual variability. This study was aimed at quantifying the impact of multiple alleles on EFV disposition. Plasma samples from 169 human immunodeficiency virus (HIV) patients characterized for CYP2B6, CYP2A6, and CYP3A4/5 allelic diversity were used to build up a population pharmacokinetic model using NONMEM (non-linear mixed effects modeling), the aim being to seek a general approach combining genetic and demographic covariates. Average clearance (CL) was 11.3 l/h with a 65% interindividual variability that was explained largely by CYP2B6 genetic variation (31%). CYP2A6 and CYP3A4 had a prominent influence on CL, mostly when CYP2B6 was impaired. Pharmacogenetics fully accounted for ethnicity, leaving body weight as the only significant demographic factor influencing CL. Square roots of the numbers of functional alleles best described the influence of each gene, without interaction. Functional genetic variations in both principal and accessory metabolic pathways demonstrate a joint impact on EFV disposition. Therefore, dosage adjustment in accordance with the type of polymorphism (CYP2B6, CYP2A6, or CYP3A4) is required in order to maintain EFV within the therapeutic target levels.
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Background: It is suggested that a low dose of valganciclovir can be equally effective than a standard dose for cytomegalovirus (CMV) prophylaxis after kidney transplantation. The aim of our study was to determine the ganciclovir exposure observed under a routine daily dosage of 450 mg valganciclovir in kidney transplant recipients with a wide range of renal function. Methods: In this prospective study, kidney transplant recipients with a GFR MDRD above 25 mL/min at risk for CMV (donor or recipient seropositive for CMV) received a dose of valganciclovir (450 mg daily) prophylaxis for 3 months. Ganciclovir levels at trough (Ctrough) and at peak (C3h) were measured monthly. Ganciclovir exposure (AUC0-24) was estimated using Bayesian non-linear mixed-effect modelling (NONMEM) and compared between 3 groups of patients according to their kidney function: GFRMDRD 26-39 mL/min (Group 1), GFRMDRD 40-59 mL/min (Group 2) and GFRMDRD 60-90 mL/min (Group 3). CMV DNAemia was assessed during and after prophylaxis using PCR. Results: Thirty-six patients received 450 mg daily of valganciclovir for 3 months. Median ganciclovir C3h was 3.9 mg/L (range: 1.3-7.1) and Ctrough was 0.4 mg/L (range 0.1-2.7). Median (range) AUC0-24 of ganciclovir was 59.3 mg.h/L (39.0-85.3) in Group 1 patients, 35.8 mg.h/L (24.9-55.8) in Group 2 patients and 29.6 mg.h/L (22.0- 43.2) in Group 3 patients (p<0.001). Anemia was more common in Group 1 patients compared to patients on the other groups (p=0.01). No differences in other adverse events according to ganciclovir exposure were observed. CMV DNAemia was not detected during prophylaxis. After discontinuing prophylaxis, CMV DNAemia was seen in 8/34 patients (23.5%) and 4/36 patients (11%) developed CMV disease. Conclusion: A routine dosage of valganciclovir achieved plasma levels of ganciclovir in patients with GFR>60 mL/min similar to those previously reported using oral ganciclovir. A daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.
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Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.
Resumo:
Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumour (GIST). However, the treatment must be taken indefinitely and is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene), and is also bound to the alpha1-acid glycoprotein (AAG) in plasma. Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations were measured in 59 patients receiving Glivec® at diverse dosage regimens, using a validated chromatographic method developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one-compartment model with first-order absorption described the data appropriately, with an average apparent clearance of 12.4 l/h, a volume of distribution of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T and the AAG phenotype appears to modulate the disposition of imatinib. Large inter-individual variability (CV %) remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen. This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help in individualising the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.
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AIM: This study aims to investigate the clinical and demographic factors influencing gentamicin pharmacokinetics in a large cohort of unselected premature and term newborns and to evaluate optimal regimens in this population. METHODS: All gentamicin concentration data, along with clinical and demographic characteristics, were retrieved from medical charts in a Neonatal Intensive Care Unit over 5 years within the frame of a routine therapeutic drug monitoring programme. Data were described using non-linear mixed-effects regression analysis ( nonmem®). RESULTS: A total of 3039 gentamicin concentrations collected in 994 preterm and 455 term newborns were included in the analysis. A two compartment model best characterized gentamicin disposition. The average parameter estimates, for a median body weight of 2170 g, were clearance (CL) 0.089 l h(-1) (CV 28%), central volume of distribution (Vc ) 0.908 l (CV 18%), intercompartmental clearance (Q) 0.157 l h(-1) and peripheral volume of distribution (Vp ) 0.560 l. Body weight, gestational age and post-natal age positively influenced CL. Dopamine co-administration had a significant negative effect on CL, whereas the influence of indomethacin and furosemide was not significant. Both body weight and gestational age significantly influenced Vc . Model-based simulations confirmed that, compared with term neonates, preterm infants need higher doses, superior to 4 mg kg(-1) , at extended intervals to achieve adequate concentrations. CONCLUSIONS: This observational study conducted in a large cohort of newborns confirms the importance of body weight and gestational age for dosage adjustment. The model will serve to set up dosing recommendations and elaborate a Bayesian tool for dosage individualization based on concentration monitoring.
Resumo:
Manuel O, Pascual M, Perrottet N, Lamoth F, Venetz J-P, Decosterd LA, Buclin T, Meylan PR. Ganciclovir exposure under a 450 mg daily dosage of valganciclovir for cytomegalovirus prevention in kidney transplantation: a prospective study. Clin Transplant 2010: 24: 794-800. Abstract: This prospective study aimed at determining the ganciclovir exposure observed under a daily dosage of 450 mg valganciclovir routinely applied to kidney transplant recipients with a GFR above 25 mL/min at risk for cytomegalovirus (CMV) disease. Ganciclovir levels at trough (C(trough) ) and at peak (C(3 h) ) were measured monthly. Ganciclovir exposure (area under the curve [AUC(0-24) ]) was estimated using Bayesian non-linear mixed-effect modeling (NONMEM). Thirty-six patients received 450 mg of valganciclovir daily for three months. Median ganciclovir C(3 h) was 3.9 mg/L (range: 1.3-7.1), and C(trough) was 0.4 mg/L (range 0.1-2.7). Median AUC(0-24) of ganciclovir was 59.3 mg h/L (39.0-85.3) in patients with GFR(MDRD) 26-39 mL/min, 35.8 mg h/L (24.9-55.8) in patients with GFR(MDRD) 40-59 mL/min, and 29.6 mg h/L (22.0-43.2) in patients with GFR(MDRD) ≥ 60 mL/min. No major differences in adverse events according to ganciclovir exposure were observed. CMV viremia was not detected during prophylaxis. After discontinuing prophylaxis, CMV viremia was seen in 8/36 patients (22%), and 4/36 patients (11%) developed CMV disease. Ganciclovir exposure after administration of valganciclovir 450 mg daily in recipients with GFR ≥60 mL/min was comparable to those previously reported with oral ganciclovir. A routine daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.
Resumo:
Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukemia (CML) and gastrointestinal stromal tumor (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P-glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualization. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after the latest dose, were measured in 59 patients receiving Glivec at diverse regimens, using a validated HPLC-UV method developed for this study. The results were analyzed by non-linear mixed effect modeling (NONMEM). A one-compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. At present, only the MDR1 polymorphism has been assessed and seems to affect the pharmacokinetic parameters of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40 %) and distribution volume (71 %). Together with intra-patient variability (34 %), this translates into an 8-fold width of the 90 %-prediction interval of plasma concentrations expected under a fixed dosing regimen. This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring program for imatinib. It may help to individualize the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.
Resumo:
Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastro-intestinal stromal tumour (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occur in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after latest dose, were measured in 59 patients receiving Glivec® at diverse regimens, using a validated chromatographic method (HPLC-UV) developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one- compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T appears to affect the disposition of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen ! This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help to individualise the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.
Resumo:
Context There are no evidence syntheses available to guide clinicians on when to titrate antihypertensive medication after initiation. Objective To model the blood pressure (BP) response after initiating antihypertensive medication. Data sources electronic databases including Medline, Embase, Cochrane Register and reference lists up to December 2009. Study selection Trials that initiated antihypertensive medication as single therapy in hypertensive patients who were either drug naive or had a placebo washout from previous drugs. Data extraction Office BP measurements at a minimum of two weekly intervals for a minimum of 4 weeks. An asymptotic approach model of BP response was assumed and non-linear mixed effects modelling used to calculate model parameters. Results and conclusions Eighteen trials that recruited 4168 patients met inclusion criteria. The time to reach 50% of the maximum estimated BP lowering effect was 1 week (systolic 0.91 weeks, 95% CI 0.74 to 1.10; diastolic 0.95, 0.75 to 1.15). Models incorporating drug class as a source of variability did not improve fit of the data. Incorporating the presence of a titration schedule improved model fit for both systolic and diastolic pressure. Titration increased both the predicted maximum effect and the time taken to reach 50% of the maximum (systolic 1.2 vs 0.7 weeks; diastolic 1.4 vs 0.7 weeks). Conclusions Estimates of the maximum efficacy of antihypertensive agents can be made early after starting therapy. This knowledge will guide clinicians in deciding when a newly started antihypertensive agent is likely to be effective or not at controlling BP.
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Introduction Women with Chagas disease receiving treatment with nifurtimox are discouraged from breast feeding. Many patients who would receive treatment with nifurtimox live in extreme poverty, have limited access to resources such as clean water and baby formula and may not have safe alternatives to breast milk. Aim We aimed to estimate, using limited available pharmacokinetics data, potential infant exposure to nifurtimox through breast milk. Methods Original nifurtimox plasma concentrations were obtained from published studies. Pharmacokinetic parameters were estimated using non-linear mixed-effect modelling with NONMEM V.VI. A total of 1000 nifurtimox plasma-concentration profiles were simulated and used to calculate the amount of drug that an infant would be exposed to, if breast fed 150 ml/kg/day. Results Breast milk concentrations on the basis of peak plasma levels (1361 ng/ml) and milk-plasma ratio were estimated. We calculated infant nifurtimox exposure of a breastfed infant of a mother treated with this drug to be below 10% of the maternal weight-adjusted dose, even if milk-plasma ratio were overestimated. Simulation led to similar estimates. Discussion Risk for significant infant exposure to nifurtimox through breast milk seems small and below the level of exposure of infants with Chagas disease receiving nifurtimox treatment. This potential degree of exposure may not justify discontinuation of breast feeding.
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INTRODUCTION: Osteoset(®) T is a calcium sulphate void filler containing 4% tobramycin sulphate, used to treat bone and soft tissue infections. Despite systemic exposure to the antibiotic, there are no pharmacokinetic studies in humans published so far. Based on the observations made in our patients, a model predicting tobramycin serum levels and evaluating their toxicity potential is presented. METHODS: Following implantation of Osteoset(®) T, tobramycin serum concentrations were monitored systematically. A pharmacokinetic analysis was performed using a non-linear mixed effects model based on a one compartment model with first-degree absorption. RESULTS: Data from 12 patients treated between October 2006 and March 2008 were analysed. Concentration profiles were consistent with the first-order slow release and single-compartment kinetics, whilst showing important variability. Predicted tobramycin serum concentrations depended clearly on both implanted drug amount and renal function. DISCUSSION AND CONCLUSION: Despite the popularity of aminoglycosides for local antibiotic therapy, pharmacokinetic data for this indication are scarce, and not available for calcium sulphate as carrier material. Systemic exposure to tobramycin after implantation of Osteoset(®) T appears reassuring regarding toxicity potential, except in case of markedly impaired renal function. We recommend in adapting the dosage to the estimated creatinine clearance rather than solely to the patient's weight.