105 resultados para industry concentration
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Introduction: As imatinib pharmacokinetics are highly variable, plasma levels differ largely between patients under the same dosage. Retrospective studies in chronic myeloid leukemia (CML) patients showed significant correlations between low levels and suboptimal response, as well as between high levels and poor tolerability. Monitoring of trough plasma levels, targeting 1000 μg/L and above, is thus increasingly advised. Our study was launched to assess prospectively the clinical usefulness of systematic imatinib TDM in CML patients. This preliminary analysis addresses the appropriateness of the dosage adjustment approach applied in this study, which targets the recommended trough level and allows an interval of 4-24 h after last drug intake for blood sampling. Methods: Blood samples from the first 15 patients undergoing 1st TDM were obtained 1.5-25 h after last dose. Imatinib plasma levels were measured by LC-MS/MS and the concentrations were extrapolated to trough based on a Bayesian approach using a population pharmacokinetic model. Trough levels were predicted to differ significantly from the target in 12 patients (10 <750 μg/L; 2 >1500 μg/L along with poor tolerance) and individual dose adjustments were proposed. 8 patients underwent a 2nd TDM cycle. Trough levels of 1st and 2nd TDM were compared, the sample drawn 1.5 h after last dose (during distribution phase) was excluded from the analysis. Results: Individual dose adjustments were applied in 6 patients. Observed concentrations extrapolated to trough ranged from 360 to 1832 μg/L (median 725; mean 810, CV 52%) on 1st TDM and from 720 to 1187 μg/L (median 950; mean 940, CV 18%) on 2nd TDM cycle. Conclusions: These preliminary results suggest that TDM of imatinib using a Bayesian interpretation is able to target the recommended trough level of 1000 μg/L and to reduce the considerable differences in trough level exposure between patients (with CV decreasing from 52% to 18%). While this may simplify blood collection in daily practice, as samples do not have to be drawn exactly at trough, the largest possible interval to last drug intake yet remains preferable to avoid sampling during distribution phase leading to biased extrapolation. This encourages the evaluation of the clinical benefit of a routine TDM intervention in CML patients, which the randomized Swiss I-COME trial aims to.
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BACKGROUND AND OBJECTIVE: Protease inhibitors are highly bound to orosomucoid (ORM) (alpha1-acid glycoprotein), an acute-phase plasma protein encoded by 2 polymorphic genes, which may modulate their disposition. Our objective was to determine the influence of ORM concentration and phenotype on indinavir, lopinavir, and nelfinavir apparent clearance (CL(app)) and cellular accumulation. Efavirenz, mainly bound to albumin, was included as a control drug. METHODS: Plasma and cells samples were collected from 434 human immunodeficiency virus-infected patients. Total plasma and cellular drug concentrations and ORM concentrations and phenotypes were determined. RESULTS: Indinavir CL(app) was strongly influenced by ORM concentration (n = 36) (r2 = 0.47 [P = .00004]), particularly in the presence of ritonavir (r2 = 0.54 [P = .004]). Lopinavir CL(app) was weakly influenced by ORM concentration (n = 81) (r2 = 0.18 [P = .0001]). For both drugs, the ORM1 S variant concentration mainly explained this influence (r2 = 0.55 [P = .00004] and r2 = 0.23 [P = .0002], respectively). Indinavir CL(app) was significantly higher in F1F1 individuals than in F1S and SS patients (41.3, 23.4, and 10.3 L/h [P = .0004] without ritonavir and 21.1, 13.2, and 10.1 L/h [P = .05] with ritonavir, respectively). Lopinavir cellular exposure was not influenced by ORM abundance and phenotype. Finally, ORM concentration or phenotype did not influence nelfinavir (n = 153) or efavirenz (n = 198) pharmacokinetics. CONCLUSION: ORM concentration and phenotype modulate indinavir pharmacokinetics and, to a lesser extent, lopinavir pharmacokinetics but without influencing their cellular exposure. This confounding influence of ORM should be taken into account for appropriate interpretation of therapeutic drug monitoring results. Further studies are needed to investigate whether the measure of unbound drug plasma concentration gives more meaningful information than total drug concentration for indinavir and lopinavir.
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PURPOSE: To assess tobacco, alcohol, cannabis and benzodiazepine use in methadone maintenance treatment (MMT) as potential sources of variability in methadone pharmacokinetics. METHODS: Trough plasma (R)- and (S)-methadone concentrations were measured on 77 Australian and 74 Swiss MMT patients with no additional medications other than benzodiazepines. Simple and multiple regression analyses were performed for the primary metric, plasma methadone concentration/dose. RESULTS: Cannabis and methadone dose were significantly associated with lower 24-h plasma (R)- and (S)-methadone concentrations/dose. The models containing these variables explained 14-16% and 17-25% of the variation in (R)- and (S)-methadone concentration/dose, respectively. Analysis of 61 patients using only CYP3A4 metabolised benzodiazepines showed this class to be associated with higher (R)-concentration/dose, which is consistent with a potential competitive inhibition of CYP3A4. CONCLUSION: Cannabis use and higher methadone doses in MMT could in part be a response to-or a cause of-more rapid methadone clearance. The effects of cannabis and benzodiazepines should be controlled for in future studies on methadone pharmacokinetics in MMT.
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Polychlorinated biphenyls (PCBs) are carcinogenic. Estimating PCB half-life in the body based on levels in sera from exposed workers is complicated by the fact that occupational exposure to PCBs was to commercial PCB products (such as Aroclors 1242 and 1254) comprised of varying mixtures of PCB congeners. Half-lives were estimated using sera donated by 191 capacitor manufacturing plant workers in 1976 during PCB use (1946-1977), and post-exposure (1979, 1983, and 1988). Our aims were to: (1) determine the role of covariates such as gender on the half-life estimates, and (2) compare our results with other published half-life estimates based on exposed workers. All serum PCB levels were adjusted for PCB background levels. A linear spline model with a single knot was used to estimate two separate linear equations for the first two serum draws (Equation A) and the latter two (Equation B). Equation A gave half-life estimates of 1.74 years and 6.01 years for Aroclor 1242 and Aroclor 1254, respectively. Estimates were 21.83 years for Aroclor 1242 and 133.33 years for Aroclor 1254 using Equation B. High initial body burden was associated with rapid PCB elimination in workers at or shortly after the time they were occupationally exposed and slowed down considerably when the dose reached background PCB levels. These concentration-dependent half-life estimates had a transition point of 138.57 and 34.78 ppb for Aroclor 1242 and 1254, respectively. This result will help in understanding the toxicological and epidemiological impact of exposure to PCBs in humans.
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We have recently shown that at isotopic steady state (13)C NMR can provide a direct measurement of glycogen concentration changes, but that the turnover of glycogen was not accessible with this protocol. The aim of the present study was to design, implement and apply a novel dual-tracer infusion protocol to simultaneously measure glycogen concentration and turnover. After reaching isotopic steady state for glycogen C1 using [1-(13)C] glucose administration, [1,6-(13)C(2)] glucose was infused such that isotopic steady state was maintained at the C1 position, but the C6 position reflected (13)C label incorporation. To overcome the large chemical shift displacement error between the C1 and C6 resonances of glycogen, we implemented 2D gradient based localization using the Fourier series window approach, in conjunction with time-domain analysis of the resulting FIDs using jMRUI. The glycogen concentration of 5.1 +/- 1.6 mM measured from the C1 position was in excellent agreement with concomitant biochemical determinations. Glycogen turnover measured from the rate of label incorporation into the C6 position of glycogen in the alpha-chloralose anesthetized rat was 0.7 micromol/g/h.
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PURPOSE: This study assessed whether a cycle of "routine" therapeutic drug monitoring (TDM) for imatinib dosage individualization, targeting an imatinib trough plasma concentration (C min) of 1,000 ng/ml (tolerance: 750-1,500 ng/ml), could improve clinical outcomes in chronic myelogenous leukemia (CML) patients, compared with TDM use only in case of problems ("rescue" TDM). METHODS: Imatinib concentration monitoring evaluation was a multicenter randomized controlled trial including adult patients in chronic or accelerated phase CML receiving imatinib since less than 5 years. Patients were allocated 1:1 to "routine TDM" or "rescue TDM." The primary endpoint was a combined outcome (failure- and toxicity-free survival with continuation on imatinib) over 1-year follow-up, analyzed in intention-to-treat (ISRCTN31181395). RESULTS: Among 56 patients (55 evaluable), 14/27 (52 %) receiving "routine TDM" remained event-free versus 16/28 (57 %) "rescue TDM" controls (P = 0.69). In the "routine TDM" arm, dosage recommendations were correctly adopted in 14 patients (median C min: 895 ng/ml), who had fewer unfavorable events (28 %) than the 13 not receiving the advised dosage (77 %; P = 0.03; median C min: 648 ng/ml). CONCLUSIONS: This first target concentration intervention trial could not formally demonstrate a benefit of "routine TDM" because of small patient number and surprisingly limited prescriber's adherence to dosage recommendations. Favorable outcomes were, however, found in patients actually elected for target dosing. This study thus shows first prospective indication for TDM being a useful tool to guide drug dosage and shift decisions. The study design and analysis provide an interesting paradigm for future randomized TDM trials on targeted anticancer agents.
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Introduction: Imatinib trough plasma concentrations (Cmin) have been correlated with treatment response in chronic myeloid leukemia (CML) patients. The use of Cmin monitoring for optimizing imatinib dosage (therapeutic drug monitoring [TDM]) is therefore proposed for patients with unsatisfying response or tolerance ("rescue TDM"). A cycle of "routine TDM" for dosage individualization could also be beneficial to prevent unfavorable events, yet its clinical usefulness has not been evaluated. We aimed to assess prospectively whether a "routine TDM" intervention targeting imatinib Cmin of 1000 ng/mL (tolerance, 750-1500 ng/mL) could improve efficacy, tolerance, and persistence on treatment compared with "rescue TDM" use only. Patients (or Materials) and Methods: The Swiss Imatinib COncentration Monitoring Evaluation (I-COME) study was a multicenter randomized controlled trial (ISRCTN31181395). Adult patients in chronic or accelerated phase CML receiving imatinib ≤5 years were eligible. Patients were randomly (1:1) allocated to receive "routine TDM" intervention or to serve as controls with access only to "rescue TDM". All had 1-year follow-up. The primary endpoint was a combined efficacy-safety outcome (failure- and toxicity-free survival without imatinib discontinuation), analyzed in intention-to-treat. Results: Among 56 CML recruited patients, 55 had their molecular and cytogenetic response measured. 14/27 of patients receiving "routine TDM" (52% [33%-71%]) remained event-free versus 16/28 of control patients with "rescue TDM" only (57% [39%-75%]; P=0.69). In the "routine TDM" group, dosage recommendations were adopted entirely in 50% of patients (median Cmin at study end, 895 ng/mL; CV = 33%). These patients had fewer unfavorable events (28% [5%-52%]) compared with patients not receiving the advised dosage (77% [54%-99%]; P = 0.03; median Cmin at study end, 648 ng/mL; CV = 38%). Conclusion: This first prospective target concentration intervention trial could not formally demonstrate a benefit of "routine TDM" of imatinib, especially due to a small patient number and limited prescriber's adherence to dosage recommendations. Nevertheless, the patients receiving the advised dosage more often met target concentrations and the combined outcome (efficacy, tolerance, and persistence). A cycle of routine TDM could thus be favorable, at least in patients eligible for dosage adjustment. Its usefulness should, however, be further confirmed in larger trials.
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Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.
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Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments
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Background Addressing the risks of nanoparticles requires knowledge about their hazards, which is generated progressively, but also about occupational exposure and liberation into the environment. However, currently such information is not systematically collected, therefore the risk assessment of this exposure or liberation lacks quantitative data. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate on the totality of the Swiss workforce. The goal of this study was to evaluate in a representative way the current prevalence and level of nanoparticle usage in Swiss industry, the health, safety and environment measures, and the number of potentially exposed workers. Results A representative, stratified mail survey was conducted among 1,626 clients of the Swiss National Accident Insurance Fund (SUVA). SUVA insures about 80,000 manufacturing firms, which represent 84% of all Swiss manufacturing companies. 947 companies answered the survey (58.3% response rate). Extrapolation to all Swiss manufacturing companies results in 1,309 workers (95%-confidence interval, 1,073 to 1,545) across the Swiss manufacturing sector being potentially exposed to nanoparticles in 586 companies (95%-CI: 145 to 1'027). This corresponds to 0.08% (95%-CI: 0.06% to 0.09%) of all Swiss manufacturing sector workers and to 0.6% (95%-CI: 0.2% to 1.1%) of companies. The industrial chemistry sector showed the highest percentage of companies using nanoparticles (21.2% of those surveyed) and a high percentage of potentially exposed workers (0.5% of workers in these companies), but many other important sectors also reported nanoparticles. Personal protection equipment was the predominant protection strategy. Only a minority applied specific environmental protection measures. Conclusions This is the first representative nationwide study on the prevalence of nanoparticle usage across a manufacturing sector. The information about the number of companies can be used for quantitative risk assessment. Furthermore it can help policy makers designing strategies to support companies in the responsible development of safer nanomaterial use. Noting the low prevalence of nanoparticle usage, there would still seem to be time to introduce necessary protection methods in a proactive and cost effective way in Swiss industry. But if the predicted "nano-revolution" becomes true, now is the time to take action.