| 1. |
- De Cock, Roosmarijn F W, et al.
(författare)
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A Neonatal Amikacin Covariate Model Can Be Used to Predict Ontogeny of Other Drugs Eliminated Through Glomerular Filtration in Neonates
- 2014
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Ingår i: Pharmaceutical research. - : Springer Science and Business Media LLC. - 0724-8741 .- 1573-904X. ; 31:3, s. 754-767
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSERecently, a covariate model characterizing developmental changes in clearance of amikacin in neonates has been developed using birth bodyweight and postnatal age. The aim of this study was to evaluate whether this covariate model can be used to predict maturation in clearance of other renally excreted drugs.METHODSFive different neonatal datasets were available on netilmicin, vancomycin, tobramycin and gentamicin. The extensively validated covariate model for amikacin clearance was used to predict clearance of these drugs. In addition, independent reference models were developed based on a systematic covariate analysis.RESULTSThe descriptive and predictive properties of the models developed using the amikacin covariate model were good, and fairly similar to the independent reference models (goodness-of-fit plots, NPDE). Moreover, similar clearance values were obtained for both approaches. Finally, the same covariates as in the covariate model of amikacin, i.e. birth bodyweight and postnatal age, were identified on clearance in the independent reference models.CONCLUSIONSThis study shows that pediatric covariate models may contain physiological information since information derived from one drug can be used to describe other drugs. This semi-physiological approach may be used to optimize sparse data analysis and to derive individualized dosing algorithms for drugs in children.
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| 2. |
- Duong, Janna K., et al.
(författare)
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The variability in beta-cell function in placebo-treated subjects with type 2 diabetes : application of the weight-HbA1c-insulin-glucose (WHIG) model
- 2017
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Ingår i: British Journal of Clinical Pharmacology. - : WILEY-BLACKWELL. - 0306-5251 .- 1365-2125. ; 83:3, s. 487-497
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Tidskriftsartikel (refereegranskat)abstract
- AIM The weight-glycosylated haemoglobin (HbA1C)-insulin-glucose (WHIG) model describes the effects of changes in weight on insulin sensitivity (IS) in newly diagnosed, obese subjects receiving placebo treatment. Thismodel was applied to a wider population of placebo-treated subjects, to investigate factors influencing the variability in IS and beta-cell function. METHODS The WHIG model was applied to the WHIG dataset (Study 1) and two other placebo datasets (Studies 2 and 3). Studies 2 and 3 consisted of nonobese subjects and subjects with advanced type 2 diabetes mellitus (T2DM). Body weight, fasting serum insulin (FSI), fasting plasma glucose (FPG) and HbA1c were used for nonlinear mixed-effects modelling (using NONMEM v7.2 software). Sources of interstudy variability (ISV) and potential covariates (age, gender, diabetes duration, ethnicity, compliance) were investigated. RESULTS An ISV for baseline parameters (body weight and beta-cell function) was required. The baseline beta-cell function was significantly lower in subjects with advanced T2DM (median difference: Study 2: 15.6%, P < 0.001; Study 3: 22.7%, P < 0.001) than in subjects with newly diagnosed T2DM (Study 1). A reduction in the estimated insulin secretory response in subjects with advanced T2DM was observed but diabetes duration was not a significant covariate. CONCLUSION The WHIG model can be used to describe the changes in weight, IS and beta-cell function in the diabetic population. IS remained relatively stable between subjects but a large ISV in beta-cell function was observed. There was a trend towards decreasing beta-cell responsiveness with diabetes duration, and further studies, incorporating subjects with a longer history of diabetes, are required.
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| 3. |
- Gaspar, Rogerio, et al.
(författare)
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Towards a European Strategy for Medicines Research (2014-2020) : The EUFEPS Position Paper on Horizon 2020
- 2012
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 47:5, s. 979-987
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Tidskriftsartikel (refereegranskat)abstract
- Executive summary: As to the alignment of "Horizon 2020", iris a more integrated approach to European science policy than expressed in the proposals previously drafted, and specifically considers: (i) promoting excellence in Science, (ii) establishing a sound industrial leadership and (iii) expressing an ambition to address current and future societal challenges. In this respect, the quest for a knowledge-based economy in Europe should result in proposals for industrial and employment policies that will consolidate the major European advantages in the biomedical, healthcare and pharmaceutical sectors. Horizon 2020 also provides the possibility of adopting a more flexible and simplified management route to drive European research through innovation, research and development. What should be additionally considered? Unmet medical needs, under pressure from demographic changes, await the generation of new medicines and health technologies which will evolve into a driver for a unified European policy. We believe that this should be focused on harnessing pharmaceutical knowledge for clinical use, as part of a response to accommodate patient needs and economic growth based on a robust, scientific approach. The bolder ambition for European research is to unlock key bottlenecks currently undermining European competitiveness. The historical lack of an appropriate business/innovation environment with reduced access to adequate risk finance instruments has severed the path for economic growth and industrial development. These issues are of critical importance and a solution is urgently needed to foster translation from the university to the healthcare sector through the generation and support of start-ups, spin-offs, university-industry consortia, and other platforms, which support translational research. The ultimate goal is implementation of holistic programmes: the 'bench to bedside' paradigm of medicines and other healthcare products. The European Research Council supports the basic biomedical research programmes of long term importance for development of medicines; however, fundamental research initiatives on medicines development will not be competitive in such an environment. In order to strengthen the long term outlook, we must foster innovative research within the university sector, EUFEPS proposes that a fund for such research be set up within Horizon 2020, which would be open for individual research groups and which would include Public-Public Partnerships (complementing already existing Public-Private Partnerships). How do we look for implementation? There is an established research agenda for medicines research that is globally focused, and which incorporates a cooperative model between universities and industry, facilitating integration of complex technologies. Regulatory Science will play an important role in this integration. This agenda uses tools arising from systems approaches (including discovery with systems biology and also systems pharmacology) and has the potential for providing better knowledge management, as well as technological innovation (including manufacturing). It also addresses the drive towards personalised medicines and can, with support from both public and private sectors, foster translation of knowledge to new technologies and from that, to new medicinal products and complex integrated systems. This is a part of a strategy capable of solving unmet medical needs, which would increase the quality of life of patients suffering from chronic and debilitating diseases. The instruments to allow the development of a research agenda should strengthen existing partnerships such as the IMI-JU model; allow for the creation of European-network infrastructures that can bring together existing competences with adequate European coordination, thus promoting advanced training and continuous professional development for the pharmaceutical sciences. This will be the cornerstone of a knowledge management strategy, providing education and training for healthcare professionals and scientists. A key role for EUFEPS is to help the research community to embrace these new holistic policies applied to the spectrum of pharmaceutical, medical and cognate sciences.
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| 4. |
- Stevens, Jasper, et al.
(författare)
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Mechanism-based PK-PD model for the prolactin biological system response following an acute dopamine inhibition challenge : quantitative extrapolation to humans
- 2012
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 39:5, s. 463-477
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this investigation was to develop a mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) model for the biological system prolactin response following a dopamine inhibition challenge using remoxipride as a paradigm compound. After assessment of baseline variation in prolactin concentrations, the prolactin response of remoxipride was measured following (1) single intravenous doses of 4, 8 and 16 mg/kg and (2) following double dosing of 3.8 mg/kg with different time intervals. The mechanistic PK-PD model consisted of: (i) a PK model for remoxipride concentrations in brain extracellular fluid; (ii) a pool model incorporating prolactin synthesis, storage in lactotrophs, release into- and elimination from plasma; (iii) a positive feedback component interconnecting prolactin plasma concentrations and prolactin synthesis; and (iv) a dopamine antagonism component interconnecting remoxipride brain extracellular fluid concentrations and stimulation of prolactin release. The most important findings were that the free brain concentration drives the prolactin release into plasma and that the positive feedback on prolactin synthesis in the lactotrophs, in contrast to the negative feedback in the previous models on the PK-PD correlation of remoxipride. An external validation was performed using a dataset obtained in rats following intranasal administration of 4, 8, or 16 mg/kg remoxipride. Following simulation of human remoxipride brain extracellular fluid concentrations, pharmacodynamic extrapolation from rat to humans was performed, using allometric scaling in combination with independent information on the values of biological system specific parameters as prior knowledge. The PK-PD model successfully predicted the system prolactin response in humans, indicating that positive feedback on prolactin synthesis and allometric scaling thereof could be a new feature in describing complex homeostatic mechanisms.
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| 5. |
- van Dijkman, Sven C., et al.
(författare)
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Individualized Dosing Algorithms and Therapeutic Monitoring for Antiepileptic Drugs
- 2018
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Ingår i: Clinical Pharmacology and Therapeutics. - : WILEY. - 0009-9236 .- 1532-6535. ; 103:4, s. 663-673
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Tidskriftsartikel (refereegranskat)abstract
- Pharmacokinetic (PK) models exist for most antiepileptic drugs (AEDs). Yet their use in clinical practice to assess interindividual differences and derive individualized doses has been limited. Here we show how model-based dosing algorithms can be used to ensure attainment of target exposure and improve treatment response in patients. Using simulations, different treatment scenarios were explored for 11 commonly used AEDs. For each drug, five scenarios were considered: 1) all patients receive the same dose. 2) Individual clearance (CL), as predicted by population PK models, is used to personalize treatment. 3-5) Individual CL, obtained by therapeutic drug monitoring (TDM) according to different sampling schemes, is used to personalize treatment. Attainment of steady-state target exposure was used as the performance criterion to rank each scenario. In contrast to current clinical guidelines, our results show that patient demographic and clinical characteristics should be used in conjunction with TDM to personalize the treatment of seizures.
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