The Experts below are selected from a list of 114330 Experts worldwide ranked by ideXlab platform
Mary H H Ensom - One of the best experts on this subject based on the ideXlab platform.
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A Systematic Review of Limited Sampling Strategies for Platinum Agents Used in Cancer Chemotherapy
Clinical Pharmacokinetics, 2007Co-Authors: Lillian S L Ting, Mary H H EnsomAbstract:Despite evidence in the literature suggesting that a strong correlation exists between the pharmacokinetic parameters and pharmacodynamic effect of anticancer agents, many of these agents are still dosed by body surface area. Therapeutic drug monitoring with the aim of pharmacokinetic-guided dosing would not only maintain target concentrations associated with efficacy but may potentially minimise the likelihood of dose-related systemic toxicities. The pharmacokinetic parameter that displays the best correlation with the pharmacodynamics of anticancer drugs is the area under the plasma concentration-time curve (AUC). However, accurate determination of the AUC requires numerous blood samples over an extended interval, which is not feasible in clinical practice. Therefore, limited Sampling Strategies (LSSs) have been proposed as a means to accurately and precisely estimate pharmacokinetic parameters with a minimal number of blood samples. LSSs have been developed for many drugs, particularly ciclosporin and other immunosuppressants, as well as for certain anticancer drugs. This systematic review evaluates LSSs developed for the platinum compounds and categorises 18 pertinent citations according to criteria adapted from the US Preventive Services Task Force. Thirteen citations (four level I, six level II-1, three level II-2) pertained to LSSs for carboplatin, four citations (one level II-1, one level II-2, two level III) to cisplatin LSSs, and one citation (level II-2) to nedaplatin. Based on the current evidence, it appears that LSSs may be useful for pharmacokinetic-guided dosage adjustments of carboplatin in both adults and children with cancer. Although some validation studies suggest that LSSs can be extended to different cancer populations or different chemotherapy regimens, other studies dispute this finding. Although the use of LSSs to predict the pharmacokinetic parameters of cisplatin and nedaplatin appear promising, the quality of evidence from published studies does not support routine implementation at this time. LSSs represent one approach in which clinicians can make specific dosage adjustments for individual patients to optimise outcomes. However, the limitations of these Strategies must also be taken into consideration. There is also a need for prospective studies to demonstrate that application of LSSs for platinum agents ultimately improves patient response and decreases systemic toxicities.
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beyond cyclosporine a systematic review of limited Sampling Strategies for other immunosuppressants
Therapeutic Drug Monitoring, 2006Co-Authors: Lillian S L Ting, Eric Villeneuve, Mary H H EnsomAbstract:Therapeutic drug monitoring has gained much attention in the management of immunosuppressive therapy. Area under the plasma drug concentration-time curve (AUC) is the pharmacokinetic (PK) parameter most commonly used to assess total exposure to a drug. However, estimation of AUC requires multiple blood samples throughout the dosing period, which is often inconvenient and expensive. Limited Sampling Strategies (LSSs) are therefore developed to estimate AUC and other PK parameters accurately and precisely while minimizing the number of blood samples needed. This greatly reduces costs, labor and inconvenience for both patients and clinical staff. In the therapeutic management of solid organ transplantation, LSSs for cyclosporine are commonplace and have been extensively reviewed. Thus, this systematic review paper focuses on other immunosuppressive agents and categorizes the 24 pertinent citations according to the U.S. Preventive Services Task Force rating scale. Thirteen articles (3 level I, 1 level II-1, 2 level II-2, and 7 level III) involved LSSs for mycophenolate, 7 citations (1 level I and 6 level III) for tacrolimus (TAC), and 3 citations (all level III) for other drugs (sirolimus) or multiple drugs. The 2 main approaches to establishing LSSs, multiple regression and Bayesian analyses, are also reviewed. Important elements to consider for future LSS studies, including proper validation of LSSs, convenient Sampling times, and application of LSSs to the appropriate patient population and drug formulation are discussed. Limited Sampling Strategies are a useful tool to help clinicians make decisions on drug therapy. However, patients' pathophysiology, environmental and genetic factors, and pharmacologic response to therapy, in conjunction with PK profiling tools such as LSSs, should be considered collectively for optimal therapy management.
Shivendu Shivendu - One of the best experts on this subject based on the ideXlab platform.
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managing piracy pricing and Sampling Strategies for digital experience goods in vertically segmented markets
Information Systems Research, 2005Co-Authors: Ramnath K Chellappa, Shivendu ShivenduAbstract:Digital goods lend themselves to versioning but also suffer from piracy losses. This paper develops a pricing model for digital experience goods in a segmented market and explores the optimality of Sampling as a piracy-mitigating strategy. Consumers are aware of the true fit of an experience good to their tastes only after consumption, and as piracy offers an additional (albeit illegal) consumption opportunity, traditional segmentation findings from economics and Sampling recommendations from marketing, need to be revisited. We develop a two-stage model of piracy for a market where consumers are heterogeneous in their marginal valuation for quality and their moral costs. In our model, some consumers pirate the product in the first stage allowing them to update their fit-perception that may result in re-evaluation of their buying/pirating decision in the second stage. We recommend distinct pricing and Sampling Strategies for underestimated and overestimated products and suggest that any potential benefits of piracy can be internalized through product Sampling. Two counterintuitive results stand out. First, piracy losses are more severe for products that do not live up to their hype rather than for those that have been undervalued in the market, thus requiring a greater deterrence investment for the former, and second, unlike physical goods where Sampling is always beneficial for underestimated products, Sampling for digital goods is optimal only under narrowly defined circumstances due to the price boundaries created by both piracy and segmentation.
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managing piracy pricing and Sampling Strategies for digital experience goods in vertically segmented markets
2003Co-Authors: Ramnath K Chellappa, Shivendu ShivenduAbstract:This paper models the pricing of digital experience goods such as online video in a vertically segmented market under threat of piracy. By definition consumers know the true fit of an experience good only after they have consumed it and piracy offers an illegal consumption method. We develop a two-stage model of piracy where some consumers pirate in the first stage thus updating their perception of a product's fit while deciding to keep the pirated copy or buy a legitimate one in the second stage. Our results show that the effect of piracy can be mitigated by suitable pricing Strategies and some externality benefits of piracy can be internalized through product Sampling. Counter to intuition, we show that losses due to piracy are more severe for products that don't live up to their hype rather than for products that tend to be valued in the market, thus requiring a greater investment in deterrence for the former. Further, our analysis points out that Sampling Strategies are optimal only under narrowly defined conditions for vertically segmented digital experience products, unlike physical goods where Sampling is always beneficial when valued attributes have been underestimated by consumers.
Rachel Ward - One of the best experts on this subject based on the ideXlab platform.
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stable and robust Sampling Strategies for compressive imaging
IEEE Transactions on Image Processing, 2014Co-Authors: Felix Krahmer, Rachel WardAbstract:In many signal processing applications, one wishes to acquire images that are sparse in transform domains such as spatial finite differences or wavelets using frequency domain samples. For such applications, overwhelming empirical evidence suggests that superior image reconstruction can be obtained through variable density Sampling Strategies that concentrate on lower frequencies. The wavelet and Fourier transform domains are not incoherent because low-order wavelets and low-order frequencies are correlated, so compressive sensing theory does not immediately imply Sampling Strategies and reconstruction guarantees. In this paper, we turn to a more refined notion of coherence-the so-called local coherence-measuring for each sensing vector separately how correlated it is to the sparsity basis. For Fourier measurements and Haar wavelet sparsity, the local coherence can be controlled and bounded explicitly, so for matrices comprised of frequencies sampled from a suitable inverse square power-law density, we can prove the restricted isometry property with near-optimal embedding dimensions. Consequently, the variable-density Sampling strategy we provide allows for image reconstructions that are stable to sparsity defects and robust to measurement noise. Our results cover both reconstruction by l1-minimization and total variation minimization. The local coherence framework developed in this paper should be of independent interest, as it implies that for optimal sparse recovery results, it suffices to have bounded average coherence from sensing basis to sparsity basis-as opposed to bounded maximal coherence-as long as the Sampling strategy is adapted accordingly.
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beyond incoherence stable and robust Sampling Strategies for compressive imaging
2012Co-Authors: Felix Krahmer, Rachel WardAbstract:In many signal processing applications, one wishes to acquire images that are sparse in transform domains such as spatial finite differences or wavelets using frequency domain samples. For such applications, overwhelming empirical evidence suggests that superior image reconstruction can be obtained through variable density Sampling Strategies that concentrate on lower frequencies. The wavelet and Fourier transform domains are not incoherent because low-order wavelets and low-order frequencies are correlated, so compressed sensing theory does not immediately imply Sampling Strategies and reconstruction guarantees. In this paper we turn to a more refined notion of coherence – the so-called local coherence – measuring for each sensing vector separately how correlated it is to the sparsity basis. For Fourier measurements and Haar wavelet sparsity, the local coherence can be controlled, so for matrices comprised of frequencies sampled from suitable power-law densities, we can prove the restricted isometry property with near-optimal embedding dimensions. Consequently, the variable-density Sampling Strategies we provide — which are independent of the ambient dimension up to logarithmic factors — allow for image reconstructions that are stable to sparsity defects and robust to measurement noise. Our results cover both reconstruction by `1-minimization and by total variation minimization.
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stable and robust Sampling Strategies for compressive imaging
arXiv: Computer Vision and Pattern Recognition, 2012Co-Authors: Felix Krahmer, Rachel WardAbstract:In many signal processing applications, one wishes to acquire images that are sparse in transform domains such as spatial finite differences or wavelets using frequency domain samples. For such applications, overwhelming empirical evidence suggests that superior image reconstruction can be obtained through variable density Sampling Strategies that concentrate on lower frequencies. The wavelet and Fourier transform domains are not incoherent because low-order wavelets and low-order frequencies are correlated, so compressive sensing theory does not immediately imply Sampling Strategies and reconstruction guarantees. In this paper we turn to a more refined notion of coherence -- the so-called local coherence -- measuring for each sensing vector separately how correlated it is to the sparsity basis. For Fourier measurements and Haar wavelet sparsity, the local coherence can be controlled and bounded explicitly, so for matrices comprised of frequencies sampled from a suitable inverse square power-law density, we can prove the restricted isometry property with near-optimal embedding dimensions. Consequently, the variable-density Sampling strategy we provide allows for image reconstructions that are stable to sparsity defects and robust to measurement noise. Our results cover both reconstruction by $\ell_1$-minimization and by total variation minimization. The local coherence framework developed in this paper should be of independent interest in sparse recovery problems more generally, as it implies that for optimal sparse recovery results, it suffices to have bounded \emph{average} coherence from sensing basis to sparsity basis -- as opposed to bounded maximal coherence -- as long as the Sampling strategy is adapted accordingly.
Saeed Rezaee - One of the best experts on this subject based on the ideXlab platform.
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development and validation of limited Sampling Strategies for estimation of cyclosporine area under the concentration time curve in hematopoietic stem cell transplant patients
Therapeutic Drug Monitoring, 2011Co-Authors: Molouk Hadjibabaie, Iman Vazirian, Masoud Iravani, Seyed Asadollah Moosavi, Kamran Alimoghaddam, Ardeshir Ghavamzadeh, Saeed RezaeeAbstract:Abstract:The aim of this study was to develop and validate limited Sampling Strategies for accurately predicting 12-hour area under the concentration–time curve (AUC0–12 h) to provide a practical method for more precise therapeutic drug monitoring of cyclosporine A in stem cell transplant patients.
Kate L Baker - One of the best experts on this subject based on the ideXlab platform.
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environmental and spatial characterisation of bacterial community composition in soil to inform Sampling Strategies
Soil Biology & Biochemistry, 2009Co-Authors: Kate L Baker, Silke Langenheder, Graeme W Nicol, Dean Ricketts, K Killham, Colin D Campbell, James I ProsserAbstract:Soil physicochemical properties and microbial communities are highly heterogeneous and vary widely over spatial scales, necessitating careful consideration of Sampling Strategies to provide representative and reproducible soil samples across field sites. To achieve this, the study aimed to establish appropriate Sampling methodology and to determine links between the variability of parameters, utilising two Sampling Strategies. The first (design 1) involved extracting 25 cores from random locations throughout the field and pooling them into five sets of five cores. The second (design 2) involved a further 25 cores within five 1 m 2 sub-plots. Sub-samples from each sub-plot were pooled in order to determine between and within sub-plot variability. All samples were analysed independently and as pooled sub-samples. Results indicate that pooling spatially separated samples significantly reduced the variability in pH, compared to individual samples. Pooling samples from a small area resulted in lower within sub-plot variability than between sub-plots for pH and bacterial community composition assessed by terminalrestriction fragment length polymorphism analysis. Following multivariate statistical analysis, a large amount of variation in community composition was explained by soil pH, which is remarkable given the relatively small size of the Sampling area and minor differences in pH. Moisture content was also important in determining bacterial communities in the random design (design 1). In the 1 m 2 sub-plot design (design 2), the spatial location of the plots explained a large degree of the variation in bacterial community composition between plots, which was due to spatial autocorrelation of pH and possible additional environmental parameters. This study emphasises the importance of Sampling design for obtaining representative samples from soil.
