| 1. |
- Baverel, Paul G., et al.
(författare)
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Dose-Exposure-Response Relationship of the Investigational Anti-Interleukin-13 Monoclonal Antibody Tralokinumab in Patients With Severe, Uncontrolled Asthma
- 2018
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Ingår i: Clinical Pharmacology and Therapeutics. - : Wiley. - 0009-9236 .- 1532-6535. ; 103:5, s. 826-835
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Tidskriftsartikel (refereegranskat)abstract
- Interleukin (IL)-13 is involved in the pathogenesis of some types of asthma. Tralokinumab is a human immunoglobulin G(4) monoclonal antibody that specifically binds to IL-13. Two placebo-controlled phase II studies (phase IIa, NCT00873860 and phase IIb, NCT01402986) have been conducted in which tralokinumab was administered subcutaneously. This investigation aimed to characterize tralokinumab's dose-exposure-response (forced expiratory volume in 1 s (FEV1)) relationship in patients with asthma and to predict the most appropriate dose for phase III. An integrated population pharmacokinetic-pharmacodynamic (PK/PD) modeling analysis was required for phase III dose selection, due to differing phase II patient populations, designs, and regimens. Analysis of combined datasets enabled the identification of tralokinumab's dose-exposure-FEV1 response relationship in patients with asthma. Near-maximal FEV1 increase was predicted at a dose of 300 mg SC once every 2 weeks (Q2W). This dose was chosen for tralokinumab in the phase III clinical development program for treatment of severe, uncontrolled asthma.
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| 2. |
- Dodds, Michael G, et al.
(författare)
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Robust population pharmacokinetic experiment design.
- 2005
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 32:1, s. 33-64
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Tidskriftsartikel (refereegranskat)abstract
- The population approach to estimating mixed effects model parameters of interest in pharmacokinetic (PK) studies has been demonstrated to be an effective method in quantifying relevant population drug properties. The information available for each individual is usually sparse. As such, care should be taken to ensure that the information gained from each population experiment is as efficient as possible by designing the experiment optimally, according to some criterion. The classic approach to this problem is to design "good" sampling schedules, usually addressed by the D-optimality criterion. This method has the drawback of requiring exact advanced knowledge (expected values) of the parameters of interest. Often, this information is not available. Additionally, if such prior knowledge about the parameters is misspecified, this approach yields designs that may not be robust for parameter estimation. In order to incorporate uncertainty in the prior parameter specification, a number of criteria have been suggested. We focus on ED-optimality. This criterion leads to a difficult numerical problem, which is made tractable here by a novel approximation of the expectation integral usually solved by stochastic integration techniques. We present two case studies as evidence of the robustness of ED-optimal designs in the face of misspecified prior information. Estimates from replicate simulated population data show that such misspecified ED-optimal designs recover parameter estimates that are better than similarly misspecified D-optimal designs, and approach estimates gained from D-optimal designs where the parameters are correctly specified.
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| 3. |
- Foracchia, Marco, et al.
(författare)
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POPED, a software for optimal experiment design in population kinetics.
- 2004
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Ingår i: Computer Methods and Programs in Biomedicine. - 0169-2607 .- 1872-7565. ; 74:1, s. 29-46
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Tidskriftsartikel (refereegranskat)abstract
- Population kinetic analysis is the methodology used to quantify inter-subject variability in kinetic studies. It entails the collection of (possibly sparse) data from dynamic experiments in a group of subjects and their quantitative interpretation by means of a mathematical model. This methodology is widely used in the pharmaceutical industry (where it is termed "pharmacokinetic population analysis") and recently it is becoming increasingly used in other areas of biomedical research. Unlike traditional kinetic studies, where the number of subjects can be quite small, population kinetic studies require large numbers of subjects. It is, therefore, of great interest to design these studies in the most efficient manner possible, to maximize the information content provided by the data. In this paper we propose an algorithm and a computer program, POPED, for the optimal design of a population kinetic experiment. In particular, the number of samples for each subject and the design of the individual sampling strategies, i.e. the number and location of the time points at which the output variable is sampled, will be considered. Among the various criteria proposed in the literature, D and ED optimality are the ones implemented in our software program, since they are the most widely used. A brief description of the techniques employed to perform design optimization is given, together with some details on their actual implementation. Some examples are then presented to show the program usage and the results provided.
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| 4. |
- Hooker, Andrew C, et al.
(författare)
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An evaluation of population D-optimal designs via pharmacokinetic simulations.
- 2003
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Ingår i: Annals of Biomedical Engineering. - 0090-6964 .- 1573-9686. ; 31:1, s. 98-111
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Tidskriftsartikel (refereegranskat)abstract
- One goal of large scale clinical trials is to determine how a drug is processed by, and cleared from, the human body [i.e., its pharmacokinetic (PK) properties] and how these PK properties differ between individuals in a population (i.e., its population PK properties). Due to the high cost of these studies and the limited amount of data (e.g., blood samples) available from each study subject, it would be useful to know how many measurements are needed and when those measurements should be taken to accurately quantify population PK model parameters means and variances. Previous studies have looked at optimal design strategies of population PK experiments by developing an optimal design for an individual study (i.e., no interindividual variability was considered in the design), and then applying that design to each individual in a population study (where interindividual variability is present). A more algorithmically and informationally intensive approach is to develop a population optimal design, which inherently includes the assessment of interindividual variability. We present a simulation-based evaluation of these two design methods based on nonlinear Gaussian population PK models. Specifically, we compute standard individual and population D-optimal designs and compare population PK model parameter estimates based on simulated optimal design measurements. Our results show that population and standard D-optimal designs are not significantly different when both designs have the same number of samples per individual. However, population optimal designs allow for sampling schedules where the number of samples per individual is less than the number of model parameters, the theoretical limit allowed in standard optimal design. These designs with a low number of samples per individual are shown to be nearly as robust in parameter estimation as standard D-optimal designs. In the limit of just one sample per individual, however, population D-optimal designs are shown to be inadequate.
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| 5. |
- Hooker, Andrew C., et al.
(författare)
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Simultaneous population optimal design for pharmacokinetic-pharmacodynamic experiments.
- 2005
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 7:4, s. E759-85
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Tidskriftsartikel (refereegranskat)abstract
- Multiple outputs or measurement types are commonly gathered in biological experiments. Often, these experiments are expensive (such as clinical drug trials) or require careful design to achieve the desired information content. Optimal experimental design protocols could help alleviate the cost and increase the accuracy of these experiments. In general, optimal design techniques ignore between-individual variability, but even work that incorporates it (population optimal design) has treated simultaneous multiple output experiments separately by computing the optimal design sequentially, first finding the optimal design for one output (eg, a pharmacokinetic [PK] measurement) and then determining the design for the second output (eg, a pharmacodynamic [PD] measurement). Theoretically, this procedure can lead to biased and imprecise results when the second model parameters are also included in the first model (as in PK-PD models). We present methods and tools for simultaneous population D-optimal experimental designs, which simultaneously compute the design of multiple output experiments, allowing for correlation between model parameters. We then apply these methods to simulated PK-PD experiments. We compare the new simultaneous designs to sequential designs that first compute the PK design, fix the PK parameters, and then compute the PD design in an experiment. We find that both population designs yield similar results in designs for low sample number experiments, with simultaneous designs being possibly superior in situations in which the number of samples is unevenly distributed between outputs. Simultaneous population D-optimality is a potentially useful tool in the emerging field of experimental design.
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| 6. |
- Keenan, Thomas M, et al.
(författare)
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Automated identification of axonal growth cones in time-lapse image sequences.
- 2006
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Ingår i: Journal of Neuroscience Methods. - : Elsevier BV. - 0165-0270 .- 1872-678X. ; 151:2, s. 232-8
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Tidskriftsartikel (refereegranskat)abstract
- The isolation and purification of axon guidance molecules has enabled in vitro studies of the effects of axon guidance molecule gradients on numerous neuronal cell types. In a typical experiment, cultured neurons are exposed to a chemotactic gradient and their growth is recorded by manual identification of the axon tip position from two or more micrographs. Detailed and statistically valid quantification of axon growth requires evaluation of a large number of neurons at closely spaced time points (e.g. using a time-lapse microscopy setup). However, manual tracing becomes increasingly impractical for recording axon growth as the number of time points and/or neurons increases. We present a software tool that automatically identifies and records the axon tip position in each phase-contrast image of a time-lapse series with minimal user involvement. The software outputs several quantitative measures of axon growth, and allows users to develop custom measurements. For, example analysis of growth velocity for a dissociated E13 mouse cortical neuron revealed frequent extension and retraction events with an average growth velocity of 0.05 +/- 0.14 microm/min. Comparison of software-identified axon tip positions with manually identified axon tip positions shows that the software's performance is indistinguishable from that of skilled human users.
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| 7. |
- Kerwin, William, et al.
(författare)
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Quantitative magnetic resonance imaging analysis of neovasculature volume in carotid atherosclerotic plaque.
- 2003
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Ingår i: Circulation. - 0009-7322 .- 1524-4539. ; 107:6, s. 851-6
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Neovasculature within atherosclerotic plaques is believed to be associated with infiltration of inflammatory cells and plaque destabilization. The aim of the present investigation was to determine whether the amount of neovasculature present in advanced carotid plaques can be noninvasively measured by dynamic, contrast-enhanced MRI.METHODS AND RESULTS: A total of 20 consecutive patients scheduled for carotid endarterectomy were recruited to participate in an MRI study. Images were obtained at 15-second intervals, and a gadolinium contrast agent was injected coincident with the second of 10 images in the sequence. The resulting image intensity within the plaque was tracked over time, and a kinetic model was used to estimate the fractional blood volume. For validation, matched sections from subsequent endarterectomy were stained with ULEX and CD-31 antibody to highlight microvessels. Finally, all microvessels within the matched sections were identified, and their total area was computed as a fraction of the plaque area. Results were obtained from 16 participants, which showed fractional blood volumes ranging from 2% to 41%. These levels were significantly higher than the histological measurements of fractional vascular area. Nevertheless, the 2 measurements were highly correlated, with a correlation coefficient of 0.80 (P<0.001).CONCLUSIONS: Dynamic contrast-enhanced MRI provides an indication of the extent of neovasculature within carotid atherosclerotic plaque. MRI therefore provides a means for prospectively studying the link between neovasculature and plaque vulnerability.
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