| 1. |
- Sohler, D, et al.
(author)
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Band-terminating states in Ag-101
- 2004
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In: Nuclear Physics, Section A. - : Elsevier BV. - 0375-9474 .- 1873-1554. ; 733:1-2, s. 37-52
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Journal article (peer-reviewed)abstract
- Excited states of the neutron deficient Ag-101 nucleus have been investigated via the Cr-50(Ni-58, 3rho1alpha) heavy-ion induced reaction at 261 meV by use of in-beam spectroscopic methods. On the basis of the measured gammagamma-cincidence relations and angular distribution ratios high-spin bands have been extended up to I-pi = 35/2(+), 45/2((-)) and (49/2(-)). The negative parity states at the highest energy have been interpreted as terminating non-collective oblate states in the framework of the Nilsson-Strutinsky cranking formalism.
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| 2. |
- Yngman, Gunnar, et al.
(author)
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An introduction of the full random effects model
- 2022
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In: CPT. - : John Wiley & Sons. - 2163-8306. ; 11:2, s. 149-160
-
Journal article (peer-reviewed)abstract
- The full random-effects model (FREM) is a method for determining covariate effects in mixed-effects models. Covariates are modeled as random variables, described by mean and variance. The method captures the covariate effects in estimated covariances between individual parameters and covariates. This approach is robust against issues that may cause reduced performance in methods based on estimating fixed effects (e.g., correlated covariates where the effects cannot be simultaneously identified in fixed-effects methods). FREM covariate parameterization and transformation of covariate data records can be used to alter the covariate-parameter relation. Four relations (linear, log-linear, exponential, and power) were implemented and shown to provide estimates equivalent to their fixed-effects counterparts. Comparisons between FREM and mathematically equivalent full fixed-effects models (FFEMs) were performed in original and simulated data, in the presence and absence of non-normally distributed and highly correlated covariates. These comparisons show that both FREM and FFEM perform well in the examined cases, with a slightly better estimation accuracy of parameter interindividual variability (IIV) in FREM. In addition, FREM offers the unique advantage of letting a single estimation simultaneously provide covariate effect coefficient estimates and IIV estimates for any subset of the examined covariates, including the effect of each covariate in isolation. Such subsets can be used to apply the model across data sources with different sets of available covariates, or to communicate covariate effects in a way that is not conditional on other covariates.
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| 3. |
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| 4. |
- Brekkan, Ari, et al.
(author)
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Sensitivity of Pegfilgrastim Pharmacokinetic and Pharmacodynamic Parameters to Product Differences in Similarity Studies
- 2019
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In: AAPS Journal. - : Springer. - 1550-7416. ; 21:85
-
Journal article (peer-reviewed)abstract
- In this work, a previously developed pegfilgrastim (PG) population pharmacokinetic-pharmacodynamic (PKPD) model was used to evaluate potential factors of importance in the assessment of PG PK and PD similarity. Absolute neutrophil count (ANC) was the modelled PD variable. A two-way cross-over study was simulated where a reference PG and a potentially biosimilar test product were administered to healthy volunteers. Differences in delivered dose amounts or potency between the products were simulated. A different baseline absolute neutrophil count (ANC) was also considered. Additionally, the power to conclude PK or PD similarity based on areas under the PG concentration-time curve (AUC) and ANC-time curve (AUEC) were calculated. Delivered dose differences between the products led to a greater than dose proportional differences in AUC but not in AUEC, respectively. A 10% dose difference from a 6 mg dose resulted in 51% and 7% differences in AUC and AUEC, respectively. These differences were more pronounced with low baseline ANC. Potency differences up to 50% were not associated with large differences in either AUCs or AUECs. The power to conclude PK similarity was affected by the simulated dose difference; with a 4% dose difference from 6 mg the power was approximately 29% with 250 subjects. The power to conclude PD similarity was high for all delivered dose differences and sample sizes.
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| 5. |
- Delattre, Isabelle K., et al.
(author)
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Population Pharmacokinetic Modeling and Optimal Sampling Strategy for Bayesian Estimation of Amikacin Exposure in Critically Ill Septic Patients
- 2010
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In: Therapeutic Drug Monitoring. - 0163-4356 .- 1536-3694. ; 32:6, s. 749-756
-
Journal article (peer-reviewed)abstract
- Because the sepsis-induced pharmacokinetic (PK) modifications need to be considered in aminoglycoside dosing, the present study aimed to develop a population PK model for amikacin (AMK) in severe sepsis and to subsequently propose an optimal sampling strategy suitable for Bayesian estimation of the drug PK parameters. Concentration-time profiles for AMK were obtained from 88 critically ill septic patients during the first 24 hours of antibiotic treatment. The population PK model was developed using a nonlinear mixed effects modeling approach. Covariate analysis included demographic data, pathophysiological characteristics, and comedication. Optimal sampling times were selected based on a robust Bayesian design criterion. Taking into account clinical constraints, a two-point sampling approach was investigated. A two-compartment model with first-order elimination best fitted the AMK concentrations. Population PK estimates were 19.2 and 9.34 L for the central and peripheral volume of distribution and 4.31 and 2.21 L/h for the intercompartmental and total body clearance. Creatinine clearance estimated using the Cockcroft-Gault equation was retained in the final model. The two optimal sampling times were 1 hour and 6 hours after onset of the drug infusion. Predictive performance of individual Bayes estimates computed using the proposed optimal sampling strategy was reported: mean prediction errors were less than 5% and root mean square errors were less than 30%. The present study confirmed the significant influence of the creatinine clearance on the PK disposition of AMK during the first hours of treatment in critically ill septic patients. Based on the population estimates, an optimal sampling strategy suitable for Bayesian estimation of the drug PK parameters was developed, meeting the need of clinical practice.
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| 6. |
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| 7. |
- Ernest II, Charles, et al.
(author)
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Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model
- 2014
-
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 41:6, s. 639-654
-
Journal article (peer-reviewed)abstract
- D-optimal designs for discrete-type responses have been derived using generalized linear mixed models, simulation based methods and analytical approximations for computing the fisher information matrix (FIM) of non-linear mixed effect models with homogeneous probabilities over time. In this work, D-optimal designs using an analytical approximation of the FIM for a dichotomous, non-homogeneous, Markov-chain phase advanced sleep non-linear mixed effect model was investigated. The non-linear mixed effect model consisted of transition probabilities of dichotomous sleep data estimated as logistic functions using piecewise linear functions. Theoretical linear and nonlinear dose effects were added to the transition probabilities to modify the probability of being in either sleep stage. D-optimal designs were computed by determining an analytical approximation the FIM for each Markov component (one where the previous state was awake and another where the previous state was asleep). Each Markov component FIM was weighted either equally or by the average probability of response being awake or asleep over the night and summed to derive the total FIM (FIMtotal). The reference designs were placebo, 0.1, 1-, 6-, 10- and 20-mg dosing for a 2- to 6-way crossover study in six dosing groups. Optimized design variables were dose and number of subjects in each dose group. The designs were validated using stochastic simulation/re-estimation (SSE). Contrary to expectations, the predicted parameter uncertainty obtained via FIMtotal was larger than the uncertainty in parameter estimates computed by SSE. Nevertheless, the D-optimal designs decreased the uncertainty of parameter estimates relative to the reference designs. Additionally, the improvement for the D-optimal designs were more pronounced using SSE than predicted via FIMtotal. Through the use of an approximate analytic solution and weighting schemes, the FIMtotal for a non-homogeneous, dichotomous Markov-chain phase advanced sleep model was computed and provided more efficient trial designs and increased nonlinear mixed-effects modeling parameter precision.
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| 8. |
- Faraj, Alan, et al.
(author)
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Model-based approaches to prospectively power pediatric pharmacokinetic trials with limited sample size
-
Other publication (other academic/artistic)abstract
- Rare disease studies in pediatric subjects are challenging due to small sample sizes. Pharmacokinetic (PK) information in pediatric subjects is important and often used for matching strategy towards adults informing pediatric development program. Prior to studying PK in children, it is important to optimize the sparse sampling schedule and show that the study is designed to estimate key PK parameters with sufficient certainty. In this work, the sampling schedule in children was optimized for marzeptacog alfa activated (MarzAA) and dalcinonacog alfa (DalcA), two drugs in development for treatment of hemophilia. Subsequently, evaluation of different model-based approaches to calculate the power to estimate clearance (CL) and volume of distribution (V) using a fixed sample size (n=24) was performed. Usage of Bayesian priors (up to 2x inflation of the adult priors) performed well (power 80 %), but with lower power with decreasing informativeness (5x and 10x inflation of the adult priors), in particular for DalcA. Reusing the full adult model or a simplified model for standalone analysis of the pediatric data did not perform well (<80% power). Fixing the adult PK parameters except for CL and V performed well when pooling adult and pediatric data (power 100 %). In general, the power to estimate V alone or CL together with V was lower than for CL, indicating that the sampling schedules were more informative for CL. Although Bayesian prior approaches were shown to perform well without need of pooling data, other approaches that require less technical expertise and no need for simplification of the adult model were found to be good alternatives when pooling of data is possible.
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| 9. |
- Faraj, Alan
(author)
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Pharmacometric models to inform dose selection and study design : Applied in hemophilia and tuberculosis
- 2024
-
Doctoral thesis (other academic/artistic)abstract
- While tuberculosis is a global pandemic, hemophilia is a rare disease which many have not heard of. Due to tuberculosis mainly being a problem in developing countries and hemophilia being a rare disease, they are not as heard of as other diseases such as cancer or metabolic diseases which are on the rise in Western societies. The quality of life for patients suffering from these diseases is notably impaired and novel drugs are warranted to further improve the treatment and management of both diseases. As market incentives are a limiting factor, it is important that the efforts that are taken to develop novel drugs are carried out in an informative manner. One strategy to incorporate as much information as possible to inform decision making in drug development is to use pharmacometric methods. Such strategies enable simultaneous analysis of different types of data that are generated during drug development programs. In this thesis, the aim was to develop and apply pharmacometric models to facilitate dose selection and study designs in clinical programs that aim at developing new drugs for tuberculosis and hemophilia. A standardized analysis approach of early clinical trials studying drugs against tuberculosis was presented including power calculations that showed the number of patients needed to detect drug effects. Such efforts are important as showing drug effect in early trials will aid decision making into significantly longer and costlier late trials. The approach was used to analyze a clinical trial studying if the current dose of meropenem can be lowered without negatively impacting drug effects and improving the already poor tolerability of the drug. The study found that lowering the dose may lower activity without any improvement of the tolerability properties. Furthermore, population pharmacokinetic models were developed for two novel hemostatic drugs in development for prophylactic and on-demand treatment of hemophilia. Based on the models, clinical trials in adult and pediatric subjects were supported. One of the trials were performed and it was showed with a model-based analysis that the new drug which is given subcutanously has similar efficacy as current intravenously given standard of care alternatives. Using the developed models, different strategies for designing pharmacokinetic trials in children was also presented. In conclusion, the work performed within this thesis has contributed to the development of new drugs against tuberculosis and hemophilia.
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| 10. |
- Faraj, Alan, et al.
(author)
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Subcutaneous Marzeptacog Alfa (Activated) for On‐Demand Treatment of Bleeding Events in Subjects With Hemophilia A or B With Inhibitors
- 2024
-
In: Clinical Pharmacology and Therapeutics. - : John Wiley & Sons. - 0009-9236 .- 1532-6535. ; 115:3, s. 498-505
-
Journal article (peer-reviewed)abstract
- Marzeptacog alfa (MarzAA) is under development for subcutaneous treatment of episodic bleeds in patients with hemophilia A/B and was studied in a phase III trial evaluating MarzAA compared with standard-of-care (SoC) for on-demand use. The work presented here aimed to evaluate MarzAA and SoC treatment of bleeding events on a standardized four-point efficacy scale (poor, fair, good, and excellent). Two continuous-time Markov modeling approaches were explored; a four-state model analyzing all four categories of bleeding improvement and a two-state model analyzing a binarized outcome (treatment failure (poor/fair), and treatment success (good/excellent)). Different covariates impacting improvement of bleeding episodes as well as a putative relationship between MarzAA exposure and improvement of bleeding episodes were evaluated. In the final four-state model, higher baseline diastolic blood pressure and higher age (> 33 years of age) were found to negatively and positively impact improvement of bleeding condition, respectively. Bleeding events occurring in knees and ankles were found to improve faster than bleeding events at other locations. The covariate effects had most impact on early treatment success (≤ 3 hours) whereas at later timepoints (> 12 hours), treatment success was similar for all patients indicating that these covariates might be clinically relevant for early treatment response. A statistically significant relationship between MarzAA zero-order absorption and improvement of bleedings (P < 0.05) were identified albeit with low precision. No statistically significant difference in treatment response between MarzAA and intravenous SoC was identified, indicating the potential of MarzAA for treatment of episodic bleeding events with a favorable subcutaneous administration route.
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| 11. |
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| 12. |
- Gao, Xindong, et al.
(author)
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Epitaxy of Ultrathin NiSi2 Films with Predetermined Thickness
- 2011
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In: Electrochemical and solid-state letters. - : The Electrochemical Society. - 1099-0062 .- 1944-8775. ; 14:7, s. H268-H270
-
Journal article (peer-reviewed)abstract
- This letter presents a proof-of-concept process for tunable, self-limiting growth of ultrathin epitaxial NiSi2 films on Si (100). The process starts with metal sputter-deposition, followed by wet etching and then silicidation. By ionizing a fraction of the sputtered Ni atoms and biasing the Si substrate, the amount of Ni atoms incorporated in the substrate after wet etching can be controlled. As a result, the thickness of the NiSi2 films is increased from 4.7 to 7.2 nm by changing the nominal substrate bias from 0 to 600 V. The NiSi2 films are characterized by a specific resistivity around 50 mu Omega cm.
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| 13. |
- Gennemark, Peter, 1974, et al.
(author)
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Optimal Design in Population Kinetic Experiments by Set-Valued Methods
- 2011
-
In: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 13:4, s. 495-507
-
Journal article (peer-reviewed)abstract
- We propose a new method for optimal experimental design of population pharmacometric experiments based on global search methods using interval analysis; all variables and parameters are represented as intervals rather than real numbers. The evaluation of a specific design is based on multiple simulations and parameter estimations. The method requires no prior point estimates for the parameters, since the parameters can incorporate any level of uncertainty. In this respect, it is similar to robust optimal design. Representing sampling times and covariates like doses by intervals gives a direct way of optimizing with rigorous sampling and dose intervals that can be useful in clinical practice. Furthermore, the method works on underdetermined problems for which traditional methods typically fail.
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| 14. |
- Geroldinger, Martin, et al.
(author)
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Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials
- 2023
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In: Orphanet Journal of Rare Diseases. - : BioMed Central (BMC). - 1750-1172. ; 18:1
-
Journal article (peer-reviewed)abstract
- BackgroundRecommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set from epidermolysis bullosa research to build recommendations for count, binary, and ordinal outcome variables. For this purpose, parametric (model averaging), semiparametric (generalized estimating equations type [GEE-like]) and nonparametric (generalized pairwise comparisons [GPC] and a marginal model implemented in the R package nparLD) methods were chosen by an international consortium of statisticians.ResultsIt was found that there is no uniformly best method for the aforementioned types of outcome variables, but in particular situations, there are methods that perform better than others. Especially if maximizing power is the primary goal, the prioritized unmatched GPC method was able to achieve particularly good results, besides being appropriate for prioritizing clinically relevant time points. Model averaging led to favorable results in some scenarios especially within the binary outcome setting and, like the GEE-like semiparametric method, also allows for considering period and carry-over effects properly. Inference based on the nonparametric marginal model was able to achieve high power, especially in the ordinal outcome scenario, despite small sample sizes due to separate testing of treatment periods, and is suitable when longitudinal and interaction effects have to be considered.ConclusionOverall, a balance has to be found between achieving high power, accounting for cross-over, period, or carry-over effects, and prioritizing clinically relevant time points.
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| 15. |
- Gorska, M, et al.
(author)
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Spectroscopy of the T-z=1 nuclei close to Sn-100
- 1997
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In: Acta Physica Polonica B. - 0587-4254 .- 1509-5770. ; 28:1-2, s. 303-307
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Journal article (peer-reviewed)abstract
- The two nuclei Cd-98 and Sn-102, closest neighbours of Sn-100, have been studied with a recoil catcher setup, following the reactions: Ni-58(Ti-46, alpha 2n)Cd-98 and Ni-58(Cr-50, alpha 2n)Sn-102. Long lived isomeric states were measured in Cd-98 I-pi = (8+), t(1/2) = 0.48(8) mu s and in Sn-102 I-pi = (6(+)) with t(1/2) = 1.0(6) mu s. The proposed experimental level schemes of the isomeric decay are presented and compared to the shell model predictions.
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| 16. |
- Guastalla, G., et al.
(author)
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Analysis and Results of the 104Sn Coulomb Excitation Experiment
- 2014
-
In: Journal of Physics: Conference Series. - : IOP Publishing. - 1742-6596 .- 1742-6588. ; 533:1
-
Conference paper (peer-reviewed)abstract
- The analysis of the Coulomb excitation experiment conducted on 104Sn required a strict selection of the data in order to reduce the large background present in the gamma-ray energy spectra and identify the gamma-ray peak corresponding to the Coulomb excitation events. As a result the B(E2; 0 + -> 2+) value could be extracted, which established the downward trend towards 100Sn and therefore the robustness of the N=Z=50 core against quadrupole excitations.
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| 17. |
- Guastalla, G., et al.
(author)
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Coulomb Excitation of Sn-104 and the Strength of the Sn-100 Shell Closure
- 2013
-
In: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 110:17, s. 172501-
-
Journal article (peer-reviewed)abstract
- A measurement of the reduced transition probability for the excitation of the ground state to the first 2(+) state in Sn-104 has been performed using relativistic Coulomb excitation at GSI. Sn-104 is the lightest isotope in the Sn chain for which this quantity has been measured. The result is a key point in the discussion of the evolution of nuclear structure in the proximity of the doubly magic nucleus Sn-100. The value B(E2; 0(+) -> 2(+)) = 0.10(4) e(2)b(2) is significantly lower than earlier results for Sn-106 and heavier isotopes. The result is well reproduced by shell model predictions and therefore indicates a robust N = Z = 50 shell closure.
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| 18. |
- Harisubramanyabalaji, Subramani Palanisamy, et al.
(author)
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Improving Image Classification Robustness Using Predictive Data Augmentation
- 2018
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In: Computer Safety, Reliability, and Security. - Cham : Springer. - 9783319992280 - 9783319992297 ; , s. 548-561
-
Conference paper (peer-reviewed)abstract
- Safer autonomous navigation might be challenging if there is a failure in sensing system. Robust classifier algorithm irrespective of camera position, view angles, and environmental condition of an autonomous vehicle including different size & type (Car, Bus, Truck, etc.) can safely regulate the vehicle control. As training data play a crucial role in robust classification of traffic signs, an effective augmentation technique enriching the model capacity to withstand variations in urban environment is required. In this paper, a framework to identify model weakness and targeted augmentation methodology is presented. Based on off-line behavior identification, exact limitation of a Convolutional Neural Network (CNN) model is estimated to augment only those challenge levels necessary for improved classifier robustness. Predictive Augmentation (PA) and Predictive Multiple Augmentation (PMA) methods are proposed to adapt the model based on acquired challenges with a high numerical value of confidence. We validated our framework on two different training datasets and with 5 generated test groups containing varying levels of challenge (simple to extreme). The results show impressive improvement by 5-20% in overall classification accuracy thereby keeping their high confidence.
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| 19. |
- Hennig, Stefanie, et al.
(author)
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Application of the Optimal Design Approach to Improve a Pretransplant Drug Dose Finding Design for Ciclosporin
- 2012
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In: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 52:3, s. 347-360
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Journal article (peer-reviewed)abstract
- A time and sampling intensive pretransplant test dose design was to be reduced, but at the same time optimized so that there was no loss in the precision of predicting the individual pharmacokinetic (PK) estimates of posttransplant dosing. The following variables were optimized simultaneously: sampling times, ciclosporin dose, time of second dose, infusion duration, and administration order, using a published ciclosporin population PK model as prior information. The original design was reduced from 22 samples to 6 samples/patient and both doses (intravenous oral) were administered within 8 hours. Compared with the prior information given by the published ciclosporin population PK model, the expected standard deviations (SDs) of the individual parameters for clearance and bioavailability could be reduced by, on average, 40% under the optimized sparse designs. The gain of performing the original rich design compared with the optimal reduced design, considering the standard errors of the parameter estimates, was found to be minimal. This application demonstrates, in a practical clinical scenario, how optimal design techniques may be used to improve diagnostic procedures given available software and methods.
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| 20. |
- Hennig, Stefanie, et al.
(author)
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Trial treatment length optimization with an emphasis on disease progression studies
- 2009
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In: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 49:3, s. 323-335
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Journal article (peer-reviewed)abstract
- Optimal design has been used in the past mainly to optimize sampling schedules for clinical trials. Optimization on design variables other than sampling times has been published in the literature only once before. This study shows, as an example, optimization on the length of treatment periods to obtain reliable estimates of drug effects on longterm disease progression studies. Disease progression studies are high in cost, effort, and time; therefore, optimization of treatment length is highly recommended to avoid failure or loss of information. Results are provided for different drug effects (eg, protective and symptomatic) and for different lengths of studies and sampling schedules. The merits of extending the total study length versus inclusion of more samples per participants are investigated. The authors demonstrate that if no observations are taken during the washout period, a trial can lose up to 40% of its efficiency. Furthermore, when optimization of treatment length is performed using multiple possible drug effect models simultaneously, these studies show high power in discriminating between different drug effect models.
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| 21. |
- Juul, Rasmus Vestergaard, et al.
(author)
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A Pharmacokinetic-Pharmacodynamic Model of Morphine Exposure and Subsequent Morphine Consumption in Postoperative Pain
- 2016
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In: Pharmaceutical research. - : Springer Science and Business Media LLC. - 0724-8741 .- 1573-904X. ; 33:5, s. 1093-1103
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Journal article (peer-reviewed)abstract
- To characterize the pharmacokinetic-pharmacodynamic (PK-PD) relationship between exposure of morphine and subsequent morphine consumption and to develop simulation tools for model validation. Dose, formulation and time of morphine administration was available from a published study in 63 patients receiving intravenous, oral immediate release or oral controlled release morphine on request after hip surgery. The PK-PD relationship between predicted exposure of morphine and morphine consumption was modeled using repeated time to event (RTTE) modeling in NONMEM. To validate the RTTE model, a visual predictive check method was developed with simulated morphine consumption given the exposure of preceding morphine administration. The probability of requesting morphine was found to be significantly related to the exposure of morphine as well as night/day. Oral controlled release morphine was more effective than intravenous and oral immediate release formulations at equivalent average concentrations. Maximum effect was obtained for 8 h by oral controlled release doses a parts per thousand yenaEuro parts per thousand 15 mg, where probability of requesting a new dose was reduced to 20% for a typical patient. This study demonstrates the first quantitative link between exposure of morphine and subsequent morphine consumption and introduces an efficient visual predictive check approach with simulation of adaptive dosing.
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| 22. |
- Juul, Rasmus Vestergaard, et al.
(author)
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Analysis of opioid consumption in clinical trials : a simulation based analysis of power of four approaches
- 2017
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In: Journal of Pharmacokinetics and Pharmacodynamics. - : SPRINGER/PLENUM PUBLISHERS. - 1567-567X .- 1573-8744. ; 44:4, s. 325-333
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Journal article (peer-reviewed)abstract
- Inconsistent trial design and analysis is a key reason that few advances in postoperative pain management have been made from clinical trials analyzing opioid consumption data. This study aimed to compare four different approaches to analyze opioid consumption data. A repeated time-to-event (RTTE) model in NONMEM was used to simulate clinical trials of morphine consumption with and without a hypothetical adjuvant analgesic in doses equivalent to 15-62% reduction in morphine consumption. Trials were simulated with duration of 24-96 h. Monte Carlo simulation and re-estimation were performed to determine sample size required to demonstrate efficacy with 80% power using t test, Mann-Whitney rank sum test, time-to-event (TTE) modeling and RTTE modeling. Precision of efficacy estimates for RTTE models were evaluated in 500 simulations. A sample size of 50 patients was required to detect 37% morphine sparing effect with at least 80% power in a 24 h trial with RTTE modeling whereas the required sample size was 200 for Mann-Whitney, 180 for t-test and 76 for TTE models. Extending the trial duration from 24 to 96 h reduced the required sample size by 3.1 fold with RTTE modeling. Precise estimate of potency was obtained with a RTTE model accounting for both morphine effects and time-varying covariates on opioid consumption. An RTTE analysis approach proved better suited for demonstrating efficacy of opioid sparing analgesics than traditional statistical tests as a lower sample size was required due the ability to account for time-varying factors including PK.
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| 23. |
- Keutzer, Lina, et al.
(author)
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Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data : Differences, Similarities and Challenges Illustrated with Rifampicin
- 2022
-
In: Pharmaceutics. - : MDPI. - 1999-4923. ; 14:8
-
Journal article (peer-reviewed)abstract
- Pharmacometrics (PM) and machine learning (ML) are both valuable for drug development to characterize pharmacokinetics (PK) and pharmacodynamics (PD). Pharmacokinetic/pharmacodynamic (PKPD) analysis using PM provides mechanistic insight into biological processes but is time- and labor-intensive. In contrast, ML models are much quicker trained, but offer less mechanistic insights. The opportunity of using ML predictions of drug PK as input for a PKPD model could strongly accelerate analysis efforts. Here exemplified by rifampicin, a widely used antibiotic, we explore the ability of different ML algorithms to predict drug PK. Based on simulated data, we trained linear regressions (LASSO), Gradient Boosting Machines, XGBoost and Random Forest to predict the plasma concentration-time series and rifampicin area under the concentration-versus-time curve from 0-24 h (AUC(0-24h)) after repeated dosing. XGBoost performed best for prediction of the entire PK series (R-2: 0.84, root mean square error (RMSE): 6.9 mg/L, mean absolute error (MAE): 4.0 mg/L) for the scenario with the largest data size. For AUC(0-24h) prediction, LASSO showed the highest performance (R-2: 0.97, RMSE: 29.1 h center dot mg/L, MAE: 18.8 h center dot mg/L). Increasing the number of plasma concentrations per patient (0, 2 or 6 concentrations per occasion) improved model performance. For example, for AUC(0-24h) prediction using LASSO, the R-2 was 0.41, 0.69 and 0.97 when using predictors only (no plasma concentrations), 2 or 6 plasma concentrations per occasion as input, respectively. Run times for the ML models ranged from 1.0 s to 8 min, while the run time for the PM model was more than 3 h. Furthermore, building a PM model is more time- and labor-intensive compared with ML. ML predictions of drug PK could thus be used as input into a PKPD model, enabling time-efficient analysis.
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| 24. |
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| 25. |
- Kristoffersson, Anders N., et al.
(author)
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Inter occasion variability in individual optimal design
- 2015
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In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 42:6, s. 735-750
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Journal article (peer-reviewed)abstract
- Inter occasion variability (IOV) is of importance to consider in the development of a design where individual pharmacokinetic or pharmacodynamic parameters are of interest. IOV may adversely affect the precision of maximum a posteriori (MAP) estimated individual parameters, yet the influence of inclusion of IOV in optimal design for estimation of individual parameters has not been investigated. In this work two methods of including IOV in the maximum a posteriori Fisher information matrix (FIMMAP) are evaluated: (i) MAP(occ)-the IOV is included as a fixed effect deviation per occasion and individual, and (ii) POPocc-the IOV is included as an occasion random effect. Sparse sampling schedules were designed for two test models and compared to a scenario where IOV is ignored, either by omitting known IOV (Omit) or by mimicking a situation where unknown IOV has inflated the IIV (Inflate). Accounting for IOV in the FIMMAP markedly affected the designs compared to ignoring IOV and, as evaluated by stochastic simulation and estimation, resulted in superior precision in the individual parameters. In addition MAP(occ) and POPocc accurately predicted precision and shrinkage. For the investigated designs, the MAP(occ) method was on average slightly superior to POPocc and was less computationally intensive.
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| 26. |
- Kubart, Tomas, et al.
(author)
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Studies of hysteresis effect in reactive HiPIMS deposition of oxides
- 2011
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In: Surface & Coatings Technology. - : Elsevier. - 0257-8972 .- 1879-3347. ; 205:Suppl. 2, s. S303-S306
-
Journal article (peer-reviewed)abstract
- High power impulse magnetron sputtering (HiPIMS) has proven to be capable of substantial improvement of the quality of deposited coatings. Lately, there have been a number of reports indicating that the hysteresis effect may be reduced in HiPIMS mode resulting in an increase of the deposition rate of stoichiometric compound as compared to a direct current magnetron sputtering process in oxide mode. In this contribution, we have studied the hysteresis behaviour of Ti metal targets sputtered in Ar + O(2) mixtures. For fixed pulse on time and a constant average power, there is an optimum frequency minimizing the hysteresis. The effect of gas dynamics was analyzed by measurements of the gas refill time and rarefaction. Results indicate that the gas rarefaction may be responsible for the observed hysteresis behaviour. The results are in agreement with a previous study of Al oxide reactive process.
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| 27. |
- Lagergren, K, et al.
(author)
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Coexistence of superdeformed shapes in Er-154
- 2001
-
In: Physical Review Letters. - : American Physical Society. - 0031-9007 .- 1079-7114. ; 8702:2
-
Journal article (peer-reviewed)abstract
- A new superdeformed rotational band has been observed in Er-154 using the Euroball Ge detector array. The new band and the one previously observed can be understood as based on coexisting superdeformed structures at prolate and triaxial shapes, respectively. The observation resolves long-standing difficulties in the theoretical interpretation of superdeformed states in Er-154.
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| 28. |
- Lledó-García, Rocío, et al.
(author)
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Ethically Attractive Dose-Finding Designs for Drugs With a Narrow Therapeutic Index
- 2012
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In: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 52:1, s. 29-38
-
Journal article (peer-reviewed)abstract
- A simulation-based comparison study on the relative merits of dose-control trials (DCTs) with exposure-response analysis versus concentration-control trials (CCTs) for drugs with narrow therapeutic index showed that DCT designs are more informative about the exposure-response relationship. The authors revisit the question employing optimal design methodology and propose strategies for designing ethically attractive trials for these drugs, balancing between individual-collective risk and informativeness. An optimal study was performed considering a hypothetical immunosuppressant agent with 2 clinical end points. Different scenarios were optimized applying cost-based designs (unwanted events vs number of sub-jects/trial or maximal individual risk). Dose/exposure targets and number of subjects per trial/arm were optimized. Prior information inclusion on baseline risks was evaluated. DCTs were more informative, needing smaller studies to provide the same information as CCTs. Using the number of unwanted events-rather than subjects-as cost resulted in ethically more attractive designs. Including prior baseline risk information reduced the number of subject/events and allowed the use of targets closer to the optimal. Designing dose-finding trials for some narrow therapeutic index drugs may be improved by using DCTs with exposure-response analysis, cost-based designs, prior information, and optimal design analysis providing information on the ethical trade-off between individual risk and information gain.
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| 29. |
- Niebecker, Ronald, et al.
(author)
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Population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism-the Hokusai-VTE phase 3 study
- 2015
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In: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 80:6, s. 1374-1387
-
Journal article (peer-reviewed)abstract
- AIMS: This study characterized the population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism in the Hokusai-VTE phase 3 study. The impact of the protocol-specified 50% dose reductions applied to patients with body weight ≤ 60 kg, creatinine clearance (CLcr ) of 30 to 50 ml min(-1) or concomitant P-glycoprotein inhibitor on edoxaban exposure was assessed using simulations.METHODS: The sparse data from Hokusai-VTE, 9531 concentrations collected from 3707 patients, were pooled with data from 13 phase 1 studies. In the analysis, the covariate relationships used for dose reductions were estimated and differences between healthy subjects and patients as well as additional covariate effects of age, race and gender were explored based on statistical and clinical significance.RESULTS: A linear two-compartment model with first order absorption preceded by a lag time best described the data. Allometrically scaled body weight was included on disposition parameters. Apparent clearance was parameterized as non-renal and renal. The latter increased non-linearly with increasing CLcr . Compared with healthy volunteers, inter-compartmental clearance and the CLcr covariate effect were different in patients (+64.6% and +274%). Asian patients had a 22.6% increased apparent central volume of distribution. The effect of co-administration of P-glycoprotein inhibitors seen in phase 1 could not be confirmed in the phase 3 data. Model-based simulations revealed lower exposure in dose-reduced compared with non-dose-reduced patients.CONCLUSIONS: The adopted dose-reduction strategy resulted in reduced exposure compared with non-dose-reduced, thereby overcompensating for covariate effects. The clinical impact of these differences on safety and efficacy remains to be evaluated.
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| 30. |
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| 31. |
- Nyberg, Joakim, 1978-, et al.
(author)
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Edoxaban Exposure-Response Analysis and Clinical Utility Index Assessment in Patients With Symptomatic Deep-Vein Thrombosis or Pulmonary Embolism
- 2016
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In: CPT. - : Wiley. - 2163-8306. ; 5:4, s. 222-232
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Journal article (peer-reviewed)abstract
- Edoxaban exposure-response relationships from the phase III study evaluating edoxaban for prevention and treatment of venous thromboembolism (VTE) in patients with acute deep vein thrombosis (DVT) and/or pulmonary embolism (PE) were assessed by parametric time-to-event analysis. Statistical significant exposure-response relationships were recurrent VTE with hazard ratio (HR) based on average edoxaban concentration at steady state (C-av) (HRCav) 50.98 (i.e., change in the HR with every 1 ng/mL increase of C-av); the composite of recurrent DVT and nonfatal PE with HRC(av)50.99; and the composite of recurrent DVT, nonfatal PE, and all-cause mortality HRC(av)50.98, and all death using maximal edoxaban concentration (C-max) with HR (C-max) 50.99. No statistical significant exposure-response relationships were found for clinically relevant bleeding or major adverse cardiovascular event. Results support the recommendation of once-daily edoxaban 60 mg, and a reduced 30 mg dose in patients with moderate renal impairment, body weight <= 60 kg, or use of P-glycoprotein inhibitors verapamil or quinidine.
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| 32. |
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| 33. |
- Nyberg, Joakim, et al.
(author)
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Methods and software tools for design evaluation for population pharmacokinetics-pharmacodynamics studies
- 2015
-
In: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 79:1, s. 6-17
-
Journal article (peer-reviewed)abstract
- Population Pharmacokinetic (PK)-Pharmacodynamic (PD) (PKPD) models are increasingly used in drug development and in academic research. Hence designing efficient studies is an important task. Following the first theoretical work on optimal design for nonlinear mixed effect models, this research theme has grown rapidly. There are now several different software tools that implement an evaluation of the Fisher information matrix for population PKPD. We compared and evaluated five software tools: PFIM, PkStaMP, PopDes, PopED, and POPT. The comparisons were performed using two models: i) a simple one compartment warfarin PK model; ii) a more complex PKPD model for Pegylated-interferon (peg-interferon) with both concentration and response of viral load of hepatitis C virus (HCV) data. The results of the software were compared in terms of the standard error values of the parameters (SE) predicted from the software and the empirical SE values obtained via replicated clinical trial simulation and estimation. For the warfarin PK model and the peg-interferon PKPD model all software gave similar results. Of interest it was seen, for all software, that the simpler approximation to the Fisher information matrix, using the block diagonal matrix, provided predicted SE values that were closer to the empirical SE values than when the more complicated approximation was used (the full matrix). For most PKPD models, using any of the available software tools will provide meaningful results, avoiding cumbersome simulation and allowing design optimization.
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| 34. |
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| 35. |
- Nyberg, Joakim, et al.
(author)
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PopED : An extended, parallelized, nonlinear mixed effects models optimal design tool
- 2012
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In: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 108:2, s. 789-805
-
Journal article (peer-reviewed)abstract
- Several developments have facilitated the practical application and increased the general use of optimal design for nonlinear mixed effects models. These developments include new methodology for utilizing advanced pharmacometric models, faster optimization algorithms and user friendly software tools. In this paper we present the extension of theoptimal design software PopED, which incorporates many of these recent advances into aneasily useable enhanced GUI. Furthermore, we present new solutions to problems related to the design of experiments such as: faster and more robust FIM calculations and optimizations, optimizing over cost/utility functions and diagnostic tools and plots to evaluate designperformance. Examples for; (i) Group size optimization and efficiency translation, (ii) Cost/constraint optimization, (iii) Optimizations with different FIM approximations and (iv) optimization with parallel computing demonstrate the new features in PopED and underline the potential use of this tool when designing experiments.
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| 36. |
- Nyberg, Joakim, 1978-
(author)
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Practical Optimal Experimental Design in Drug Development and Drug Treatment using Nonlinear Mixed Effects Models
- 2011
-
Doctoral thesis (other academic/artistic)abstract
- The cost of releasing a new drug on the market has increased rapidly in the last decade. The reasons for this increase vary with the drug, but the need to make correct decisions earlier in the drug development process and to maximize the information gained throughout the process is evident. Optimal experimental design (OD) describes the procedure of maximizing relevant information in drug development and drug treatment processes. While various optimization criteria can be considered in OD, the most common is to optimize the unknown model parameters for an upcoming study. To date, OD has mainly been used to optimize the independent variables, e.g. sample times, but it can be used for any design variable in a study. This thesis addresses the OD of multiple continuous or discrete design variables for nonlinear mixed effects models. The methodology for optimizing and the optimization of different types of models with either continuous or discrete data are presented and the benefits of OD for such models are shown. A software tool for optimizing these models in parallel is developed and three OD examples are demonstrated: 1) optimization of an intravenous glucose tolerance test resulting in a reduction in the number of samples by a third, 2) optimization of drug compound screening experiments resulting in the estimation of nonlinear kinetics and 3) an individual dose-finding study for the treatment of children with ciclosporin before kidney transplantation resulting in a reduction in the number of blood samples to ~27% of the original number and an 83% reduction in the study duration. This thesis uses examples and methodology to show that studies in drug development and drug treatment can be optimized using nonlinear mixed effects OD. This provides a tool than can lower the cost and increase the overall efficiency of drug development and drug treatment.
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| 37. |
- Nyberg, Joakim, et al.
(author)
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Properties of the full random-effect modeling approach with missing covariate data
- 2024
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In: Statistics in Medicine. - : John Wiley & Sons. - 0277-6715 .- 1097-0258. ; 43:5, s. 935-952
-
Journal article (peer-reviewed)abstract
- During drug development, a key step is the identification of relevant covariates predicting between-subject variations in drug response. The full random effects model (FREM) is one of the full-covariate approaches used to identify relevant covariates in nonlinear mixed effects models. Here we explore the ability of FREM to handle missing (both missing completely at random (MCAR) and missing at random (MAR)) covariate data and compare it to the full fixed-effects model (FFEM) approach, applied either with complete case analysis or mean imputation. A global health dataset (20 421 children) was used to develop a FREM describing the changes of height for age Z-score (HAZ) over time. Simulated datasets (n = 1000) were generated with variable rates of missing (MCAR) covariate data (0%-90%) and different proportions of missing (MAR) data condition on either observed covariates or predicted HAZ. The three methods were used to re-estimate model and compared in terms of bias and precision which showed that FREM had only minor increases in bias and minor loss of precision at increasing percentages of missing (MCAR) covariate data and performed similarly in the MAR scenarios. Conversely, the FFEM approaches either collapsed at ≥70% of missing (MCAR) covariate data (FFEM complete case analysis) or had large bias increases and loss of precision (FFEM with mean imputation). Our results suggest that FREM is an appropriate approach to covariate modeling for datasets with missing (MCAR and MAR) covariate data, such as in global health studies.
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| 38. |
- Nyberg, Joakim, 1978-, et al.
(author)
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RETRACTED: Population Kinetics of 0.9% Saline Distribution in Hemorrhaged Awake and Isoflurane-anesthetized Volunteers
- 2019
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In: Anesthesiology. - : Ovid Technologies (Wolters Kluwer Health). - 0003-3022 .- 1528-1175. ; 131:3, s. 501-511
-
Journal article (peer-reviewed)abstract
- Background: Population-based, pharmacokinetic modeling can be used to describe variability in fluid distribution and dilution between individuals and across populations. The authors hypothesized that dilution produced by crystalloid infusion after hemorrhage would be larger in anesthetized than in awake subjects and that population kinetic modeling would identify differences in covariates. Methods: Twelve healthy volunteers, seven females and five males, mean age 28 +/- 4.3 yr, underwent a randomized crossover study. Each subject participated in two separate sessions, separated by four weeks, in which they were assigned to an awake or an anesthetized arm. After a baseline period, hemorrhage (7 ml/kg during 20 min) was induced, immediately followed by a 25 ml/kg infusion during 20 min of 0.9% saline. Hemoglobin concentrations, sampled every 5 min for 60 min then every 10 min for an additional 120 min, were used for population kinetic modeling. Covariates, including body weight, sex, and study arm (awake or anesthetized), were tested in the model building. The change in dilution was studied by analyzing area under the curve and maximum plasma dilution. Results: Anesthetized subjects had larger plasma dilution than awake subjects. The analysis showed that females increased area under the curve and maximum plasma dilution by 17% (with 95% CI, 1.08 to 1.38 and 1.07 to 1.39) compared with men, and study arm (anesthetized increased area under the curve by 99% [0.88 to 2.45] and maximum plasma dilution by 35% [0.71 to 1.63]) impacted the plasma dilution whereas a 10-kg increase of body weight resulted in a small change (less than1% [0.93 to 1.20]) in area under the curve and maximum plasma dilution. Mean arterial pressure was lower in subjects while anesthetized (P < 0.001). Conclusions: In awake and anesthetized subjects subjected to controlled hemorrhage, plasma dilution increased with anesthesia, female sex, and lower body weight. Neither study arm nor body weight impact on area under the curve or maximum plasma dilution were statistically significant and therefore no effect can be established.
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| 39. |
- Nyberg, Joakim, et al.
(author)
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Serial correlation in optimal design for nonlinear mixed effects models
- 2012
-
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 39:3, s. 239-249
-
Journal article (peer-reviewed)abstract
- In population modeling two sources of variability are commonly included; inter individual variability and residual variability. Rich sampling optimal design (more samples than model parameters) using these models will often result in a sampling schedule where some measurements are taken at exactly the same time point, thereby maximizing the signal-to-noise ratio. This behavior is a result of not appropriately taking into account error generation mechanisms and is often clinically unappealing and may be avoided by including intrinsic variability, i.e. serially correlated residual errors. In this paper we extend previous work that investigated optimal designs of population models including serial correlation using stochastic differential equations to optimal design with the more robust, and analytic, AR(1) autocorrelation model. Further, we investigate the importance of correlation strength, design criteria and robust designs. Finally, we explore the optimal design properties when estimating parameters with and without serial correlation. In the investigated examples the designs and estimation performance differs significantly when handling serial correlation.
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| 40. |
- Nyberg, Joakim, et al.
(author)
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Simultaneous optimal experimental design on dose and sample times
- 2009
-
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 36:2, s. 125-145
-
Journal article (peer-reviewed)abstract
- Optimal experimental design can be used for optimizing new pharmacokinetic (PK)-pharmacodynamic (PD) studies to increase the parameter precision. Several methods for optimizing non-linear mixed effect models has been proposed previously but the impact of optimizing other continuous design parameters, e.g. the dose, has not been investigated to a large extent. Moreover, the optimization method (sequential or simultaneous) for optimizing several continuous design parameters can have an impact on the optimal design. In the sequential approach the time and dose where optimized in sequence and in the simultaneous approach the dose and time points where optimized at the same time. To investigate the sequential approach and the simultaneous approach; three different PK-PD models where considered. In most of the cases the optimization method did change the optimal design and furthermore the precision was improved with the simultaneous approach.
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| 41. |
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| 42. |
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| 43. |
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| 44. |
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| 45. |
- Remmerfelt, Emelie, et al.
(author)
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Conceptualisations of personal growth in Ghanaian Orthodox Christians
- 2021
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In: Mental Health, Religion & Culture. - : Routledge. - 1367-4676 .- 1469-9737. ; 24:9, s. 887-898
-
Journal article (peer-reviewed)abstract
- Personal growth is integral to mental health. Hegemonic psychological theories about personal growth were formulated in an individualistic culture where people experience an independent self. Conceptualisations of personal growth may be different in collectivistic cultures where people experience an interdependent self. Ghanaian Orthodox Christians are embedded in a collectivistic culture where religion permeates every-day life. The aim of this study was to investigate how Ghanaian Orthodox Christians conceptualise personal growth. We interviewed 12 participants from the University of Ghana who belonged to different Orthodox Christian Churches. The results showed that the participants wanted material success, and they acknowledged that this takes effort. Relationships were facilitating their ambitions, and for that reason learning to adapt to social norms was important. Most important of all was their relationship to God. The results implied a conceptualisation of personal growth that relies on an interdependent experience of the self.
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| 46. |
- Ribbing, Jakob, et al.
(author)
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The Lasso – A Novel Method for Predictive Covariate Model Building in Nonlinear Mixed Effects Models
- 2007
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In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 34:4, s. 485-517
-
Journal article (peer-reviewed)abstract
- Covariate models for population pharmacokinetics and pharmacodynamics are often built with a stepwise covariate modelling procedure (SCM). When analysing a small dataset this method may produce a covariate model that suffers from selection bias and poor predictive performance. The lasso is a method suggested to remedy these problems. It may also be faster than SCM and provide a validation of the covariate model. The aim of this study was to implement the lasso for covariate selection within NONMEM and to compare this method to SCM. In the lasso all covariates must be standardised to have zero mean and standard deviation one. Subsequently, the model containing all potential covariate–parameter relations is fitted with a restriction: the sum of the absolute covariate coefficients must be smaller than a value, t. The restriction will force some coefficients towards zero while the others are estimated with shrinkage. This means in practice that when fitting the model the covariate relations are tested for inclusion at the same time as the included relations are estimated. For a given SCM analysis, the model size depends on the P-value required for selection. In the lasso the model size instead depends on the value of t which can be estimated using cross-validation. The lasso was implemented as an automated tool using PsN. The method was compared to SCM in 16 scenarios with different dataset sizes, number of investigated covariates and starting models for the covariate analysis. Hundred replicate datasets were created by resampling from a PK-dataset consisting of 721 stroke patients. The two methods were compared primarily on the ability to predict external data, estimate their own predictive performance (external validation), and on the computer run-time. In all 16 scenarios the lasso predicted external data better than SCM with any of the studied P-values (5%, 1% and 0.1%), but the benefit was negligible for large datasets. The lasso cross-validation provided a precise and nearly unbiased estimate of the actual prediction error. On a single processor, the lasso was faster than SCM. Further, the lasso could run completely in parallel whereas SCM must run in steps. In conclusion, the lasso is superior to SCM in obtaining a predictive covariate model on a small dataset or on small subgroups (e.g. rare genotype). Run in parallel the lasso could be much faster than SCM. Using cross-validation, the lasso provides a validation of the covariate model and does not require the user to specify a P-value for selection.
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| 47. |
- Sandstedt, Mårten, 1972-, et al.
(author)
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Evaluation of an AI-based, automatic coronary artery calcium scoring software
- 2020
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In: European Radiology. - : Springer. - 0938-7994 .- 1432-1084. ; 30:3, s. 1671-1678
-
Journal article (peer-reviewed)abstract
- ObjectivesTo evaluate an artificial intelligence (AI)–based, automatic coronary artery calcium (CAC) scoring software, using a semi-automatic software as a reference.MethodsThis observational study included 315 consecutive, non-contrast-enhanced calcium scoring computed tomography (CSCT) scans. A semi-automatic and an automatic software obtained the Agatston score (AS), the volume score (VS), the mass score (MS), and the number of calcified coronary lesions. Semi-automatic and automatic analysis time were registered, including a manual double-check of the automatic results. Statistical analyses were Spearman’s rank correlation coefficient (⍴), intra-class correlation (ICC), Bland Altman plots, weighted kappa analysis (κ), and Wilcoxon signed-rank test.ResultsThe correlation and agreement for the AS, VS, and MS were ⍴ = 0.935, 0.932, 0.934 (p < 0.001), and ICC = 0.996, 0.996, 0.991, respectively (p < 0.001). The correlation and agreement for the number of calcified lesions were ⍴ = 0.903 and ICC = 0.977 (p < 0.001), respectively. The Bland Altman mean difference and 1.96 SD upper and lower limits of agreements for the AS, VS, and MS were − 8.2 (− 115.1 to 98.2), − 7.4 (− 93.9 to 79.1), and − 3.8 (− 33.6 to 25.9), respectively. Agreement in risk category assignment was 89.5% and κ = 0.919 (p < 0.001). The median time for the semi-automatic and automatic method was 59 s (IQR 35–100) and 36 s (IQR 29–49), respectively (p < 0.001).ConclusionsThere was an excellent correlation and agreement between the automatic software and the semi-automatic software for three CAC scores and the number of calcified lesions. Risk category classification was accurate but showing an overestimation bias tendency. Also, the automatic method was less time-demanding.Key Points• Coronary artery calcium (CAC) scoring is an excellent candidate for artificial intelligence (AI) development in a clinical setting.• An AI-based, automatic software obtained CAC scores with excellent correlation and agreement compared with a conventional method but was less time-consuming.
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| 48. |
- Silber, Hanna E., et al.
(author)
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Optimization of the intravenous glucose tolerance test in T2DM patients using optimal experimental design
- 2009
-
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 36:3, s. 281-295
-
Journal article (peer-reviewed)abstract
- Intravenous glucose tolerance test (IVGTT) provocations are informative, but complex and laborious, for studying the glucose-insulin system. The objective of this study was to evaluate, through optimal design methodology, the possibilities of more informative and/or less laborious study design of the insulin modified IVGTT in type 2 diabetic patients. A previously developed model for glucose and insulin regulation was implemented in the optimal design software PopED 2.0. The following aspects of the study design of the insulin modified IVGTT were evaluated; (1) glucose dose, (2) insulin infusion, (3) combination of (1) and (2), (4) sampling times, (5) exclusion of labeled glucose. Constraints were incorporated to avoid prolonged hyper- and/or hypoglycemia and a reduced design was used to decrease run times. Design efficiency was calculated as a measure of the improvement with an optimal design compared to the basic design. The results showed that the design of the insulin modified IVGTT could be substantially improved by the use of an optimized design compared to the standard design and that it was possible to use a reduced number of samples. Optimization of sample times gave the largest improvement followed by insulin dose. The results further showed that it was possible to reduce the total sample time with only a minor loss in efficiency. Simulations confirmed the predictions from PopED. The predicted uncertainty of parameter estimates (CV) was low in all tested cases, despite the reduction in the number of samples/subject. The best design had a predicted average CV of parameter estimates of 19.5%. We conclude that improvement can be made to the design of the insulin modified IVGTT and that the most important design factor was the placement of sample times followed by the use of an optimal insulin dose. This paper illustrates how complex provocation experiments can be improved by sequential modeling and optimal design.
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| 49. |
- Sjögren, Erik, 1977-, et al.
(author)
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Optimal experimental design for assessment of enzyme kinetics in a drug discovery screening environment
- 2011
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In: Drug Metabolism And Disposition. - : American Society for Pharmacology & Experimental Therapeutics (ASPET). - 0090-9556 .- 1521-009X. ; 39:5, s. 858-863
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Journal article (peer-reviewed)abstract
- A penalized ED-optimal design with a discrete parameter distribution was used to find an optimal experimental design for assessment of enzyme kinetics in a screening environment. A data set for enzyme kinetic data (Vmax and Km) was collected from previously reported studies and every Vmax/Km pair (n=76) was taken to represent a unique drug compound. The design was restricted to 15 samples, an incubation time of up to 40 min and starting concentrations (C0) for the incubation between 0.01 and 100 µM. The optimization was performed by finding the sample times and C0 returning the lowest uncertainty (SE) of the model parameter estimates. Individual optimal designs (I-OD), one general optimal design (G-OD) and one for laboratory practice pragmatically modified design (OD) were obtained. In addition, a standard design (STD-D), representing a commonly applied approach for metabolic stability investigations, was constructed. Simulations were performed for OD and STD-D using the Michaelis-Menten (MM) equation and enzyme kinetic parameters were estimated both with MM and a mono exponential (EXP) decay. OD generated a better result (RSE) for 99% of the compounds and an equal or better result (RMSE) for 78% of the compounds. Furthermore, high-quality estimates (RMSE <30%) of both Vmax and Km could be obtained for a considerable number (26%) of the investigated compounds. The results presented in this study demonstrate that the output could generally be improved when compared to that obtained from the standard approaches used today.
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| 50. |
- Sohler, D, et al.
(author)
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Maximally aligned states in Ag-99
- 2003
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In: European Physical Journal A. Hadrons and Nuclei. - : Springer Science and Business Media LLC. - 1434-6001 .- 1434-601X. ; 16:2, s. 171-175
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Journal article (peer-reviewed)abstract
- Excited states of Ag-99 were populated via the Cr-50 + Ni-58 (261 MeV) reaction using the NORDBALL detector array equipped with charged-particle and neutron. detector systems for reaction channel separation. On the basis of the measured gammagamma-coincidence relations and angular distribution ratios a significantly extended level scheme has been constructed up to E-x similar to 7.8 MeV and I = 35/2. The experimental results were described within the framework of the shell model. Candidates for states fully aligned in the pig(9/2)(-3)nu(d(5/2),g(7/2))(2) valence configuration space were found at 4109 and 6265 keV.
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