scholarly journals Assessing Romiplostim Dose and Platelet Response-Guided Titration to Support Use of Romiplostim in ITP Patients Less Than 12 Months from Diagnosis

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4221-4221
Author(s):  
Ekaterina Gibiansky ◽  
Florencio Serrano Castillo ◽  
Hossam A Saad ◽  
Vincent Chow ◽  
Sameer Doshi

Abstract Background: Romiplostim, a subcutaneous treatment for adult ITP, uses a platelet response-guided dose adjustment algorithm (USPI dosing, Table 1) to maintain patients' platelet count (PC). Romiplostim was recently approved for patients with ITP ≤ 12 months from diagnosis. Objectives: The primary objective of this analysis was to confirm the appropriateness of romiplostim dose and platelet response-guided titration for patients with ITP ≤ 12 months from diagnosis using a model based approach. Methods: Data from 268 adult patients with ITP ≤ 12 months from diagnosis was extracted from 7 previously conducted clinical studies and used to develop a model based on a previously published model of romiplostim dose-response in ITP patients (Perez-Ruixo et al, 2012). Following the model update, patient characteristics (time from diagnosis, PC at baseline, sex, age, weight, number of prior therapies, region, and use of rescue medications) were assessed to identify any potential factors influencing dose or platelet response in ITP patients ≤ 12 months from diagnosis. The model was qualified for simulation using standard methods modified to account for response-guided dosing. Additionally, observed and predicted platelet responses (incidence of durable response, sustained response, and duration of response) were compared for patients stratified by time from ITP diagnosis (<3, 3 to ≤ 6, and 6 to ≤ 12 months). Simulations were then conducted using prescribed dosing guidance to predict PC and romiplostim doses over 52 weeks of treatment in patients ≤ 6 months and > 6 to ≤ 12 months from diagnosis. Results: The analysis dataset included 7854 PC from 268 patients (with median baseline PC of 18 x 10 9/L and median time since diagnosis of 3 months) receiving romiplostim weekly for up to 3 years at doses ranging from 1 to 15 mg/kg. The updated model (Figure 1) consisted of a drug-sensitive progenitor cell compartment (Pre), 4 maturation compartments (Transit), and a peripheral blood compartment (Circ). Romiplostim increased production of platelet precursors in Pre in 2 ways: 1. linearly with romiplostim exposure (immediate response), and 2. as a function of cumulative administered dose. Response to romiplostim was bimodal with approximately 50% of patients more sensitive to romiplostim treatment with drug sensitivity proportional to time since diagnosis. In the other 50% of patients, immediate response was reduced and there was no cumulative effect of romiplostim dosing on platelet response over time. Age was associated with average platelet transit time where a patient of 30, 60, or 90 years would have a platelet transit time of 6.3, 7.5, and 8.3 days respectively. No other covariates were found to influence any model parameters. Model predicted and observed platelet responses were similar for ITP patients stratified by time from ITP diagnosis (<3, 3 to ≤ 6 and 6 to ≤ 12 months). Simulations (Figure 2) showed that romiplostim prescribed dosing is effective in maintaining PC of 50 - 250 x 10 9/L following titration (approximately 65% of subjects) and minimizing the proportion <20 or >400 x 10 9/L regardless of time since ITP diagnosis or sensitivity to romiplostim treatment. The predicted <35% of subjects above 400 x 10 9/L is consistent with what was observed in the adult ITP safety datasets. Conclusions: An updated model of romiplostim dose and platelet response was developed using data from ITP patients ≤12 months from diagnosis. Clinical trial simulations using the updated model predicted that weekly dosing of romiplostim according to the dose titration rules in the label adequately maintained platelet counts in patients with ITP ≤ 12 months from diagnosis. Figure 1 Figure 1. Disclosures Gibiansky: Amgen: Consultancy. Serrano Castillo: Amgen: Current Employment, Current equity holder in publicly-traded company. Saad: Amgen: Current Employment, Current equity holder in publicly-traded company. Chow: Amgen: Current Employment, Current equity holder in publicly-traded company. Doshi: Amgen: Current equity holder in publicly-traded company; Amgen: Current Employment.

Author(s):  
Michael D. Collins ◽  
Elvis Han Cui ◽  
Seung Won Hyun ◽  
Weng Kee Wong

AbstractThe key aim of this paper is to suggest a more quantitative approach to designing a dose–response experiment, and more specifically, a concentration–response experiment. The work proposes a departure from the traditional experimental design to determine a dose–response relationship in a developmental toxicology study. It is proposed that a model-based approach to determine a dose–response relationship can provide the most accurate statistical inference for the underlying parameters of interest, which may be estimating one or more model parameters or pre-specified functions of the model parameters, such as lethal dose, at maximal efficiency. When the design criterion or criteria can be determined at the onset, there are demonstrated efficiency gains using a more carefully selected model-based optimal design as opposed to an ad-hoc empirical design. As an illustration, a model-based approach was theoretically used to construct efficient designs for inference in a developmental toxicity study of sea urchin embryos exposed to trimethoprim. This study compares and contrasts the results obtained using model-based optimal designs versus an ad-hoc empirical design.


2017 ◽  
Vol 27 (9) ◽  
pp. 2694-2721 ◽  
Author(s):  
Joseph Wu ◽  
Anindita Banerjee ◽  
Bo Jin ◽  
Sandeep M Menon ◽  
Steven W Martin ◽  
...  

Characterizing clinical dose–response is a critical step in drug development. Uncertainty in the dose–response model when planning a dose-ranging study can often undermine efficiency in both the design and analysis of the trial. Results of a previous meta-analysis on a portfolio of small molecule compounds from a large pharmaceutical company demonstrated a consistent dose–response relationship that was well described by the maximal effect model. Biologics are different from small molecules due to their large molecular sizes and their potential to induce immunogenicity. A model-based meta-analysis was conducted on the clinical efficacy of 71 distinct biologics evaluated in 91 placebo-controlled dose–response studies published between 1995 and 2014. The maximal effect model, arising from receptor occupancy theory, described the clinical dose–response data for the majority of the biologics (81.7%, n = 58). Five biologics (7%) with data showing non-monotonic trend assuming the maximal effect model were identified and discussed. A Bayesian model-based hierarchical approach using different joint specifications of prior densities for the maximal effect model parameters was used to meta-analyze the whole set of biologics excluding these five biologics ( n = 66). Posterior predictive distributions of the maximal effect model parameters were reported and they could be used to aid the design of future dose-ranging studies. Compared to the meta-analysis of small molecules, the combination of fewer doses, narrower dosing ranges, and small sample sizes further limited the information available to estimate clinical dose–response among biologics.


Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 102
Author(s):  
Frauke Kachholz ◽  
Jens Tränckner

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.


2018 ◽  
Vol 127 ◽  
pp. S165
Author(s):  
C. Terhaard ◽  
J. Vermaire ◽  
T. Dijkema ◽  
M. Philippens ◽  
P. Braam ◽  
...  

Author(s):  
Shunki Nishii ◽  
Yudai Yamasaki

Abstract To achieve high thermal efficiency and low emission in automobile engines, advanced combustion technologies using compression autoignition of premixtures have been studied, and model-based control has attracted attention for their practical applications. Although simplified physical models have been developed for model-based control, appropriate values for their model parameters vary depending on the operating conditions, the engine driving environment, and the engine aging. Herein, we studied an onboard adaptation method of model parameters in a heat release rate (HRR) model. This method adapts the model parameters using neural networks (NNs) considering the operating conditions and can respond to the driving environment and the engine aging by training the NNs onboard. Detailed studies were conducted regarding the training methods. Furthermore, the effectiveness of this adaptation method was confirmed by evaluating the prediction accuracy of the HRR model and model-based control experiments.


2012 ◽  
Vol 16 (9) ◽  
pp. 3083-3099 ◽  
Author(s):  
H. Xie ◽  
L. Longuevergne ◽  
C. Ringler ◽  
B. R. Scanlon

Abstract. Irrigation development is rapidly expanding in mostly rainfed Sub-Saharan Africa. This expansion underscores the need for a more comprehensive understanding of water resources beyond surface water. Gravity Recovery and Climate Experiment (GRACE) satellites provide valuable information on spatio-temporal variability in water storage. The objective of this study was to calibrate and evaluate a semi-distributed regional-scale hydrologic model based on the Soil and Water Assessment Tool (SWAT) code for basins in Sub-Saharan Africa using seven-year (July 2002–April 2009) 10-day GRACE data and multi-site river discharge data. The analysis was conducted in a multi-criteria framework. In spite of the uncertainty arising from the tradeoff in optimising model parameters with respect to two non-commensurable criteria defined for two fluxes, SWAT was found to perform well in simulating total water storage variability in most areas of Sub-Saharan Africa, which have semi-arid and sub-humid climates, and that among various water storages represented in SWAT, water storage variations in soil, vadose zone and groundwater are dominant. The study also showed that the simulated total water storage variations tend to have less agreement with GRACE data in arid and equatorial humid regions, and model-based partitioning of total water storage variations into different water storage compartments may be highly uncertain. Thus, future work will be needed for model enhancement in these areas with inferior model fit and for uncertainty reduction in component-wise estimation of water storage variations.


1995 ◽  
Vol 79 (3) ◽  
pp. 1008-1026 ◽  
Author(s):  
D. R. Fine ◽  
D. Glasser ◽  
D. Hildebrandt ◽  
J. Esser ◽  
R. E. Lurie ◽  
...  

Hepatic function can be characterized by the activity/time curves obtained by imaging the aorta, spleen, and liver. Nonparametric deconvolution of the activity/time curves is clinically useful as a diagnostic tool in determining organ transit times and flow fractions. The use of this technique is limited, however, because of numerical and noise problems in performing deconvolution. Furthermore, the interaction of part of the tracer with the spleen and gastrointestinal tract, before it enters the liver, further obscures physiological information in the deconvolved liver curve. In this paper, a mathematical relationship is derived relating the liver activity/time curve to portal and hepatic behavior. The mathematical relationship is derived by using transit time spectrum/residence time density theory. Based on this theory, it is shown that the deconvolution of liver activity/time curves gives rise to a complex combination of splenic, gastrointestinal, and liver dependencies. An anatomically and physiologically plausible parametric model of the hepatic vascular system has been developed. This model is used in conjunction with experimental data to estimate portal, splenic, and hepatic physiological blood flow parameters for eight normal volunteers. These calculated parameters, which include the portal flow fraction, the splenic blood flow fraction, and blood transit times are shown to adequately correspond to published values. In particular, the model of the hepatic vascular system identifies the portal flow fraction as 0.752 +/- 0.022, the splenic blood flow fraction as 0.180 +/- 0.023, and the liver mean transit time as 13.4 +/- 1.71 s. The model has also been applied to two portal hypertensive patients. The variation in some of the model parameters is beyond normal limits and is consistent with the observed pathology.


2012 ◽  
Vol 12 (12) ◽  
pp. 3719-3732 ◽  
Author(s):  
L. Mediero ◽  
L. Garrote ◽  
A. Chavez-Jimenez

Abstract. Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.


2020 ◽  
Vol 61 (2) ◽  
pp. 25-34 ◽  
Author(s):  
Yibo Li ◽  
Hang Li ◽  
Xiaonan Guo

In order to improve the accuracy of rice transplanter model parameters, an online parameter identification algorithm for the rice transplanter model based on improved particle swarm optimization (IPSO) algorithm and extended Kalman filter (EKF) algorithm was proposed. The dynamic model of the rice transplanter was established to determine the model parameters of the rice transplanter. Aiming at the problem that the noise matrices in EKF algorithm were difficult to select and affected the best filtering effect, the proposed algorithm used the IPSO algorithm to optimize the noise matrices of the EKF algorithm in offline state. According to the actual vehicle tests, the IPSO-EKF was used to identify the cornering stiffness of the front and rear tires online, and the identified cornering stiffness value was substituted into the model to calculate the output data and was compared with the measured data. The simulation results showed that the accuracy of parameter identification for the rice transplanter model based on the IPSO-EKF algorithm was improved, and established an accurate rice transplanter model.


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