| 1. |
- Ibrahim, Moustafa M. A.
(författare)
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Pharmacometric evaluation and improvement of models and study designs - applied in diabetes
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Pharmacometric models are increasingly used to improve the efficiency of the drug development process and increase our understanding of the studied underlying pathophysiological system. These models require assumptions for handling different types of data and the different model components, and the appropriateness of such assumptions must be carefully inspected for unbiased conclusions. The aim of this thesis was to develop new models, that by acknowledging the complexity of the data captures more information, and novel methodologies for model evaluation, as well as applying models to improve study designs, with practical illustrations in the therapeutic area of diabetes. Two new models were developed. An integrated minimal model was developed to enable clinical trial simulations in presence of endogenous insulin secretion while deriving the important physiological indices for clinical diagnosis. A multi-state model was developed for improved handling of survival data in presence of competing risks and interval-censored data. New methodologies for model evaluations were developed that include residual modeling and linearization for assessing possible improvements of the structural and statistical model components as well as using simulations to assess the captured information from the data between structurally different models. A mapping approach for parameters carrying similar information between different models was developed, allowing the derivation of physiological indices from the integrated glucose insulin model. Models were also successfully applied with the purpose of improving study designs, either based on anticipated drug effect or for assessment of physiological indices. In conclusion, new more informative models were developed by acknowledging the complexity of the data, novel methods were proposed and applied for model development/evaluation process, and models were used to improve study designs for clinical trials and clinical diagnosis.
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| 2. |
- Macchi, Chiara, et al.
(författare)
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Leptin, Resistin, and Proprotein Convertase Subtilisin/Kexin Type 9 - The Role of STAT3
- 2020
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Ingår i: The American journal of pathology. - : Elsevier BV. - 1525-2191 .- 0002-9440. ; 190:11, s. 2226-2236
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Tidskriftsartikel (refereegranskat)abstract
- In a condition of dysfunctional visceral fat depots, as in the case of obesity, alterations in adipokines levels may be detrimental for the cardiovascular system. The proinflammatory leptin and resistin adipokines have been described as possible links between obesity and atherosclerosis. The present study was aimed at evaluating whether proprotein convertase subtilisin/kexin type 9 (PCSK9), a key regulator of low-density lipoprotein metabolism, is induced by leptin and resistin through the involvement of the inflammatory pathway of signal transducer and activator of transcript 3 (STAT3). In HepG2 cells, leptin and resistin upregulated PCSK9 gene and protein expression as well as the phosphorylation of STAT3. Upon STAT3 silencing, leptin and resistin lost their ability to activate PCSK9. The knock-down of STAT3 did not affect the expression of leptin and resistin receptors as well as that of PCSK9. The analysis of human PCSK9 promoter region showed that the two adipokines raise PCSK9 promoter activity via the involvement of sterol regulatory element motif. In healthy male, a positive association between circulating leptin and PCSK9 levels was found only when BMI was < 25 kg/m2. In conclusion, our study identified STAT3 as one of the molecular regulators of leptin- and resistin-mediated transcriptional induction of PCSK9.
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| 3. |
- Smith, Mike K., et al.
(författare)
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Model Description Language (MDL) : A Standard for Modeling and Simulation
- 2017
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Ingår i: CPT. - : WILEY. - 2163-8306. ; 6:10, s. 647-650
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Tidskriftsartikel (refereegranskat)abstract
- Recent work on Model Informed Drug Discovery and Development (MID3) has noted the need for clarity in model description used in quantitative disciplines such as pharmacology and statistics. 1-3 Currently, models are encoded in a variety of computer languages and are shared through publications that rarely include original code and generally lack reproducibility. The DDMoRe Model Description Language (MDL) has been developed primarily as a language standard to facilitate sharing knowledge and understanding of models.
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