| 1. |
- Backstrom, E., et al.
(author)
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Possible Extraction of Drugs from Lung Tissue During Broncho-alveolar Lavage Suggest Uncertainty in the Procedure's Utility for Quantitative Assessment of Airway Drug Exposure
- 2022
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In: Journal of Pharmaceutical Sciences. - : Elsevier. - 0022-3549 .- 1520-6017. ; 111:3, s. 852-858
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Journal article (peer-reviewed)abstract
- Following inhaled dosing, broncho-alveolar lavage (BAL) is often used for sampling epithelial lining fluid (ELF) to determine drug concentration in the lungs. This study aimed to explore the technique's suitability. Urea is typically used to estimate the dilution factor between the BAL fluid and physiological ELF, since it readily permeates through all fluids in the body. As representatives of permeable small molecule drugs with high, medium and low tissue distribution properties, propranolol, diazepam, indomethacin and AZD4721 were infused intravenously to steady state to ensure equal unbound drug concentrations throughout the body. The results showed that propranolol had higher unbound concentrations in the ELF compared to the plasma whilst this was not the case for the other compounds. Experiments with different BAL volumes and repeated lavaging indicated that the amount of drug extracted is very sensitive to experimental procedure. In addition, the results show that the unbound concentrations in ELF compared to plasma differs dependent on molecule class and tissue distribution properties. Overall data suggests that lavaging can remove drug from lung tissue in addition to ELF and highlights significant uncertainty in the robustness of the procedure for determining ELF drug concentrations. (c) 2021 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.
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| 2. |
- Hamm, Gregory R., et al.
(author)
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Revealing the Regional Localization and Differential Lung Retention of Inhaled Compounds by Mass Spectrometry Imaging
- 2020
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In: Journal of Aerosol Medicine. - : Mary Ann Liebert Inc. - 1941-2711 .- 1941-2703. ; 33:1, s. 43-53
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Journal article (peer-reviewed)abstract
- Background: For the treatment of respiratory disease, inhaled drug delivery aims to provide direct access to pharmacological target sites while minimizing systemic exposure. Despite this long-held tenet of inhaled therapeutic advantage, there are limited data of regional drug localization in the lungs after inhalation. The aim of this study was to investigate the distribution and retention of different chemotypes typifying available inhaled drugs [slowly dissolving neutral fluticasone propionate (FP) and soluble bases salmeterol and salbutamol] using mass spectrometry imaging (MSI).Methods: Salmeterol, salbutamol, and FP were simultaneously delivered by inhaled nebulization to rats. In the same animals, salmeterol-d(3), salbutamol-d(3), and FP-d(3) were delivered by intravenous (IV) injection. Samples of lung tissue were obtained at 2- and 30-minute postdosing, and high-resolution MSI was used to study drug distribution and retention.Results: IV delivery resulted in homogeneous lung distribution for all molecules. In comparison, while inhalation also gave rise to drug presence in the entire lung, there were regional chemotype-dependent areas of higher abundance. At the 30-minute time point, inhaled salmeterol and salbutamol were preferentially retained in bronchiolar tissue, whereas FP was retained in all regions of the lungs.Conclusion: This study clearly demonstrates that inhaled small molecule chemotypes are differentially distributed in lung tissue after inhalation, and that high-resolution MSI can be applied to study these retention patterns.
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| 3. |
- Loryan, Irena, Associate Professor (Docent), 1977-, et al.
(author)
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Unbound Brain-to-Plasma Partition Coefficient, K-p,K-uu,K-brain-a Game Changing Parameter for CNS Drug Discovery and Development
- 2022
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In: Pharmaceutical research. - : Springer Nature. - 0724-8741 .- 1573-904X. ; 39:7, s. 1321-1341
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Journal article (peer-reviewed)abstract
- Purpose More than 15 years have passed since the first description of the unbound brain-to-plasma partition coefficient (K-p,K-uu,K-brain) by Prof. Margareta Hammarlund-Udenaes, which was enabled by advancements in experimental methodologies including cerebral microdialysis. Since then, growing knowledge and data continue to support the notion that the unbound (free) concentration of a drug at the site of action, such as the brain, is the driving force for pharmacological responses. Towards this end, K-p,K-uu,K-brain is the key parameter to obtain unbound brain concentrations from unbound plasma concentrations. Methods To understand the importance and impact of the K-p,K-uu,K-brain concept in contemporary drug discovery and development, a survey has been conducted amongst major pharmaceutical companies based in Europe and the USA. Here, we present the results from this survey which consisted of 47 questions addressing: 1) Background information of the companies, 2) Implementation, 3) Application areas, 4) Methodology, 5) Impact and 6) Future perspectives. Results and conclusions From the responses, it is clear that the majority of the companies (93%) has established a common understanding across disciplines of the concept and utility of K-p,K-uu,K-brain as compared to other parameters related to brain exposure. Adoption of the K-p,K-uu,K-brain concept has been mainly driven by individual scientists advocating its application in the various companies rather than by a top-down approach. Remarkably, 79% of all responders describe the portfolio impact of K-p,K-uu,K-brain implementation in their companies as 'game-changing'. Although most companies (74%) consider the current toolbox for K-p,K-uu,K-brain assessment and its validation satisfactory for drug discovery and early development, areas of improvement and future research to better understand human brain pharmacokinetics/pharmacodynamics translation have been identified.
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| 4. |
- Nyman, Elin, et al.
(author)
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Mechanisms of a sustained anti-inflammatory drug response in alveolar macrophages unraveled with mathematical modeling
- 2020
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In: CPT. - : John Wiley & Sons. - 2163-8306. ; 9:12, s. 707-717
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Journal article (peer-reviewed)abstract
- Both initiation and suppression of inflammation are hallmarks of the immune response. If not balanced, the inflammation may cause extensive tissue damage, which is associated with common diseases, e.g. asthma and atherosclerosis. Anti-inflammatory drugs come with side-effects which may be aggravated by high and fluctuating drug concentrations. To remedy this, an anti-inflammatory drug should have an appropriate pharmacokinetic half-life or better still: a sustained anti-inflammatory drug response. However, we still lack a quantitative mechanistic understanding of such sustained effects. Here, we study the anti-inflammatory response to a common glucocorticoid drug, Dexamethasone. We find a sustained response 22 hours after drug removal. With hypothesis testing using mathematical modeling, we unravel the underlying mechanism - a slow release of Dexamethasone from the receptor-drug complex. The developed model is in agreement with time-resolved training and testing data, and is used to simulate hypothetical treatment schemes. This work opens up for a more knowledge-driven drug development, to find sustained anti-inflammatory responses and fewer side effects.
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| 5. |
- Sadiq, Muhammad Waqas, et al.
(author)
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Lung pharmacokinetics of inhaled and systemic drugs : A clinical evaluation
- 2021
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In: British Journal of Pharmacology. - : John Wiley & Sons. - 0007-1188 .- 1476-5381. ; 178:22, s. 4440-4451
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Journal article (peer-reviewed)abstract
- Background and Purpose Human pharmacokinetic studies of lung-targeted drugs are typically limited to measurements of systemic plasma concentrations, which provide no direct information on lung target-site concentrations. We aimed to evaluate lung pharmacokinetics of commonly prescribed drugs by sampling different lung compartments after inhalation and oral administration. Experimental Approach Healthy volunteers received single, sequential doses of either inhaled salbutamol, salmeterol and fluticasone propionate (n = 12), or oral salbutamol and propranolol (n = 6). Each participant underwent bronchoscopies and gave breath samples for analysis of particles in exhaled air at two points after drug administration (1 and 6, 2 and 9, 3 and 12, or 4 and 18 h). Lung samples were taken via bronchosorption, bronchial brush, mucosal biopsy and bronchoalveolar lavage during each bronchoscopy. Blood samples were taken during the 24 h after administration. Pharmacokinetic profiles were generated by combining data from multiple individuals, covering all sample timings. Key Results Pharmacokinetic profiles were obtained for each drug in lung epithelial lining fluid, lung tissue and plasma. Inhalation of salbutamol resulted in approximately 100-fold higher concentrations in lung than in plasma. Salmeterol and fluticasone concentration ratios in lung versus plasma were higher still. Bronchosorption- and bronchoalveolar-lavage-generated profiles of inhaled drugs in epithelial lining fluid were comparable. For orally administered drugs, epithelial-lining-fluid concentrations were overestimated in bronchoalveolar-lavage-generated profiles. Conclusion and Implications Combining pharmacokinetic data derived from several individuals and techniques sampling different lung compartments enabled generation of pharmacokinetic profiles for evaluation of lung targeting after inhaled and oral drug delivery.
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| 6. |
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| 7. |
- Wieslander, Håkan, et al.
(author)
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Deep learning and conformal prediction for hierarchical analysis of large-scale whole-slide tissue images
- 2021
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In: IEEE journal of biomedical and health informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-2194 .- 2168-2208. ; 25:2, s. 371-380
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Journal article (peer-reviewed)abstract
- With the increasing amount of image data collected from biomedical experiments there is an urgent need for smarter and more effective analysis methods. Many scientific questions require analysis of image subregions related to some specific biology. Finding such regions of interest (ROIs) at low resolution and limiting the data subjected to final quantification at high resolution can reduce computational requirements and save time. In this paper we propose a three-step pipeline: First, bounding boxes for ROIs are located at low resolution. Next, ROIs are subjected to semantic segmentation into sub-regions at mid-resolution. We also estimate the confidence of the segmented sub-regions. Finally, quantitative measurements are extracted at high resolution. We use deep learning for the first two steps in the pipeline and conformal prediction for confidence assessment. We show that limiting final quantitative analysis to sub regions with high confidence reduces noise and increases separability of observed biological effects.
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