| 1. |
- Jacobsson, Jesper, 1984-, et al.
(författare)
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An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles
- 2022
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Ingår i: Nature Energy. - : Springer Nature. - 2058-7546. ; 7:1, s. 107-115
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Tidskriftsartikel (refereegranskat)abstract
- Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences.
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| 2. |
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| 3. |
- Abourraja, Mohamed Nezar, et al.
(författare)
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A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics
- 2022
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Ingår i: Proceedings of the 2022 Winter Simulation Conference. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Demands for health care are becoming overwhelming for healthcare systems around the world regarding theavailability of resources, particularly, in emergency departments (EDs) that are continuously open and mustserve immediately any patient who comes in. Efficient management of EDs and their resources is requiredmore than ever. This could be achieved either by optimizing resource utilization or by the improvement ofhospital layout. This paper investigates, through data-driven simulation alternative designs of workflowsand layouts to operate the ED of the Uppsala University Hospital in Sweden. Results are analyzed tounderstand the requirements across the hospital for reduced waiting times in the ED. The main observationrevealed that introducing a new ward dedicated to patients having complex diagnoses with a capacity ofless than 20 beds leads to lower waiting times. Furthermore, the use of data-mining was of great help inreducing the efforts of building the simulation model.
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| 4. |
- Ahmad, Amais, et al.
(författare)
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IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 4 : Prediction accuracy and software comparisons with improved data and modelling strategies
- 2020
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Ingår i: European journal of pharmaceutics and biopharmaceutics. - : Elsevier BV. - 0939-6411 .- 1873-3441. ; 156, s. 50-63
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Tidskriftsartikel (refereegranskat)abstract
- Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlusTM (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project.Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters.On average, PK parameters (Area Under the Concentration-time curve (AUC0-tlast), Maximal concentration (Cmax), half-life (t1/2)) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC0-tlast and around 90% of the simulations were within 10-fold error for AUC0-tlast. Oral bioavailability (Foral) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE > 1. When compared across different formulations and routes of administration, AUC0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise.
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| 5. |
- Boodaghian Asl, Arsineh, et al.
(författare)
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A hybrid modeling approach to simulate complex systems and classify behaviors
- 2024
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Ingår i: NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS. - : Springer Nature. - 2192-6662. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Many important systems, both natural and artificial, are complex in nature, and models and simulations are one of the main instruments to study them. In this paper, we present an approach where a complex social system is represented at a high level of abstraction as a network, thereby addressing several challenges such as quantification, intervention, adaptation and validation. The network represents the factors that influence the mental health and wellbeing in children and young people. In this article, we present an approach that links a system dynamics simulation to simulate the network and ranking algorithms to measure the vertices' behaviors. The network is enhanced by adding edge strengths in the form of correlations between vertices (established through literature). Such an approach allows us to exploit the network structure to qualify and quantify the vertices of the network, to overlay different processes over the network topology, to add and remove new vertices, and therefore interact dynamically. This in turn allows for the qualification of vertices' importance and network resilience. System dynamics simulation allows for policy analysis, where different scenarios are analyzed by stimulating a set of vertices and the effect over the network is observed. This approach allows for an abstract, flexible, yet comprehensive way of analyzing a complex social network at any scale.
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| 6. |
- Boodaghian Asl, Arsineh, et al.
(författare)
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Simulation and Model Validation for Mental Health Factors Using a Multi-Methodology Hybrid Approach
- 2021
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Ingår i: Proceedings - Winter Simulation Conference. - : Institute of Electrical and Electronics Engineers Inc..
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Konferensbidrag (refereegranskat)abstract
- To promote policy analysis and decision-making in mental health and well-being, simulations are used to scrutinize causal maps and provide policymakers reasonable evidence. This paper proposes and illustrates a multi-methodology hybrid approach by building a hierarchy of models, moving from a systems dynamics model to a simulation based on PageRank to quantify and assess a complex mental health map. The motives are: (1) to aid scenario analysis and comparison for possible policy interventions, (2) to quantify and validate mental health factors, and (3) to gain new insights into the core and confounding factors that affect mental health. The results indicate that the approach identifies factors that cause significant and frequent variation on mental health. Furthermore, validation confirms PageRank accuracy and detects minor fluctuations and variation in model's output behavior.
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| 7. |
- Boodaghian Asl, Arsineh, et al.
(författare)
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Using pageRank and social network analysis to specify mental health factors
- 2021
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Ingår i: Proceedings of the Design Society: 23rd International Conference on Engineering Design, ICED 2021. - : Cambridge University Press (CUP). ; , s. 3379-3388
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Konferensbidrag (refereegranskat)abstract
- Various factors influence mental well-being, and span individual, social and familial levels. These factors are connected in many ways, forming a complex web of factors and providing pathways for developing programs to improve well-being and for further research. These factors can be studied individually using traditional methods and mapped together to be analyzed holistically from a complex system perspective. This study provides a novel approach using PageRank and social network analysis to understand such maps. The motives are: (1) to realize the most influential factors in such complex networks, (2) to understand factors that influence variations from different network aspects. A previously developed map for children's mental well-being was adopted to evaluate the approach. To achieve our motives, we have developed an approach using PageRank and Social Network Analysis. The results indicate that regardless of the network scale, two key factors called "Quantity and Quality of Relationships" and "Advocacy" can influence children's mental well-being significantly. Moreover, the divergence analysis reveals that one factor, "Recognition/Value Placed on well-being at School" causes a wide range of diffusion throughout the system.
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| 8. |
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| 9. |
- Darwich, Adam S., et al.
(författare)
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IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3 : Identifying gaps in system parameters by analysing In Silico performance across different compound classes
- 2017
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 96, s. 626-642
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Tidskriftsartikel (refereegranskat)abstract
- Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp (R) Simulator, and GastroPlus (TM)) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (F-oral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foralwas also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. F-oral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.
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| 10. |
- Darwich, Adam S., et al.
(författare)
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Investigating the Connections Between Delivery of Care, Reablement, Workload, and Organizational Factors in Home Care Services : Mixed Methods Study
- 2023
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Ingår i: JMIR Human Factors. - : JMIR Publications Inc.. - 2292-9495. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Home care is facing increasing demand due to an aging population. Several challenges have been identified in the provision of home care, such as the need for support and tailoring support to individual needs. Goal-oriented interventions, such as reablement, may provide a solution to some of these challenges. The reablement approach targets adaptation to disease and relearning of everyday life skills and has been found to improve health-related quality of life while reducing service use.Objective: The objective of this study is to characterize home care system variables (elements) and their relationships (connections) relevant to home care staff workload, home care user needs and satisfaction, and the reablement approach. This is to examine the effects of improvement and interventions, such as the person-centered reablement approach, on the delivery of home care services, workload, work-related stress, home care user experience, and other organizational factors. The main focus was on Swedish home care and tax-funded universal welfare systems.Methods: The study used a mixed methods approach where a causal loop diagram was developed grounded in participatory methods with academic health care science research experts in nursing, occupational therapy, aging, and the reablement approach. The approach was supplemented with theoretical models and the scientific literature. The developed model was verified by the same group of experts and empirical evidence. Finally, the model was analyzed qualitatively and through simulation methods.Results: The final causal loop diagram included elements and connections across the categories: stress, home care staff, home care user, organization, social support network of the home care user, and societal level. The model was able to qualitatively describe observed intervention outcomes from the literature. The analysis suggested elements to target for improvement and the potential impact of relevant studied interventions. For example, the elements "workload" and "distress" were important determinants of home care staff health, provision, and quality of care.Conclusions: The developed model may be of value for informing hypothesis formulation, study design, and discourse within the context of improvement in home care. Further work will include a broader group of stakeholders to reduce the risk of bias. Translation into a quantitative model will be explored.
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| 11. |
- Darwich, Adam S., et al.
(författare)
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Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy
- 2021
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Ingår i: Annual Review of Pharmacology and Toxicology. - : Annual Reviews Inc.. - 0362-1642 .- 1545-4304. ; 61:36, s. 1-21
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Tidskriftsartikel (refereegranskat)abstract
- Model-informed precision dosing (MIPD) has become synonymous with modern approaches forindividualizing drug therapy, in which the characteristics of each patient are considered as opposedto applying a one-size-fits-all alternative. This review provides a brief account of the currentknowledge, practices, and opinions on MIPD while defining an achievable vision for MIPDin clinical care based on available evidence.We begin with a historical perspective on variabilityin dose requirements and then discuss technical aspects of MIPD, including the need for clinicaldecision support tools, practical validation, and implementation of MIPD in health care.Wealso discuss novel ways to characterize patient variability beyond the common perceptions of geneticcontrol. Finally, we address current debates on MIPD from the perspectives of the new drugdevelopment, health-care economics, and drug regulations.
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| 12. |
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| 13. |
- El-Katheeb, Eman, et al.
(författare)
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Time to revisit Child-Pugh score as the basis for predicting drug clearance in hepatic impairment
- 2021
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Ingår i: Alimentary Pharmacology and Therapeutics. - : Wiley. - 0269-2813 .- 1365-2036. ; 54:4, s. 388-401
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundPrescription information for many drugs entering the market lacks dosage guidance for hepatic impairment. Dedicated studies for assessing the fate of drugs in hepatic impairment commonly stratify patients using Child-Pugh score. Child-Pugh is a prognostic clinical score with limitations in reflecting the liver's metabolic capacity.AimsTo demonstrate the need for better drug dosing approaches in hepatic impairment, summarise the current status, identify knowledge gaps related to drug kinetic parameters in hepatic impairment, propose solutions for predicting the liver disease impact on drug exposure and discuss barriers to dosing guidance in those patients.MethodsRelevant reports on dosage adjustment in hepatic impairment were analysed concerning the prediction of the impairment impact on drug kinetics using physiologically-based pharmacokinetic (PBPK) modelling.ResultsPBPK models are suggested as a potential framework to understand drug clearance changes in hepatic impairment. Quantifying changes in abundance and activity of drug-metabolising enzymes and transporters, understanding the impact of shunting, and accounting for interindividual variations in drug absorption could help in extending the success of these models in hepatically-impaired populations. These variables might not correlate with Child-Pugh score as a whole. Therefore, new metabolic activity markers, imaging techniques and other scoring systems are proposed to either support or substitute Child-Pugh score.ConclusionsMany physiological changes in hepatic impairment determining the fate of drugs do not necessarily correlate with Child-Pugh score. Quantifying these changes in individual patients is essential in future hepatic impairment studies. Further studies assessing Child-Pugh alternatives are recommended to allow better prediction of drug exposure.
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| 14. |
- El-Khateeb, Eman, et al.
(författare)
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Using Prior Knowledge on Systems Through PBPK to Gain Further Insight into Routine Clinical Data on Trough Concentrations: The Case of Tacrolimus in Chronic Kidney Disease
- 2023
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Ingår i: Therapeutic Drug Monitoring. - : Ovid Technologies (Wolters Kluwer Health). - 0163-4356 .- 1536-3694. ; 45:6, s. 743-753
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Tidskriftsartikel (refereegranskat)abstract
- Background: Routine therapeutic drug monitoring (TDM) relies heavily on measuring trough drug concentrations. Trough concentrations are affected not only by drug bioavailability and clearance, but also by various patient and disease factors and the volume of distribution. This often makes interpreting differences in drug exposure from trough data challenging. This study aimed to combine the advantages of top-down analysis of therapeutic drug monitoring data with bottom-up physiologically-based pharmacokinetic (PBPK) modeling to investigate the effect of declining renal function in chronic kidney disease (CKD) on the nonrenal intrinsic metabolic clearance (CLint) of tacrolimus as a case example.Methods: Data on biochemistry, demographics, and kidney function, along with 1167 tacrolimus trough concentrations for 40 renal transplant patients, were collected from the Salford Royal Hospital's database. A reduced PBPK model was developed to estimate CLint for each patient. Personalized unbound fractions, blood-to-plasma ratios, and drug affinities for various tissues were used as priors to estimate the apparent volume of distribution. Kidney function based on the estimated glomerular filtration rate (eGFR) was assessed as a covariate for CLint using the stochastic approximation of expectation and maximization method.Results: At baseline, the median (interquartile range) eGFR was 45 (34.5-55.5) mL/min/1.73 m2. A significant but weak correlation was observed between tacrolimus CLint and eGFR (r = 0.2, P < 0.001). The CLint declined gradually (up to 36%) with CKD progression. Tacrolimus CLint did not differ significantly between stable and failing transplant patients.Conclusions: Kidney function deterioration in CKD can affect nonrenal CLint for drugs that undergo extensive hepatic metabolism, such as tacrolimus, with critical implications in clinical practice. This study demonstrates the advantages of combining prior system information (via PBPK) to investigate covariate effects in sparse real-world datasets.
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| 15. |
- Ling, Stephanie F., et al.
(författare)
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Population Pharmacokinetic Analysis and Simulation of Alternative Dosing Regimens for Biosimilars to Adalimumab and Etanercept in Patients with Rheumatoid Arthritis
- 2024
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Ingår i: Pharmaceutics. - : MDPI AG. - 1999-4923. ; 16:6, s. 702-702
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Tidskriftsartikel (refereegranskat)abstract
- Efficacy to biologics in rheumatoid arthritis (RA) patients is variable and is likely influenced by each patient’s circulating drug levels. Using modelling and simulation, the aim of this study was to investigate whether adalimumab and etanercept biosimilar dosing intervals can be altered to achieve therapeutic drug levels at a faster/similar time compared to the recommended interval. RA patients starting subcutaneous Amgevita or Benepali (adalimumab and etanercept biosimilars, respectively) were recruited and underwent sparse serum sampling for drug concentrations. Drug levels were measured using commercially available kits. Pharmacokinetic data were analysed using a population approach (popPK) and potential covariates were investigated in models. Models were compared using goodness-of-fit criteria. Final models were selected and used to simulate alternative dosing intervals. Ten RA patients starting the adalimumab biosimilar and six patients starting the etanercept biosimilar were recruited. One-compartment PK models were used to describe the popPK models for both drugs; no significant covariates were found. Typical individual parameter estimates were used to simulate altered dosing intervals for both drugs. A simulation of dosing the etanercept biosimilar at a lower rate of every 10 days reached steady-state concentrations earlier than the usual dosing rate of every 7 days. Simulations of altered dosing intervals could form the basis for future personalised dosing studies, potentially saving costs whilst increasing efficacy.
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| 16. |
- Margolskee, Alison, et al.
(författare)
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IMI - oral biopharmaceutics tools project - evaluation of bottom-up PBPK prediction success part 1 : Characterisation of the OrBiTo database of compounds
- 2017
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 96, s. 598-609
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Tidskriftsartikel (refereegranskat)abstract
- Predicting oral bioavailability (F-oral) is of importance for estimating systemic exposure of orally administered drugs. Physiologically-based pharmacokinetic (PBPK) modelling and simulation have been applied extensively in biopharmaceutics recently. The Oral Biopharmaceutical Tools (OrBiTo) project (Innovative Medicines Initiative) aims to develop and improve upon biopharmaceutical tools, including PBPK absorption models. A large-scale evaluation of PBPK models may be considered the first step. Here we characterise the OrBiTo active pharmaceutical ingredient (API) database for use in a large-scale simulation study. The OrBiTo database comprised 83 APIs and 1475 study arms. The database displayed a median logP of 3.60 (2.40-4.58), human blood-to-plasma ratio of 0.62 (0.57-0.71), and fraction unbound in plasma of 0.05 (0.01-0.17). The database mainly consisted of basic compounds (48.19%) and Biopharmaceutics Classification System class II compounds (55.81%). Median human intravenous clearance was 16.9 L/h (interquartile range: 11.6-43.6 L/h; n = 23), volume of distribution was 80.8 L (54.5-239 L; n = 23). The majority of oral formulations were immediate release (IR: 87.6%). Human Foral displayed a median of 0.415 (0.203-0.724; n = 22) for IR formulations. The OrBiTo database was found to be largely representative of previously published datasets. 43 of the APIs were found to satisfy the minimum inclusion criteria for the simulation exercise, and many of these have significant gaps of other key parameters, which could potentially impact the interpretability of the simulation outcome. However, the OrBiTo simulation exercise represents a unique opportunity to perform a large-scale evaluation of the PBPK approach to predicting oral biopharmaceutics.
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| 17. |
- Margolskee, Alison, et al.
(författare)
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IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2 : An introduction to the simulation exercise and overview of results
- 2017
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 96, s. 610-625
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Tidskriftsartikel (refereegranskat)abstract
- Orally administered drugs are subject to a number of barriers impacting bioavailability (F-oral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp (R), and GastroPlus (TM)) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, F-oral and relative AUC (F-rel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.
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| 18. |
- Marzano, Luca, 1995-, et al.
(författare)
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A novel analytical framework for risk stratification of real‐world data using machine learning: A small cell lung cancer study
- 2022
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Ingår i: Clinical and Translational Science. - : Wiley. - 1752-8054 .- 1752-8062. ; 15:10, s. 2437-2447
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Tidskriftsartikel (refereegranskat)abstract
- In recent studies, small cell lung cancer (SCLC) treatment guidelines based on Veterans’ Administration Lung Study Group limited/extensive disease staging and resulted in broad and inseparable prognostic subgroups. Evidence suggests that the eight versions of tumor, node, and metastasis (TNM) staging can play an important role to address this issue. The aim of the present study was to improve the detection of prognostic subgroups from a real-word data (RWD) cohort of patients and analyze their patterns using a development pipeline with thoracic oncologists and machine learning methods. The method detected subgroups of patients informing unsupervised learning (partition around medoids) including the impact of covariates on prognosis (Cox regression and random survival forest). An analysis was carried out using patients with SCLC (n = 636) with stage IIIA–IVB according to TNM classification. The analysis yielded k = 7 compacted and well-separated clusters of patients. Performance status (Eastern Cooperative Oncology Group-Performance Status), lactate dehydrogenase, spreading of metastasis, cancer stage, and CRP were the baselines that characterized the subgroups. The selected clustering method outperformed standard clustering techniques, which were not capable of detecting meaningful subgroups. From the analysis of cluster treatment decisions, we showed the potential of future RWD applications to understand disease, develop individualized therapies, and improve healthcare decision making.
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| 19. |
- Marzano, Luca, 1995-, et al.
(författare)
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Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis
- 2023
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Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. ; 302, s. 18-22
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Tidskriftsartikel (refereegranskat)abstract
- Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinical oncological data with the purpose of studying survival outcomes and chemotherapy treatment decision in a real-world cohort of small cell lung cancer patients treated at Karolinska University Hospital (Stockholm, Sweden). The results highlighted the potential role of process mining in oncology to study prognosis and survival outcomes with longitudinal models directly extracted from clinical data derived from healthcare.
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| 20. |
- Marzano, Luca, 1995-, et al.
(författare)
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Diagnosing an overcrowded emergency department from its Electronic Health Records
- 2024
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Ingår i: Scientific Reports. - : Nature Research. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand its dynamics. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitute a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.
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| 21. |
- McAllister, Mark, et al.
(författare)
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Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series
- 2022
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Ingår i: Pharmaceutics. - : MDPI AG. - 1999-4923. ; 14:5, s. 1010-1010
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Tidskriftsartikel (refereegranskat)abstract
- A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.
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| 22. |
- Melillo, Nicola, et al.
(författare)
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A latent variable approach to account for correlated inputs in global sensitivity analysis
- 2021
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744.
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Tidskriftsartikel (refereegranskat)abstract
- In drug development decision-making is often supported through model-based methods, such as physiologically-based pharmacokinetics (PBPK). Global sensitivity analysis (GSA) is gaining use for quality assessment of model-informed inference. However, the inclusion and interpretation of correlated factors in GSA has proven an issue. Here we developed and evaluated a latent variable approach for dealing with correlated factors in GSA. An approach was developed that describes the correlation between two model inputs through the causal relationship of three independent factors: the latent variable and the unique variances of the two correlated parameters. The latent variable approach was applied to a set of algebraic models and a case from PBPK. Then, this method was compared to Sobol’s GSA assuming no correlations, Sobol’s GSA with groups and the Kucherenko approach. For the latent variable approach, GSA was performed with Sobol’s method. By using the latent variable approach, it is possible to devise a unique and easy interpretation of the sensitivity indices while maintaining the correlation between the factors. Compared methods either consider the parameters independent, group the dependent variables into one unique factor or present difficulties in the interpretation of the sensitivity indices. In situations where GSA is called upon to support model-informed decision-making, the latent variable approach offers a practical method, in terms of ease of implementation and interpretability, for applying GSA to models with correlated inputs that does not violate the independence assumption. Prerequisites and limitations of the approach are discussed.
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| 23. |
- Orfanidis, C., et al.
(författare)
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Monitoring neurological disorders with AI-enabled wearable systems
- 2022
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Ingår i: DigiBiom 2022. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 24-28
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Konferensbidrag (refereegranskat)abstract
- The age distribution has changed in Europe over the last decade. The group of 45 year-olds and above has increased and the median age in the EU is estimated to increase by 4.5 years during the next 3 decades reaching a median age of approximately 48.2 years according to Eurostat. A similar trend is noticeable in the United States, where the median age increased by 3.3 years from 2000 to 2020 according to Statista. Neurological diseases, such as Huntington disease, have a highly variable onset of 30 - 50 years but they are more prevalent to the older population. One of the first observable physical symptoms is chorea which includes random, uncontrollable and involuntary movements. Internet of Things and wearable systems can assist long-term monitoring of digital biomarkers such as plantar pressure and gait pattern which are associated with the aforementioned neurological disease. Emerging artificial intelligence models can be utilized to monitor the related digital biomarkers and check if these demonstrate a potential pattern denoting the presence or the development of a neurological disease. Enabling long-term monitoring by utilizing a unobtrusive wearable will increase the possibilities of early diagnosis, a longer life expectancy, and an improved quality of life for the patient.
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| 24. |
- Scotcher, Daniel, et al.
(författare)
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Physiologically Based Pharmacokinetic Modeling of TransporterMediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats
- 2021
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Ingår i: Molecular Pharmaceutics. - : American Chemical Society (ACS). - 1543-8384 .- 1543-8392. ; 18:8, s. 2997-3009
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Tidskriftsartikel (refereegranskat)abstract
- Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug-drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro-in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis-Menten constant (K-m,K-u) of gadoxetate was 106 mu M (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK-IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE-MRI profiles and elimination from the liver. Therefore, in vivo rat DCE-MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE-MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.
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| 25. |
- Takita, Hiroyuki, et al.
(författare)
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Application of the nested enzyme-within-enterocyte (NEWE) turnover model for predicting the time course of pharmacodynamic effects
- 2020
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Ingår i: CPT. - : Wiley. - 2163-8306. ; 9:11, s. 617-627
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Tidskriftsartikel (refereegranskat)abstract
- The gut wall consists of many biological elements including enterocytes. Rapid turnover, a prominent feature of the enterocytes, has generally been ignored in the development of enterocyte-targeting drugs, although it has a comparable rate to other kinetic rates. Here, we investigated the impact of enterocyte turnover on the pharmacodynamics of enterocyte-targeting drugs by applying a model accounting for turnover of enterocytes and target proteins. Simulations showed that the pharmacodynamics depend on enterocyte lifespan when drug-target affinity is strong and half-life of target protein is long. Inter-individual variability of enterocyte lifespan, which can be amplified by disease conditions, has a substantial impact on the variability of response. However, our comprehensive literature search showed that the enterocyte turnover causes a marginal impact on currently approved enterocyte-targeting drugs due to their relatively weak target affinities. This study proposes a model-informed drug development approach for selecting enterocyte-targeting drugs and their optimal dosage regimens.
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| 26. |
- Wilson, Clive G., et al.
(författare)
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Integration of advanced methods and models to study drug absorption and related processes : An UNGAP perspective.
- 2022
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 172
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Tidskriftsartikel (refereegranskat)abstract
- This collection of contributions from the European Network on Understanding Gastrointestinal Absorption-related Processes (UNGAP) community assembly aims to provide information on some of the current and newer methods employed to study the behaviour of medicines. It is the product of interactions in the immediate pre-Covid period when UNGAP members were able to meet and set up workshops and to discuss progress across the disciplines. UNGAP activities are divided into work packages that cover special treatment populations, absorption processes in different regions of the gut, the development of advanced formulations and the integration of food and pharmaceutical scientists in the food-drug interface. This involves both new and established technical approaches in which we have attempted to define best practice and highlight areas where further research is needed. Over the last months we have been able to reflect on some of the key innovative approaches which we were tasked with mapping, including theoretical, in silico, in vitro, in vivo and ex vivo, preclinical and clinical approaches. This is the product of some of us in a snapshot of where UNGAP has travelled and what aspects of innovative technologies are important. It is not a comprehensive review of all methods used in research to study drug dissolution and absorption, but provides an ample panorama of current and advanced methods generally and potentially useful in this area.This collection starts from a consideration of advances in a priori approaches: an understanding of the molecular properties of the compound to predict biological characteristics relevant to absorption. The next four sections discuss a major activity in the UNGAP initiative, the pursuit of more representative conditions to study lumenal dissolution of drug formulations developed independently by academic teams. They are important because they illustrate examples of in vitro simulation systems that have begun to provide a useful understanding of formulation behaviour in the upper GI tract for industry. The Leuven team highlights the importance of the physiology of the digestive tract, as they describe the relevance of gastric and intestinal fluids on the behaviour of drugs along the tract. This provides the introduction to microdosing as an early tool to study drug disposition. Microdosing in oncology is starting to use gamma-emitting tracers, which provides a link through SPECT to the next section on nuclear medicine. The last two papers link the modelling approaches used by the pharmaceutical industry, in silico to Pop-PK linking to Darwich and Aarons, who provide discussion on pharmacometric modelling, completing the loop of molecule to man.
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| 27. |
- Yau, Estelle, et al.
(författare)
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Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution
- 2020
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Ingår i: AAPS Journal. - : Springer Nature. - 1550-7416. ; 22:2, s. 1-13
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Tidskriftsartikel (refereegranskat)abstract
- In physiologically based pharmacokinetic (PBPK) modelling, the large number of input parameters, limited amount of available data and the structural model complexity generally hinder simultaneous estimation of uncertain and/or unknown parameters. These parameters are generally subject to estimation. However, the approaches taken for parameter estimation vary widely. Global sensitivity analyses are proposed as a method to systematically determine the most influential parameters that can be subject to estimation. Herein, a global sensitivity analysis was conducted to identify the key drug and physiological parameters influencing drug disposition in PBPK models and to potentially reduce the PBPK model dimensionality. The impact of these parameters was evaluated on the tissue-to-unbound plasma partition coefficients (Kpus) predicted by the Rodgers and Rowland model using Latin hypercube sampling combined to partial rank correlation coefficients (PRCC). For most drug classes, PRCC showed that LogP and fraction unbound in plasma (fup) were generally the most influential parameters for Kpu predictions. For strong bases, blood:plasma partitioning was one of the most influential parameter. Uncertainty in tissue composition parameters had a large impact on Kpu and Vss predictions for all classes. Among tissue composition parameters, changes in Kpu outputs were especially attributed to changes in tissue acidic phospholipid concentrations and extracellular protein tissue:plasma ratio values. In conclusion, this work demonstrates that for parameter estimation involving PBPK models and dimensionality reduction purposes, less influential parameters might be assigned fixed values depending on the parameter space, while influential parameters could be subject to parameters estimation.
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| 28. |
- Zhang, Chen, et al.
(författare)
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Serious Gaming of Logistics Management in Pediatric Emergency Medicine
- 2020
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Ingår i: INTERNATIONAL JOURNAL OF SERIOUS GAMES. - : SERIOUS GAMES SOC. - 2384-8766. ; 7:1, s. 47-77
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Tidskriftsartikel (refereegranskat)abstract
- Access blocks throughout the entire healthcare system and overcrowding issues are pervasive in many emergency departments where the coordination and strategic management of resources could be supported by serious games and simulations approaches. However, existing studies have not addressed the reciprocal relation between patient inflow and working systems in serious games design in order to reflect the logistical features of an emergency department and to facilitate the players improve the work performance of the system. To address the issue, this paper presents a serious game based on a multi-method simulation approach of complex healthcare processes as well as the game mechanics selected to promote understanding the logistical features of an ED, which points to the next level of conducting simulations or gaming aimed for training decision making skills in operative environments. Results of the experiment confirmed that the serious game encouraged participants to proactively manage the human resources of the emergency department. Certain managerial recommendations can be made: a patient flow multiplier of 120% could lead to a significant erosion of the system's defensive ability; however, proactive anticipation from management is the key for making an emergency organization more resilient.
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