A model-based approach using GSK3772847, an anti-interleukin-33 receptor monoclonal antibody, as a showcase to predict SC administration PK and free target dynamics based on PK and total target measurements after IV administration.

Integrated modeling of the pharmacokinetic (PK) and target binding, by means of a TMDD model, can provide valuable insights into the expected pharmacodynamic (PD) effects of monoclonal antibodies (mAbs). Optimal characterization of the human PK and target binding for mAbs requires data obtained after intravenous (IV) administration which can be combined with subcutaneous (SC) data to further this characterization. Integration of free and/or total target measurements in a population TMDD model will allow quantification of target engagement which is the first step in the cascade leading to efficacy. However, the assays for determination of free target concentrations are analytically challenging and are inherently biased to overpredict the true concentrations in the presence of mAb:target complexes. For that reason, the objective of the current research was to evaluate the predictive value of free target concentrations in a TMDD model developed using PK and total target observations only. Further, a secondary objective was to demonstrate that prediction of SC data is feasible, based on an existing IV model and typical values of mAb parameters reported for SC absorption. GSK3772847, a human immunoglobulin G2 sigma isotype (IgG2f) mAb that binds to the extracellular domain of the interleukin-33 receptor (IL-33R or ST2) and neutralizes IL-33-mediated ST2 signaling, was used as a model compound for mAbs in this study.

Two new user-friendly methods to assess pharmacometric parameter identifiability on categorical and continuous scales.

Parameter identifiability methods assess whether the parameters of a model are uniquely determined by the observations. While the success of a model fit can provide some information on this, it can be valuable to determine identifiability before any fit has been attempted, or to separate identifiability from other issues. Two concepts that lean themselves well for identifiability analysis and have been underutilized are the sensitivity matrix (SM) and the Fisher information matrix (FIM). This paper presents two newly developed methods, one based on the SM and one based on the FIM. Both methods can assess local identifiability for a wide set of models, can be used with limited effort, and are freely available. The methods require the proposed model in the form of a set of differential equations, the parameter values, and the study design as input. They can be used a priori, as they do not need observed values or a successful model fit. Traditional methods provide a single categorical (yes/no) answer to the question of identifiability. In many cases, this is not very informative, and identifiability depends on study design (e.g., dose levels or observation times) and parameter values. Indicators on a continuous scale characterizing the level of identifiability would provide more detailed and relevant information, for example, to guide model development. Our two methods provide both categorical and continuous indicators. Both methods indicate which parameter combinations are difficult to identify by calculating the directions in parameter space that are least identifiable. The methods were validated with an example problem.

Navigating the landscape of parameter identifiability methods: A workflow recommendation for model development.

In pharmacometric modeling, it is often important to know whether the data is sufficiently rich to identify the parameters of a proposed model. While it may be possible to assess this based on the results of a model fit, it is often difficult to disentangle identifiability issues from other model fitting and numerical problems. Furthermore, it can be of value to ascertain identifiability beforehand. This paper compares four methods for parameter identifiability, namely Differential Algebra for Identifiability of SYstems (DAISY), the sensitivity matrix method (SMM), Aliasing, and the Fisher information matrix method (FIMM). We discuss the characteristics of the methods and apply them to a set of applications, consisting of frequently used PK model structures, with suitable dosing regimens and sampling times. These applications were selected to validate the methods and demonstrate their usefulness. While traditional identifiability analysis provides a categorical result [PLoS One, 6, 2011, e27755; CPT Pharmacometrics Syst Pharmacol, 8, 2019, 259; Bioinformatics, 30, 2014, 1440], we argue that in practice a continuous scale better reflects the limitations on the data and is more informative. The methods were generally consistent in their evaluation of the applications. The Fisher information matrix method seemed to provide the most consistent answers. All methods provided information on the parameters that were unidentifiable. Some of the results were unexpected, indicating identifiability issues where none were foreseen, but could be explained upon further analysis. This illustrated the usefulness of identifiability assessment.

Pharmacokinetics and pharmacodynamics of finerenone in patients with chronic kidney disease and type 2 diabetes: Insights based on FIGARO-DKD and FIDELIO-DKD.

AIMS: To perform dose-exposure-response analyses to determine the effects of finerenone doses. MATERIALS AND METHODS: Two randomized, double-blind, placebo-controlled phase 3 trials enrolling 13 026 randomized participants with type 2 diabetes (T2D) from global sites, each with an estimated glomerular filtration rate (eGFR) of 25 to 90 mL/min/1.73 m2 , a urine albumin-creatinine ratio (UACR) of 30 to 5000 mg/g, and serum potassium ≤ 4.8 mmol/L were included. Interventions were titrated doses of finerenone 10 or 20 mg versus placebo on top of standard of care. The outcomes were trajectories of plasma finerenone and serum potassium concentrations, UACR, eGFR and kidney composite outcomes, assessed using nonlinear mixed-effects population pharmacokinetic (PK)/pharmacodynamic (PD) and parametric time-to-event models. RESULTS: For potassium, lower serum levels and lower rates of hyperkalaemia were associated with higher doses of finerenone 20 mg compared to 10 mg (p < 0.001). The PK/PD model analysis linked this observed inverse association to potassium-guided dose titration. Simulations of a hypothetical trial with constant finerenone doses revealed a shallow but increasing exposure-potassium response relationship. Similarly, increasing finerenone exposures led to less than dose-proportional increasing reductions in modelled UACR. Modelled UACR explained 95% of finerenone's treatment effect in slowing chronic eGFR decline. No UACR-independent finerenone effects were identified. Neither sodium-glucose cotransporter-2 (SGLT2) inhibitor nor glucagon-like peptide-1 receptor agonist (GLP-1RA) treatment significantly modified the effects of finerenone in reducing UACR and eGFR decline. Modelled eGFR explained 87% of finerenone's treatment effect on kidney outcomes. No eGFR-independent effects were identified. CONCLUSIONS: The analyses provide strong evidence for the effectiveness of finerenone dose titration in controlling serum potassium elevations. UACR and eGFR are predictive of kidney outcomes during finerenone treatment. Finerenone's kidney efficacy is independent of concomitant use of SGLT2 inhibitors and GLP-1RAs.

Longitudinal efficacy and safety modeling and simulation framework to aid dose selection of belantamab mafodotin for patients with multiple myeloma.

Belantamab mafodotin, a monomethyl auristatin F (MMAF)-containing monoclonal antibody-drug conjugate (ADC), demonstrated deep and durable responses in the DRiving Excellence in Approaches to Multiple Myeloma (DREAMM)-1 and pivotal DREAMM-2 studies in patients with relapsed/refractory multiple myeloma. As with other MMAF-containing ADCs, ocular adverse events were observed. To predict the effects of belantamab mafodotin dosing regimens and dose-modification strategies on efficacy and ocular safety end points, DREAMM-1 and DREAMM-2 data across a range of doses were used to develop an integrated simulation framework incorporating two separate longitudinal models and the published population pharmacokinetic model. A concentration-driven tumor growth inhibition model described the time course of serum M-protein concentration, a measure of treatment response, whereas a discrete time Markov model described the time course of ocular events graded with the GSK Keratopathy and Visual Acuity scale. Significant covariates included baseline ß2 -microglobulin on growth rate, baseline M-protein on kill rate, extramedullary disease on the effect compartment rate constant, and baseline soluble B cell maturation antigen on maximal effect. Efficacy and safety end points were simulated for various doses with dosing intervals of 1, 3, 6, and 9 weeks and various event-driven dose-modification strategies. Simulations predicted that lower doses and longer dosing intervals were associated with lower probability and lower overall time with Grade 3+ and Grade 2+ ocular events compared with the reference regimen (2.5 mg/kg every 3 weeks), with a less-than-proportional reduction in efficacy. The predicted improved benefit-risk profiles of certain dosing schedules and dose modifications from this integrated framework has informed trial designs for belantamab mafodotin, supporting dose-optimization strategies.

Bread Products from Blends of African Climate Resilient Crops: Baking Quality, Sensory Profile and Consumers' Perception.

With food insecurity rising dramatically in Sub-Saharan Africa, promoting the use of sorghum, cowpea and cassava flours in staple food such as bread may reduce wheat imports and stimulate the local economy through new value chains. However, studies addressing the technological functionality of blends of these crops and the sensory properties of the obtained breads are scarce. In this study, cowpea varieties (i.e., Glenda and Bechuana), dry-heating of cowpea flour and cowpea to sorghum ratio were studied for their effects on the physical and sensory properties of breads made from flour blends. Increasing cowpea Glenda flour addition from 9 to 27% (in place of sorghum) significantly improved bread specific volume and crumb texture in terms of instrumental hardness and cohesiveness. These improvements were explained by higher water binding, starch gelatinization temperatures and starch granule integrity during pasting of cowpea compared to sorghum and cassava. Differences in physicochemical properties among cowpea flours did not significantly affect bread properties and texture sensory attributes. However, cowpea variety and dry-heating significantly affected flavour attributes (i.e., beany, yeasty and ryebread). Consumer tests indicated that composite breads could be significantly distinguished for most of the sensory attributes compared to commercial wholemeal wheat bread. Nevertheless, the majority of consumers scored the composite breads from neutral to positive with regard to liking. Using these composite doughs, chapati were produced in Uganda by street vendors and tin breads by local bakeries, demonstrating the practical relevance of the study and the potential impact for the local situation. Overall, this study shows that sorghum, cowpea and cassava flour blends can be used for commercial bread-type applications instead of wheat in Sub-Saharan Africa.

Effect of Bioprocessing on Techno-Functional Properties of Climate-Resilient African Crops, Sorghum and Cowpea.

Sorghum and cowpea are very compatible for intercropping in hot and dry environments, and they also have complementary nutritional compositions. Thus, the crops have the potential to improve food security in regions threatened by climate change. The aim of this study was to investigate different enzymes (carbohydrate-degrading, proteases and phytases) and lactic acid bacteria (LAB) fermentation to improve the techno-functional properties of sorghum and cowpea flours. Results show that sorghum carbohydrates were very resistant to hydrolysis induced by bioprocessing treatments. Most of the protease treatments resulted in low or moderate protein solubilization (from ca. 6.5% to 10%) in sorghum, while the pH adjustment to 8 followed by alkaline protease increased solubility to 40%. With cowpea, protease treatment combined with carbohydrate-degrading enzymes increased the solubility of proteins from 37% up to 61%. With regard to the techno-functional properties, LAB and amylase treatment decreased the sorghum peak paste viscosities (from 504 to 370 and 325 cPa, respectively), while LAB and chemical acidification increased cowpea viscosity (from 282 to 366 and 468 cPa, respectively). When the bioprocessed sorghum and cowpea were tested in breadmaking, only moderate effects were observed, suggesting that the modifications by enzymes and fermentation were not strong enough to improve breadmaking.

Towards the creation of personalized bakery products using 3D food printing.

Bakery products with interesting color, shape and texture have been created using 3D food printing. Current research focuses on the development of new formulations and the optimization of the printing and post-printing treatment processes, in order to obtain high-quality 3D-printed bakery products. Knowledge about food rheology is useful for the development of dough formulations with good 3D-printability. Additives such as hydrocolloids could improve the printability of dough, and novel ingredients are introduced via 3D printing to produce functional bakery products with potential health benefits. One of the main future promises of 3D printing lies in its ability to produce bakery products that are personalized in terms of sensorial properties and nutritional composition, in order to meet the preferences and dietary requirements of individual consumers. This chapter addresses the most recent developments in 3D-printed bakery foods and highlights some important research topics to further advance this field.

Dose-Exposure-Response Analysis of the Nonsteroidal Mineralocorticoid Receptor Antagonist Finerenone on UACR and eGFR: An Analysis from FIDELIO-DKD.

BACKGROUND AND OBJECTIVE: Finerenone reduces the risk of kidney failure in patients with chronic kidney disease and type 2 diabetes. Changes in the urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) are surrogates for kidney failure. We performed dose-exposure-response analyses to determine the effects of finerenone on these surrogates in the presence and absence of sodium glucose co-transporter-2 inhibitors (SGLT2is) using individual patient data from the FIDELIO-DKD study. METHODS: Non-linear mixed-effects population pharmacokinetic/pharmacodynamic models were used to quantify disease progression in terms of UACR and eGFR during standard of care and pharmacodynamic effects of finerenone in the presence and absence of SGLT2i use. RESULTS: The population pharmacokinetic/pharmacodynamic models adequately described effects of finerenone exposure in reducing UACR and slowing eGFR decline over time. The reduction in UACR achieved with finerenone during the first year predicted its subsequent effect in slowing progressive eGFR decline. SGLT2i use did not modify the effects of finerenone. The population pharmacokinetic/pharmacodynamic model demonstrated with 97.5% confidence that finerenone was at least 94.1% as efficacious in reducing UACR in patients using an SGLT2i compared with patients not using an SGLT2i based on the 95% confidence interval of the SGLT2i-finerenone interaction from 94.1 to 122%. The 95% confidence interval of the SGLT2i-finerenone interaction for the UACR-mediated effect on chronic eGFR decline was 9.5-144%. CONCLUSIONS: We developed a model that accurately describes the finerenone dose-exposure-response relationship for UACR and eGFR. The model demonstrated that the early UACR effect of finerenone predicted its long-term effect on eGFR decline. These effects were independent of concomitant SGLT2i use.

Towards Sustainable Shifts to Healthy Diets and Food Security in Sub-Saharan Africa with Climate-Resilient Crops in Bread-Type Products: A Food System Analysis.

Massive urbanization and increasing disposable incomes favor a rapid transition in diets and lifestyle in sub-Saharan Africa (SSA). As a result, the SSA population is becoming increasingly vulnerable to the double burden of malnutrition and obesity. This, combined with the increasing pressure to produce sufficient food and provide employment for this growing population together with the threat of climate change-induced declining crop yields, requires urgent sustainable solutions. Can an increase in the cultivation of climate-resilient crops (CRCs) and their utilization to produce attractive, convenient and nutritious bread products contribute to climate change adaptation and healthy and sustainable diets? A food system analysis of the bread food value chain in SSA indicates that replacement of refined, mostly imported, wheat in attractive bread products could (1) improve food and nutrition security, (2) bring about a shift to more nutritionally balanced diets, (3) increase economic inclusiveness and equitable benefits, and (4) improve sustainability and resilience of the food system. The food system analysis also provided systematic insight into the challenges and hurdles that need to be overcome to increase the availability, affordability and uptake of CRCs. Proposed interventions include improving the agronomic yield of CRCs, food product technology, raising consumer awareness and directing policies. Overall, integrated programs involving all stakeholders in the food system are needed.

Mechanism-based modeling of the effect of a novel inhibitor of vascular adhesion protein-1 on albuminuria and renal function markers in patients with diabetic kidney disease.

The vascular adhesion protein-1 (VAP-1) inhibitor ASP8232 reduces albuminuria in patients with type 2 diabetes and chronic kidney disease. A mechanism-based model was developed to quantify the effects of ASP8232 on renal markers from a placebo-controlled Phase 2 study in diabetic kidney disease with 12 weeks of ASP8232 treatment. The model incorporated the available pharmacokinetic, pharmacodynamic (plasma VAP-1 concentration and activity), serum and urine creatinine, serum cystatin C, albumin excretion rate, urinary albumin-to-creatinine ratio, and urine volume information in an integrated manner. Drug-independent time-varying changes and different drug effects could be quantified for these markers using the model. Through simulations, this model provided the opportunity to dissect the relationship and longitudinal association between the estimated glomerular filtration rate and albuminuria and to quantify the pharmacological effects of ASP8232. The developed drug-independent model may be useful as a starting point for other compounds affecting the same biomarkers in a similar time scale.

Designing Mechanical Properties of 3D Printed Cookies through Computer Aided Engineering.

Additive manufacturing or 3D printing can be applied in the food sector to create food products with personalized properties such as shape, texture, and composition. In this article, we introduce a computer aided engineering (CAE) methodology to design 3D printed food products with tunable mechanical properties. The focus was on the Young modulus as a proxy of texture. Finite element modelling was used to establish the relationship between the Young modulus of 3D printed cookies with a honeycomb structure and their structure parameters. Wall thickness, cell size, and overall porosity were found to influence the Young modulus of the cookies and were, therefore, identified as tunable design parameters. Next, in experimental tests, it was observed that geometry deformations arose during and after 3D printing, affecting cookie structure and texture. The 3D printed cookie porosity was found to be lower than the designed one, strongly influencing the Young modulus. After identifying the changes in porosity through X-ray micro-computed tomography, a good match was observed between computational and experimental Young's modulus values. These results showed that changes in the geometry have to be quantified and considered to obtain a reliable prediction of the Young modulus of the 3D printed cookies.

Difference in postprandial GLP-1 response despite similar glucose kinetics after consumption of wheat breads with different particle size in healthy men.

PURPOSE: Underlying mechanisms of the beneficial health effects of low glycemic index starchy foods are not fully elucidated yet. We varied the wheat particle size to obtain fiber-rich breads with a high and low glycemic response and investigated the differences in postprandial glucose kinetics and metabolic response after their consumption. METHODS: Ten healthy male volunteers participated in a randomized, crossover study, consuming 13C-enriched breads with different structures; a control bread (CB) made from wheat flour combined with wheat bran, and a kernel bread (KB) where 85 % of flour was substituted with broken wheat kernels. The structure of the breads was characterized extensively. The use of stable isotopes enabled calculation of glucose kinetics: rate of appearance of exogenous glucose, endogenous glucose production, and glucose clearance rate. Additionally, postprandial plasma concentrations of glucose, insulin, glucagon, incretins, cholecystokinin, and bile acids were analyzed. RESULTS: Despite the attempt to obtain a bread with a low glycemic response by replacing flour by broken kernels, the glycemic response and glucose kinetics were quite similar after consumption of CB and KB. Interestingly, the glucagon-like peptide-1 (GLP-1) response was much lower after KB compared to CB (iAUC, P < 0.005). A clear postprandial increase in plasma conjugated bile acids was observed after both meals. CONCLUSIONS: Substitution of 85 % wheat flour by broken kernels in bread did not result in a difference in glucose response and kinetics, but in a pronounced difference in GLP-1 response. Thus, changing the processing conditions of wheat for baking bread can influence the metabolic response beyond glycemia and may therefore influence health.

Can cyclist safety be improved with intelligent transport systems?

In recent years, Intelligent Transport Systems (ITS) have assisted in the decrease of road traffic fatalities, particularly amongst passenger car occupants. Vulnerable Road Users (VRUs) such as pedestrians, cyclists, moped riders and motorcyclists, however, have not been that much in focus when developing ITS. Therefore, there is a clear need for ITS which specifically address VRUs as an integrated element of the traffic system. This paper presents the results of a quantitative safety impact assessment of five systems that were estimated to have high potential to improve the safety of cyclists, namely: Blind Spot Detection (BSD), Bicycle to Vehicle communication (B2V), Intersection safety (INS), Pedestrian and Cyclist Detection System+Emergency Braking (PCDS+EBR) and VRU Beacon System (VBS). An ex-ante assessment method proposed by Kulmala (2010) targeted to assess the effects of ITS for cars was applied and further developed in this study to assess the safety impacts of ITS specifically designed for VRUs. The main results of the assessment showed that all investigated systems affect cyclist safety in a positive way by preventing fatalities and injuries. The estimates considering 2012 accident data and full penetration showed that the highest effects could be obtained by the implementation of PCDS+EBR and B2V, whereas VBS had the lowest effect. The estimated yearly reduction in cyclist fatalities in the EU-28 varied between 77 and 286 per system. A forecast for 2030, taking into accounts the estimated accident trends and penetration rates, showed the highest effects for PCDS+EBR and BSD.

The structure of wheat bread influences the postprandial metabolic response in healthy men.

Postprandial high glucose and insulin responses after starchy food consumption, associated with an increased risk of developing several metabolic diseases, could possibly be improved by altering food structure. We investigated the influence of a compact food structure; different wheat products with a similar composition were created using different processing conditions. The postprandial glucose kinetics and metabolic response to bread with a compact structure (flat bread, FB) was compared to bread with a porous structure (control bread, CB) in a randomized, crossover study with ten healthy male volunteers. Pasta (PA), with a very compact structure, was used as the control. The rate of appearance of exogenous glucose (RaE), endogenous glucose production, and glucose clearance rate (GCR) was calculated using stable isotopes. Furthermore, postprandial plasma concentrations of glucose, insulin, several intestinal hormones and bile acids were analyzed. The structure of FB was considerably more compact compared to CB, as confirmed by microscopy, XRT analysis (porosity) and density measurements. Consumption of FB resulted in lower peak glucose, insulin and glucose-dependent insulinotropic polypeptide (ns) responses and a slower initial RaE compared to CB. These variables were similar to the PA response, except for RaE which remained slower over a longer period after PA consumption. Interestingly, the GCR after FB was higher than expected based on the insulin response, indicating increased insulin sensitivity or insulin-independent glucose disposal. These results demonstrate that the structure of wheat bread can influence the postprandial metabolic response, with a more compact structure being more beneficial for health. Bread-making technology should be further explored to create healthier products.

Reduced-Sodium Lunches Are Well-Accepted by Uninformed Consumers Over a 3-Week Period and Result in Decreased Daily Dietary Sodium Intakes: A Randomized Controlled Trial.

BACKGROUND: Processed foods are major contributors to excessive sodium intake in Western populations. We investigated the effect of food reformulation on daily dietary sodium intake. OBJECTIVE: To determine whether uninformed consumers accept reduced-sodium lunches and to determine the effect of consuming reduced-sodium lunches on 24-hour urinary sodium excretion. DESIGN: A single-blind randomized controlled pretest-posttest design with two parallel treatment groups was used. PARTICIPANTS/SETTING: Participants chose foods in an experimental real-life canteen setting at the Restaurant of the Future in Wageningen, the Netherlands, from May 16 until July 1, 2011. INTERVENTION: After a run-in period with regular foods for both groups, the intervention group (n=36) consumed foods with 29% to 61% sodium reduction (some were partially flavor compensated). The control group (n=38) continued consuming regular foods. MAIN OUTCOME MEASURES: Outcomes for assessment of acceptance were the amount of foods consumed, energy and sodium intake, remembered food liking, and intensity of sensory aspects. Influence on daily dietary sodium intake was assessed by 24-hour urinary sodium excretion. STATISTICAL ANALYSES PERFORMED: Between and within-subject comparisons were assessed by analysis of covariance. RESULTS: Energy intake and amount consumed of each food category per lunch remained similar for both groups. Compared with the control group, the intervention group's sodium intake per lunch was significantly reduced by -1,093 mg (adjusted difference) (95% CI -1,285 to -901), equivalent to 43 mmol sodium. Remembered food liking, taste intensity, and saltiness were scored similarly for almost all of the reduced-sodium foods compared with the regular foods. After consuming reduced-sodium lunches, compared with the control group, intervention participants' 24-hour urinary sodium excretion was significantly lower by -40 mEq (adjusted difference) (95% CI -63 to -16) than after consuming regular lunches, and this reflects a decreased daily sodium intake of 1 g. CONCLUSIONS: Comparing the two treatment groups, consumption of reduced-sodium foods over a 3-week period was well accepted by the uninformed participants in an experimental real-life canteen setting. The reduced-sodium foods did not trigger compensation behavior during the remainder of the day in the intervention group compared with the control group, as reflected by 24-hour urinary sodium excretion. Therefore, offering reduced-sodium foods without explicitly informing consumers of the sodium reduction can contribute to daily sodium intake reduction.

A salt reduction of 50% in bread does not decrease bread consumption or increase sodium intake by the choice of sandwich fillings.

Bread is a major contributor to sodium intake in many countries. Reducing the salt (NaCl) content in bread might be an effective way to reduce overall sodium intake. The objectives of this study were to examine the effects of gradually lowering the salt content in brown bread, with and without flavor compensation (KCl and yeast extract), on bread consumption and sodium intake compensation by choice of sandwich fillings. A total of 116 participants (age: 21 ± 3 y; BMI: 22 ± 2 kg/m²) consumed a buffet-style breakfast on weekdays for 4 wk. Participants received either regular bread (control group: n = 39), bread whose salt content was gradually lowered each week by 0, 31, 52, and 67% (reduced group: n = 38), or bread whose salt content was also gradually lowered each week but which was also flavor compensated (compensated group: n = 39). A reduction of up to 52% of salt in bread did not lead to lower consumption of bread compared to the control (P = 0.57), whereas less bread was consumed when salt was reduced by 67% (P = 0.006). When bread was flavor compensated, however, a reduction of 67% did not lead to lower consumption (P = 0.69). Salt reduction in bread (with and without flavor compensation) did not induce sodium intake compensation (P = 0.31). In conclusion, a salt reduction of up to 52% in bread or even up to 67% in flavor-compensated bread neither affected bread consumption nor choice of sandwich fillings.