Slipping Away: Slippage in hazard ratios over datacuts and its impact on immuno-oncology combination economic evaluations.

OBJECTIVES: This study examines the impact of slippage in hazard ratios (tending towards the null over subsequent datacuts) for overall survival for combination treatment with a PD-(L)-1 inhibitor and a tyrosine kinase inhibitor (TKI) in advanced renal cell carcinoma (RCC). METHODS: Four trials' Kaplan Meier curves were digitized over several datacuts and fitted with standard parametric curves. Accuracy and consistency of early data projections were calculated versus observed restricted mean survival time (RMST) and fitted lifetime survival from the longest follow-up datacut. The change in economically justifiable price (eJP) was calculated fitting the same curve to both arms, using an assumed average utility of 0.7 and willingness-to-pay threshold of £30,000 per QALY. The eJP represents the lifetime justifiable price increment for the new treatment, including differences in drug, administration and disease-related costs. RESULTS: Slippage in hazard ratios was observed in trials with longer follow-up, potentially influenced by subsequent PD-(L)-1 use after TKI monotherapy, early stoppage of PD-(L)-1 and development of resistance. Lognormal and log-logistic curves were more likely to over-predict the observed result; Gompertz and gamma under-predicted. Statistical measures for goodness of fit did not reliably predict the RMST. Large differences in incremental mean life years were observed between even the penultimate and final datacuts for the majority of the fitted curves, meaningfully impacting the eJP. CONCLUSIONS: This work demonstrates the challenge in predicting treatment benefits with novel therapies using immature data. Incorporating information on the impact of subsequent treatment is likely to play a key role in improving predictions.

Evaluation of the effect of CYP2D6 and OCT1 polymorphisms on the pharmacokinetics of tramadol: Implications for clinical safety and dose rationale in paediatric chronic pain.

AIMS: Our investigation aimed to assess the dose rationale of tramadol in paediatric patients considering the effect of CYP2D6/OCT1 polymorphisms on systemic exposure. Recommendations were made for the oral dose of tramadol to be used in a prospective study in children (3 months to < 18 years old) with chronic pain. METHODS: Intravenous pharmacokinetic and genotype data from neonatal patients (n = 46) were available for this analysis. The time course of tramadol and O-desmethyltramadol (M1) concentrations was characterized using a nonlinear mixed effects approach in conjunction with extrapolation principles. Clinical trial simulations were then implemented to explore the effects of polymorphism, maturation and developmental growth on the disposition of tramadol and M1. Reported efficacious exposure range in adult subjects were used as reference. RESULTS: The pharmacokinetics of tramadol and M1 was characterized by a two-compartment model. The total clearance of tramadol (CLPP) comprised CYP2D6-mediated metabolism (CLPM) and other pathways (CLPO). Age-related changes in CLPM, CLPO and M1 clearance (CLMO) were described by a sigmoid function, with CYP2D6 as a covariate on CLPP and CLPM,  and OCT1 on CLMO. Simulation scenarios including different CYP2D6/OCT1 combinations revealed that steady-state concentrations are above the putative ranges for analgesia in >15% and >70% of subjects after doses of 3 and 8 mg/kg, respectively. CONCLUSIONS: In the absence of genotyping, reference exposure ranges can be used to define the dose rationale for tramadol in paediatric chronic pain. However, a starting dose of 0.5 mg/kg/day should be considered, followed by stepwise titration to the desired analgesic response.

Bridging toxicological properties of environmental chemicals between animals and humans using healthy organoid systems.

The application of organoids derived from animal tissues and human-induced pluripotent stem cells to safety assessments of environmental chemicals has been introduced over the last decade. One of the objectives of this approach is to develop an alternative method for animal toxicological studies, while another is to focus on the local reactions of chemicals in each organ/tissue. One of the most important goals is bridging the toxicological properties of chemicals between animals and humans, which may be compared on a level playing field using healthy organoids derived from both animals and humans in vitro, excluding species difference in the absorption, distribution, metabolism, and excretion properties of chemicals in vivo. An overview of the application of organoid systems to safety assessments of environmental chemicals, including general toxicology, developmental toxicology, carcinogenicity, and mutagenicity, was provided herein, and bridging strategies using both animal and human organoids are proposed as a future perspective.

Tumoral Pharmacokinetic-Pharmacodynamic Simulation of Doxorubicin-Encapsulated Polymeric Micelles Using a Tissue-Isolated Tumor Perfusion System.

Pharmacokinetic (PK) elucidation of polymeric micelles delivering anticancer drugs is crucial for accurate antitumor PK-pharmacodynamic (PK-PD) simulations. Particularly, establishing a methodology to quantify the tumor inflow and outflow of anticancer drugs encapsulated in polymeric micelles is an essential challenge. General tumor biodistribution experiments are disadvantageous in that inflow quantification is easy, but outflow quantification is challenging. We addressed this issue by proposing a quantification method that combines a tissue-isolated tumor perfusion system with microdialysis. This method aims to determine tumoral drug inflow and outflow by quantifying the drugs released from the polymeric micelles via a tumor-embedded microdialysis probe and perfusate, respectively. Furthermore, we evaluated the feasibility of this method by perfusing pH-sensitive polyethylene glycol-poly(aspartate-hydrazone-doxorubicin/phenylalanine)n (PPDF-Hyd-DOX) in a tissue-isolated tumor perfusion system, and we quantified tumor inflow and outflow released DOX. Based on the quantitative results, we performed compartmental analyses by incorporating the gamma-distributed delay function and calculated the PK rate constants. These parameters were input into a tumor-bearing rat compartment model for ex vivo-in vivo extrapolation (EVIVE) of the rat plasma PPDF-Hyd-DOX concentrations and simulated intratumorally released DOX concentrations. The simulation profiles demonstrated a good fit with the Walker 256 intratumoral released DOX concentration profiles previously reported. This EVIVE-PK model was coupled with the threshold natural-growth tumor PD model, and PK-PD analysis was performed. This model exhibited a better fit to the tumor weight profile of Walker 256-bearing rats treated with PPDF-Hyd-DOX than that of our previously reported PK-PD model. Thus, EVIVE, based on a tissue-isolated tumor perfusion system with microdialysis, is a promising approach for the PK-PD simulation of polymeric micelle anticancer therapy.

Pharmacometrics-Enhanced Bayesian Borrowing for Pediatric Extrapolation - A Case Study of the DINAMO Trial.

Bayesian borrowing analyses have an important role in the design and analysis of pediatric trials. This paper describes use of a prespecified Pharmacometrics Enhanced Bayesian Borrowing (PEBB) analysis that was conducted to overcome an expectation for reduced statistical power in the pediatric DINAMO trial due to a greater than expected variability in the primary endpoint. The DINAMO trial assessed the efficacy and safety of an empagliflozin dosing regimen versus placebo and linagliptin versus placebo on glycemic control (change in HbA1c over 26 weeks) in young people with type 2 diabetes (T2D). Previously fitted pharmacokinetic and exposure-response models for empagliflozin and linagliptin based on available historical data in adult and pediatric patients with T2D were used to simulate participant data and derive the informative component of a Bayesian robust mixture prior distribution. External experts and representatives from the U.S. Food and Drug Administration provided recommendations to determine the effective sample size of the prior and the weight of the informative prior component. Separate exposure response-based Bayesian borrowing analyses for empagliflozin and linagliptin showed posterior mean and 95% credible intervals that were consistent with the trial results. Sensitivity analyses with a full range of alternative weights were also performed. The use of PEBB in this analysis combined advantages of mechanistic modeling of pharmacometric differences between adults and young people with T2D, with advantages of partial extrapolation through Bayesian dynamic borrowing. Our findings suggest that the described PEBB approach is a promising option to optimize the power for future pediatric trials.

One step toward precision dosing of caffeine in preterm infants: An external evaluation of published population pharmacokinetic models.

BACKGROUND: Several population pharmacokinetic (PopPK) models of caffeine in preterm infants have been published, but the extrapolation of these models to facilitate model-informed precision dosing (MIPD) in clinical practice is uncertain. This study aimed to comprehensively evaluate their predictive performance using an external, independent dataset. METHODS: Data used for external evaluation were based on an independent cohort of preterm infants. Currently available PopPK models for caffeine in preterm infants were identified and re-established. Prediction- and simulation-based diagnostics were used to assess model predictability. The influence of prior information was assessed using Bayesian forecasting. RESULTS: 120 plasma samples from 76 preterm infants were included in the evaluation dataset. Twelve PopPK models of caffeine in preterm infants were re-established based on our previously published study. Although two models showed superior predictive performance, none of the 12 PopPK models met all the clinical acceptance criteria of these external evaluation items. Besides, the external predictive performances of most models were unsatisfactory in prediction- and simulation-based diagnostics. Nevertheless, the application of Bayesian forecasting significantly improved the predictive performance, even with only one prior observation. CONCLUSIONS: Two models that included the most covariates had the best predictive performance across all external assessments. Inclusion of different covariates, heterogeneity of preterm infant characteristics, and different study designs influenced predictive performance. Thorough evaluation is needed before these PopPK models can be implemented in clinical practice. The implementation of MIPD for caffeine in preterm infants could benefit from the combination of PopPK models and Bayesian forecasting as a helpful tool.

General Population Mortality Adjustment in Survival Extrapolation of Cancer Trials: Exploring Plausibility and Implications for Cost-Effectiveness Analyses in HER2-Positive Breast Cancer in Sweden.

BACKGROUND: In economic evaluations of novel therapies, assessing lifetime effects based on trial data often necessitates survival extrapolation, with the choice of model affecting outcomes. The aim of this study was to assess accuracy and variability between alternative approaches to survival extrapolation. METHODS: Data on HER2-positive breast cancer patients from the Swedish National Breast Cancer Register were used to fit standard parametric distribution (SPD) models and excess hazard (EH) models adjusting the survival projections based on general population mortality (GPM). Models were fitted using 6-y data for stage I and II, 4-y data for stage III, and 2-y data for stage IV cancer reflecting an early data cutoff while maintaining sufficient events for comparison of model estimates with actual long-term outcomes. We compared model projections of 15-y survival and restricted mean survival time (RMST) to 15-y registry data and explored the variability between models in extrapolations of long-term survival. RESULTS: Among 11,224 patients compared with the observed registry 15-y RMST estimates across the disease stages, EH cure models provided the most accurate estimates in patients with stage I to III cancer, whereas EH models without cure most closely matched survival in patients with stage IV cancer, in which cure assumption was less plausible. The Akaike information criterion-averaged model projections varied as follows: -8.2% to +5.3% for SPD models, -4.9% to +5.2% for the EH model without a cure assumption, and -19.3% to -0.2% for the EH model with a cure assumption. EH models significantly reduced between-model variance in the predicted RMSTs over a 50-y time horizon compared with SPD models. CONCLUSIONS: EH models may be considered as alternatives to SPD models to produce more accurate and plausible survival extrapolation that accounts for general population mortality. HIGHLIGHTS: Excess hazard (EH) methods have been suggested as an approach to incorporate background mortality rates in economic evaluation using survival extrapolation.We highlight that EH models with or without a cure assumption can produce more accurate survival projections and significantly reduce between-model variability in comparison with standard parametric distribution models across cancer stages.EH models may be a preferred modeling method to reduce model uncertainty in health economic modeling since models that would otherwise have produced implausible extrapolations are constrained by the EH framework.Reduced uncertainty in economic evaluations will enhance the application of evidence-based health care decision making.

Inhibition of human UDP-glucuronosyltransferase (UGT) enzymes by darolutamide: Prediction of in vivo drug-drug interactions.

Darolutamide is a potent second-generation, selective nonsteroidal androgen receptor inhibitor (ARI), which has been approved by the US Food and Drug Administration (FDA) in treating castrate-resistant, non-metastatic prostate cancer (nmCRPC). Whether darolutamide affects the activity of UDP-glucuronosyltransferases (UGTs) is unknown. The purpose of the present study is to evaluate the inhibitory effect of darolutamide on recombinant human UGTs and pooled human liver microsomes (HLMs), and explore the potential for drug-drug interactions (DDIs) mediated by darolutamide through UGTs inhibition. The product formation rate of UGTs substrates with or without darolutamide was determined by HPLC or UPLC-MS/MS to estimate the inhibitory effect and inhibition modes of darolutamide on UGTs were evaluated by using the inhibition kinetics experiments. The results showed that 100 µM darolutamide exhibited inhibitory effects on most of the 12 UGTs tested. Inhibition kinetic studies of the enzyme revealed that darolutamide noncompetitively inhibited UGT1A1 and competitively inhibited UGT1A7 and 2B15, with the Ki of 14.75 ± 0.78 µM, 14.05 ± 0.42 µM, and 6.60 ± 0.08 µM, respectively. In particular, it also potently inhibited SN-38, the active metabolite of irinotecan, glucuronidation in HLMs with an IC50 value of 3.84 ± 0.46 µM. In addition, the in vitro-in vivo extrapolation (IVIVE) method was used to quantitatively predict the risk of darolutamide-mediated DDI via inhibiting UGTs. The prediction results showed that darolutamide may increase the risk of DDIs when administered in combination with substrates of UGT1A1, UGT1A7, or UGT2B15. Therefore, the combined administration of darolutamide and drugs metabolized by the above UGTs should be used with caution to avoid the occurrence of potential DDIs.

Paediatric Drug Development in Japan: Current Status and Future Challenges.

INTRODUCTION: Until around 2000, the number of medicinal products labelled for paediatric use was limited worldwide. Regulatory measures to promote paediatric drug development in the US and Europe and the establishment of an international guideline (ICH-E11) have led to an increase in the number of paediatric labels. In Japan, efforts have been made to promote the development of paediatric drugs. This study was aimed to examine whether these supportive efforts are successful in Japan. METHODS: This study examined the number of new drugs approved for paediatric indications in Japan from 2006 to 2023, as well as the clinical data package, that is, characteristics of the approved paediatric drugs and paediatric clinical trials, and the percentage of extrapolation of adult data, in the most recent 9-year period. RESULTS: The number of paediatric drug approvals showed an increasing trend between 2006 and 2023 with some fluctuations. The proportion of drugs indicated for paediatric patients to the total number of approved drugs was about 30% until 2022, but increased to 48% in 2023. During the period from 2015 to 2023, simultaneous development in adults and children accounted for 59% (159/269) of paediatric development, but the complete extrapolation of adult data to paediatric populations has not been widely utilized (11.2%, 30/269). CONCLUSIONS: The number of paediatric drug approvals has shown an upward trend, suggesting that measures to promote the development of paediatric drugs may have been exerting a favourable effect in Japan. However, there is still a limited number of drugs that have additional indications for paediatric use. Appropriate development strategies, such as the extrapolation of adult data to paediatric populations, should be considered if scientifically justified.

In Vitro Hepatic Clearance Evaluations of Per- and Polyfluoroalkyl Substances (PFAS) across Multiple Structural Categories.

Toxicokinetic (TK) assays and in vitro-in vivo extrapolation (IVIVE) models are New Approach Methods (NAMs) used to translate in vitro points of departure to exposure estimates required to reach equivalent blood concentrations. Per- and polyfluoroalkyl substances (PFAS) are a large chemical class with wide-ranging industrial applications for which only limited toxicity data are available for human health evaluation. To address the lack of TK data, a pooled primary human hepatocyte suspension model was used with targeted liquid chromatography-mass spectrometry to investigate substrate depletion for 54 PFAS. A median value of 4.52 µL/(min x million cells) was observed across those that showed significant clearance, with 35 displaying no substrate depletion. Bayesian modeling propagated uncertainty around clearance values for use in IVIVE models. Structural evaluations showed the fluorotelomer carboxylic acids were the only PFAS carboxylates showing appreciable clearance, and per- and polyfluorosulfonamides were more readily metabolized than other PFAS sulfonates. Biotransformation product prediction, using the chemical transformation simulator, suggested hydrolysis of PFAS sulfonamides to more stable sulfonic acids, which is an important consideration for exposure modeling. This effort greatly expands the PFAS in vitro toxicokinetic dataset, enabling refined TK modeling, in silico tool development, and NAM-based human health evaluations across this important set of emerging contaminants.

Template-based synergy extrapolation analysis for prediction of muscle excitations.

Objective.Accurate prediction of unmeasured muscle excitations can reduce the required wearable surface electromyography (sEMG) sensors, which is a critical factor in the study of physiological measurement. Synergy extrapolation uses synergy excitations as building blocks to reconstruct muscle excitations. However, the practical application of synergy extrapolation is still limited as the extrapolation process utilizes unmeasured muscle excitations it seeks to reconstruct. This paper aims to propose and derive methods to provide an avenue for the practical application of synergy extrapolation with non-negative matrix factorization (NMF) methods.Approach.Specifically, a tunable Gaussian-Laplacian mixture distribution NMF (GLD-NMF) method and related multiplicative update rules are derived to yield appropriate synergy excitations for extrapolation. Furthermore, a template-based extrapolation structure (TBES) is proposed to extrapolate unmeasured muscle excitations based on synergy weighting matrix templates totally extracted from measured sEMG datasets, improving the extrapolation performance. Moreover, we applied the proposed GLD-NMF method and TBES to selected muscle excitations acquired from a series of single-leg stance tests, walking tests and upper limb reaching tests.Main results.Experimental results show that the proposed GLD-NMF and TBES could extrapolate unmeasured muscle excitations accurately. Moreover, introducing synergy weighting matrix templates could decrease the number of sEMG sensors in a series of experiments. In addition, verification results demonstrate the feasibility of applying synergy extrapolation with NMF methods.Significance.With the TBES method, synergy extrapolation could play a significant role in reducing data dimensions of sEMG sensors, which will improve the portability of sEMG sensors-based systems and promotes applications of sEMG signals in human-machine interfaces scenarios.

Population Modeling in Metal Risk Assessment: Extrapolation of Toxicity Tests to the Population Level.

Population models can be a useful tool for ecological risk assessment to increase ecological realism. In the present study, population models were used to extrapolate toxicity test results of four metals (Ag, Cu, Ni, Zn) to the population level. In total, three primary producers, five invertebrate species, and five fish species were covered. The ecological modeling-based laboratory to population effect extrapolation factor (ECOPEX factor), defined as the ratio of the predicted 10% effect concentration (EC10) at the population level and the observed EC10 for the laboratory toxicity test, ranged from 0.7 to 78.6, with a median of 2.8 (n = 27). Population modeling indicated clearly higher effect concentrations in most of the cases (ECOPEX factor >2 in 14 out of 27 cases), but in some cases the opposite was observed (in three out of 27 cases). We identified five main contributors to the variability in ECOPEX factors: (1) uncertainty about the toxicity model, (2) uncertainty about the toxicity mechanism of the metal, (3) uncertainty caused by test design, (4) impact of environmental factors, and (5) impact of population endpoint chosen. Part of the uncertainty results from a lack of proper calibration data. Nonetheless, extrapolation with population models typically reduced the variability in EC10 values between tests. To explore the applicability of population models in a regulatory context, we included population extrapolations in a species sensitivity distribution for Cu, which increased the hazardous concentration for 5% of species by a factor 1.5 to 2. Furthermore, we applied a fish population model in a hypothetical Water Framework Directive case using monitored Zn concentrations. This article includes recommendations for further use of population models in (metal) risk assessment. Environ Toxicol Chem 2024;43:2308-2328. © 2024 SETAC.

Estimating expected years of life lost of psychiatric disorders in Taiwan: A Nationwide cohort study.

OBJECTIVES: This study employed a national longitudinal cohort to assess expected years of life lost (EYLL) in newly diagnosed psychiatric patients. METHODS: Data from Taiwan's National Death Registry and Health Insurance Research Database were scrutinized to identify patients with various psychiatric disorders. Disorders were ranked hierarchically, and age groups were categorized as young, middle-aged, and older adults. We utilized the semiparametric survival extrapolation method to estimate life expectancy (LE) and EYLL. Modifying effect of comorbid conditions and socioeconomic characteristics were also explored. RESULTS: Among the 5,757,431 cases, young adults with dementia, alcohol use disorder, schizophrenia, and bipolar disorder experienced an excess of 15 years of EYLL. Middle-aged adults faced approximately 9 years or more of EYLL, while older adults had lower EYLL values. Comorbid conditions, low income levels, and living in rural areas were associated with higher EYLL. CONCLUSIONS: This study underscores the substantial EYLL among young adults with psychiatric disorders and the significant impact of specific disorders on EYLL. Early intervention, tailored support, and healthcare system readiness are imperative for improved outcomes. Resource allocation and targeted interventions focusing on early detection and comprehensive treatment can alleviate the economic burden.

Tissue-Engineered Oral Epithelium for Dental Material Testing: Toward In Vitro Biomimetic Models.

Tissue-engineered oral epithelium (ΤΕΟΕ) was developed after comparing various culture conditions, including submerged (SUB) and air-liquid interface (ALI) human cell expansion options. Barrier formation was evaluated via transepithelial electrical resistance (TEER) and calcein permeation via spectrofluorometry. TEOE was further assessed for long-term viability via live/dead staining and development of intercellular connections via transmission electron microscopy. Tissue architecture was evaluated via histochemistry and the expression of pancytokeratin (pCK) via immunohistochemistry. The effect of two commonly used dental resinous monomers on TEOE was evaluated for alterations in cell viability and barrier permeability. ALI/keratinocyte growth factor-supplemented (ALI-KGS) culture conditions led to the formation of an 8-20-layer thick, intercellularly connected epithelial barrier. TEER values of ALI-KGS-developed TEOE decreased compared with all other tested conditions, and the established epithelium intensively expressed pCK. Exposure to dental monomers affected the integrity and architecture of TEOE and induced cellular vacuolation, implicating hydropic degeneration. Despite structural modifications, the permeability of TEOE was not substantially affected after exposure to the monomers. In conclusion, the biological properties of the TEOE mimicking the physiological functional conditions and its value as biocompatibility assessment tool for dental materials were characterized.

Developmental neurotoxicity evaluation of acrylamide based on in vitro to in vivo extrapolation by pregnancy PBTK modelling.

Acrylamide (ACR) is a known neurotoxicant that can pass the placenta and has been detected in breast milk. Some in vivo and in vitro studies indicate that ACR exposure might lead to developmental neurotoxicity (DNT). Here, we have developed a physiologically-based toxicokinetic model for a pregnant human population using PK-Sim. We performed an in vitro to in vivo extrapolation (IVIVE) of data collected from human neuroblastoma SH-SY5Y cells exposed during differentiation to ACR. The developed PBTK model was successfully evaluated and predicted fetal plasma concentrations in the low nM range after exposing the model to an estimated average daily intake for pregnant women. The IVIVE showed that low concentrations of ACR (fM-nM) that induced attenuated differentiation of the SH-SY5Y neuronal cell model, were relevant for human exposure to ACR from oral intake. However, doses estimated in the IVIVE from concentrations in the µM range, were found to be unrealistic by exposure through food intake for an average daily intake. However, in case of exposure due to environmental pollution or occupational exposure, these concentrations may be reached in fetal plasma. The findings in this study raise the concern regarding ACR exposure during pregnancy as well as the relevance of testing concentrations in vitro that are several orders of magnitude higher than the predicted fetal plasma concentrations.

The evolution of clinical trials for pediatric pulmonary hypertension: are the needs of patients and their caregivers being met?

INTRODUCTION: Pediatric pulmonary hypertension is a rare condition. Survival remains poor in the current management era. There is a lack of data regarding the medical management of pediatric pulmonary hypertension and most pulmonary vasodilators are used off-label in children. AREAS COVERED: Pediatric pulmonary hypertension clinical trials' design and realization face many hurdles, including poor recruitment, limited available pharmacologic and physiologic data in children of various ages, ethical issues, and the lack of validated trial endpoint. Innovative clinical trial designs have emerged and may allow us to overcome some of these issues. Extrapolation of adult data to children, with additional pharmacokinetic and safety data, remains extremely important and valid in etiologies where the pediatric and the adult pathophysiologies are believed to be similar. EXPERT OPINION: Close collaboration between sponsors, regulators, patients, caregivers, physicians and researchers is necessary to develop efficacious and safe drugs for pediatric pulmonary hypertension. The increasing involvement of patients' and caregivers' participation in the development of clinical trials should help shape future research that is feasible and meaningful to the patients.

Advancing research and development of anti-infectives for children with a focus on antiretroviral therapy: A clinical development perspective.

The HIV treatment landscape for adults has progressed dramatically in recent decades; however, paediatric populations continue to experience delayed and limited access to effective and safe antiretroviral therapy options. Despite current incentive programmes, formulation research and development and approved drug dosing for children have been limited, particularly for neonates (aged <4 wk). Regulatory approval of drug formulations and dosing in children may lag behind adult approvals by years. Formulation and trial design adjustments complicate paediatric drug development, all of which are vital to accommodate for physiological differences, organ maturation, and rapid weight gain, which are most significant in the youngest children. To facilitate more rapid anti-infective drug development for paediatric populations, regulatory agencies provide guidelines that include extrapolating efficacy and safety data from relevant populations; using pharmacokinetic (PK) bridging and modelling to reduce sample sizes and limit the number of PK studies needed before efficacy analyses; and enrolling age- or weight-based cohorts in parallel rather than sequentially for clinical trials. Ensuring access to approved drugs poses an additional challenge, as uncertainty in demand leads to manufacturing and supply complexity with potentially higher costs that can be a barrier to uptake. Here we summarise challenges in drug development for children living with HIV, which are not unique to antiretrovirals. We aim to propose strategies for how model-based approaches and global partnerships can overcome some of these barriers to accelerate paediatric drug development, with particular reference to HIV, and how lessons learnt from HIV could be extended to other anti-infectives.

Albumin-Mediated Drug Uptake by Organic Anion Transporter 1/3 Is Real: Implications for the Prediction of Active Renal Secretion Clearance.

Modulation of the transport-mediated active uptake by human serum albumin (HSA) for highly protein-bound substrates has been reported and improved the in vitro-to-in vivo extrapolation (IVIVE) of hepatic clearance. However, evidence for the relevance of such a phenomenon in the case of renal transporters is sparse. In this study, transport of renal organic anion transporter 1 or 3 (OAT1/3) substrates into conditionally immortalized proximal tubular epithelial cells transduced with OAT1/3 was measured in the presence and absence of 1 and 4% HSA while keeping the unbound substrate concentration constant (based on measured fraction unbound, fu,inc). In the presence of 4% HSA, the unbound intrinsic active uptake clearance (CLint,u,active) of six highly protein-bound substrates increased substantially relative to the HSA-free control (3.5- to 122-fold for the OAT1 CLint,u,active, and up to 28-fold for the OAT3 CLint,u,active). The albumin-mediated uptake effect (fold increase in CLint,u,active) was more pronounced with highly bound substrates compared to no effect seen for weakly protein-bound substrates adefovir (OAT1-specific) and oseltamivir carboxylate (OAT3-specific). The relationship between OAT1/3 CLint,u,active and fu,inc agreed with the facilitated-dissociation model; a relationship was established between the albumin-mediated fold change in CLint,u,active and fu,inc for both the OAT1 and OAT3, with implications for IVIVE modeling. The relative activity factor and the relative expression factor based on global proteomic quantification of in vitro OAT1/3 expression were applied for IVIVE of renal clearance. The inclusion of HSA improved the bottom-up prediction of the level of OAT1/3-mediated secretion and renal clearance (CLsec and CLr), in contrast to the underprediction observed with the control (HSA-free) scenario. For the first time, this study confirmed the presence of the albumin-mediated uptake effect with renal OAT1/3 transporters; the extent of the effect was more pronounced for highly protein-bound substrates. We recommend the inclusion of HSA in routine in vitro OAT1/3 assays due to considerable improvements in the IVIVE of CLsec and CLr.

Ecological niche modeling of Lactarius deliciosus using kuenm R package: Insights into habitat preferences.

Understanding species habitat preferences is essential for conservation and management efforts, as it enables the identification of areas with a higher likelihood of species presence. Lactarius deliciosus (L.) Gray, an economically important edible mushroom, is influenced by various environmental variables, yet information regarding its ecological niche remains elusive. Therefore, in this study, we aim to address this gap by modeling the fundamental niche of L. deliciosus. Specifically, we explore its distribution patterns in response to large-scale environmental factors, including long-term temperature averages and topography. We employed 242 presence-only georeferenced points in Europe obtained from the Global Biodiversity Information Facility (GBIF). Utilizing the Kuenm R package, we constructed 210 models incorporating five sets of environmental variables, 14 regularization multiplier values, and three feature class combinations. Evaluation metrics included statistical significance, predictive power, and model complexity. The final model was transferred to Turkiye, with careful consideration of extrapolation risk using MESS (multivariate similarity surface) and MoD (most dissimilar variable) metrics. In alignment with all three evaluation criteria, the algorithm implemented in Kuenm identified the best model as the linear-quadratic combination with a regularization multiplier of 0.2, based on variables selected by the contribution importance method. Results underscore temperature-related variables as critical determinants of L. deliciosus habitat preferences within the calibration area, with solar radiation also playing a significant role in the final model. These results underscored the effectiveness of ecological niche modeling (ENM) in understanding how climatic patterns may alter the distribution of species like L. deliciosus. The findings contribute to the development of informed conservation strategies and decision-making in dynamic environments. Emphasizing a comprehensive approach to ecological modeling is crucial for promoting sustainable forest management.

Short-Term Precipitation Radar Echo Extrapolation Method Based on the MS-DD3D-RSTN Network and STLoss Function.

Short-term precipitation forecasting is essential for agriculture, transportation, urban management, and tourism. The radar echo extrapolation method is widely used in precipitation forecasting. To address issues like forecast degradation, insufficient capture of spatiotemporal dependencies, and low accuracy in radar echo extrapolation, we propose a new model: MS-DD3D-RSTN. This model employs spatiotemporal convolutional blocks (STCBs) as spatiotemporal feature extractors and uses the spatial-temporal loss (STLoss) function to learn intra-frame and inter-frame changes for end-to-end training, thereby capturing the spatiotemporal dependencies in radar echo signals. Experiments on the Sichuan dataset and the HKO-7 dataset show that the proposed model outperforms advanced models in terms of CSI and POD evaluation metrics. For 2 h forecasts with 20 dBZ and 30 dBZ reflectivity thresholds, the CSI metrics reached 0.538, 0.386, 0.485, and 0.198, respectively, representing the best levels among existing methods. The experiments demonstrate that the MS-DD3D-RSTN model enhances the ability to capture spatiotemporal dependencies, mitigates forecast degradation, and further improves radar echo prediction performance.