Unexplained Variability Research Articles

Everolimus Concentration in Saliva to Predict Stomatitis: A Feasibility Study in Patients with Cancer.

Most patients with cancer treated with everolimus experience stomatitis, which seriously affects the quality of life. The salivary concentrations of everolimus may predict the incidence and severity of stomatitis. The authors aimed to examine whether it was feasible to quantify the everolimus concentration in saliva and subsequently use it to predict stomatitis. Saliva and whole blood samples were taken from patients with cancer, who were treated with everolimus in the dosage of either 10 mg once a day or 5 mg twice a day. Everolimus concentrations in saliva samples were measured by liquid chromatography-tandem mass spectrometry. A published population pharmacokinetic model was extended with the everolimus concentration in saliva to assess any association between everolimus in the blood and saliva. Subsequently, the association between the occurrence of stomatitis and the everolimus concentration in saliva was studied. Eleven patients were included in this study; saliva samples were available from 10 patients, including 3 patients with low-grade stomatitis. Everolimus concentrations were more than 100-fold lower in saliva than in whole blood (accumulation ratio 0.00801 and relative standard error 32.5%). Interindividual variability (67.7%) and residual unexplained variability (84.0%) were high. The salivary concentration of everolimus tended to be higher in patients with stomatitis, 1 hour postdose ( P = 0.14). Quantification of the everolimus concentration in saliva was feasible and revealed a nonsignificant correlation between everolimus concentration in the saliva and the occurrence of stomatitis. If future research proves this relationship to be significant, the everolimus concentration in the saliva may be used as an early predictor of stomatitis without invasive sampling. Thereby, in patients with high salivary everolimus concentrations, precautions can be taken to decrease the incidence and severity of stomatitis.

Factors affecting inter-individual variability in endoxifen concentrations in patients with breast cancer: results from the prospective TOTAM trial

IntroductionEndoxifen—the principal metabolite of tamoxifen—is subject to a high inter-individual variability in serum concentration. Numerous attempts have been made to explain this, but thus far only with limited success. By applying predictive modeling, we aimed to identify factors that determine the inter-individual variability. Our purpose was to develop a prediction model for endoxifen concentrations, as a strategy to individualize tamoxifen treatment by model-informed dosing in order to prevent subtherapeutic exposure (endoxifen < 16 nmol/L) and thus potential failure of therapy.MethodsTamoxifen pharmacokinetics with demographic and pharmacogenetic data of 303 participants of the prospective TOTAM study were used. The inter-individual variability in endoxifen was analyzed according to multiple regression techniques in combination with multiple imputations to adjust for missing data and bootstrapping to adjust for the over-optimism of parameter estimates used for internal model validation.ResultsKey predictors of endoxifen concentration were CYP2D6 genotype, age and weight, explaining altogether an average-based optimism corrected 57% (95% CI 0.49–0.64) of the inter-individual variability. CYP2D6 genotype explained 54% of the variability. The remaining 3% could be explained by age and weight. Predictors of risk for subtherapeutic endoxifen (< 16 nmol/L) were CYP2D6 genotype and age. The model showed an optimism-corrected discrimination of 90% (95% CI 0.86–0.95) and sensitivity and specificity of 66% and 98%, respectively. Consecutively, there is a high probability of misclassifying patients with subtherapeutic endoxifen concentrations based on the prediction rule.ConclusionThe inter-individual variability of endoxifen concentration could largely be explained by CYP2D6 genotype and for a small proportion by age and weight. The model showed a sensitivity and specificity of 66 and 98%, respectively, indicating a high probability of (misclassification) error for the patients with subtherapeutic endoxifen concentrations (< 16 nmol/L). The remaining unexplained inter-individual variability is still high and therefore model-informed tamoxifen dosing should be accompanied by therapeutic drug monitoring.

A Review of Sentiment, Semantic and Event-Extraction-Based Approaches in Stock Forecasting

Stock forecasting is a significant and challenging task. The recent development of web technologies has transformed the communication channel to allow the public to share information over the web such as news, social media contents, etc., thus causing exponential growth of web data. The massively available information might be the key to revealing the financial market’s unexplained variability and facilitating forecasting accuracy. However, this information is usually in unstructured natural language and consists of different inherent meanings. Although a human can easily interpret the inherent messages, it is still complicated to manually process such a massive amount of textual data due to the constraint of time, ability, energy, etc. Due to the different properties of text sources, it is crucial to understand various text processing approaches to optimize forecasting performance. This study attempted to summarize and discuss the current text-based financial forecasting approaches in the aspect of semantic-based, sentiment-based, event-extraction-based, and hybrid approaches. Afterward, the study discussed the strength and weakness of each approach, followed with their comparison and suitable application scenarios. Moreover, this study also highlighted the future research direction in text-based stock forecasting, where the overall discussion is expected to provide insightful analysis for future reference.

Impact of Hospital Practice and Staffing Differences on Transesophageal Echocardiography Use in Cardiac Valve or Coronary Artery Bypass Graft Surgery

To identify and quantify the predictors of intraoperative transesophageal echocardiography (TEE) use among the patients undergoing cardiac valve or isolated coronary artery bypass graft (CABG) surgery. An observational cohort study. This study used the Centers for Medicare and Medicaid Services administrative claims dataset of the beneficiaries undergoing valve or isolated CABG surgery between 2013 to 2015. Adults aged ≥65 years of age undergoing cardiac valve or isolated CABG surgery. Generalized linear mixed-model (GLMM) analyses were used to examine the relationship between the TEE and patient characteristics, hospital factors, and staffing differences, while accounting for clustering within hospitals. The proportion of variation in TEE use attributable to patient-level characteristics was quantified using odds ratios. Hospital-level factors and staffing differences were quantified using the median odds ratios (MOR) and interval odds ratios (IOR). Among 261,860 patients (123,702 valve procedures and 138,158 isolated CABG), the GLMM analysis demonstrated that the strongest predictor for intraoperative TEE use was the hospital where the surgery occurred (MOR for TEE of 2.57 in valve and 4.16 in isolated CABG). The TEE staffing variable reduced the previously unexplained across-hospital variability by 9% in valve and 21% in isolated CABG, and hospitals with anesthesiologist TEE staffing (versus mixed) were more likely to use TEE in both valve and CABG (MOR for TEE of 1.21 in valve and 1.84 in isolated CABG). Hospital practice was the strongest predictor for TEE use overall. In isolated CABG surgery, hospitals with anesthesiologist TEE staffing were a primary predictor for TEE use.

Genome-Wide Association and Transcriptome-Wide Association Studies Identify Novel Susceptibility Genes Contributing to Colorectal Cancer.

Background Colorectal cancer (CRC) is among the most common cancers diagnosed worldwide. Although genome-wide association studies have effectively identified the genetic basis of CRC, there is still unexplained variability in genetic risk. Transcriptome-wide association studies (TWAS) integrate summary statistics from CRC genome-wide association studies (GWAS) with gene expression data to prioritize these GWAS findings and uncover additional gene-trait correlations. Methods First, we carried out a post-GWAS analysis using summary statistics from a large-scale GWAS of CRC (n = 4,562 cases, n = 382,756 controls). Second, combined with the expression weight sets from GTEx (v7), susceptibility genes were identified with the FUSION software. Colocalization, conditional and fine-mapping analyses, phenome-wide association study (pheWAS), and Mendelian randomization were employed to further characterize the observed correlations. Results In the post-GWAS analyses, we first identified new genome-wide significant associations: three genomic risk loci were identified at 8q24.21 (rs6983267, P = 6.98 × 10−12), 15q13.3 (rs58658771, P = 1.40 × 10−10), and 18q21.1 (rs6507874, P = 1.91 × 10−14). In addition, the TWAS also identified four loci statistically significantly associated with CRC risk, largely explained by expression regulation, including six candidate genes (DUSP10, POU5F1B, C11orf53, COLCA1, COLCA2, and GREM1-AS1). We further discovered evidence that low expression of COLCA2 is correlated with CRC risk with Mendelian randomization. Conclusions We discovered novel CRC risk loci and candidate functional genes by merging gene expression and GWAS summary data, offering new insight into the molecular processes underlying CRC development. This makes it easier to prioritize potential genes for follow-up functional research in CRC.

Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing.

In genes related to drug pharmacokinetics, molecular variations determine interindividual variability in the therapeutic efficacy and adverse drug reactions. The assessment of single-nucleotide variants (SNVs) is used with growing frequency in pharmacogenetic practice, and recently, high-throughput genomic analyses obtained through next-generation sequencing (NGS) have been recognized as powerful tools to identify common, rare and novel variants. These genetic profiles remain underexplored in Latin-American populations, including Colombia. In this study, we investigated the variability of 35 genes included in the ADME core panel (absorption, distribution, metabolism, and excretion) by whole-exome sequencing (WES) of 509 unrelated Colombian individuals with no previous reports of adverse drug reactions. Rare variants were filtered according to the minor allele frequencies (MAF) <1% and potential deleterious consequences. The functional impact of novel and rare missense variants was assessed using an optimized framework for pharmacogenetic variants. Bioinformatic analyses included the identification of clinically validated variants described in PharmGKB and ClinVar databases. Ancestry from WES data was inferred using the R package EthSEQ v2.1.4. Allelic frequencies were compared to other populations reported in the public gnomAD database. Our analysis revealed that rare missense pharmacogenetic variants were 2.1 times more frequent than common variants with 121 variants predicted as potentially deleterious. Rare loss of function (LoF) variants were identified in 65.7% of evaluated genes. Regarding variants with clinical pharmacogenetic effect, our study revealed 89 sequence variations in 28 genes represented by missense (62%), synonymous (22.5%), splice site (11.2%), and indels (3.4%). In this group, ABCB1, ABCC2, CY2B6, CYP2D6, DPYD, NAT2, SLC22A1, and UGTB2B7, are the most polymorphic genes. NAT2, CYP2B6 and DPYD metabolizer phenotypes demonstrated the highest variability. Ancestry analysis indicated admixture in 73% of the population. Allelic frequencies exhibit significant differences with other Latin-American populations, highlighting the importance of pharmacogenomic studies in populations of different ethnicities. Altogether, our data revealed that rare variants are an important source of variability in pharmacogenes involved in the pharmacokinetics of drugs and likely account for the unexplained interindividual variability in drug response. These findings provide evidence of the utility of WES for pharmacogenomic testing and into clinical practice.

Clinical Pharmacokinetics of Gentamicin in Various Patient Populations and Consequences for Optimal Dosing for Gram-Negative Infections: An Updated Review.

Gentamicin is an aminoglycoside antibiotic with a small therapeutic window that is currently used primarily as part of short-term empirical combination therapy. Gentamicin dosing schemes still need refinement, especially for subpopulations where pharmacokinetics can differ from pharmacokinetics in the general adult population: obese patients, critically ill patients, paediatric patients, neonates, elderly patients and patients on dialysis. This review summarizes the clinical pharmacokinetics of gentamicin in these patient populations and the consequences for optimal dosing of gentamicin for infections caused by Gram-negative bacteria, highlighting new insights from the last 10 years. In this period, several new population pharmacokinetic studies have focused on these subpopulations, providing insights into the typical values of the most relevant pharmacokinetic parameters, the variability of these parameters and possible explanations for this variability, although unexplained variability often remains high. Both dosing schemes and pharmacokinetic/pharmacodynamic (PK/PD) targets varied widely between these studies. A gentamicin starting dose of 7 mg/kg based on total body weight (or on adjusted body weight in obese patients) appears to be the optimal strategy for increasing the probability of target attainment (PTA) after the first administration for the most commonly used PK/PD targets in adults and children older than 1 month, including critically ill patients. However, evidence that increasing the PTA results in higher efficacy is lacking; no studies were identified that show a correlation between estimated or predicted PK/PD target attainment and clinical success. Although it is unclear if performing therapeutic drug monitoring (TDM) for optimization of the PTA is of clinical value, it is recommended in patients with highly variable pharmacokinetics, including patients from all subpopulations that are critically ill (such as elderly, children and neonates) and patients on intermittent haemodialysis. In addition, TDM for optimization of the dosing interval, targeting a trough concentration of at least < 2 mg/L but preferably < 0.5–1 mg/L, has proven to reduce nephrotoxicity and is therefore recommended in all patients receiving more than one dose of gentamicin. The usefulness of the daily area under the plasma concentration–time curve for predicting nephrotoxicity should be further investigated. Additionally, more research is needed on the optimal PK/PD targets for efficacy in the clinical situations in which gentamicin is currently used, that is, as monotherapy for urinary tract infections or as part of short-term combination therapy.

Patterns, Predictors, and Intercenter Variability in Empiric Gram-Negative Antibiotic Use Across 928 United States Hospitals.

Empiric antibiotic use among hospitalized adults in the United States (US) is largely undescribed. Identifying factors associated with broad-spectrum empiric therapy may inform antibiotic stewardship interventions and facilitate benchmarking. We performed a retrospective cohort study of adults discharged in 2019 from 928 hospitals in the Premier Healthcare Database. "Empiric" gram-negative antibiotics were defined by administration before day 3 of hospitalization. Multivariable logistic regression models with random effects by hospital were used to evaluate associations between patient and hospital characteristics and empiric receipt of broad-spectrum, compared to narrow-spectrum, gram-negative antibiotics. Of 8 017 740 hospitalized adults, 2 928 657 (37%) received empiric gram-negative antibiotics. Among 1 781 306 who received broad-spectrum therapy, 30% did not have a common infectious syndrome present on admission (pneumonia, urinary tract infection, sepsis, or bacteremia), surgery, or an intensive care unit stay in the empiric window. Holding other factors constant, males were 22% more likely (adjusted odds ratio [aOR], 1.22 [95% confidence interval, 1.22-1.23]), and all non-White racial groups 6%-13% less likely (aOR range, 0.87-0.94), to receive broad-spectrum therapy. There were significant prescribing differences by region, with the highest adjusted odds of broad-spectrum therapy in the US West South Central division. Even after model adjustment, there remained substantial interhospital variability: Among patients receiving empiric therapy, the probability of receiving broad-spectrum antibiotics varied as much as 34+ percentage points due solely to the admitting hospital (95% interval of probabilities: 43%-77%). Empiric gram-negative antibiotic use is highly variable across US regions, and there is high, unexplained interhospital variability. Sex and racial disparities in the receipt of broad-spectrum therapy warrant further investigation.

Pharmacogenetics of Dolutegravir Plasma Exposure Among Southern Africans With Human Immunodeficiency Virus.

Dolutegravir is a component of preferred antiretroviral therapy (ART) regimens. We characterized the pharmacogenetics of dolutegravir exposure after ART initiation in the ADVANCE trial in South Africa. Genome-wide genotyping followed by imputation was performed. We developed a population pharmacokinetic model for dolutegravir using nonlinear mixed-effects modeling. Linear regression models examined associations with unexplained variability in dolutegravir area under the concentration-time curve (AUCVAR). Genetic associations were evaluable in 284 individuals. Of 9 polymorphisms previously associated with dolutegravir pharmacokinetics, the lowest P value with AUCVAR was UGT1A1 rs887829 (P = 1.8 × 10-4), which was also associated with log10 bilirubin (P = 8.6 × 10-13). After adjusting for rs887829, AUCVAR was independently associated with rs28899168 in the UGT1A locus (P = .02), as were bilirubin concentrations (P = 7.7 × 10-8). In the population pharmacokinetic model, rs887829 T/T and C/T were associated with 25.9% and 10.8% decreases in dolutegravir clearance, respectively, compared with C/C. The lowest P value for AUCVAR genome-wide was CAMKMT rs343942 (P = 2.4 × 10-7). In South Africa, rs887829 and rs28899168 in the UGT1A locus were independently associated with dolutegravir AUCVAR. The novel rs28899168 association warrants replication. This study enhances understanding of dolutegravir pharmacogenetics in Africa.

Enantiospecific pharmacokinetics of intravenous dexmedetomidine in beagles.

The goal of this study was to investigate the pharmacokinetic (PK) behaviour of dexmedetomidine in dogs administered as a pure enantiomer versus as part of a racemic mixture. Eight unmedicated intact purpose‐bread beagles were included. Two intravenous treatments of either medetomidine or dexmedetomidine were administered at 10‐ to 14‐day intervals. Atipamezole or saline solution was administered intramuscularly 45 min later. Venous blood samples were collected into EDTA collection tubes, and the quantification of dexmedetomidine and levomedetomidine was performed by chiral LC–MS/MS. All dogs appeared sedated after each treatment without complication. Plasma concentrations of levomedetomidine were measured only in the racemic group and were 51.4% (51.4%–56.1%) lower than dexmedetomidine. Non‐compartmental analysis (NCA) was performed for both drugs, while dexmedetomidine data were further described using a population pharmacokinetic approach. A standard two‐compartment mammillary model with linear elimination with combined additive and multiplicative error model for residual unexplained variability was established for dexmedetomidine. An exponential model was finally retained to describe inter‐individual variability on parameters of clearance (Cl1) and central and peripheral volumes of distribution (V1, V2). No effect of occurrence, levomedetomidine or atipamezole could be observed on dexmedetomidine PK parameters. Dexmedetomidine did not undergo significantly different PK when administered alone or as part of the racemic mixture in otherwise unmedicated dogs.

P677. Sex-Specific Polygenic Regulation of Dopamine Synthesis in Striatum in Vivo

Striatal presynaptic dopamine synthesis is implicated in neuropsychiatric illnesses like schizophrenia but shows considerable unexplained individual variability. We hypothesized that cumulative functional genetic variation in a network of proteins regulating tyrosine hydroxylase (TH), the dopamine synthesis rate-limiting enzyme, would contribute to dopamine synthesis capacity in the living human brain, measured by [18F]-FDOPA PET. Given prior work suggesting sex differences in the regulation of dopamine, we also tested for sex-specific effects.

Explainable Analytics to Predict the Quality of Life in Patients with Prostate Cancer from Longitudinal Data

ABSTRACT Prostate cancer (PCa) is a complicated cancer with high level of unexplained variability that might affect the patient’s health-related quality of life (HRQoL). Using 2670 patients’ information with 433 measures per patient, our objective is to identify the minimal set of important variables which can predict 1-year follow-up HRQoL for PCa patients while adding interpretability to the proposed model. We address three problems of dimension reduction, prediction, and interpretability by first developing deep neural networks on top of a clustering algorithm to extract minimal set of important variables of baseline visit. Second, we build a model to predict a 1-year follow-up of HRQoL for PCa patients using the extracted important baseline variables. Third, we utilize Bayesian networks method to provide insights into the proposed model results to discover the relationship between patients’ baseline variables and their 1-year follow-up satisfaction. The results support the use of the proposed machine-learning technique as an essential tool in identifying potential baseline variables for predicting 1-year HRQoL. Furthermore, our approach to interpret the findings will help to establish guidelines for a better shared decision-making platform for PCa patients.

Improving transparency-A call to include social housing information in biomedical research articles involving nonhuman primates.

The social setting of animal subjects in the research environment has known effects on a variety of dependent measures used in biomedical research. Proper evaluation of the robustness of published research is dependent upon transparent, detailed, and accurate reporting of research methods, including the animals' social housing conditions. However, to date, most research articles utilizing nonhuman primates (NHPs) provide only partial data on this topic, hampering transparency, and reproducibility. Therefore, we call for the inclusion of information pertaining to the social aspects of the animals' housing conditions in publications involving NHPs to improve transparency. We argue that including this information in scientific publications is crucial for the interpretation of research findings in the appropriate contextand for understanding unexplained variability in study findings. Finally, the inclusion of this information in publications will additionally familiarize scientists with how other researchers conducting similar studies are housing their animals and will encourage them to consider the implications of various housing conditions on their research outcomes.

Population Pharmacokinetics of Melphalan for Pediatric Patients Undergoing Hematopoietic Cell Transplantation.

Melphalan is an alkylating agent used as part of conditioning prior to pediatric hematopoietic cell transplantation (HCT). We performed a single-center, prospective pharmacokinetic study of 37 pediatric patients undergoing HCT from March 2015 to 2019. The primary objective was to develop and validate a population pharmacokinetic model for melphalan in a diverse group of pediatric HCT recipients. Nonlinear mixed-effects modeling was implemented to describe plasma concentration-time data of melphalan. A 2-compartment, proportional error model with weight on clearance best fit the data. Final parameter estimates were clearance, 19.1 L/h/25 kg; volume of the central compartment, 8.5 L/25 kg; volume of the peripheral compartment, 5.8 L/25 kg; and intercompartmental clearance 12.4 L/h/25 kg. Residual unexplained variability was low, at 12.5%. Results suggest the empiric weight-based dosing (mg/kg) used in children <12kg or 2 years of age may result in subtherapeutic exposure. Model-based dosing of melphalan in pediatric HCT may help inform individualized dosing strategies to improve clinical outcomes and limit drug-related adverse events in pediatric HCT recipients.

Population Pharmacokinetics of Moxifloxacin in Children.

Moxifloxacin is a fluoroquinolone that is commonly used in adults, but not children. Certain clinical situations compel pediatric clinicians to use moxifloxacin, despite its potential for toxicity and limited pharmacokinetics (PK) data. Our objective was to further characterize the pharmacokinetics of moxifloxacin in children. We performed an opportunistic, open-label population PK study of moxifloxacin in children <18 years of age who received moxifloxacin as part of standard care. A set of structural PK models and residual error models were explored using nonlinear mixed-effects modeling. Covariates with known biological relationships were investigated for their influence on PK parameters. We obtained 43 moxifloxacin concentrations from 14 participants who received moxifloxacin intravenously (n=8) or orally (n=6). The dose of moxifloxacin was 10mg/kg daily in participants ≤40kg and 400mg daily in participants >40kg. The population mean clearance and mean volume of distribution were 18.2L/h and 167L, respectively. The oral absorption was described by a first-order process. The estimated extent of oral bioavailability was highly variable (range 20-91%). Total body weight was identified as a covariate on clearance and volume of distribution, and substantially reduced the random unexplained inter-individual variability for both parameters. No participants experienced suspected serious adverse reactions related to moxifloxacin. These data add to the existing literature to support use of moxifloxacin in children in certain situations; however, further prospective studies on the safety and efficacy of moxifloxacin are needed.

PREDICTIVE PERFORMANCE OF DIFFERENT POPULATION PHARMACOKINETIC MODELS IN A REAL-WORLD COHORT OF CROHN’S DISEASE PATIENTS

Abstract INTRODUCTION We have previously published the results of an infliximab (IFX) population PK model in children and young adults with Crohn’s disease (CD). We found that prediction accuracy was improved with less unexplained variability when the five covariates of drug clearance were included. We also developed a clinical decision support tool (RoadMABTM) to promote physician driven model-informed precision dosing. As IFX has a relatively long half-life, it is currently unknown under what conditions (Bayesian posterior) model performance would be improved. In this study, the aim is to evaluate the precision and bias of three population PK models in a real-world cohort of CD patients. METHODS We investigated CD subjects who were anti-TNF naïve and started IFX induction between 2019-2020 at Cincinnati Children’s Hospital Medical Center. All subjects had a minimum of four IFX doses and a minimum of two IFX concentrations measured with a drug-tolerant assay (Esoterix, LabCorp specialty lab, Calabasas, CA) as a part of their clinical care. We measured the mean predictive error (MPE) and the root mean squared error (RMSE) for describing the bias and precision, respectively, of the prediction of the most recent IFX level (which was excluded from the Bayesian estimation). Predictions were based on the selected PK mode, the available covariates of drug clearance (weight, serum albumin, erythrocyte sedimentation rate, neutrophil CD64 expression and antibody to IFX concentration) and prior IFX levels. Two modes were used to compare model performance. In RoadMABTM, the poly-exponential (POLY-1) mode enables last known covariates (if &amp;lt;182 days) and last known IFX level. The ordinary differential equations (ODE-N) mode enables all covariates within the last 182 days and the last N (-1, -2, -3) IFX levels (Figure 1). RESULTS We identified 105 subjects who met study criteria. The median (IQR) age at first IFX infusion was 14.6 years (11.8-16.8). The median (IQR) starting dose was 8.6 mg/kg (5.4-10) and 47% were female. For all 3 PK models, we found minimal bias and improved precision in the ODE-1 mode (Table1). While there was little difference in the precision (RMSE) when the POLY-1 mode was used, we found an improvement in bias (MPE) in this mode. In a smaller subset (n=36), we also compared model performance to predict an infusion5 or infusion6 level when an infusion4 (week14) level was known. All three models performed equally well in the POLY-1 mode with the Xiong et al. model showing superior precision with ODE-1. Finally, we compared model performance to predict an infusion3 (week6) level from the start of IFX (n=38) based on the covariates of drug clearance alone. CONCLUSION Based on our data, in CD patients, precision dosing for IFX should be largely based on the last known IFX concentration and the most recent covariates of drug clearance.

REAL-WORLD VEDOLIZUMAB PHARMACOKINETIC STUDY IN CHILDREN IDENTIFIES TWO NOVEL BIOMARKERS OF DRUG CLEARANCE

Abstract INTRODUCTION Use of vedolizumab in pediatric inflammatory bowel disease (IBD) often requires an interval intensification from standard dosing due to distinct pharmacokinetics (PK) in children. Adult population PK models found inclusion of albumin, weight, anti-TNF naivety and antibodies-to-vedolizumab (ATV) as covariates of drug clearance (CL) improved model accuracy. We aimed to build a population-PK model for children and identify novel covariates of drug CL to better account for pediatric-specific variability in vedolizumab PK. METHODS This was a prospective multicenter cohort study for pediatric IBD patients starting vedolizumab. Vedolizumab dosing regimens were managed by the treating clinician. Stool, serum and plasma were collected at standardized intervals for robust PK sampling and biomarker analysis. Population PK analysis were conducted with nonlinear mixed effects modeling (NONMEM 7.5). A 1-compartment model with proportional error model was created based on the PK data. In the final model, novel covariates were identified using a stepwise approach. A decrease in the objective function value (OFV) &amp;gt;3.84 was considered significant (P&amp;lt;0.05). RESULTS Twenty-one patients had a total of 277 infusions with 274 measured vedolizumab peak and trough concentrations. Among these, 57% were male, 76% had Crohn’s disease, and 81% had prior anti-TNF exposure. The median (IQR) age was 16 years (13-18), and median weight was 52kg (41-71). Baseline biomarkers are described in Table 1. Baseline CL was inversely correlated with albumin (R=-0.54, P= 0.012), hemoglobin (R=-0.45, P= 0.048), and platelets (R=-0.5, P= 0.026). There was a positive correlation of CL with CRP (R=0.8, P&amp;lt; 0.001), neutrophil CD64 (nCD64, R=0.68, P= 0.001), fecal calprotectin (FCP, R=0.63, P= 0.009), and BSA (R=0.59, P= 0.007). The final model estimated CL as 0.168 L/d (relative standard error (RSE), 13%) and volume (V) distribution as 3.97L (8%). The interindividual variability (IIV) of the final model was 62.2% (25%) of CL and 37% (8%) of V. Covariates that significantly decreased the OFV were incorporated into the final model including weight for V and albumin, ESR, and nCD64 for CL. Prior anti-TNF, immunomodulators (MTX, n=3) or ATV (n=1) did not impact CL. Baseline CL &amp;lt;0.161 L/d predicted an end of induction FCP remission (&amp;lt;250μg/g) with an area under the curve (AUC) 0.7 (sensitivity 0.8, specificity 0.75) with the final model. A cut-off of 37 μg/mL at infusion-3 and 20 μg/mL at infusion-4 predicted end of induction clinical remission (Figure 1). CONCLUSIONS We describe a novel pediatric PK model for vedolizumab that identified novel covariates, including ESR and nCD64, that may guide model-informed precision dosing. Larger cohorts should establish whether additional compartments and pediatric-specific covariates can further decrease the remaining unexplained variability.

PREDICTIVE PERFORMANCE OF DIFFERENT POPULATION PHARMACOKINETIC MODELS IN A REAL-WORLD COHORT OF CROHN’S DISEASE PATIENTS

We have previously published the results of an infliximab (IFX) population PK model in children and young adults with Crohn’s disease (CD). We found that prediction accuracy was improved with less unexplained variability when the five covariates of drug clearance were included. We also developed a clinical decision support tool (RoadMABTM) to promote physician driven model-informed precision dosing. As IFX has a relatively long half-life, it is currently unknown under what conditions (Bayesian posterior) model performance would be improved.

Chapter 19 - Genetics in aphasia recovery

Considerable research efforts have been exerted toward understanding the mechanisms underlying recovery in aphasia. However, predictive models of spontaneous and treatment-induced recovery remain imprecise. Some of the hitherto unexplained variability in recovery may be accounted for with genetic data. A few studies have examined the effects of the BDNF val66met polymorphism on aphasia recovery, yielding mixed results. Advances in the study of stroke genetics and genetics of stroke recovery, including identification of several susceptibility genes through candidate-gene or genome-wide association studies, may have implications for the recovery of language function. The current chapter discusses both the direct and indirect evidence for a genetic basis of aphasia recovery, the implications of recent findings within the field, and potential future directions to advance understanding of the genetics-recovery associations.

Highly Variable Paracetamol Pharmacokinetics After Multiple Oral Dosing in Frail Older People: A Population Pharmacokinetic Analysis.

Paracetamol pharmacokinetics (PK) is highly variable in older fit adults after intravenous administration. Frailty and oral administration likely result in additional variability. The aim was to determine oral paracetamol PK and variability in geriatric inpatients. A population PK analysis, using NONMEM7.2, was performed on 245 paracetamol samples in 40 geriatric inpatients (median age 87 [range 80-95] years, bodyweight 66.4 [49.3-110] kg, 92.5% frail [Edmonton Frail Scale]). All subjects received paracetamol 1000mg as tablet (72.5%) or granulate (27.5%) three times daily. Simulations of dosing regimens (1000mg every 6 hours [q6h] or q8h) were performed to determine target attainment, using mean steady-state concentration (Css-mean) of 10mg/L as target. A one-compartment model with first order absorption and lag time best described the data. The inter-individual variability was high, with absorption rate constant containing the highest variability. The inter-individual variability could not be explained by covariates. Simulations of 1000mg q6h and q8h resulted in a Css-mean of 10.8 [25-75th percentiles 8.2-12.7] and 8.13 [6.3-9.6]mg/L, respectively, for the average geriatric inpatient. The majority of the population remained off-target (22.2% [q6h] and 52.2% [q8h] <8mg/L; 31.3 [q6h] and 7.6% [q8h] >12mg/L). A population of average geriatric inpatients achieved target Css-mean with paracetamol 1000mg q6h, while q8h resulted in underexposure for the majority of them. Due to high unexplained variability, a relevant proportion remained either above or below the target concentration of 10mg/L. Research focusing on PK, efficacy and safety is needed to recommend dosing regimens.