Mixed-effects Modeling Approach Research Articles

Integrating Clopidogrel's First-Pass Effect in a Joint Semi-Physiological Population Pharmacokinetic Model of the Drug and Its Inactive Carboxylic Acid Metabolite.

Clopidogrel (CLO), a pro-drug for preventing thrombotic events, undergoes rapid absorption and extensive metabolism, with approximately 85-90% converted to an inactive carboxylic acid metabolite (CLO-CA) and the remaining to an active thiol (CLO-TH). Few pharmacokinetic models for the drug and its metabolites exist, with most focusing on CLO-TH. Although CLO-CA is inactive, its predominant (compared to its parent drug and metabolites) presence in plasma underscores the importance of characterizing its formation and pharmacokinetic profile. This study aimed to characterize the process of the absorption of CLO and its conversion to CLO-CA via developing a population pharmacokinetic model. Individual participants' data from two bioequivalence studies were utilized. Extensive blood samples were collected at predetermined intervals, including 841 concentrations of CLO and 1149 of CLO-CA. A nonlinear, mixed-effects modelling approach using NONMEM® software (v 7.5) was applied. A one-compartment model was chosen for CLO, while a two-compartment proved optimal for CLO-CA. Absorption from the depot compartment was modeled via two transit compartments, incorporating transit rate constants (Ktr). A semi-physiological model explained the first-pass effect of CLO, integrating a liver compartment. The estimated mean transit times (MTTs) for the studies were 0.470 and 0.410 h, respectively. The relative bioavailability for each study's generic medicine compared to the reference were 1.08 and 0.960, respectively. Based on the estimated parameters, the fractions metabolized to inactive metabolites (FiaM_st1 and FiaM_st2) were determined to be 87.27% and 86.87% for the two studies, respectively. The appropriateness of the final model was confirmed. Our model offers a robust framework for elucidating the pharmacokinetic profiles of CLO and CLO-CA.

Five multivariate Duchenne muscular dystrophy progression models bridging six-minute walk distance and MRI relaxometry of leg muscles.

The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 modelvariables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials.

Population pharmacokinetics of a novel PCSK9 antisense oligonucleotide.

The aim of this study was to characterize the population pharmacokinetics of AZD8233, an antisense oligonucleotide (ASO) that targets the PCSK9 transcript to reduce hepatocyte PCSK9 protein production and plasma levels. AZD8233 utilizes generation 2.5S-constrained ethyl motif (cET) chemistry and is conjugated to a triantennary N-acetylgalactosamine (GalNAc3) ligand for targeted hepatocyte uptake. A non-linear mixed-effect modelling approach utilizing NONMEM software was applied to AZD8233 concentration-time data from 3416 samples in 219 participants from four phase 1-2 studies, one in healthy volunteers (NCT03593785) and three in patients with dyslipidaemia (NCT04155645, NCT04641299 and NCT04823611). The final model described the AZD8233 plasma concentration-time profile from four phase 1-2 studies in healthy volunteers or participants with dyslipidaemia, covering a dose range of 4 to 120 mg. The pharmacokinetics of AZD8233 were adequately described by a two-compartment model with first-order absorption. The supra-proportional increase in maximum plasma concentration (Cmax) across the observed dose range was described by non-linear Michaelis-Menten elimination (maximum elimination rate, 9.9mg/h [12% relative standard error]; concentration yielding half-maximal elimination rate, 4.8mg/L [18% relative standard error]). Body weight, sex, estimated glomerular filtration rate and disease status (healthy participant vs. patient with dyslipidaemia) were identified as factors affecting exposure to AZD8233. Covariate analysis showed body weight to be the main factor affecting exposure to AZD8233, which largely explained the higher Cmax observed in the Asian population relative to non-Asians.

PK Modeling of L-4-Boronophenylalanine and Development of Bayesian Predictive Platform for L-4-Boronophenylalanine PKs for Boron Neutron Capture Therapy.

L-4-[(10B)]Boronophenylalanine (BPA) is an amino acid analogue with a boron-10 moiety. It is most widely used as a boron carrier in boron neutron capture therapy. In this study, a Bayesian predictive platform of blood boron concentration based on a BPA pharmacokinetic (PK) model was developed. This platform is user-friendly and can predict the individual boron PK and optimal time window for boron neutron capture therapy in a simple way. The present study aimed to establish a PK model of L-4-boronophenylalanine and develop a Bayesian predictive platform for blood boron PKs for user-friendly estimation of boron concentration during neutron irradiation of neutron capture therapy. Whole blood boron concentrations from seven previous reports were graphically extracted and analyzed using the nonlinear mixed-effects modeling (NONMEM) approach. Model robustness was assessed using nonparametric bootstrap and visual predictive check approaches. The visual predictive check indicated that the final PK model is able to adequately predict observed concentrations. The Shiny package was used to input real-time blood boron concentration data, and during the following irradiation session blood boron was estimated with an acceptably short calculation time for the determination of irradiation time. Finally, a user-friendly Bayesian estimation platform for BPA PKs was developed to optimize individualized therapy for patients undergoing BNCT.

Understanding hemoglobin contribution to high-dose methotrexate disposition-population pharmacokinetics in pediatric patients with hematological malignancies.

The aim of the present study was to develop a population pharmacokinetic model for methotrexate (MTX) during high-dose treatment (HDMTX) in pediatric patients with acute lymphoblastic leukemia (ALL) and non-Hodgkin's lymphoma (NHL) and to describe the influence of variability factors. The study included 50 patients of both sexes (aged 1-18years) who received 3 or 5g/m2 of HDMTX. A nonlinear mixed effect modeling approach was applied for data analysis. Parameter estimation was performed by first-order conditional estimation method with interaction (FOCEI), whereas stepwise covariate modeling was used to assess variability factors. The final model is a two-compartment model that incorporates the effect of body surface area and the influence of hemoglobin and serum creatinine on MTX clearance (CL). Population pharmacokinetic values for a typical subject were estimated at 5.75 L/h/m2 for clearance (CL), 21.3 L/m2 for volume of the central compartment (V1), 8.2 L/m2 for volume of the peripheral compartment (V2), and 0.087 L/h/m2 for intercompartmental clearance (Q). According to the final model, MTX CL decreases with increasing serum creatinine, whereas a positive effect was captured for hemoglobin. A difference of almost 32% in MTX CL was observed among patients' hemoglobin values reported in the study. The developed population pharmacokinetic model can contribute to the therapy optimization during HDMTX in pediatric patients with ALL and NHL. In addition to renal function and body weight, it describes the influence of hemoglobin on CL, allowing better understanding of its contribution to the disposition of HDMTX.

Slow waves during deep sleep support cardiac function

Introduction The role of sleep in cardiovascular health, particularly the impact of deep non-rapid eye movement (NREM) sleep, is gaining interest in the prevention of cardiovascular diseases (Grandner et al., 2016). Essentially slow waves, prominent brain oscillations during deep sleep, seem to represent an important cardiovascular recovery process for the human body. However, to date, the specific mechanisms through which sleep affects cardiovascular function and whether slow waves accelerate recovery remain elusive. Methods Here, we explored the role of slow waves in promoting cardiovascular function. In this randomized, cross-over trial involving 18 healthy male participants (Huwiler et al., 2023), we investigated how experimentally enhancing slow waves via auditory stimulation (Huwiler et al., 2022) impacts cardiovascular dynamics during sleep and next-day cardiac function, assessed via an echocardiography. All participants underwent three experimental nights including two conditions for slow wave enhancement and one SHAM control condition while brain oscillatory, blood pressure, and cardiac dynamics were continuously measured during sleep. Results Using a linear mixed-effect model approach, we found auditory stimulation to significantly increase slow wave activity (F(2, 33.095) = 11.397, p < 0.001) during times of stimulation. This slow wave enhancement coincided with a dynamic cardiovascular activation, indicated through short increases in blood pressure and a biphasic heart rate response. After sleep, we found a significant increase in general longitudinal strain (F(2, 34) = 81.17, p < 0.001), an increase in left-ventricular ejection fraction (F(2, 34) = 4.55, p = 0.018), and a decrease in E/e’ ratio (F(2, 34) = 3.38, p = 0.046) for both slow wave stimulation conditions compared to SHAM. Discussion/Conclusion We show that slow wave stimulation induces a cardiovascular activation response possibly related to increasing cardiovascular stability during sleep (De Zambotti et al., 2016). Moreover, we demonstrate that slow wave stimulation enhances left-ventricular systolic and diastolic function, both together indicating improved cardiac function. Altogether, this points towards the functional involvement of slow waves in promoting cardiovascular health. Therefore, sleep slow wave stimulation may be considered a potential supplementary method in treating cardiovascular diseases involving decreased left-ventricular function. Furthermore, our findings hint that enhancing slow waves could potentially optimize post-exercise recovery processes and increase cardiovascular well-being.

Drivers of geophagy by red brocket deer (Mazama americana) at Amazonian interior forest mineral licks.

Mineral licks are key ecological components of the Amazon rainforest, providing critical dietary functions for herbivorous and frugivorous mammals and birds, which help maintain the structure and function of the forest itself through seed and nutrient dispersal. One of the most frequent visitors of interior forest mineral licks in the Amazon is the red brocket deer (Mazama americana), a large-bodied ruminant frugivore and seed predator. While several hypotheses for the drivers of geophagy exist, including mineral supplementation, toxin adsorption, and habitat selection, robust data on geophagy for the red brocket deer for large numbers of mineral licks is nonexistent. We used soil data from 83 mineral licks in conjunction with camera trap data from 52 of those mineral licks and a mixed-effects modeling approach to test the three proposed hypotheses of geophagy for the red brocket deer. We found that consumed soils at mineral licks had elevated concentrations of almost all major and minor biologically active minerals measured, including Ca, Na, Mg, K, Cu, Zn, and Mn. Model results suggest that all three hypotheses hold true to some extent for the red brocket deer, with the greatest support for the mineral supplementation hypothesis, in particular with respect to Mg, Ca, Na, Cu, and Zn. This study provides critical information on the feeding ecology of the red brocket deer in the wild, and the first robust analysis of geophagy of an Amazonian mammal involving a large sample size of interior forest mineral licks.

Evaluating Holistic Education and Digital Learning model for advancing SDG4: a longitudinal mixed-effects modeling approach

Evaluating Holistic Education and Digital Learning model for advancing SDG4: a longitudinal mixed-effects modeling approach

Radial increment dynamics of Maritime pine (Pinus pinaster Ait.) in pure and mixed stands with Scots pine (Pinus sylvestris L.) under changing environmental conditions

Forest dynamics are undergoing profound alteration due to the fact that climate change is increasing the frequency and severity of abiotic and biotic forest disturbances. Because of the unpredictable nature of the drought periods and the variation in their severity, Mediterranean forests are typically more vulnerable. Mediterranean Pinus pinaster forests are showing decay symptoms linked to climate change. There is clear evidence that promoting mixtures can serve as an effective forest adaptation strategy. In this regard, we sought to better understand the responses of P. pinaster radial growth dynamics to various factors, in both mixed and pure forest stands, and provide valuable insights into P. pinaster dynamics when mixed with P. sylvestris. In this study, we examined the variation of intra-annual cumulative radial increment patterns in response to the climate of P. pinaster between pure and mixed stands with P. sylvestris. Using data from band dendrometers collected over five consecutive climatically distinct years (2016–2020), a nonlinear mixed-effect model approach was used to analyze the differences in intra-annual cumulative radial increment patterns for P. pinaster between years in mixed and pure stands. The intra-annual radial increment pattern of P. pinaster showed significant year-to-year variation and varied with tree size, with greater increment in larger trees. Trees in mixed stands had a higher mean radial increment compared to corresponding ones in pure stands. Increased summer maximum temperatures negatively affected tree cumulative annual increment regardless of composition, but with a lower impact on trees in pure stands. Spring precipitation increased the length of the growing season, while higher spring maximum temperatures triggered an earlier inflection point. Our results highlight the high plasticity of P. pinaster in adapting to varying intra- and inter-annual environmental conditions and competition with other species and suggest that promoting mixtures with P. sylvestris may be an interesting management strategy for adaptation to climate change.

Population Pharmacokinetic Analysis of Atomoxetine and its Metabolites in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder.

Atomoxetine (ATX) is a non-stimulant used to treat attention-deficit/hyperactivity disorder (ADHD) and systemic exposure is highly variable due to polymorphic cytochrome P450 2D6 (CYP2D6) activity. The objective of this study was to characterize the time course of ATX and metabolites (4-hydroxyatomoxetine (4-OH); N-desmethylatomoxetine (NDA); and 2-carboxymethylatomoxetine (2-COOH)) exposure following oral ATX dosing in children with ADHD to support individualized dosing. A nonlinear mixed-effect modeling approach was used to analyze ATX, 4-OH, and NDA plasma and urine, and 2-COOH urine profiles obtained over 24-72 hours from children with ADHD (n = 23) following a single oral ATX dose. Demographics and CYP2D6 activity score (AS) were evaluated as covariates. Simulations were performed to explore the ATX dosing in subjects with various CYP2D6 AS. A simultaneous pharmacokinetic modeling approach was used in which a model for ATX, 4-OH, and NDA in plasma and urine, and 2-COOH in urine was developed. Plasma ATX, 4-OH, and NDA were modeled using two-compartment models with first-order elimination. CYP2D6 AS was a significant determinant of ATX apparent oral clearance (CL/F), fraction metabolized to 4-OH, and systemic exposure of NDA. CL/F of ATX varied almost 7-fold across the CYP2D6 AS groups: AS 2: 20.02 L/hour; AS 1: 19.00 L/hour; AS 0.5: 7.47 L/hour; and AS 0: 3.10 L/hour. The developed model closely captures observed ATX, 4-OH, and NDA plasma and urine, and 2-COOH urine profiles. Application of the model shows the potential for AS-based dosing recommendations for improved individualized dosing.

Comparing the impact of atezolizumab plus bevacizumab and lenvatinib on the liver function in hepatocellular carcinoma patients: A mixed-effects regression model approach.

This retrospective study compared the impact of atezolizumab plus bevacizumab (Atez/Bev) and lenvatinib (LEN) on the liver function in patients with hepatocellular carcinoma. We included 526 patients who received Atez/Bev and 731 who received LEN March 2018 and July 2022 in this study. We conducted a 1:1 propensity-score-matched analysis and identified 324 patients in each group for inclusion in the present analysis. Nonlinear mixed-effects regression models were employed, allowing for the evaluation and inclusion of cases where treatment was interrupted due to disease progression, adverse events, or loss to follow-up. These models were used to compare the ALBI score between the Atez/Bev and LEN groups. Following propensity score matching, the mean ALBI scores in the Atez/Bev and LEN groups were -2.41 ± 0.40 and -2.44 ± 0.42 at baseline, and -2.17 ± 0.56 and -2.19 ± 0.58 at 12 weeks, respectively. Although the ALBI score significantly worsened during treatment in both groups (p < 0.001), there was no significant difference in the rate of ALBI score deterioration between the groups (p = 0.06). Subgroup analyses showed that LEN-treated patients with BCLC advanced stage (p = 0.02) and those who initially received the full dose (p < 0.001) had a significantly greater worsening of ALBI score compared to Atez/Bev. Using a nonlinear mixed-effects regression approach, which allowed for the inclusion of cases with treatment interruption, we found no significant difference in the trend of liver function deterioration between the Atez/Bev and LEN groups. Caution should be exercised for LEN-treated patients with BCLC advanced stage or those receiving the full dose of LEN.

Thinking about it: the impact of COVID-19-related stimuli on prospective memory.

Since 2020, information regarding COVID-19 has been a constant presence in the news, in our conversations and thoughts. Continuous exposure to this type of stimuli could have an impact on cognitive processes essential for our everyday activities, such as prospective memory (PM). PM is the ability to remember to perform an intention at a specific point in the future, like remembering to take prescribed medicines at a specific time or to turn off the stove after cooking. Do COVID-related stimuli affect our ability to perform a PM task? To answer this question, we proposed a novel version of the classical paradigm used to investigate PM. Namely, this paradigm includes a baseline condition, in which an ongoing task is presented alone, and a PM condition in which the same task is proposed again together with a second (prospective) task. In this study, a short video clip was presented between the baseline and the PM condition. The video clip displayed either neutral, negative, or COVID-related content. Additionally, participants were asked to respond to two questionnaires and a series of questions regarding their well-being and experience with the pandemic. Namely, the DASS-21 scale (evaluating depression, anxiety, and stress), and the COVID-19-PTSD questionnaire (a questionnaire evaluating post-traumatic stress disorder symptoms related to the pandemic experience) were administered. Participants' performance and responses were analyzed using a linear mixed effect (LME) model approach, and correlation analyses were run to highlight possible correlations between participants' scores in the DASS-21, the COVID-19-PTSD, and the additional questions on their personal experience with the pandemic. The LME models revealed significant effects of the displayed video on performance: in line with previous studies, the clip displaying standard negative contents led to impaired accuracy in the ongoing task in the PM condition, compared to the Baseline. In contrast, participants who saw the COVID-related clip showed improved accuracy in the ongoing task compared to the other participants, selectively in the block performed after the video clip was displayed (PM condition). Furthermore, the explanatory power of the LME model calculated on accuracy to the ongoing trials was enhanced by the inclusion of the scores in the anxiety subscale of the DASS-21, suggesting a detrimental role of anxiety. Altogether, these results indicate a different effect of the exposure to classical negative contents (associated with a cost in terms of accuracy in the ongoing task between the baseline and the PM condition) and the pandemic-related one, which was instead characterized by a higher accuracy to ongoing trials compared to the other video clips. This counterintuitive finding seems to suggest that COVID-related stimuli are processed as "acute stressors" rather than negative stimuli, thus inducing a state of increased alertness and responsivity.

Exposure-Response Relationships between the Factor B Inhibitor Iptacopan and Complement Biomarkers in Healthy Volunteers and Patients (Pts) with Paroxysmal Nocturnal Hemoglobinuria (PNH), C3 Glomerulopathy (C3G) or IgA Nephropathy (IgAN)

Background: Iptacopan is the first oral proximal complement inhibitor that targets factor B to selectively inhibit the alternative pathway (AP) of the complement system. Iptacopan is currently being investigated in Phase III trials in PNH, C3G and IgAN. AP biomarkers can be used to evaluate the inhibitory effect of iptacopan. Wieslab ® ex vivo assay measures the amount of soluble C5b-9 (sC5b-9) formation in serum after AP activation. Plasma sC5b-9 is the final product of complement activation and is also known as the membrane attack complex. Plasma Bb levels increase following AP activation. Aim: To characterize exposure-response relationships between iptacopan and AP biomarkers Wieslab ®, Bb and sC5b-9 to rationalize the iptacopan dose selection. Methods: This analysis was based on final data from a Phase I clinical trial enrolling healthy volunteers (X2101 [EUDRACT2015-005567-16]) and 4 Phase II trials enrolling pts with PNH (X2201 [NCT03439839] and X2204 [NCT03896152]), C3G (X2202 [NCT03832114]) and IgAN (X2203 [NCT03373461]). In these trials, oral iptacopan was administered in doses ranging from 5-400 mg single dose and from 10-200 mg twice daily (bid). A longitudinal mixed-effects modeling approach was applied to the AP biomarkers used in this study: serum Wieslab ® assay, plasma Bb and plasma sC5b-9. Direct response sigmoid Emax models were considered as most appropriate and biologically plausible for all biomarkers, reflecting the rapid biomarker response following exposure to iptacopan. The exposure metric driving the response was the observed time-matching pharmacokinetic (PK) data. A population PK (popPK) model built on bid dose levels (10-200 mg) using data from pts (not healthy volunteers) simulated steady state exposure over 6 months of iptacopan bid dosing in each population. Results: The modeling dataset contained 247 participants, of which 88 (36%) were healthy volunteers, 29 (12%) were pts with PNH, 27 (11%) were pts with C3G, and 103 (42%) were pts with IgAN. Overall, 69 (28%) participants were female, and the median age (range) was 38 (18-78) years. A total of 2317, 2296 and 2279 samples for Wieslab ®, Bb and C5b-9, respectively, were used in the modeling, with the same number of time-matched PK samples. The biomarker responses decreased monotonically with saturation of effect and without apparent time lag, which was expected based on the mechanism of iptacopan. An exposure-dependent decrease in Wieslab ® was seen in pts and healthy volunteers, with estimated iptacopan concentrations required to achieve 90% of the maximum response (EC 90) being 1281 ng/mL (90% confidence interval [CI] 1207, 1418) and 706 ng/mL (90% CI 653, 788), respectively. Based on simulations from the popPK model, this exposure was expected to be reached at steady state trough concentration (C trough) by an estimated 74% of pts at 200 iptacopan mg bid, compared with 44% and 18% receiving 100 mg bid and 50 mg bid, respectively ( Table). The interindividual variability of Wieslab ® response decreased as iptacopan dose increased to 200 mg bid and C trough to ≥1300g/mL. A clear decrease from baseline in plasma Bb was seen following iptacopan treatment, with an EC 90 value of 521 ng/mL (90% CI 268, 912). Based on simulations from the popPK model, this exposure was expected to be reached by 97% of pts treated with iptacopan 200 mg bid, compared with 91% and 79% receiving 100 mg bid and 50 mg bid, respectively ( Table). For sC5b-9, the EC 90 value was 682 ng/mL (90% CI 503, 894) across all participants. This exposure was expected to be achieved by 94%, 83% and 64% of pts receiving iptacopan 200 mg bid, 100 mg bid and 50 mg bid, respectively ( Table). Age, weight, sex and ethnicity did not affect the biomarker responses. Conclusions: In this analysis, iptacopan 200 mg bid was the dose at which the highest proportion of participants achieved EC 90 values for the AP biomarkers Wieslab ®, Bb and sC5b9. Other than pts having higher EC 90 values than healthy volunteers for Wieslab ®, no differences were found in EC 90 values between the trial populations, demonstrating that no dose adjustment is needed between them. A response plateau was achieved by the iptacopan 200 mg bid dose for Wieslab ® and lower doses for Bb and C5b-9, suggesting higher doses would not lead to greater responses. In summary, these data support the use of oral iptacopan at 200 mg bid to achieve rapid, substantial and sustained inhibition of the complement AP in pts with PNH, C3G or IgAN.

Exposure-Response Relationships between the Complement Factor B Inhibitor Iptacopan and Lactate Dehydrogenase (LDH) and Hemoglobin (Hb) in Patients (Pts) with Paroxysmal Nocturnal Hemoglobinuria (PNH)

Background: PNH is an ultrarare disease characterized by complement-mediated hemolysis and subsequent anemia, bone marrow failure and thrombosis. In pts not treated with complement inhibitors, intravascular hemolysis (IVH) results from unregulated progression of the complement system and membrane attack complex formation. IVH is controlled in pts treated with anti-C5 therapy, but extravascular hemolysis (EVH) may emerge and cause persistent anemia. High LDH levels are a marker of ongoing IVH, while anemia can result from both IVH and EVH. Iptacopan is the first oral proximal complement inhibitor targeting factor B to selectively inhibit the alternative pathway of the complement cascade. As shown in PNH Phase III trials (APPLY-PNH [NCT04558918] and APPOINT-PNH [NCT04820530]), iptacopan can achieve good control of hemolysis. Aim: To support the dose selection for iptacopan, this analysis characterizes the exposure-response relationships between iptacopan and efficacy measures (LDH and Hb) in pts with PNH. The effect of prior anti-C5 treatment status has also been evaluated. Methods: This analysis is based on data from 4 clinical trials enrolling pts with PNH.Final data were used from the completed Phase II trials X2201 (NCT03439839; pts with active hemolysis despite anti-C5 therapy received concomitant iptacopan) and X2204 (NCT03896152; anti-C5-naïve pts received iptacopan monotherapy), in which iptacopan was administered orally in doses ranging from 25 to 200 mg twice daily (bid). Data up to the cut-off dates of 26 September 2022 and 2 November 2022 were used from the Phase III trials, APPLY-PNH (pts previously treated with anti-C5) and APPOINT-PNH (pts not treated with complement inhibitors including anti-C5), respectively, in which oral iptacopan was administered at 200 mg bid. A longitudinal mixed-effects modeling approach was applied to LDH and Hb. To account for the delay between exposure and response, indirect response models were developed for LDH and Hb. The models were used to predict the long-term (6 months) LDH and Hb responses for various iptacopan bid dose levels and to estimate (using simulation) the proportion of pts achieving LDH ≤1.5 × upper limit of normal (ULN) and Hb ≥12 g/dL. Results: The modeling dataset contained 161 pts with PNH; 94 (58%) were female, and median (range) age was 45 (18-84) years. For modeling of LDH and Hb levels, 2812 and 2587 samples were used, respectively, as well as 1577 pharmacokinetic samples. In total, 53 (33%) pts had not received anti-C5 treatment. Of the remaining 108 pts, 16 (15%) received iptacopan as add-on therapy to anti-C5 (pts from X2201) and 92 (85%) had previously received anti-C5 (pts from APPLY-PNH). The indirect response models were considered biologically plausible and adequately described the data using a common EC 50 value to both anti-C5-naïve pts and pts currently receiving or who previously received anti-C5. The estimated concentration of iptacopan required to achieve 90% of the maximum response (EC 90) of LDH was 268 ng/mL (90% confidence interval [CI] 238, 302), irrespective of prior anti-C5 treatment status ( Figure). The estimated typical LDH value after iptacopan treatment at an exposure &amp;gt;EC 90 was 237 U/L (90% CI 224, 250) within the normal LDH range (&amp;lt;250 U/L). Iptacopan 200 mg bid was the dose at which the highest proportion of pts (86%) achieved LDH ≤1.5 × ULN. While baseline LDH levels differed between anti-C5-naïve pts and pts currently receiving or who previously received anti-C5, similar proportions of these pts achieved LDH ≤1.5 × ULN (84% and 88%, respectively). The estimated EC 90 of Hb ≥12 g/dL was 1968 ng/mL (90% CI 1661, 2333) ( Figure); 89% of all pts were expected to reach EC 90 exposure at iptacopan 200 mg bid. The estimated Hb value after treatment with iptacopan at an exposure &amp;gt;EC 90 was 12.7 g/dL (90% CI 12.4, 13.0). 70% of pts were expected to achieve Hb normalization (≥12 g/dL) with iptacopan 200 mg bid. Similar proportions of anti-C5-naïve pts and pts who were currently receiving or who previously received anti-C5 achieved Hb ≥12 g/dL (71% and 68%, respectively). Conclusions: Indirect response models were developed to describe the exposure-response relationships between iptacopan and efficacy measures (LDH and Hb) in pts with PNH. The analysis demonstrated that 200 mg bid is the dose of oral iptacopan that achieves LDH ≤1.5 × ULN and Hb normalization in the highest proportion of patients regardless of prior treatment status.

Analyzing sales of the Korean restaurant franchise during the COVID-19 pandemic with the mixed-effects model approach.

Using point-of-sales (POS) data, the sales trends of 48 member stores of a Korean restaurant franchise during the COVID-19 pandemic were analyzed. As daily sales are nested in each member store of a franchise, the hierarchical structure of POS data was fully and effectively utilized by employing a mixed-effects model. The results showed that although sales volumes in all member stores were negatively affected by the pandemic, the level of impact varied according to store location: sales at some stores were drastically reduced, while a few others even achieved a slight increase in sales during the pandemic. These findings suggest that the government support policy for small business owners should be designed in a locally optimized way, to take account of neighborhood characteristics and the degree of sales loss for individual business owners.

Development and internal validation of a clinical prediction model for individualized dosing of BAY 81-8973, A full-length recombinant factor VIII, in pediatric patients with haemophilia A

BackgroundAs the most commonly used coagulation factor VIII (FVIII) concentrate in China, the individualized dosing prediction model of Kovaltry (BAY81–8973) is not fully investigated in pediatric patients. The prophylaxis tailored by population pharmacokinetic (PopPK) model can optimize dosing regimens. ObjectivesThis study aimed to develop PopPK models of BAY 81–8973 in pediatric patients, identify quantitative relationships of blood type (as a substitution for von Willebrand factor) on FVIII clearance and provide model-informed precision dosing (MIPD) procedures. MethodsPediatric patients with severe hemophilia A were enrolled and PK tests were conducted. The blood samples were collected at six time point. One-stage-based activated partial thromboplastin time was used for FVIII activity. Basic demographics and key covariates (blood type and von Willebrand factor antigen) were collected. A nonlinear mixed-effect modeling (NONMEM) approach was employed to establish PopPK model. Simulations were performed to evaluate current dosing regimens and present MIPD strategies. ResultsA total of 30 pediatric patients were included in the analysis. In the final model, Fat-free mass calculated from weight, age, and height was included as a size descriptor which affect FVIII apparent volume of distribution and clearance. Both von Willebrand factor antigen (VWF:Ag) and blood type accounted for the interindividual variability of FVIII clearance, but only one can retain in the final model. Therefore, two PopPK models based on VWF:Ag or blood type were developed. When the VWF:Ag value is doubled, the FVIII clearance is reduced by 35 %. Compared with blood type non-O, the clearance in pediatric patients with blood type O increased by 25.9 %. Weight-based dosing without regard to age and blood type resulted in large differences in FVIII trough activity. Patient demographics, dosing information, sparse blood samples and PopPK model together with Bayesian estimate constituted the MIPD workflow. Using it, the individual parameters and optimized dosing regimen could be achieved. ConclusionThis is the first predictive model designed to predict individualized dosing of BAY 81–8973 in pediatric patients with Hemophilia A. These results are useful in the PK-guided prophylaxis among pediatric patients and hold great potential to improve their long-term clinical outcomes.

A - 07 The Role of Age and Cognitive Reserve in Moderating the Cognitive Effects of Chemotherapy.

The aim of this exploratory study is to assess the cognitive effects of chemotherapy (CT) in women with breast cancer and to understand the role of age and cognitive reserve (CR) in the development of these effects. A group of women with early breast cancer with indication for CT (n = 32) and a group of healthy subjects (n = 32) were recruited. Both groups performed neuropsychological assessment at two time points- at baseline (before the initiation of CT and 6months later). Additionally, Cognitive Reserve Index questionnaire (CRIq), a comprehensive measure of CR, was applied. The cognitive tests were combined in a unique z-score for attention and executive function domain. The longitudinal cognitive assessment was analyzed using a mixed effect modeling approach with patient's vs controls as grouping factor and adjusted for age, CR, years of education and baseline cognitive performance as fixed factors. Mean age and education years for both groups were 49 (SD ± 8) years and 17 (SD ± 3), respectively. The level of CR was equally distributed across both samples, with 75% of participants presenting a high level of CR. The mixed effects model analysis did not show a significant effect for group. For Attention, a three-way interaction among CR, age and years of education was significant (p = 0.04). For the executive functions, none of the factors were significant. Our results suggest that CT did not contribute significantly for the development of cognitive decline in cancer patients. However, age, years of education and CR have a joint impact on attention, but not executive functions.

Me, myself and you: How self-consciousness influences time perception

Several investigations have shown that the processing of self-relevant information differs from processing objective information. The present study aimed to investigate the effect of social stimuli on subjective time processing. Here, social stimuli are images of an unknown male and female person and an image of participants’ self. Forty university students were tested with a time reproduction task in which they were asked to reproduce the duration of the stimulus previously presented. Images of others or themselves were used to mark the temporal intervals. Participants also performed questionnaires to evaluate the level of anxiety and depression as well as self-consciousness. A generalised linear mixed-effects model approach was adopted. Results showed that male participants with higher Private Self-Consciousness scores showed higher time perception accuracy than females. Also, female participants reported higher scores for the Public Self-Consciousness subscale than male participants. The findings are discussed in terms of social context models of how attention is solicited and arousal is generated by social stimuli, highlighting the effect of social context on subjective perception of time.

Population pharmacokinetic modeling and dosing simulation of avalglucosidase alfa for selecting alternative dosing regimen in pediatric patients with late-onset pompe disease

Avalglucosidase alfa (AVAL) was approved in the United States (2021) for patients with late-onset Pompe disease (LOPD), aged ≥ 1 year. In the present study, pharmacokinetic (PK) simulations were conducted to propose alternative dosing regimens for pediatric LOPD patients based on a bodyweight cut-off. Population PK (PopPK) analysis was performed using nonlinear mixed effect modeling approach on pooled data from three clinical trials with LOPD patients, and a phase 2 study (NCT03019406) with infantile-onset Pompe disease (IOPD: 1–12 years) patients. A total of 2257 concentration-time points from 91 patients (LOPD, n = 75; IOPD, n = 16) were included in the analysis. The model was bodyweight dependent allometric scaling with time varying bodyweight included on clearance and distribution volume. Simulations were performed for two dosing regimens (20 mg/kg or 40 mg/kg) with different bodyweight cut-off (25, 30, 35 and 40 kg) by generating virtual pediatric (1–17 years) and adult patients. Corresponding simulated individual exposures (maximal concentration, Cmax and area under the curve in the 2-week dosing interval, AUC2W), and distributions were calculated. It was found that dosing of 40 mg/kg and 20 mg/kg in pediatric patients < 30 kg and ≥ 30 kg, respectively, achieved similar AVAL exposure (based on AUC2W) to adult patients receiving 20 mg/kg. PK simulations conducted on the basis of this model provided supporting data for the currently approved US labelling for dosing adapted bodyweight in LOPD patients ≥ 1 year by USFDA.

A mixed-model approach for estimating drivers of microbiota community composition and differential taxonomic abundance.

Next-generation sequencing (NGS) and metabarcoding approaches are increasingly applied to wild animal populations, but there is a disconnect between the widely applied generalized linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology typically applied to metabarcoding data. Here, we describe the suitability of a novel GLMM-based approach for analyzing the taxon-specific sequence read counts derived from standard metabarcoding data. This approach allows decomposition of the contribution of different drivers to variation in community composition (e.g., age, season, individual) via interaction terms in the model random-effects structure. We provide guidance to implementing this approach and show how these models can identify how responsible specific taxonomic groups are for the effects attributed to different drivers. We applied this approach to two cross-sectional data sets from the Soay sheep population of St. Kilda. GLMMs showed agreement with dissimilarity-based approaches highlighting the substantial contribution of age and minimal contribution of season to microbiota community compositions, and simultaneously estimated the contribution of other technical and biological factors. We further used model predictions to show that age effects were principally due to increases in taxa of the phylum Bacteroidetes and declines in taxa of the phylum Firmicutes. This approach offers a powerful means for understanding the influence of drivers of community structure derived from metabarcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate contributions of additional factors such as host or microbe phylogeny to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities. IMPORTANCE NGS and fecal metabarcoding methods have provided powerful opportunities to study the wild gut microbiome. A wealth of data is, therefore, amassing across wild systems, generating the need for analytical approaches that can appropriately investigate simultaneous factors at the host and environmental scale that determine the composition of these communities. Here, we describe a generalized linear mixed-effects model (GLMM) approach to analyze read count data from metabarcoding of the gut microbiota, allowing us to quantify the contributions of multiple host and environmental factors to within-host community structure. Our approach provides outputs that are familiar to a majority of field ecologists and can be run using any standard mixed-effects modeling packages. We illustrate this approach using two metabarcoding data sets from the Soay sheep population of St. Kilda investigating age and season effects as worked examples.