https://dspace.ewha.ac.kr/handle/2015.oak/171622 Sat, 04 Apr 2026 05:19:28 GMT 2026-04-04T05:19:28Z https://dspace.ewha.ac.kr/handle/2015.oak/274944 Title: Prediction of infliximab and anti-drug antibody concentrations in patients with inflammatory bowel disease using machine learning models with real-world data from a prospective cohort study Ewha Authors: 김명규 Abstract: Background: Although population pharmacokinetic models are the standard approach for identifying inter-individual variability and optimizing infliximab concentration, their development and validation are complex and time-consuming. Therefore, this study aimed to develop and evaluate machine learning (ML) models to predict infliximab and anti-drug antibody (ADA) concentrations in patients with inflammatory bowel disease (IBD) receiving maintenance infliximab therapy. Methods: A total of 1,806 infliximab and ADA concentration measurements were prospectively collected from 149 IBD patients. Recurrent neural networks (RNN)-based models, including long short-term memory (LSTM) and gated recurrent unit (GRU) architectures, as well as regression-based models such as Elastic Net, Support Vector Regression, Random Forest (RF), and extreme gradient boosting (XGBoost), were developed. Recursive multi-step prediction was applied to evaluate short-term forecasting performance. Results: RF outperformed in predicting infliximab concentrations, and XGBoost yielded the best performance in predicting ADA levels (2-fold accuracy, 86.67% and 96.67%, respectively). The infliximab prediction model maintained acceptable accuracy up to two recursive predictions steps but exhibited a notable performance decline at the third step. In contrast, the ADA model showed robust performance across all three recursive steps, maintaining 2-fold accuracy exceeding 96%. Conclusion: ML models were developed to predict infliximab and ADA concentrations, with RF and XGBoost showing the best performance for infliximab and ADA prediction, respectively. The ADA model demonstrated stable multi-step forecasting capability. These models may support individualized dosing strategies and reduce the need for frequent therapeutic drug monitoring in clinical practice. Copyright © 2026 Kim, Song, Hong, Kim, Kim, Chang and Kim. Thu, 01 Jan 2026 00:00:00 GMT https://dspace.ewha.ac.kr/handle/2015.oak/274944 2026-01-01T00:00:00Z https://dspace.ewha.ac.kr/handle/2015.oak/274945 Title: Analysis of predictive value of animal repeated dose toxicity study results for clinical safety of US FDA-approved anticancer drugs between 2019 and 2023 Ewha Authors: 배승진; 임경민 Abstract: The translational relevance of nonclinical animal studies in predicting clinical safety outcomes remains poorly understood in oncology drug development. This study aimed to qualitatively assess the concordance between toxicological findings from animal repeat-dose toxicity studies and treatment-emergent adverse events (TEAEs) in clinical trials of 63 anticancer drugs approved by the U.S. FDA from 2019 to 2023. We extracted nonclinical and clinical safety data from FDA review documents and categorized observations across 20 organ systems using a Concordant Positive/Concordant Negative/Animal-only Positive/Clinical-only Positive classification framework. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated by organ class and animal species. Among 63 anti-cancer drugs analyzed, hematologic, hepatobiliary, and gastrointestinal systems exhibited high concordance (notably high PPV and sensitivity), while bone/tooth and lymphatic systems showed low translational predictivity. Predictive performance was similar across rats, dogs, and monkeys, with no statistically significant interspecies differences. These findings suggest that current animal models offer organ-specific, but not species-specific, translational value for anti-cancer drugs. A shift toward validated, human-relevant alternative models is recommended for organ classes with low predictive performance in animal studies, to enhance translational accuracy while reducing animal sacrifice. © 2026 Elsevier Inc. Thu, 01 Jan 2026 00:00:00 GMT https://dspace.ewha.ac.kr/handle/2015.oak/274945 2026-01-01T00:00:00Z https://dspace.ewha.ac.kr/handle/2015.oak/274941 Title: Nationwide insights on early childhood neurodevelopment during a global health crisis: evidence from COVID-19 in South Korea Ewha Authors: 이한길 Abstract: Background The COVID-19 pandemic has disrupted early childhood environments globally, raising concerns about its potential impacts on neurodevelopment. Although early childhood is a critical developmental period, large-scale evidence from South Korea – where strict social distancing and unique caregiving structures were in place – remains limited. We aim to evaluate age- and domain-specific neurodevelopmental outcomes among children aged 0–5 years before and during the pandemic, focusing on differences by age and sex. Methods We analysed children aged 0–5 years using data from a national health screening programme and a pre–post comparison design with repeated cross-sectional data. We compared the pre-pandemic (July 2018–March 2020) and pandemic (April 2020–December 2021) periods. We categorised children into infants (9–12 months), toddlers (18–36 months), and preschoolers (42–71 months). We measured developmental outcomes using the Korean Developmental Screening Test across six domains: gross motor, fine motor, cognition, language, social skills, and self-help. We conducted multivariable logistic regression and difference-in-differences analyses. Results We analysed 6253076 assessments from 2797459 children. Peer-level developmental status declined significantly during the pandemic across all age groups, with the most pronounced decrease among toddlers (adjusted odds ratio (aOR)=0.92; 95% confidence interval (CI)=0.91–0.92), followed by infants and preschoolers. The language domain experienced the greatest decline (aOR=0.87; 95% CI=0.86–0.88), whereas the gross motor domain showed significant improvement (aOR=1.13; 95% CI=1.11–1.15). Boys were more adversely affected than girls, particularly in gross motor and social skill domains. Conclusions The COVID-19 pandemic led to significant developmental declines among young children, particularly in language and social domains and among toddlers. Boys were more adversely affected than girls, especially in language and socioemotional skills, highlighting sex-related vulnerabilities. Prioritising early screening and interventions targeting these key domains, alongside sex-sensitive strategies and caregiver support, will be essential to mitigate developmental disruptions during future pandemics. © 2026 The Author(s) Thu, 01 Jan 2026 00:00:00 GMT https://dspace.ewha.ac.kr/handle/2015.oak/274941 2026-01-01T00:00:00Z https://dspace.ewha.ac.kr/handle/2015.oak/274928 Title: Moderating effect of avoidance on the relationship between depression and suicidal ideation across different types of trauma exposure Ewha Authors: 류인균; 윤수정 Abstract: Background Suicidal ideation following trauma exposure is frequently associated with depressive and post-traumatic stress disorder (PTSD) symptoms; however, the interactive effects of depression and distinct PTSD symptom clusters on suicidal ideation remain poorly understood. Aims To examine whether specific PTSD symptom clusters-namely intrusion, avoidance and hyperarousal-moderate the association between depressive symptoms and suicidal ideation, and whether these effects vary across different trauma types. Method Medical records of 127 psychiatric out-patients with a history of at least one traumatic event were analysed. All participants had completed the Hamilton Rating Scale for Depression, the Impact of Event Scale-Revised, and the suicidal ideation item of the Beck Depression Inventory II. Trauma types were categorised into early versus late, single versus multiple, and interpersonal versus non-interpersonal. Results Hierarchical regression analyses identified a significant moderating effect of avoidance symptoms on the relationship between depression and suicidal ideation (β = 0.19, P = 0.012), whereas intrusion and hyperarousal symptoms did not show such effects. Specifically, higher levels of avoidance were associated with a stronger positive relationship between depression and suicidal ideation. This moderating effect was observed only among individuals with late (β = 0.28, P = 0.002), single (β = 0.29, P = 0.002) or non-interpersonal trauma (β = 0.34, P = 0.018); it was not evident among those with early, multiple or interpersonal trauma. Conclusions These findings underscore the relevance of targeting avoidance symptoms to mitigate suicidal ideation, particularly in individuals with late-onset, single-incident or non-interpersonal trauma exposure. Exposure-based therapeutic interventions may offer particular benefit for reducing suicidal ideation among trauma-exposed individuals with depressive symptoms. © The Author(s), 2026. Published by Cambridge University Press. Thu, 01 Jan 2026 00:00:00 GMT https://dspace.ewha.ac.kr/handle/2015.oak/274928 2026-01-01T00:00:00Z