Search Results (13,203)

Automatic detection of sensitive fields in structured data is a critical prerequisite for privacy compliance and data governance. However, existing approaches face severe cross-domain generalization challenges. Hand-crafted pattern rules often fail under highly heterogeneous naming conventions, while single statistical models tend to overfit and degrade sharply under distribution shifts between training and deployment domains. These limitations stem from the weak semantic signals and distributional heterogeneity of structured data, which make it difficult to simultaneously capture explicit rules and latent, variant-sensitive attributes. To address these challenges, we propose a detection framework based on multi-view complementary features and a Hierarchical Gated Residual Network (HGRN). The framework first constructs a full-spectrum feature system that integrates explicit rules and implicit statistical fingerprints (e.g., entropy and character texture) to fill the semantic gap. It then introduces a decision mechanism combining robust priors with dynamic residual calibration: a random forest provides a stable probabilistic anchor, which is further nonlinearly corrected by a learnable gating-and-expert network. This design explicitly resolves the cognitive conflict between rule-dominated regions and complex distributional regions. Experiments on multiple real-world datasets—including DeSSI, CMS Open Payments and Home Credit—show that the proposed method achieves a Macro-F1 of 0.9408 on DeSSI and exhibits strong in-domain performance. Under strict frozen-model cross-domain transfer, HGRN mitigates the catastrophic collapse observed in pure neural baselines and maintains moderate detection capability, offering interpretable trust allocation between rule-based priors and data-driven correction in both financial and healthcare scenarios. Full article

mRNA vaccines are a relevant approach in cancer immunotherapy, using messenger RNA to induce immune responses against tumor-associated antigens. In this review, BNT111 and BNT122 are compared as representative off-the-shelf and personalized models. BNT111 is a fixed mRNA vaccine that has demonstrated significant antitumor efficacy against shared melanoma antigens, particularly when combined with immune checkpoint inhibitors. It allows a standardized production via in vitro transcription (IVT) in a cell-free system. Conversely, BNT122 is a personalized vaccine designed to match an individual’s tumor mutations by targeting patient-specific neoantigens to elicit more robust immune responses. It has significant suitability in the adjuvant setting to target minimal residual disease. Despite favorable safety and immunogenicity, the effectiveness of these vaccines is influenced by various factors, including tumor heterogeneity, differences in antigen expression, off-target effects on mRNA-LNP distribution, molecular instability, and complex manufacturing constraints. Neither approach can be directly considered as the definitive optimal vaccine. A comprehensive analysis of their strengths and limitations is vital for a balanced and objective future research direction. Collectively, this emphasizes the need for further improvements in vaccine design and strategies, prioritizing high-quality, safe, and accessible treatments for every cancer-based patient and ensuring their successful integration into healthcare. Full article

Background: PPPs are central to Saudi Arabia’s Vision 2030 healthcare transformation, yet evidence on their impact on accessibility, quality, and sustainability remains limited. The purpose of this study was to evaluate the perceived associations between PPP implementation under Vision 2030 and three healthcare system outcomes—service accessibility (geographical, financial, technological), care quality (clinical outcomes, patient satisfaction, efficiency), and reform sustainability (economic, operational, adaptive)—from the perspectives of healthcare professionals and patients in Saudi Arabia. Methods: A cross-sectional, mixed-methods design was employed. Surveys were administered to 150 healthcare professionals and 210 patients at PPP-operated facilities (response rates of 61.2% and 65.6%, respectively). Descriptive and inferential statistics—including t-tests, ANOVA, chi-square tests, and multiple regression analysis adjusted for age, sex, education, household income, comorbidities, and facility type were used to assess associations between PPP initiatives and outcomes. Instrument reliability was confirmed (Cronbach’s α ≥ 0.7), and content validity was supported by an expert-panel content validity index of 0.91. Thematic analysis of open-ended responses captured stakeholder perceptions and challenges (inter-coder κ = 0.83). Results: Among professionals, 56.6% reported improved accessibility following the implementation of PPP, with 60.6% endorsing telemedicine as a key facilitator. However, 64.6% indicated financial access remained unchanged or worsened due to persistent out-of-pocket expenditures, and a statistically significant urban–rural gap was observed (p = 0.008). Quality indicators showed positive trends, including improved patient outcomes (52%), reduced waiting times (60.6%), and high satisfaction with hygiene and safety (74%). Sustainability assessments were cautiously favorable (mean financial viability = 3.4/5), though subsidy dependence remained a concern. Adjusted regression analysis identified financial accessibility (β = 0.31, p < 0.001) and reduced waiting times (β = 0.23, p = 0.005) as variables significantly associated with patient-reported outcomes. Conclusions: PPPs were associated with measurable improvements in healthcare accessibility, quality, and efficiency in Saudi Arabia. However, achieving the Vision 2030 objectives requires reforms that address financial equity, service distribution, workforce nationalization, and governance. Full article

Background: Periprosthetic joint infections (PJIs), a significant complication of total knee replacement surgery, are influenced by patient, surgeon, and healthcare system factors. Natural disasters can disrupt healthcare services and alter microbiological factors in the hospital environment. The impact of natural disasters on pathogen distribution in periprosthetic joint infection (PJI) is unclear. Therefore, this study investigated the association between the 2023 Kahramanmaraş-centered earthquakes in Türkiye and changes in microbiological patterns of PJI after knee arthroplasty. Methods: This retrospective cohort study included patients who developed PJI following total knee arthroplasty at the study center. The patients were divided into two groups based on the timing of their PJI diagnosis: pre-earthquake and post-earthquake. The demographic characteristics, comorbid diseases, and perioperative characteristics of each patient were recorded, and their microbiological profiles were analyzed. Logistic regression analysis examined the relationships between patient-related factors and causative agents. Results: 56 patients were studied and divided into two groups: 26 patients in the pre-earthquake group and 30 in the post-earthquake group. Furthermore, 79 bacterial isolates were obtained from these patients. Demographic, metabolic, and preoperative characteristics were similar between the two groups. No significant difference was found in the overall distribution of bacterial isolates. However, Gram-negative organisms, primarily Acinetobacter baumannii and Pseudomonas aeruginosa, increased in the isolate distribution after the earthquake. Patient analysis revealed that polymicrobial PJIs were significantly more frequent after the earthquake (56.7% vs. 23.1%; p = 0.011). Diabetes mellitus (DM) and smoking were associated with an increased risk of polymicrobial infection; the association was not statistically significant. Conclusions: In the post-earthquake period, patients who had undergone total knee arthroplasty and developed PJI showed a higher proportion of polymicrobial infections and a numerical increase in Gram-negative pathogens, along with more complex infection patterns compared to the pre-earthquake period. Although both patient groups demonstrated similar characteristics regarding patient-related and surgical factors, the observed changes indicate that the pressure on the healthcare system after a natural disaster can affect a hospital’s microbiological ecology. Identifying these indirect effects is crucial for guiding microbiological surveillance and infection control during post-disaster recovery periods, even for elective patients. Full article

Background: A bidirectional association between diabetes and oral health is well established, yet oral self-care is overlooked in diabetes management. Health Belief Model (HBM)-guided oral care interventions have exhibited promising outcomes in the literature but have not been used to guide oral self-care interventions designed for people with diabetes (PWD). Positioned at the early conceptualization and design stage of such a program, this developmental study was to identify self-perceived needs in oral self-care practices and to obtain preliminary feedback among PWD about the blueprint of a new program—DiaOral^©. Methods: We conducted semi-structured interviews with 15 PWD recruited from a large healthcare system, with a goal to recruit patients from racially/ethnically diverse urban/suburban zip codes. Interviews explored participants’ oral self-care practices in relation to diabetes. Sample DiaOral^© content and images on a blueprint were presented and feedback was solicited. Braun and Clarke’s reflexive thematic analysis was used to code and interpret transcripts, aligning emerging themes with HBM constructs through team-based consensus. Results: Three major themes and 27 sub-themes emerged: (1) lack of knowledge on optimal oral care, (2) low perceived importance of preventive care and oral health in diabetes, and (3) low self-efficacy for performing effective oral self-care. Participants expressed satisfaction with the content and their perceived confidence and interest potentially in using the DiaOral^© program based on their preliminary review of the blueprint. Conclusions: Findings support the relevance of HBM constructs in shaping oral self-care among PWD. This developmental study suggests that the DiaOral^© blueprint is ready to move forward to website prototype development. Future work will finalize the program and evaluate its efficacy among PWD. Full article

Background: Multisite digital psychiatry trials increasingly rely on complex onboarding and implementation processes at local research sites. While outcome-focused evaluations are common, less attention has been paid to the site-level labor required to operationalize such studies in real-world settings, particularly at smaller or resource-constrained sites. This study addresses this gap by examining hidden implementation labor from a single-site reflexive perspective. Methods: This study adopts a reflexive qualitative case study approach to examine onboarding and implementation processes at a single research site participating in a multisite digital psychiatry trial (ClinicalTrials.gov: NCT04953208). The analysis draws on longitudinal experiential data, supported by site-specific documentation, onboarding timelines, troubleshooting records, device-management materials, data quality assurance activities, and internal communications generated during site coordination and implementation activities. Results: Five interrelated themes were identified: hidden labor and role overload; resource scarcity at small research sites; fragmented remote communication and technical coordination; multi-role professional contexts and competing demands; and the impact of external systemic disruptions. Findings show how administrative, technical, logistical, and coordination tasks were absorbed into individual roles, often exceeding initial role expectations. Despite limited resources, the site achieved high performance through intensified individual effort, masking the true implementation burden. This pattern is conceptualized as a high-performance paradox, in which apparent site efficiency may conceal substantial hidden labor and role compression. Conclusions: This site-level reflexive account highlights the central role of hidden labor in sustaining implementation in multisite digital psychiatry trials. Recognizing and explicitly resourcing implementation work, particularly at small research sites, may improve feasibility, sustainability, and equity across study settings. The study contributes a practice-based methodological perspective on how implementation burden can be identified through reflexive analysis of site-level trial processes. Full article

Counterfeit and unsafe medicines pose significant risks to patient safety and undermine trust in healthcare systems. This paper presents ACTMeds, a blockchain-supported pharmaceutical traceability and recall platform that considers pharmaceutical supply chain requirements and public health operational needs relevant to the Australian Capital Territory (ACT). The system integrates Ethereum smart contracts, developed using Ganache, with a React-based web application providing regulator, operator, pharmacy, and auditor interfaces, alongside a public verification portal leveraging QR and GS1 barcodes. In addition, role-based access control is enforced across the medicine lifecycle, including manufacture, custody transfer, dispensing, and recall, with immutable on-chain events generated to support auditability and accountability. To balance transparency with confidentiality, the platform prototypes a zero-knowledge (ZK) recall mechanism in which regulators can cryptographically prove that recall conditions meet predefined policy requirements without disclosing sensitive incident details. Threat modeling was conducted using the STRIDE framework, and security evaluation combined static application security testing (Solhint and ESLint) and dynamic testing. The paper further discusses deployment options, cost considerations, ZK recall performance analysis, ethical implications, and future enhancements. Security testing validated the platform’s resilience, with no high-severity vulnerabilities identified and medium-severity issues related to HTTP security headers addressed. The results indicate that a regulator-led, privacy-preserving, tamper-evident ledger can improve medicine authenticity verification and recall responsiveness while maintaining compliance and data protection obligations. Full article

Background: Diagnostic errors affect approximately 5–15% of clinical encounters globally, contributing to significant patient harm. Artificial intelligence-based clinical decision support systems (AI-CDSS) are increasingly deployed to augment clinician diagnostic performance, yet rigorous evidence from randomized controlled trials (RCTs) remains limited. This systematic review and meta-analysis aims to quantify the effect of AI-CDSS on diagnostic accuracy among healthcare professionals. Methods: We systematically searched PubMed/MEDLINE, CINAHL, Embase, Cochrane CENTRAL, and Google Scholar from 2000 to 2026. Eligible studies were peer-reviewed RCTs comparing AI-CDSS with standard care. Risk of bias was assessed using the Cochrane RoB 2 tool. Random-effects meta-analysis was performed using standardized mean differences (SMD). Certainty of evidence was evaluated using GRADE. Results: Five RCTs (N = 12,657 participants) were included. The pooled SMD was 0.182 (95% CI: 0.003–0.362; p = 0.047; I² = 68.6%), with the lower confidence bound approaching zero, indicating preliminary evidence of a modest, statistically marginal improvement with AI-CDSS. Subgroup analyses suggested greater effects for deep learning systems and chest radiology applications, though single-study subgroups preclude definitive comparative conclusions. No significant publication bias was detected (Egger’s p = 0.18). GRADE certainty was rated MODERATE. Conclusions: This meta-analysis provides preliminary evidence that AI-CDSS may modestly improve diagnostic accuracy under specific conditions; however, the marginal statistical significance and near-zero lower confidence bound necessitate cautious interpretation. Implementation should prioritize contexts with demonstrated effectiveness and include ongoing outcome monitoring. Full article

Background/Objectives: Precision nutrition informed by genetic profiling has been proposed to improve public health outcomes; however, long-term, community-based evidence remains limited. This study evaluated the long-term health and economic impacts of the Sakado Folate Project. Methods: Since 2006, residents participating in the Sakado Folate Project received gene-guided nutritional counseling focused on folate intake and related lifestyle factors. Target genes included methylenetetrahydrofolate reductase (MTHFR), angiotensinogen (AGT), adrenoreceptor B3 (ADRB3), and uncoupling protein 1 (UCP1); Δ5-fatty acid desaturase (FADS1) was incorporated later. Biochemical markers, genetic polymorphisms, and health indicators were monitored longitudinally. Population-level health outcomes and per-capita medical expenditure data were compared with regional and national statistics. Results: In program participants (n = 888), folate status and biochemical indicators improved: 76.1% achieved the serum folate target (≥9.5 ng/mL) and 55.3% achieved the serum total homocysteine target (≤7 μmol/L). Healthier lifestyle behaviors were observed across 99,565 Sakado residents, with the city recording the highest proportion of individuals actively attempting lifestyle improvement (31%) of all districts in the region. Disease prevalence was lower in Sakado City than in Saitama Prefecture overall, at standardized prevalence ratios of 52% for stroke and 86% for cerebral infarction. Per-capita medical expenditure was also lower in Sakado City (¥337,800) than the national average (¥392,044) in 2021. Conclusions: Long-term implementation of a community-based, gene-guided nutritional intervention may improve population health outcomes and reduce healthcare expenditures. Integrating nutrigenomics into public health strategies alongside community education and food environment improvements may contribute to sustainable healthcare systems in aging societies. Full article

Diabetes Mellitus is a chronic metabolic disorder characterized by elevated blood glucose due to defects in insulin secretion or action, or both, leading to serious short- and long-term complications if not effectively managed. However, there is limited qualitative evidence exploring how youths diagnosed with Type 1 Diabetes Mellitus (T1DM) experience disease onset, management, complications, emotional adaptation, and education within the South African public healthcare system. The study aims to investigate the lived experiences of youths living with T1DM in a selected public hospital in Limpopo province, South Africa. The objectives were to explore and describe the lived experiences of youths living with T1DM. A qualitative, explorative, descriptive, and contextual design was used to gain a thorough understanding of the experiences of youths living with T1DM. A non-probability sampling technique was used to select 12 participants using a pre-determined criterion. Data were collected through individual semi-structured interviews using an interview guide. The data were analyzed using Colaizzi’s method, where themes and sub-themes were developed with the inclusion of an independent coder. Measures to ensure trustworthiness and ethical considerations were adhered to throughout the study. The findings revealed that, despite the participants sharing the same diagnosis, they experience multiple interrelated barriers that significantly hindered effective self-care management, such as limited access to diabetic diet, glucometers and supplies, treatment and informational-related barriers, school-related challenges, transportation constraints and inadequate social support. Furthermore, the findings highlighted gaps in early recognition of symptoms, standardized diabetes education, psychosocial support, and continuity of care. The study recommends the need for holistic, patient-centred, and contextualized interventions that do not only address medical management but the socioeconomic, educational, and psychological needs of youths. Full article

Tobacco use remains a major public health challenge in Jordan, where cigarette smoking and waterpipe use are both common and dual use is increasingly prevalent. Community pharmacies are highly accessible healthcare settings, yet structured smoking-cessation services remain underutilized. This study evaluated the clinical effectiveness and implementation of Dual-Quit Digital, a pharmacist-delivered cessation counseling program tailored to the type of tobacco used, paired with a 6-month automated WhatsApp^® (Menlo Park, CA, USA) follow-up system. We conducted a pragmatic, two-arm, parallel-group, Hybrid Type 2 cluster randomized controlled trial in 16 community pharmacies in Jordan, randomized 1:1 to intervention or usual care. A total of 320 adult tobacco users were enrolled (160 per arm). The intervention combined a structured in-pharmacy pharmacist consultation, tailored behavioral support, phenotype-stratified pharmacotherapy support, and 6 months of semi-automated WhatsApp^® follow-up with telepharmacy escalation for predefined red-flag responses. The control arm received usual care, consisting of opportunistic brief advice and standard over-the-counter sales without proactive follow-up. The primary outcome was biochemically verified continuous abstinence at 6 months, defined as exhaled carbon monoxide (CO) < 10 ppm and analyzed using intention-to-treat principles. Secondary outcomes included 7-day point prevalence abstinence (PPA) at 3 and 6 months, 30-day PPA at 6 months, both-product abstinence among baseline dual users, pharmacotherapy uptake and adherence, and implementation-relevant outcomes, including service reach, feasibility of recruitment, and digital engagement metrics. All 16 pharmacies were retained, and all 320 randomized participants were included in the intention-to-treat analysis. At 6 months, CO-verified continuous abstinence was achieved by 26.3% of participants in the intervention arm compared with 11.3% in the control arm (adjusted odds ratio [aOR] 2.84, 95% CI 1.55–5.18; p < 0.001). The intervention also improved 7-day PPA at 3 months (33.1% vs. 15.6%; aOR 2.68, 95% CI 1.56–4.60; p < 0.001), 7-day PPA at 6 months (30.6% vs. 14.4%; aOR 2.62, 95% CI 1.48–4.62; p = 0.001), and 30-day PPA at 6 months (28.1% vs. 11.9%; aOR 2.89, 95% CI 1.59–5.24; p < 0.001). Among baseline dual users, both-product abstinence was higher in the intervention arm (21.9% vs. 7.8%; aOR 3.30, 95% CI 1.12–9.75; p = 0.026). Pharmacotherapy initiation was more frequent in the intervention arm (72.5% vs. 28.1%; p < 0.001), as was self-reported adherence for at least 8 weeks among initiators (56.0% vs. 26.7%; p = 0.002). In the intervention arm, active patient response rates to scheduled WhatsApp^® messages remained substantial, with 88.1% responding at Week 1, 73.8% at Week 4, 67.5% at Month 3, and 61.3% at Month 6; 145 red-flag triggers were captured from 62 participants, and 84.1% of escalations resulted in successful pharmacist follow-up within 48 h. The Dual-Quit Digital model significantly improved smoking-cessation outcomes compared with usual care and proved operationally feasible. These findings support integrating phenotype-stratified pharmacist counselling, pharmacotherapy support, and low-burden digital follow-up as a pragmatic cessation model for Jordan and similar settings. Full article

Chronic obstructive pulmonary disease (COPD) imposes a substantial physical and psychosocial burden, yet the role of loneliness remains under-recognised in clinical practice. Loneliness, defined as a subjective discrepancy between desired and actual social relationships, has emerged as a clinically relevant determinant of patient outcomes. This narrative review synthesises current evidence on the epidemiology, mechanisms, and clinical consequences of loneliness in COPD, and evaluates its implications for disease management. Available evidence indicates that loneliness affects a considerable proportion of individuals with COPD, with prevalence estimates ranging from approximately 18% to over 30%, particularly among patients with greater symptom burden, functional limitation, and oxygen dependence. Dyspnoea and advancing disease severity reduce social participation and increase vulnerability to perceived social disconnection. Loneliness influences COPD outcomes through interconnected behavioural, biological, and healthcare engagement pathways, including systemic inflammation, neuroendocrine stress responses, physical inactivity, impaired self-management, and reduced engagement with healthcare services. These mechanisms contribute to poorer clinical trajectories, as loneliness is consistently associated with reduced health-related quality of life, increased exacerbations, higher healthcare utilisation, greater risk of hospitalisation, and elevated mortality, independent of depression and anxiety. Despite this, loneliness is rarely assessed in routine respiratory care, and targeted interventions remain limited. Emerging strategies, including pulmonary rehabilitation, peer support, and digital health interventions, show promise in reducing loneliness and improving outcomes. Loneliness represents a modifiable and clinically actionable risk factor in COPD, and its integration into routine assessment and management may enhance patient engagement, optimise treatment effectiveness, and reduce healthcare burden. Addressing loneliness represents a critical opportunity to advance more effective and comprehensive COPD care. Full article

Background/Objectives: This retrospective cohort study compared hospitalization and follow-up rates in patients with newly diagnosed proliferative diabetic retinopathy (PDR) versus those without prior diabetic retinopathy (DR) screening. Methods: Using TriNetX, a global electronic health record database, 57,964 patients aged ≥ 40 years with type 2 diabetes and newly diagnosed PDR without diabetic macular edema (DME) requiring panretinal photocoagulation or intravitreal injection were included. Patients were stratified based on the presence or absence of prior DR screening in the last 5 years and balanced using propensity score matching (PSM). Primary outcomes included 30-, 60-, and 90-day hospitalization rates and repeat ophthalmic follow-up as estimated using repeat PDR diagnosis codes and repeat retinal imaging codes, including OCT, fundus photography, and fluorescein angiography. Results: Of 57,964 patients, 25,003 had no prior DR screening and 32,961 had prior DR screening. After matching, 19,316 patients were included per cohort. Patients without known DR screening had significantly higher hospitalization rates at 30 days (RR = 1.78, 95% CI 1.67–1.89), 60 days (RR = 1.59, 95% CI 1.51–1.67), and 90 days (RR = 1.51, 95% CI 1.44–1.58), and lower repeat ophthalmic visits by PDR codes at 30 days (RR = 0.458, 95% CI 0.440–0.476), 60 days (RR = 0.450, 95% CI 0.437–0.463) and 90 days (RR = 0.420, 95% CI 0.408–0.432) or by repeat retinal imaging codes at 30 days (RR = 0.450, 95% CI 0.423–0.478), 60 days (RR = 0.394, 95% CI 0.377–0.411), and 90 days (RR = 0.381, 95% CI 0.366–0.396) (all p < 0.0001). Conclusions: Absence of known prior DR screening in PDR patients is associated with higher hospitalization risk and reduced ophthalmic follow-up, suggesting that a lack of screening indicates broader gaps in healthcare engagement and disease control. Tailored strategies are needed to prevent vision loss as well as systemic complications. Full article

Background: Rural and remote health systems are diverse; while many of these settings face persistent workforce shortages and access gaps, not all are underserved. Nurses play a critical role in improving access, continuity, and quality of care in these contexts. However, evidence on their roles, the challenges they face, and the outcomes associated with their contributions remains fragmented. Objective: To map the roles, challenges, and reported outcomes of nurses working in rural and remote healthcare settings, and to examine the quality and scope of the available evidence. Design: This study employed JBI scoping review methodology and is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Methods: Eligible studies involved registered nurses (RNs) and nurse practitioners (NPs) providing care in rural or remote settings and reporting at least one outcome related to patients, services, or health systems. Six bibliographic databases (PubMed/MEDLINE, CINAHL, Embase, Scopus, Web of Science, Cochrane Library) plus Google Scholar for supplementary grey literature retrieval and targeted grey literature were searched (from 1 January 2000 to 30 September 2025). The lead author conducted screening and data extraction, supported by a 10% calibration pilot and structured peer debriefing. Design-specific critical appraisal was undertaken descriptively to inform interpretation but did not determine inclusion. Results: From 22 primary empirical studies (plus 2 contextual-only entries; 24 total, nurses’ roles clustered into direct clinical care, care coordination/navigation, telehealth facilitation, and health promotion. Reported outcomes were predominantly in access/utilization (e.g., time-to-care), quality and safety indicators, and patient-reported outcomes/experiences; clinical endpoints were less common. Conclusions: Nurses in rural and remote settings enact broad, adaptive roles that appear to support healthcare access and service continuity. The evidence base is predominantly descriptive, and causal claims about effectiveness cannot be drawn from the available studies. Standardized outcome frameworks, multi-reviewer methodologies, and effectiveness-focused primary research are needed to advance this field. Full article

Hyperoxaluria Type 1 (PH1) is a rare autosomal recessive metabolic disorder caused by mutations in the AGXT gene, leading to impaired glyoxylate metabolism and excessive oxalate accumulation, resulting in nephrolithiasis, nephrocalcinosis, and end-stage renal disease. As a rare and often neglected disease, PH1 poses a significant challenge to modern healthcare systems due to its progressive nature and limited therapeutic options. In this study, an integrated in silico approach was employed to identify pathogenic single-nucleotide polymorphisms (SNPs) and evaluate potential therapeutic candidates. Computational analyses using ConSurf, Align-GVGD, INPS-MD, CUPSAT, and iStable identified G161C and Y260C as highly deleterious variants affecting protein stability. Virtual screening, followed by ADME and toxicity assessments, identified Tauroursodeoxycholic acid (TUDCA) as a promising candidate with favorable pharmacokinetic and safety profiles. Molecular docking revealed that TUDCA exhibited higher binding affinity than the reference drug pyridoxine across native and SNP variants of AGXT proteins. Molecular dynamics simulations (300 ns) demonstrated enhanced structural stability of TUDCA-bound complexes, indicated by reduced RMSD and RMSF, improved compactness, and sustained hydrogen bonding. Furthermore, free energy landscape (FEL) and dynamic cross-correlation matrix (DCCM) analyses confirmed improved conformational stability and coordinated residue motions in SNP variant structures. Overall, these findings suggest that TUDCA may effectively stabilize structural alterations induced by pathogenic AGXT variants, highlighting its potential as a precision medicine-based therapeutic strategy for PH1. Full article