Search Results (5,024)

Background: The purpose of this preliminary study was to evaluate the use of the Zipf–Mandelbrot (ZM) law to mathematically model the percentage occurrence of adverse drug reactions (ADRs), as a function of rank, reported to the United States Food and Drug Administration Adverse Event Monitoring System (US FDA AEMS). Methods: Six commonly used but pharmacologically different hospital-based medications were examined. Nonlinear curve fitting of the two ZM coefficients was utilized to model the percentage occurrence of ADRs in a hierarchical or rank order for each drug examined. Results: The reported complications and their associated occurrence rates for all six medications were accurately modeled using the ZM law. Those medications that have a greater percentage of reported ADRs within their first ten ranks were also found to have a greater negative slope. Furthermore, a natural logarithmic transformation of both the reported FDA data and the ZM law-derived predicted values demonstrated a consistent near-linear relationship, which was statistically significant. The ratio of the coefficients of the ZM law, $a·b^{-1}$, was also found to be a potentially useful index that allows for describing and comparing the overall shape of the medication-specific distributions. Conclusions: Based upon this preliminary examination, the ZM law appears to be applicable to the mathematical modeling of US FDA-reported ADRs. Additional research to assess and utilize this law for the analysis, economic management, and possible improvement in patient outcomes may be warranted. Full article

Parkinson’s disease (PD), impacting millions worldwide, leads to motor deficits and various non-motor symptoms. Although there is no cure, treatment primarily involves dopamine replacement therapy, especially L-dopa for motor symptoms, and additional drugs are required to address non-motor effects. This underscores the increasing demand for dual-acting drugs that can effectively target both symptom types in PD. This study explored the potential effects of a standardised Mesembryanthemum tortuosum extract, Zembrin^®, in treating PD, utilising in vivo and in silico models. Zebrafish larvae were subjected to pre-treatment with reserpine, followed by exposure to Zembrin^®, with selegiline and L-dopa as positive controls. The in vivo component of this study monitored locomotion and oxidative stress, while the in silico component identified potential drug targets for the treatment of PD. Reserpine induced hypolocomotion and oxidative stress in zebrafish larvae, and Zembrin^® (12.5 µg/mL) effectively enhanced locomotion and reduced oxidative stress. The molecular docking, molecular dynamics simulations, and binding free energy calculations revealed that four mesembrine alkaloids (mesembranol, mesembrenol, mesembrenone, and mesembrine) form stable and energetically favourable complexes with monoamine oxidase B (MAO-B) and dopamine transporter (DAT), which are significant targets for addressing both the motor and non-motor effects of PD. Full article

Staphylococcus aureus, particularly methicillin-resistant S. aureus (MRSA), remains a leading cause of skin and soft tissue infections (SSTIs) worldwide. Patients with renal edema, including those with nephrotic syndrome and chronic kidney disease (CKD), and critical illness, are particularly susceptible because of barrier dysfunction, immune impairment, and altered antimicrobial pharmacokinetics. This narrative review examines the mechanisms linking renal edema to increased susceptibility to cutaneous S. aureus infection and discusses their diagnostic and therapeutic implications. Three interconnected pathophysiological pathways appear central to this susceptibility: disruption of the cutaneous barrier, nephrotic and uremic immune dysfunction, and impaired lymphatic immune surveillance. These abnormalities facilitate bacterial colonization, and invasion, while S. aureus further exploits the renal host through adhesins, toxins, biofilm formation, and immune-evasion mechanisms. The review also highlights the challenges of managing severe staphylococcal infections in patients with kidney disease and critical illness, where augmented renal clearance, expanded volume of distribution, extracorporeal renal support, and fluctuating renal function may substantially influence antimicrobial exposure. Current management requires early recognition, source control, individualized antimicrobial selection, renal-adapted dosing, therapeutic drug monitoring, and antimicrobial stewardship. Although emerging anti-virulence and immunomodulatory strategies show promise, most remain at the preclinical or early translational stage. Overall, renal edema should be regarded as a biologically active modifier of host–pathogen interactions that contributes to increased susceptibility to cutaneous S. aureus infection across the spectrum of kidney disease. Full article

Idelalisib (IDE) is a marketed chiral anticancer drug administered as the S-enantiomer, requiring sensitive monitoring of the R-enantiomer to ensure enantiomeric purity. However, no dedicated capillary electrophoresis (CE) method has been reported for trace-level quantification of R-IDE. In this study, a cyclodextrin-mediated CE method was developed for reliable detection of the R-enantiomer at the 0.1% level (LOD 2 µg/mL; LOQ 5 µg/mL). Systematic screening identified hydroxypropyl-β-cyclodextrin (HP-β-CD) with an intermediate degree of substitution (DS~6.8) as the optimal chiral selector, providing efficient enantioseparation (R_s up to 4.3). The method was validated according to ICH Q2(R2) guidelines, demonstrating suitable precision, accuracy, and robustness. Complementary NMR studies revealed hindered rotation of the 3-phenyl moiety and elucidated the molecular basis of enantioselectivity. Complexation with β-CD and HP-β-CD produced clear diastereomeric differentiation in both ¹H and ¹⁹F NMR spectra, while the simplified ¹⁹F NMR profiles enabled direct enantiomer discrimination. NOESY and ROESY experiments demonstrated distinct inclusion modes, with HP-β-CD accommodating both the fluorinated aromatic ring and the 3-phenyl moiety. These interactions may account for the superior enantioseparation observed with HP-β-CD of intermediate DS. Our validated CE method addresses the distomer determination while NMR insights provide mechanistic understanding of the chiral recognition. Full article

Mitochondria-targeting metal complexes (MTMCs) are a mechanistically distinct class of metallopharmaceuticals. Unlike first-generation platinum drugs that form nuclear DNA adducts, MTMCs exploit organelle-specific vulnerabilities such as hyperpolarised mitochondrial membrane potential (ΔΨm), elevated reactive oxygen species (ROS), limited mitochondrial DNA (mtDNA) repair capacity, and redox-dependent enzymes such as thioredoxin reductase (TrxR). We systematically searched PubMed, Web of Science, Scopus, and Google Scholar databases for studies published between 2016 and 2026, applying predefined inclusion criteria that included subcellular localization evidence and functional bioenergetic endpoints. The search identified 147 studies covering Pt(II/IV), Ru(II/III), Au(I/III), Ir(III), Os(II), Re(I), and V(IV/V) complexes and metal–organic framework nanoplatforms. Mechanistic evidence converges on four intramitochondrial target categories: inhibition of ETC (Electron Transport Chain) Complexes I/III with consequent ATP depletion; ROS overproduction, coupled with glutathione and TrxR depletion; outer mitochondrial membrane permeabilization and intrinsic apoptotic cascade activation; and mtDNA damage within a compartment limited to base excision repair. Multi-modal cell death—the co-occurrence of apoptosis, ferroptosis, necroptosis, and autophagic cell death—was a recurrent finding across the reviewed studies. This review thoroughly surveys the latest trends in MTMC drug design (metals, ligand structures, and mechanisms of action) and summarises analytical techniques for speciation, pharmacokinetics, safe monitoring, and resistance, while critically analysing translational barriers and clinical failures. To address the field’s inconsistent terminology, we introduce an explicit localization evidence hierarchy that distinguishes mitochondria-targeting complexes (through quantitative ICP-MS fractionation or co-localization with defined Pearson/Manders coefficients) from simply mitochondria-localising or mitochondria-perturbing agents, and we apply it throughout. We also point out that the idea of selectivity being purely driven by membrane voltage (ΔΨm) and thermodynamics is constrained by membrane and protein binding, as well as the transmembrane pH gradient, kinetic limitations, and demonstrated heterogeneity of cancer-cell membrane potential, and, as such, the functional mitochondrial effects must not be equated with mitochondrial accumulation. Since elemental quantification cannot distinguish intact complex from protein adducts and decomposition products, speciation-aware pharmacokinetics emerges as a prerequisite for a credible exposure–response interpretation. The translational progress will depend less on new chemotypes than on this analytical and pharmacokinetic rigour, together with organelle-level safety monitoring and biomarker-guided patient selection. Full article

Daratumumab, a human IgG1 monoclonal antibody targeting CD38, is widely used in multiple myeloma and AL amyloidosis. Despite its clinical success, many patients fail to achieve durable responses or relapse, underscoring the importance of understanding resistance mechanisms. Drawing on experience from other better-studied monoclonal antibodies, resistance to daratumumab can be categorized into four main mechanisms: (1) reduced CD38 expression on plasma cells; (2) increased expression of complement inhibitory proteins (CD55/CD59), impairing complement-mediated cytotoxicity; (3) reduced drug bioavailability due to urinary loss in non-selective nephrotic syndrome; and (4) the development of neutralizing anti-daratumumab antibodies. Anti-drug antibodies (ADAs) may represent a potential mechanism of treatment failure through effects on pharmacokinetics, efficacy, and safety, even in patients on daratumumab therapy. Seven different trials have tested anti-daratumumab antibodies. Among them, anti-daratumumab antibodies were identified in only 0–2.4% of patients, and only in a small portion of these has it been proven to be neutralizing. Overall, ADAs appear rare, but these findings are likely underestimated due to short follow-up and suboptimal timing of assessment. In conclusion, standardized ADA monitoring, particularly months after treatment interruption or in cases of inadequate response or infusion-related reactions, may improve patient management and therapeutic outcomes. Full article

Drug repurposing represents a rational and resource-efficient strategy to expand the oncological armamentarium by leveraging the established pharmacology, clinical experience, and safety-monitoring frameworks of approved non-oncological agents. Clozapine (CZP), an atypical antipsychotic characterized by broad receptor pharmacology, complex biotransformation, and clinically relevant toxicological liabilities, has emerged as a candidate of interest following preclinical evidence of context-dependent anticancer activity across multiple tumor types. As such, CZP provides an informative case study at the interface between therapeutic drug action and xenobiotic behavior. This review provides a critical and integrated synthesis of the current evidence supporting the repurposing of CZP in oncology, with particular emphasis on the relationship between its molecular mechanisms, dose–exposure requirements, pharmacological complexity, and potential toxicity. Analysis of in vitro and in vivo studies across glioblastoma, non-small cell lung cancer, breast cancer, and melanoma brain metastasis models indicates that CZP can impair tumor cell proliferation and survival through a form of mechanistic plasticity. Rather than acting through a single conserved pathway, CZP appears to disrupt shared upstream processes related to pro-survival signaling, cellular stress tolerance, and metabolic homeostasis, while engaging tumor-specific downstream responses, including autophagic cell death, mitochondria-dependent apoptosis, oxidative stress, and coordinated modulation of survival and angiogenic pathways. Despite this mechanistic rationale, translation remains substantially constrained, most notably by the order of magnitude gap between anticancer-effective concentrations in vitro and clinically achievable plasma exposures, requiring careful distinction between potentially useful anticancer pharmacology and nonspecific xenobiotic-induced cellular stress and clinically unacceptable toxicity. Key limitations include the discrepancy between anticancer-effective concentrations observed in vitro and exposures achievable during standard psychiatric dosing, the limited understanding of how CZP metabolism and metabolite formation may influence efficacy and toxicity, the absence of integrated pharmacokinetic–pharmacodynamic and toxicokinetic modeling, and the lack of dedicated clinical trial evidence. To address these challenges, this review examines complementary translational strategies, including patient-derived organoids, co-culture systems, microphysiological platforms, pharmacokinetic and toxicological modeling, and computational digital twin frameworks. Together, these approaches may support a biologically informed and risk-aware evaluation of CZP, helping to identify responsive tumor contexts, anticipate exposure-related liabilities, and prioritize rational combination strategies. By integrating therapeutic potential with xenobiotic pharmacology and toxicology, this review positions CZP within the evolving landscape of precision oncology and evidence-driven drug repurposing. Full article

Background: The onset of type 2 diabetes mellitus (T2DM) is often preceded by prediabetes, a reversible state of insulin resistance and impaired glucose regulation driven by the chronic consumption of a high-calorie diet and sedentary lifestyle. Prediabetes is characterised by impaired glucose tolerance and elevated glycated haemoglobin (HbA1c). Although metformin improves insulin sensitivity, adherence limitations to lifestyle interventions highlight the need for alternative drugs that can be effective even without dietary intervention. In our laboratory, we synthesised a novel ruthenium complex that exhibits elevated biological activity. Accordingly, this study investigated the metabolic effects of a novel ruthenium (II)–uracil Schiff base complex in HFHC diet-induced prediabetic rats, with and without dietary intervention. Methods: Forty-eight male Sprague-Dawley rats (150–180 g) were divided into two groups, the standard diet (n = 12) and HFHC diet groups (n = 36), for prediabetic induction. Prediabetic animals were randomly assigned to respective treatment groups. The ruthenium complex was administered to prediabetic rats once a day, every third day, for 12 weeks, while monitoring changes in blood glucose, caloric intake, and body weight. Results: Diet-induced prediabetes resulted in increased fasting blood glucose and elevated HbA1c. The administration of the ruthenium (II)–uracil Schiff base complex reduced fasting blood glucose, improved insulin levels and ghrelin, enhanced GLUT4 expression, and significantly increased skeletal muscle glycogen, especially when combined with dietary intervention. Conclusions: The findings showed that the ruthenium complex exerts a pronounced effect on ameliorating glucose homeostasis, enhancing skeletal muscle glucose uptake, and improving overall metabolic function. Full article

Background: Hyperuricemia is an adverse effect frequently observed during favipiravir treatment. The time course, from uric acid elevation to recovery, and quantitative relationship between drug exposure and changes in serum uric acid levels remain insufficiently characterized. We investigated the pharmacodynamic mechanism of uric acid elevation and described its time course by population pharmacokinetic and pharmacodynamic modelling. Methods: Patients who received favipiravir for coronavirus disease 2019 or severe fever with thrombocytopenia syndrome were retrospectively evaluated. The pharmacokinetics of favipiravir were described by a one-compartment model with first-order absorption and elimination. Metabolite concentrations were predicted based on previously reported values. Changes in serum uric acid levels were described by a turnover model with zero-order production and first-order elimination. The drug effect was implemented as inhibition of the uric acid elimination process. Simulations based on the final model were performed for 10 consecutive days after the clinical regimen, with a 21-day follow-up. Results: The final model supported the inhibition of uric acid elimination by favipiravir and its metabolite. Regarding simulations, serum uric acid levels reached a median peak of 6.93 mg/dL at 6.7 days after treatment initiation and returned to pre-treatment levels within 4.0 days after treatment discontinuation. Conclusions: This combined population pharmacokinetic and pharmacodynamic turnover model quantified favipiravir-associated increases in serum uric acid levels and showed a transient profile with rapid recovery after drug discontinuation. These findings underscore the need for monitoring serum uric acid levels during favipiravir treatment, particularly in patients at a higher risk of gout Full article

Background/Objectives: Special populations, including pediatric, geriatric, and organ-impaired patients, are consistently underrepresented in randomized controlled trials (RCTs), resulting in limited evidence for safe and effective dosing. Off-label use is common, and variability in drug exposure and response increases the risk of adverse drug reactions (ADRs). This review aims to examine how integrating pharmacometrics (PMX) with real-world data (RWD) can address evidence gaps by supporting dose optimization, population expansion, and safety evaluation in these vulnerable groups. Methods: A narrative literature review was conducted using PubMed, Embase, and Web of Science (January 2000–November 2025). Using Boolean combinations of PMX and RWD-related search terms, approximately 200–300 records were identified across the three databases; approximately 30 full-text articles were reviewed, and representative case studies were selected based on population diversity, methodological variation, and regulatory or clinical impact. Results: RWD–PMX integration has been applied across three domains: (i) dosing optimization through therapeutic drug monitoring (TDM)-informed PopPK modeling and model external validation in pediatric and neonatal populations; (ii) population expansion supporting dose extrapolation and regulatory decision-making for unapproved groups; and (iii) safety evaluation enabling identification of exposure–toxicity risk factors in vulnerable cohorts. Conclusions: Integrating PMX with RWD provides a practical and mechanistically grounded framework for evaluating dosing, treatment eligibility, and safety in populations insufficiently represented in clinical trials. Accumulating evidence indicates that RWD–PMX methodologies can complement traditional clinical research and inform regulatory decision-making. Continued refinement of data quality standards, validation practices, and guidance frameworks will be essential for broader adoption. Full article

Background: Chimeric antigen receptor T-cell (CAR-T) therapies have transformed the treatment of haematologic malignancies, yet their adverse event (AE) profiles across all approved agents have not been consolidated using a pharmacovigilance methodology in a single comparative analysis. Methods: Using the FDA Adverse Events Reporting System (FAERS) and OpenVigil 2.1, disproportionality analyses for all six FDA-approved CAR-T therapies were performed, stratified by target antigen: anti-CD19 agents (axicabtagene ciloleucel, tisagenlecleucel, lisocabtagene maraleucel, brexucabtagene autoleucel) and anti-BCMA agents (idecabtagene vicleucel, ciltacabtagene autoleucel). For each of the 25 most frequently reported AEs per agent, the report event counts, reporting odds ratio (ROR) with 95% confidence interval, proportional reporting ratio (PRR), and chi-squared statistic were calculated. Results: A total of 36,567 AEs were identified across all six agents. Cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome were the most frequent and most disproportionate AEs across all six therapies, with RORs exceeding 240 in every agent. Idecabtagene vicleucel had the highest ROR for cytokine release syndrome among all agents (ROR 1934.6), while brexucabtagene autoleucel had the highest ROR for immune effector cell-associated neurotoxicity syndrome (ROR 2089.6). Ciltacabtagene autoleucel exhibited a unique neurological toxicity profile, cranial nerve paralysis (ROR 3167.6, PRR 3055.0, chi² 199,190), parkinsonism (ROR 145.5, PRR 136.6, chi² 24,840), Bell’s palsy (ROR 380.4, PRR 370.3), and facial paralysis (ROR 72.7), consistent with the late neurotoxicity syndrome previously characterized, and absent from other agents’ top 25 AE lists. Brexucabtagene autoleucel demonstrated secondary malignancy signals including squamous cell carcinoma of skin (ROR 308.2) and myelodysplastic syndrome (ROR 97.9). Tisagenlecleucel showed the highest hypogammaglobulinemia signal among all agents (ROR 614.1, PRR 536.5, chi² 144,832) alongside a broad pancytopenia profile. Hemophagocytic lymphohistiocytosis was a significant finding with ciltacabtagene autoleucel (ROR 71.0) and brexucabtagene autoleucel (ROR 57.8). Conclusions: CAR-T therapies share class-wide toxicities in cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome, but exhibit clinically important drug-specific and target-class-specific AE profiles. This consolidated FAERS-based analysis corroborates and extends prior pharmacovigilance work by providing direct cross-agent comparisons, and supports the use of agent-tailored monitoring strategies, particularly for the distinctive late neurological toxicity associated with ciltacabtagene autoleucel. Full article

Epidermolysis bullosa (EB) comprises a group of rare inherited genodermatoses characterized by fragility and blistering of the skin and mucous membranes, chronic wounding, and significant morbidity including increased risk of squamous cell carcinoma in severe subtypes. Key unmet priorities include reducing diagnostic latency, establishing objective wound monitoring, enabling early detection of malignant transformation within chronic ulcerations, and developing therapies that durably modify disease progression. Artificial intelligence (AI) encompassing machine learning (ML), and deep learning (DL) is increasingly integrated into EB research and clinical practice to address these unmet needs. This structured narrative review synthesises current evidence on AI applications in EB spanning genetic diagnostics, wound assessment, inflammatory endotyping, drug repurposing, and emerging therapeutic technologies, and integrates evidence from registered clinical trials. In genomics, DL-based splicing prediction models and variant prioritisation frameworks accelerate pathogenic variant detection and reduce diagnostic latency. In wound care, convolutional neural networks-based platforms enable automated lesion segmentation and remote monitoring, while multimodal AI models predict healing trajectories and support stratification of wounds by chronicity. Computational transcriptomic analyses have identified candidate repurposing agents by reversing pathogenic gene expression signatures in EB tissue. Emerging convergence of AI with biosensors-integrated wound dressings and three-dimensional bioprinting of genetically corrected skin substitutes represents a transformative future direction. Translational barriers include limited EB-specific training datasets, algorithmic bias across diverse skin phototypes, the interpretability deficit of DL systems, and evolving regulatory frameworks for AI as a medical device. Expansion of internationally interoperable EB disease registries with standardised wound imaging protocols is identified as the single most impactful intervention to accelerate AI adoption. A minimum endpoint set for AI-assisted EB wound assessment, incorporating wound area trajectory, wound type classification, tissue composition, and paired patient-reported pain and itch scores, is proposed to standardise outcome reporting across future studies. Full article

Magnetic resonance imaging (MRI) uses radiofrequency (RF) energy to generate diagnostic images. RF–tissue interactions lead to energy absorption and tissue heating, quantified by the specific absorption rate (SAR). Although SAR limits are strictly regulated for patient safety, actual in vivo tissue temperature changes during clinical MRI examinations in humans have not been directly measured. A patient with a histologically confirmed soft tissue sarcoma of the thigh underwent a clinically indicated 3 T MRI examination 24 h prior to resection. During imaging with whole-body SAR of 2.27 W/kg, direct temperature measurements (invasive and on the skin) were obtained. Temperatures increased by 2.0 °C within the tumor and at the skin surface was 3.4 °C at the skin surface. No technical difficulties or adverse events were observed, and the patient tolerated the examination well. This first-in-human case demonstrates the feasibility and safety of direct intratumoral temperature measurement during standard 3T MRI. While MRI was performed within safety limits of SAR as a surrogate for true tissue temperature, non-invasive temperature monitoring during MRI needs improvement. Controlled RF-induced heating during MRI may open new therapeutic possibilities, including MR-guided hyperthermia for sarcomas and other solid tumors or modulation of blood–brain barrier through transient RF-induced temperature elevations facilitating drug delivery. Full article

Background/Objectives: Antibody–drug conjugates (ADCs) have transformed the therapeutic landscape of breast cancer, expanding treatment opportunities across multiple disease settings. However, their increasing clinical use has revealed a heterogeneous spectrum of toxicities that extends beyond conventional chemotherapy-related adverse events. Emerging evidence suggests that ADC-associated toxicities are driven by a complex interplay between ADC structural characteristics, including target antigen expression, payload properties, linker stability, drug-to-antibody ratio, and patient-related susceptibility factors. This review aims to provide a comprehensive overview of ADC-related toxicities in breast cancer, integrating mechanistic insights with clinical management strategies and risk-adapted approaches. Methods: A narrative review of the literature was conducted focusing on clinical trials, real-world studies, translational investigations, and mechanistic evidence related to ADC-associated toxicities in breast cancer. Particular attention was given to the relationship between ADC design, toxicity mechanisms, patient-specific risk factors, and clinical management. Results: ADC-related toxicities encompass a broad range of adverse events, including hematologic toxicity, interstitial lung disease, gastrointestinal complications, hepatotoxicity, peripheral neuropathy, stomatitis, ocular toxicity, dermatologic adverse events, and cardiovascular manifestations. Current evidence indicates that toxicity profiles differ substantially across ADCs and are influenced by multiple factors, including payload class, linker chemistry, target biology, intracellular trafficking, bystander effects, systemic payload exposure, and host-related characteristics. While several toxicities can be anticipated through careful monitoring and early intervention, clinically significant variability remains, and validated predictive biomarkers are largely lacking. Emerging real-world evidence further highlights the importance of individualized toxicity assessment and multidisciplinary management. Conclusions: ADC-related toxicity should be viewed as a multifactorial biological process resulting from the interaction between ADC design and host susceptibility rather than as a uniform class effect. A mechanistic understanding of toxicity pathways may improve risk stratification, toxicity monitoring, and personalized management strategies. Future research should focus on the development of predictive biomarkers, pharmacologic risk models, and next-generation ADC platforms with improved therapeutic indices. This review proposes an integrated framework linking ADC structural determinants, toxicity mechanisms, and clinical management to support safer and more individualized use of ADCs in breast cancer. Full article

Background/Objectives: Therapeutic drug monitoring (TDM) of cyclosporine is essential due to its narrow therapeutic index and pronounced pharmacokinetic variability. Long-term surveillance of patient results may provide insight into analytical stability and clinical practice patterns beyond conventional quality control approaches. Methods: This retrospective observational study included 48,835 routine whole blood cyclosporine concentrations analyzed at a tertiary university hospital laboratory between January 2006 and December 2025. Yearly patient percentiles (10th, 25th, 50th, 75th and 90th percentiles) were calculated to assess longitudinal trends, variability, and potential effects of analytical platform transitions. Results were analyzed overall and by sex. Results: The yearly number of reported cyclosporine results declined modestly over the study period. The overall median cyclosporine concentration was 134.4 µg/L, with negligible differences between female and male patients. The 10th, 25th, and 50th percentiles remained highly stable across the 20-year period, with coefficients of variation between 6.1% and 6.8%. Upper percentiles exhibited greater variability, but the total coefficient of variation for the 90th percentile remained below 8%. No systematic shifts associated with analytical platform transitions were observed. Conclusions: Long-term patient median and percentile analysis demonstrated remarkable temporal stability of cyclosporine concentrations over two decades, despite changes in analytical platforms and clinical practice. Continuous monitoring of patient medians and percentiles may serve as a valuable complementary quality indicator, particularly for assays with limited commutable quality control materials. Full article