Background: Levetiracetam is widely used for seizure prophylaxis, focal and generalized seizures, status epilepticus, subarachnoid hemorrhage, and traumatic brain injury. It has nearly 100% bioavailability, low protein binding, linear pharmacokinetics, and a wide therapeutic index. However, as levetiracetam is primarily eliminated via the kidneys, the impact of renal function and other factors on its pharmacokinetics remains unclear.

Aims: This study aimed to assess levetiracetam pharmacokinetics, determine the prevalence of sub-therapeutic and over-therapeutic levels, and evaluate factors affecting drug concentrations.

Methods: A retrospective study was conducted using medical records from January 2020 to December 2024. Data collected included demographics, renal function, underlying diseases, concomitant medications, dosage regimen, and measured drug levels. A one-compartment, first-order pharmacokinetic model was used, and statistical analyses identified factors influencing drug concentrations.

Results: Among 177 patients (380 serum concentrations), sub-therapeutic and over-therapeutic levels were observed in 128 (72.32%) and 4 (2.82%) patients, respectively. Age, sex, and weight had no significant impact. Enzyme-inducing drugs increased sub-therapeutic levels (71.83% vs. 57.07% in monotherapy). Patients with epilepsy, status epilepticus, and traumatic brain injury had higher sub-therapeutic rates. Notably, 95.24% of patients with augmented renal clearance had sub-therapeutic levels, with eGFR ≥ 95 ml/min/1.73m² strongly associated with drug levels below the therapeutic range (12–46 mg/L).

Conclusions: High renal function and certain diseases significantly affect levetiracetam pharmacokinetics, increasing sub-therapeutic levels. Therapeutic drug monitoring may optimize dosing, and further research is needed to improve treatment in high-risk populations.

Key Words: Levetiracetam, Therapeutic Drug Monitoring, Renal function, Augmented Renal Clearance, Traumatic Brain Injury, Epilepsy

Background: Exogenous insulin treatment is known to cause excess weight gain, but its impact may vary with different insulin dosing methods. It is unclear whether automated insulin delivery (AID) impacts weight gain differently compared to conventional care. It is hypothesised that AID, by more closely mimicking the body’s natural insulin response, may result in less weight gain and potentially lower insulin total daily dose (TDD) compared to conventional methods.

Aims: To evaluate the effect of AID systems compared to conventional insulin therapy on body weight, body mass index (BMI), and insulin TDD in patients with type 1 diabetes mellitus.

Methods: A comprehensive systematic literature search was conducted in PubMed, Scopus, Embase, and Cochrane databases to identify randomised controlled or crossover studies comparing AID to conventional care for T1DM, with a minimum duration of 12 weeks.

Results: In total 14 studies met the inclusion criteria, with data extracted for BMI (6 studies), BMI z-score (5 studies), body weight (12 studies), insulin TDD per kilogram of body weight (9 studies). The only statistically significant finding was related to body weight, where participants using AID gained a modest amount more than those in the control groups during the study period (Cohen’s d = 0.19, p <0.001).

Conclusion: The findings do not support the hypothesis that AID systems lead to reduced weight gain in T1DM patients, at least in the short- to medium-term. Longer follow-up studies may be needed to detect any potential long-term differences in weight management or insulin requirements.

Background: The principles of Concentration Guided Dosing (CGD) provide a rational basis for personalized dosing. Existing terminology such as Therapeutic Drug Monitoring (TDM) or Model Informed Precision Dosing (MIPD) may have multiple meanings or be imprecisely defined.

Aims: The purpose of this presentation is to explain and encourage the use of terminology that distinguishes between the steps of measurement and reporting of concentrations, interpretation of the measurements and subsequent prediction of individualised doses.

Methods: A brief history of CGD reveals the evolution of more accurate terminology focused on using concentration observations to provide individual drug dose guidance to clinicians.

Results: CGD is commonly implemented using either the Therapeutic Window Approach (TWA) or the Target Concentration Approach (TCA). However, only the latter approach offers a truly personalized treatment aimed at an optimally effective and safe dose for each patient.

Conclusions: CGD approaches should include a clear description of how concentrations are used to individualise dosing to achieve a clinical outcome.

Key Words: Clinical Pharmacology, Concentration Guided Dosing, Target Concentration Intervention, Therapeutic Drug Monitoring

Background: Methotrexate (MTX) is the first-line treatment for rheumatoid arthritis (RA), whereas it plays a significant role in inter-individual variability regarding the efficacy and toxicity. Methotrexate polyglutamates (MTXPGn) in erythrocytes may serve as biomarkers for treatment response, but there is still a gap in current evidence to guide MTX TDM in RA.

Aims: To investigates the correlation between MTXPGn concentrations and clinical outcomes in Chinese RA patients, and finally to optimize individualized therapy of MTX.

Methods: A prospective, single-center cohort study was designed and conducted. Efficacy outcomes were assessed using 28-joint Disease Activity Score (DAS28) and Simplified Disease Activity Index (SDAI). Safety outcomes included hepatotoxicity (defined by CTCAE) and Gastrointestinal Symptom Rating Scale (GSRS). MTXPG1-5 concentrations in erythrocytes were measured at 1, 3, and 6 months using LC-MS/MS.

Results: Currently, 59 treatment-naive RA patients receiving MTX (12.5–17.5 mg/week) was enrolled. MTXPGn concentrations increased over time, with a significant rise at 3 months. MTXPG3 was the predominant form (43.2%). At 3 and 6 months, ΔDAS28% and ΔSDAI% were significantly correlated with total and specific MTXPGn levels (P<0.05). Patients achieving ΔSDAI ≥50% had significantly higher MTXPGn concentrations (P<0.05). Specific MTXPGn concentrations were significantly elevated in patients with hepatotoxicity (P<0.05), while GSRS scores showed no significant difference.

Conclusion: Erythrocyte MTXPGn concentrations associate with MTX efficacy and hepatotoxicity in Chinese RA patients, supporting their potential role in dose optimization. Erythrocyte MTXPGn-based TDM would be expected to guide dose adjustment and improve outcomes of MTX therapy.

Keywords: Rheumatoid arthritis, methotrexate, therapeutic drug monitoring, Individualized medication

Introduction: Chemotherapy-Induced Peripheral Neuropathy (CIPN), commonly caused by Paclitaxel, significantly affects patients' quality of life by inducing neuropathic pain through abnormal sensory signal processing. This pain is challenging to treat due to its complex pathophysiology, involving altered ion channel functions like TRPV1 and neuroinflammation. Ellagic acid, a natural polyphenol known for its antioxidant and anti-inflammatory properties via the Nrf2 pathway, shows promise in alleviating CIPN symptoms. This study explores its therapeutic potential in managing neuropathy.

Aim and Objectives: This study aims to evaluate the effectiveness of ellagic acid in alleviating chemotherapy-induced neuropathy. Specific objectives include assessing its impact on thermal and cold allodynia, antioxidant activity, inflammation, and histopathological changes in nerve tissues, comparing its efficacy with pregabalin.

Methods: Neuropathy was induced in male Swiss albino mice using Paclitaxel (2 mg/kg, i.p.) for 5 days. Mice were then treated with ellagic acid (100 mg/kg and 200 mg/kg, orally) and pregabalin (5 mg/kg, orally) for 11 days. Behavioral tests measured thermal and cold allodynia, while biochemical markers assessed antioxidant levels and inflammatory mediators. Histopathological analysis of nerve tissues and in vitro studies using SH-Sy5Y neuroblastoma cells were also conducted.

Results: Ellagic acid significantly reduced thermal and cold allodynia, enhanced antioxidant levels, and decreased proinflammatory cytokines (TNF-α, IL-6). Histopathological analysis showed neuroprotection.

Conclusion: Ellagic acid alleviates chemotherapy-induced neuropathy by reducing oxidative stress and inflammation, demonstrating neuroprotective properties. Its comparable efficacy to pregabalin suggests potential as a natural therapeutic option for CIPN, meriting further clinical exploration.

Keywords: Neuropathy, Inflammation, Ellagic Acid, Pregabalin

Background: Lacosamide, a third-generation antiepileptic drug, is approved as adjunctive therapy for adults, adolescents, and children (>4 years) with partial-onset epilepsy. Despite its clinical utility, experience with therapeutic drug monitoring of lacosamide remains limited.

Aim: To assess the pharmacokinetic variability of plasma lacosamide concentrations and to evaluate the impact of concomitant antiepileptic therapy on these concentrations in pediatric patients with focal epilepsy.

Methods: Steady-state trough concentrations of lacosamide were determined in 52 epileptic patients attending the Pediatric Neurology Outpatient Clinic. Plasma lacosamide levels were quantified using a validated high-performance liquid chromatography (HPLC) assay. Furthermore, the correlation between plasma lacosamide concentration and clinical outcomes, specifically the reduction in seizure frequency over a six-month period will be assessed.

Results: A total of 52 children (mean age 10.43 ± 5.13 years) were enrolled in the study. The findings from the initial TDM visit are reported herein. The median daily dose of lacosamide was 200 mg (range: 50–400 mg). The mean plasma lacosamide concentration and concentration-to-dose ratio were 6.2 ± 2.1 mg/L and 0.04 ± 0.02, respectively, indicating a significant interindividual variability of 61.3%. Comparisons of the dose-normalized concentrations between patients receiving valproic acid and those not receiving it revealed no statistically significant differences.

Conclusion:This study demonstrates considerable pharmacokinetic variability in lacosamide plasma concentrations among pediatric patients. Moreover, our findings suggest that concomitant valproic acid therapy does not exert a significant effect on plasma lacosamide levels. This study is ongoing, with two lacosamide measurements scheduled for each patient, and further analyses will be conducted.

Background: RNA-based therapeutics represent a groundbreaking approach for treating genetic disorders, cancers, and infectious diseases. Despite their growing clinical application, the pharmacokinetics of RNA drugs and their potential for therapeutic drug monitoring (TDM) remain underexplored. Up to now, its role in RNA drug therapy has not well been established.

Aims: This review assesses the feasibility and requirement of TDM for RNA therapeutics, evaluating their pharmacokinetic variability and current measurement strategies.

Methods: A narrative literature review was conducted to identify key RNA drugs and their pharmacokinetic profiles. Data were gathered on measurement techniques, target concentrations, and inter-individual variability. AI-assisted tools such as Consensus, SciSpace, Litmaps, and Connected Papers facilitated article selection and comparison.

Results: RNA drugs exhibit diverse mechanisms, including RNA interference (-siran), mRNA-based protein synthesis, and antisense oligonucleotide activity (-rsen). Administration varies, requiring intravenous or subcutaneous delivery. Currently, TDM data are only available for a few RNA drugs: e.g. vutrisiran (polyneuropathy of hereditary transthyretin-mediated amyloidosis), remdesivir (antiviral), and mipomersen (familial hypercholesterolemia). Liquid chromatography-tandem mass spectrometry is the primary method for concentration measurement. Pharmacokinetic variability arises from enzymatic degradation, immune response differences, and variations in cellular uptake and distribution, influenced by genetic and metabolic factors.

Conclusions: While TDM has been successfully explored for a limited number of RNA therapeutics, the absence of standardized and validated target concentrations remains a significant challenge. Further clinical research is needed to refine monitoring strategies, ensuring safe and effective use of RNA drugs in precision medicine.

Key Words: RNA drug, oligonucleotide, pharmacokinetics, inter-individual variability

Background:
Rivaroxaban, a factor Xa inhibitor, is used for stroke prevention in atrial fibrillation (AF) patients. With identical dosing regimen, interindividual variability in pharmacokinetics may result in differences in rivaroxaban exposure and clinical outcomes.

Aims:
To establish a population pharmacokinetic (PPK) model of rivaroxaban, identify factors influencing its concentration, and investigate the association between drug exposure and clinical outcomes.

Methods:
This retrospective study enrolled AF patients receiving rivaroxaban therapy to measure steady-state drug concentrations. PPK modeling was performed using the Monolix 2023R1 (Lixoft SAS), with covariate selection based on a stepwise forward inclusion and backward elimination approach. The primary outcome was intracranial hemorrhage (ICH). Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to analyze the exposure-response relationship.

Results:
A total of 226 patients were enrolled and contributed 452 rivaroxaban concentrations during 2016 to 2023. A one-compartment model with first-order absorption and elimination adequately described the rivaroxaban pharmacokinetics. The estimated apparent clearance (CL/F) and volume of distribution (V/F) were 5.89 L/h and 45.96 L, respectively. Lean bodyweight significantly influenced V/F, while creatinine clearance and co-administration of cytochrome P450 3A4 or P-glycoprotein inhibitors affected CL/F. High rivaroxaban trough concentrations (>137 µg/L) was associated with an increased ICH risk (aHR: 28.3 [2.09 to 383]; P = 0.012).

Conclusions:
The pharmacokinetics of rivaroxaban is influenced by bodyweight, renal function, and drug interactions. Additionally, elevated rivaroxaban concentrations may lead to an increased ICH risk. Measurement of rivaroxaban concentration may be helpful in selected populations.

Keywords:
Rivaroxaban, atrial fibrillation, population pharmacokinetics, exposure-response analysis

Background: Dabigatran is an anticoagulant with a fixed dosing regimen. Interindividual variability in exposure may impact efficacy and safety, increasing the risk of thromboembolism or bleeding. Monitoring dabigatran concentrations may help optimize therapy in certain patients.

Aims: To evaluate dabigatran trough concentrations in Malaysian patients and explore factors influencing variability.

Methods: A prospective cohort study was conducted at a tertiary hospital in Malaysia. Adult patients (≥18 years) prescribed dabigatran 110mg or 150mg between March 2021 and June 2022 were recruited. Plasma trough concentrations were measured using the Hemoclot Thrombin Inhibitor assay. Pearson’s correlation assessed relationships between dabigatran concentrations and clinical variables. Mann-Whitney U and chi-square tests compared subgroups. Variability was quantified using the coefficient of variation and interquartile range. Point-biserial correlation evaluated associations between dabigatran concentrations and categorical variables.

Results:Sixty-nine patients were included, with a mean±SD dabigatran trough concentration of 65 ± 52.3 ng/mL. A 20-fold interindividual variability was observed, with concentrations ranging from 13.5-280 ng/mL. Significant correlations were found with CHA2DS2-VASc score (p=0.022), adherence (p=0.04), eGFR (p=0.019), diabetes (p=0.019), and calcium channel blocker use (p=0.021). No stroke events were observed, but six bleeding cases were reported (6.2%), primarily within the first six months of therapy.

Conclusion: Dabigatran is generally safe, but its efficacy and safety could be improved with concentration monitoring. Renal function, adherence, drug interactions, and comorbidities influence exposure and outcomes. While a direct correlation between bleeding risk and dabigatran concentrations was not confirmed, an exceedingly high concentration did result in bleeding.

Keywords: dabigatran, bleeding, thrombosis, concentration monitoring

Background: Therapeutic drug monitoring (TDM) is recommended for clozapine due to its high pharmacokinetic variability which may be especially prevalent in African populations.

Aims: To determine the associations between clozapine-related side-effects, plasma clozapine, its norclozapine metabolite, and clozapine concentration-to-dose ratio (C:D) among adult psychiatric outpatients in Johannesburg, South Africa.

Methods: Sixty-two participants on clozapine therapy for at least one month, with no recent dosage changes were recruited. Clozapine and norclozapine levels (ng/mL) were measured using UHPLC-MS/MS (Shimadzu 8060). The presence of side-effects and other factors were determined by interview and medical records.

Results: Plasma clozapine was significantly higher in those with hypersalivation (median: 148.3 vs 342.0, p= 0.002), and in those taking laxatives (median: 229.3 vs 418.3, p= 0.006). In a multivariable model clozapine C:D was significantly increased by the clozapine-to-norclozapine ratio (β= 0.79, p= <0.001), while the use of valproate (β= -0.63, p= 0.070), cigarettes (β= -0.48, p= 0.094), and cannabis (β= -0.48, p= 0.083) trended towards significance. In another multivariable model the plasma clozapine-to-norclozapine ratio was significantly influenced by valproate use (β= 0.98, p= <0.001), ethnicity (β= -0.56, p= 0.002), amount of caffeine consumed (β= -0.06, p= 0.038) and age (β= 0.02, p= <0.001). The selected co-variates explained 40.6% and 71.6% of the variation in the two models respectively.

Conclusions: This study, the first of its kind in an African population, developed a model for clozapine C:D prediction and demonstrated influencing factors which contribute to high variability in clozapine pharmacokinetics.

Keywords: Clozapine, Norclozapine, TDM, Pharmacokinetics, Africa