Oral Presentations 15: Pharmacometrics
Tracks
Track 3
| Wednesday, September 24, 2025 |
| 1:30 PM - 3:00 PM |
| Grand Copthorne Waterfront Hotel - Waterfront Ballroom I |
Speaker
Dr Olivier Le Tilly
Université De Tours, France
A joint target-mediated drug disposition/time-to-event model of ramucirumab in gastric cancer
Abstract
Background: Ramucirumab is an anti-VEGFR2 monoclonal antibody used in gastric and gastroesophageal junction cancers. A pharmacokinetic-pharmacodynamic (PK-PD) relationship has been highlighted in these cancers (Kim 2018, Tabernero 2017) as well as non-small cell lung cancer (Akagi 2023), using Kaplan-Meier and Cox proportional hazards analyses. However, these approaches are subject to confounding factors as disease activity can also influence drug levels (Lobet 2023).
Aims: This study aimed to assess the relationship between ramucirumab pharmacokinetics, target occupancy and overall survival (OS) using joint population target-mediated drug disposition (TMDD) and parametric survival modeling.
Methods: Data were obtained from a phase II clinical trial (SOCRATE, EudraCT 2024-513515-27-00), including 70 patients receiving ramucirumab every 2 weeks up to progression or grade 3 toxicity. Ramucirumab concentrations were measured using an ELISA method (Desvignes 2021). Ramucirumab PK and hazard function for survival were described using a TMDD and a log-logistic model, respectively.
Results: Estimated parameters were volumes of distribution (V1=2.03L, V2=2.89L), clearances (CL=0.23L/d, Q=2.01L/d), baseline target level (R0=30.2nM), immune complex elimination rate (kout=0.91d-1) and dissociation constant (KSS=0.47nM). Overall survival significantly increased with ramucirumab exposure, using either concentrations or target occupancy in the model (Δ-2LL = -42.46 and -45.10, respectively).
Conclusions: This study is the first to simultaneously depict the relationship between ramucirumab PK, target occupancy and OS, and demonstrated target-mediated nonlinear PK and an association between ramucirumab exposure and clinical efficacy. A nonlinear PK was previously suspected but never described (O’Brien 2017). These results show that TDM of ramucirumab could be promising.
Key words: Ramucirumab, oncology, pharmacokinetics
Aims: This study aimed to assess the relationship between ramucirumab pharmacokinetics, target occupancy and overall survival (OS) using joint population target-mediated drug disposition (TMDD) and parametric survival modeling.
Methods: Data were obtained from a phase II clinical trial (SOCRATE, EudraCT 2024-513515-27-00), including 70 patients receiving ramucirumab every 2 weeks up to progression or grade 3 toxicity. Ramucirumab concentrations were measured using an ELISA method (Desvignes 2021). Ramucirumab PK and hazard function for survival were described using a TMDD and a log-logistic model, respectively.
Results: Estimated parameters were volumes of distribution (V1=2.03L, V2=2.89L), clearances (CL=0.23L/d, Q=2.01L/d), baseline target level (R0=30.2nM), immune complex elimination rate (kout=0.91d-1) and dissociation constant (KSS=0.47nM). Overall survival significantly increased with ramucirumab exposure, using either concentrations or target occupancy in the model (Δ-2LL = -42.46 and -45.10, respectively).
Conclusions: This study is the first to simultaneously depict the relationship between ramucirumab PK, target occupancy and OS, and demonstrated target-mediated nonlinear PK and an association between ramucirumab exposure and clinical efficacy. A nonlinear PK was previously suspected but never described (O’Brien 2017). These results show that TDM of ramucirumab could be promising.
Key words: Ramucirumab, oncology, pharmacokinetics
Biography
I am an assistant teacher of pharmacology in Tours, France. I defended my thesis on the influence of antigen mass on monoclonal antibodies elimination using target-mediated drug disposition models. My field of study is optimizing the use of monoclonal antibodies using therapeutic drug monitoring and model-informed precision dosing.
Prof Xinjun Cai
Chief pharmacist
Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine
Model-Based Precision Dosing and Non-Adherence Remediation of Isoniazid in Chinese Tuberculosis Patients
Abstract
Background: Isoniazid (INH), a first-line drug to treat tuberculosis (TB) for more than 50 years. However, large inter-individual variability was found in its pharmacokinetics, and effects of non-adherence to INH treatment and optimal remedial dosing remains unclear.
Aims: This study aimed to develop a population pharmacokinetics (PPK) model of INH in Chinese patients with TB, to provide model-informed precision dosing and explore appropriate remedial dosing regimens for non-adherent patients.
Methods: 1012 INH therapeutic drug monitoring (TDM) results from 736 TB patients were included. A nonlinear mixed-effects modeling was used to analyze the PPK of INH. Using Monte Carlo simulations to determine optimal dosage regimens and design remedial dosing regimens.
Results: A two-compartmental model, including first-order absorption and elimination with allometric scaling, was found to best describe the PK characteristics of INH. A mixture model was used to characterize dual rates of INH elimination. Estimates of apparent clearance in fast and slow eliminators were 28.0 and 11.2 L/h, respectively. Monte Carlo simulations determined optimal dosage regimens for slow and fast eliminators with different body weight. For remedial dosing regimens, the missed dose should be taken as soon as possible when the delay does not exceed 12 h, and an additional dose is not needed. On delaying a INH dose exceed 12 h, only need to take the next single dose normally.
Conclusions: TDM and PPK modeling and simulation provide valid evidence on the precision dosing and remedial dosing regimen of INH.
Keywords: Isoniazid; PPK; model-based precision dosing; remedial dosing; tuberculosis; TDM
Aims: This study aimed to develop a population pharmacokinetics (PPK) model of INH in Chinese patients with TB, to provide model-informed precision dosing and explore appropriate remedial dosing regimens for non-adherent patients.
Methods: 1012 INH therapeutic drug monitoring (TDM) results from 736 TB patients were included. A nonlinear mixed-effects modeling was used to analyze the PPK of INH. Using Monte Carlo simulations to determine optimal dosage regimens and design remedial dosing regimens.
Results: A two-compartmental model, including first-order absorption and elimination with allometric scaling, was found to best describe the PK characteristics of INH. A mixture model was used to characterize dual rates of INH elimination. Estimates of apparent clearance in fast and slow eliminators were 28.0 and 11.2 L/h, respectively. Monte Carlo simulations determined optimal dosage regimens for slow and fast eliminators with different body weight. For remedial dosing regimens, the missed dose should be taken as soon as possible when the delay does not exceed 12 h, and an additional dose is not needed. On delaying a INH dose exceed 12 h, only need to take the next single dose normally.
Conclusions: TDM and PPK modeling and simulation provide valid evidence on the precision dosing and remedial dosing regimen of INH.
Keywords: Isoniazid; PPK; model-based precision dosing; remedial dosing; tuberculosis; TDM
Biography
Xinjun Cai serves as Chief Pharmacist at Zhejiang Integrated Traditional Chinese and Western Medicine Hospital, China, and holds a position as Master's Supervisor at Zhejiang Chinese Medical University. His research focuses on precision therapeutics for tuberculosis management, with particular emphasis on optimizing individualized anti-TB regimens through therapeutic drug monitoring (TDM). The team led by him has achieved many results in the research of pharmacokinetics/pharmacodynamics (PK/PD) modeling, toxicological research, and clinical pharmacology of anti-tuberculosis drugs, received funding from multiple national-level scientific research projects, and published many journal papers. The long-term goal of his team research is to improve the efficacy of anti-TB drugs and reducing the occurrence of adverse reactions and drug resistance.
Mr Stef Schouwenburg
Erasmus University Medical Center
Intravenous cefuroxime target attainment in neonates and infants: pooled population pharmacokinetic study
Abstract
Background: Cefuroxime is a widely prescribed beta-lactam antibiotic, particularly in pediatric cardiac and medical-surgical intensive care units.
Aims: To describe intravenous cefuroxime disposition in critically ill pediatric patients. Moreover, target attainment of currently applied dosing regimens were evaluated and suggestions for improvement of these dosing regimens were provided.
Methods: This pooled population pharmacokinetic (popPK) study combined two datasets for analysis in NONMEM v7.5. Cefuroxime exposure was simulated using the percentage of time above the minimum inhibitory concentration (%T>MIC). PK profiles of different dosage regimens (intermittent/continuous) were simulated with the developed popPK model. A target of 90% of cases 100%T>(4x)MIC8mg/L was used.
Results: The cohort consisted of 45 pediatric patient’s with a median (range) age of 391 days (0-6131), and bodyweight of 9.0 kg (2.8-70.0). A two-compartment popPK model with first-order elimination and allometric scaling best described cefuroxime disposition. Postnatal age and creatinine clearance were the best descriptive covariates for cefuroxime clearance. Simulations evaluating the current cefuroxime dosing regimens stratified for eGFR levels illustrated moderate (eGFR <30 and 30-80 mL/min./1.73m2) and poor (eGFR 80-120 and >120 mL/min/1.73m2) cefuroxime target attainment across the entire age range. Alternative dosing regimens, including four times daily schedules and continuous infusion, improved target attainment, particularly in older children and those with augmented renal clearance.
Conclusions: While applying the current dosing regimens, underexposure due to enhance renal functions is possible. Future research should focus on individualized dosing strategies to optimize cefuroxime exposure and efficacy in pediatric populations.
Key Words: Cefuroxime, Pediatrics, Population pharmacokinetics, PICU
Aims: To describe intravenous cefuroxime disposition in critically ill pediatric patients. Moreover, target attainment of currently applied dosing regimens were evaluated and suggestions for improvement of these dosing regimens were provided.
Methods: This pooled population pharmacokinetic (popPK) study combined two datasets for analysis in NONMEM v7.5. Cefuroxime exposure was simulated using the percentage of time above the minimum inhibitory concentration (%T>MIC). PK profiles of different dosage regimens (intermittent/continuous) were simulated with the developed popPK model. A target of 90% of cases 100%T>(4x)MIC8mg/L was used.
Results: The cohort consisted of 45 pediatric patient’s with a median (range) age of 391 days (0-6131), and bodyweight of 9.0 kg (2.8-70.0). A two-compartment popPK model with first-order elimination and allometric scaling best described cefuroxime disposition. Postnatal age and creatinine clearance were the best descriptive covariates for cefuroxime clearance. Simulations evaluating the current cefuroxime dosing regimens stratified for eGFR levels illustrated moderate (eGFR <30 and 30-80 mL/min./1.73m2) and poor (eGFR 80-120 and >120 mL/min/1.73m2) cefuroxime target attainment across the entire age range. Alternative dosing regimens, including four times daily schedules and continuous infusion, improved target attainment, particularly in older children and those with augmented renal clearance.
Conclusions: While applying the current dosing regimens, underexposure due to enhance renal functions is possible. Future research should focus on individualized dosing strategies to optimize cefuroxime exposure and efficacy in pediatric populations.
Key Words: Cefuroxime, Pediatrics, Population pharmacokinetics, PICU
Biography
Stef Schouwenburg is a Pharmacist-Researcher from Rotterdam, The Netherlands. He works at the Department of Hospital Pharmacy in the Erasmus University Medical Center.
Dr Yazhini Rajendran
Dm Clinical Pharmacology Senior Resident
Drug interaction prediction between Tacrolimus and Piperine using Physiologically Based Pharmacokinetic modeling
Abstract
Background
Bioavailability of Tacrolimus is a significant problem, with CYP3A5 expresser genotype (*1/*1 , *1/*3) that rapidly metabolise the drug, requiring higher dose >0.2 mg/kg. While pharmacokinetic (PK) boosters like ketoconazole and diltiazem enhance tacrolimus bioavailability, safety concerns highlight the need for alternative strategies. Piperine, derived from the Piperaceae family, being used as a food supplement, enhances bioavailability by increasing gastrointestinal absorption, membrane fluidity, and inhibiting CYP450 enzymes. While its PK boosting effects are known with drugs like carbamazepine and phenytoin, its interaction with Tacrolimus remains unstudied.
Aim
This aim of this study is to develop a PBPK model to predict the interaction between Tacrolimus and Piperine.
Methods
GastroPlus software was employed for developing and validating the PBPK model, incorporating published clinical PK data for Tacrolimus. The model simulated the impact of Piperine (20 mg BID for seven days) on Tacrolimus pharmacokinetics.
Results
The baseline models for Tacrolimus and Piperine were validated individually and prediction errors were within two folds. The combination of physicochemical properties, elimination parameters and physiology accounted for disposition of both the drugs were accurate in the developed models. The simulated model predicted significant drug interaction between Piperine and Tacrolimus involving the CYP and non-CYP mediated mechanisms. The study results may aid in reducing the dose of tacrolimus in patients with CYP3A5 expresser profile.
Conclusion
This is the first PBPK-based evaluation of Tacrolimus-Piperine interaction, providing a foundation for future clinical studies in organ transplant recipients.
Keywords: PBPK Modeling, Piperine, Tacrolimus, Interaction, Bioavailability enhancer
Bioavailability of Tacrolimus is a significant problem, with CYP3A5 expresser genotype (*1/*1 , *1/*3) that rapidly metabolise the drug, requiring higher dose >0.2 mg/kg. While pharmacokinetic (PK) boosters like ketoconazole and diltiazem enhance tacrolimus bioavailability, safety concerns highlight the need for alternative strategies. Piperine, derived from the Piperaceae family, being used as a food supplement, enhances bioavailability by increasing gastrointestinal absorption, membrane fluidity, and inhibiting CYP450 enzymes. While its PK boosting effects are known with drugs like carbamazepine and phenytoin, its interaction with Tacrolimus remains unstudied.
Aim
This aim of this study is to develop a PBPK model to predict the interaction between Tacrolimus and Piperine.
Methods
GastroPlus software was employed for developing and validating the PBPK model, incorporating published clinical PK data for Tacrolimus. The model simulated the impact of Piperine (20 mg BID for seven days) on Tacrolimus pharmacokinetics.
Results
The baseline models for Tacrolimus and Piperine were validated individually and prediction errors were within two folds. The combination of physicochemical properties, elimination parameters and physiology accounted for disposition of both the drugs were accurate in the developed models. The simulated model predicted significant drug interaction between Piperine and Tacrolimus involving the CYP and non-CYP mediated mechanisms. The study results may aid in reducing the dose of tacrolimus in patients with CYP3A5 expresser profile.
Conclusion
This is the first PBPK-based evaluation of Tacrolimus-Piperine interaction, providing a foundation for future clinical studies in organ transplant recipients.
Keywords: PBPK Modeling, Piperine, Tacrolimus, Interaction, Bioavailability enhancer
Biography
Dr. Yazhini R. is a dedicated clinical pharmacologist currently pursuing a DM in Clinical Pharmacology at PGIMER, Chandigarh. She completed her **MBBS and MD in Pharmacology** from the prestigious All India Institute of Medical Sciences (AIIMS), Raipur. With a keen interest in Therapeutic Drug Monitoring (TDM) of immunosuppressants, her work focuses on optimizing drug therapy for better patient outcomes.
Mr Luong Vuong
Ku Leuven
An optimised fluconazole dosing strategy in critically ill patients
Abstract
Background: Invasive candidiasis, particularly candidaemia, is a life-threatening complication in critically ill patients. Fluconazole is the recommended step-down therapy from echinocandins for fluconazole-susceptible Candida spp. However, standard fluconazole dosing does not achieve adequate exposure in critically ill patients.
Aims: This study aimed to identify factors that impact fluconazole target attainment and provide a dosing regimen ensuring adequate pharmacokinetic–pharmacodynamic (PKPD) target attainment in critically ill patients.
Methods: An individual patient data meta-analysis was conducted, combining fluconazole concentration data from eight published studies. We developed a population pharmacokinetics (popPK) model and used multiple imputation to handle missing covariate data. We performed Monte Carlo simulations to identify a dosing strategy with at least a 90% probability of PKPD target attainment (PTA) in every patient.
Results: Data from 177 critically ill patients were included. A two-compartment popPK model with linear elimination best described the data. Continuous renal replacement therapy (CRRT) status, estimated glomerular filtration rate, and total body weight (BW) were statistically significant covariates. However, with standard dosing, only CRRT status and BW were clinically relevant with the PTA dropping below 90% for all patients on CRRT, and for patients not undergoing CRRT weighing more than 60 kg. An optimised dosing regimen considering the patient’s CRRT status and BW is proposed.
Conclusion: We have developed a fluconazole dosing regimen that could achieve adequate population-wide PKPD target attainment in critically ill patients. Confirmation that the proposed dosing regimen achieves optimal fluconazole exposure is required.
Keywords: Population pharmacokinetics, Monte Carlo simulation, Individual patient data meta-analysis
Aims: This study aimed to identify factors that impact fluconazole target attainment and provide a dosing regimen ensuring adequate pharmacokinetic–pharmacodynamic (PKPD) target attainment in critically ill patients.
Methods: An individual patient data meta-analysis was conducted, combining fluconazole concentration data from eight published studies. We developed a population pharmacokinetics (popPK) model and used multiple imputation to handle missing covariate data. We performed Monte Carlo simulations to identify a dosing strategy with at least a 90% probability of PKPD target attainment (PTA) in every patient.
Results: Data from 177 critically ill patients were included. A two-compartment popPK model with linear elimination best described the data. Continuous renal replacement therapy (CRRT) status, estimated glomerular filtration rate, and total body weight (BW) were statistically significant covariates. However, with standard dosing, only CRRT status and BW were clinically relevant with the PTA dropping below 90% for all patients on CRRT, and for patients not undergoing CRRT weighing more than 60 kg. An optimised dosing regimen considering the patient’s CRRT status and BW is proposed.
Conclusion: We have developed a fluconazole dosing regimen that could achieve adequate population-wide PKPD target attainment in critically ill patients. Confirmation that the proposed dosing regimen achieves optimal fluconazole exposure is required.
Keywords: Population pharmacokinetics, Monte Carlo simulation, Individual patient data meta-analysis
Biography
My-Luong Vuong holds a Pharm.D. from Hanoi University of Pharmacy, Vietnam, along with a Master's in Epidemiology from the University of Antwerp, Belgium. He is passionate about combatting antimicrobial resistance, a significant healthcare challenge in his home country Vietnam. He’s currently doing a PhD in pharmacometrics at Leuven Pharmacometrics Research Group, KU Leuven, where his research focuses on utilizing pharmacometrics to optimise antimicrobial dosing in intensive care unit patients to improve their clinical outcomes. Besides, he is also interested in enhancing the methodological aspect of pharmacometrics research.
Mr Stef Schouwenburg
Erasmus University Medical Center
Performance evaluation of ceftriaxone population pharmacokinetic models in children
Abstract
Background: Sepsis affects approximately 8% of pediatric intensive care unit (PICU) admissions in high-income countries. Ceftriaxone, a broad-spectrum beta-lactam antibiotic, is widely used for treating severe infections and bacterial meningitis in children. Despite its frequent use, limited studies address the population pharmacokinetic (popPK) of ceftriaxone in pediatrics.
Aims: To externally evaluate pediatric ceftriaxone popPK model peformance, enabling selection of the model best suited to this population.
Methods: This study used data from the EXPAT Kids study, a prospective PK/PD study. Included popPK models were implemented in NONMEM, with diagnostic goodness-of-fit and visual predictive check analyses performed to assess model accuracy. Predictive performance was evaluated using the relative prediction error, relative root mean square error, and mean (absolute) percentage error.
Results: The predictive performance of the evaluated models varied widely. Included models showed only modest performance and generally seem to overpredict ceftriaxone concentrations. Unbound ceftriaxone popPK models did not perform adequately. None of the models met all the predefined thresholds for accuracy and precision.
Conclusion: Our external dataset comprised high ceftriaxone trough concentrations, indicating re-evaluation of current ceftriaxone dosing regimens to minimize the risk of overdosing and prevent toxicity. Future research should focus on the fine dosing balance for ceftriaxone (especially in meningitis patients) considering adequate exposure but preventing high trough concentrations. Model informed precision dosing may enhance the use of the optimal individual dosage for critically ill children. However, our findings highlight the importance of externally evaluating ceftriaxone popPK models in the PICU population.
Key words: Ceftriaxone, Population Pharmacokinetics, Pediatrics
Aims: To externally evaluate pediatric ceftriaxone popPK model peformance, enabling selection of the model best suited to this population.
Methods: This study used data from the EXPAT Kids study, a prospective PK/PD study. Included popPK models were implemented in NONMEM, with diagnostic goodness-of-fit and visual predictive check analyses performed to assess model accuracy. Predictive performance was evaluated using the relative prediction error, relative root mean square error, and mean (absolute) percentage error.
Results: The predictive performance of the evaluated models varied widely. Included models showed only modest performance and generally seem to overpredict ceftriaxone concentrations. Unbound ceftriaxone popPK models did not perform adequately. None of the models met all the predefined thresholds for accuracy and precision.
Conclusion: Our external dataset comprised high ceftriaxone trough concentrations, indicating re-evaluation of current ceftriaxone dosing regimens to minimize the risk of overdosing and prevent toxicity. Future research should focus on the fine dosing balance for ceftriaxone (especially in meningitis patients) considering adequate exposure but preventing high trough concentrations. Model informed precision dosing may enhance the use of the optimal individual dosage for critically ill children. However, our findings highlight the importance of externally evaluating ceftriaxone popPK models in the PICU population.
Key words: Ceftriaxone, Population Pharmacokinetics, Pediatrics
Biography
Stef Schouwenburg is a Pharmacist-Researcher from Rotterdam, the Netherlands. He works at the Erasmus University Medical Center and is finishing up his PhD-trajectory.
Mrs Afnan Abdul Roda
hospital pharmacist in training and clinical pharmacologist in training
Amsterdam UMC
Clozapine optimal timing for optimal monitoring (COTTON)
Abstract
Background: Therapeutic drug monitoring (TDM) is essential for optimizing clozapine treatment. Current guidelines recommend blood sampling 12 (±2) hours after intake for once-daily dosing. However, this timing is primarily based on twice-daily dosing regimens and its suitability for once daily dosing remains uncertain.
Aims: This study aims to evaluate the validity of current TDM practice for once-daily clozapine dosing.
Methods: This retrospective, single-center study includes patients with treatment-resistant schizophrenia spectrum disorders on stable once-daily clozapine, with TDM performed as part of standard care. Bayesian analysis was used to predict individual concentration-time profiles. Predicted clozapine concentrations at 10, 11, 13, and 14 hours post-intake were compared to the 12-hour reference value, with deviations exceeding 20% considered clinically significant.
Results: Data were collected from seven patients (86% male, 14% non-smoker) with a clozapine dose of 246±109 mg (mean±SD). A total of 22 clozapine samples were analyzed, of which two outliers were excluded. The mean clozapine concentration at t=12 was 608±255 μg/L. The mean percentage differences from the 12-hour reference value were 6.4±2.0%, 3.1±1.0%, -2.9±1.0%, and -5.7±1.8% at t=10, 11, 13 and 14 hours, respectively.
Conclusions: These preliminary findings suggest that the current sampling window of 12 (±2) hours post-intake is appropriate for the clinical interpretation of clozapine levels in once-daily dosing. However, given the limited dataset and absence of the consideration of inter-occasion PK variability (IOV), additional data and further analysis is required to confirm the sampling window for once-daily clozapine dosing.
Keywords: Clozapine, therapeutic drug monitoring, population pharmacokinetics, sampling time, schizophrenia
Aims: This study aims to evaluate the validity of current TDM practice for once-daily clozapine dosing.
Methods: This retrospective, single-center study includes patients with treatment-resistant schizophrenia spectrum disorders on stable once-daily clozapine, with TDM performed as part of standard care. Bayesian analysis was used to predict individual concentration-time profiles. Predicted clozapine concentrations at 10, 11, 13, and 14 hours post-intake were compared to the 12-hour reference value, with deviations exceeding 20% considered clinically significant.
Results: Data were collected from seven patients (86% male, 14% non-smoker) with a clozapine dose of 246±109 mg (mean±SD). A total of 22 clozapine samples were analyzed, of which two outliers were excluded. The mean clozapine concentration at t=12 was 608±255 μg/L. The mean percentage differences from the 12-hour reference value were 6.4±2.0%, 3.1±1.0%, -2.9±1.0%, and -5.7±1.8% at t=10, 11, 13 and 14 hours, respectively.
Conclusions: These preliminary findings suggest that the current sampling window of 12 (±2) hours post-intake is appropriate for the clinical interpretation of clozapine levels in once-daily dosing. However, given the limited dataset and absence of the consideration of inter-occasion PK variability (IOV), additional data and further analysis is required to confirm the sampling window for once-daily clozapine dosing.
Keywords: Clozapine, therapeutic drug monitoring, population pharmacokinetics, sampling time, schizophrenia
Biography
Afnan is training to become both a hospital pharmacist and a clinical pharmacologist, with a strong interest in therapy optimization. She has always been driven by a desire to make a meaningful societal contribution, which led her to the medical field. Combining her analytical mindset with a passion for patient care, she found her place in clinical pharmacology and hospital pharmacy, where she works to refine drug therapy and improve patient outcomes.
Driven by her commitment to individualized pharmacotherapy, she chose a traineeship that provides extensive experience in wards where therapeutic drug monitoring (TDM) and pharmacokinetic/pharmacodynamic (PK/PD) relationships are particularly relevant. Through her work in psychiatry, intensive care, and infectious diseases, she continues to develop a deeper understanding of drug exposure variability and its clinical implications. By integrating research with hands-on clinical experience, she strives to enhance medication management and contribute to safer, more effective pharmacotherapy.
