Title Promoter Affiliations Abstract "Development and streamlining a validation and implementation workflow for model-informed precision dosing for biologicals and antimicrobials" "Isabel Spriet" "Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, Translational Research in GastroIntestinal Disorders, Drug Delivery and Disposition, Therapeutic and Diagnostic Antibodies, Laboratory for Clinical Infectious and Inflammatory Disorders" "It has been shown that in many specific patient populations, a standard dosing approach is not always warranting efficacy and safety. Some patients benefit from an adapted and personalized dosing strategy, in which pharmacokinetic target attainment is correlating with pharmacodynamics. Many pharmacokinetic studies, conducted in the field of antimicrobial therapy and anti-inflammatory biologicals, of us and others allowed to model exposure and PK parameters with integration of patient characteristics explaining inter- and intrapatient variability.  The next step is to personalize dosing strategies based on these models, so that pharmacokinetic target attainment is ensured, which is referred to as ‘Model-Informed Precision Dosing’ (MIPD). The goal of this application is to develop and software in order to allow MIPD for infliximab (in the setting of inflammatory bowel disease), ceftriaxone and posaconazole (in the setting of critically ill patients admitted for severe pneumonia or invasive fungal infection). Next to this, a generic and broad scale applicable validation process, including internal and (multicentric retro- and prospective) external validation, will be developed. Both objectives, development and validation of MIPD software, are key-elements to bring personalized dosing to the bedside, and will serve as proof-of-concept to enable precision dosing for many other biologicals and antimicrobials." "Model-informed precision dosing of tacrolimus in solid organ transplant recipients" "Erwin Dreesen" "Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, Translational Research in GastroIntestinal Disorders, Hepatology" "Yannick Hofferts works on clinical data analysis as well as on modeling and simulation to improve the dosing of critical medication. He uses computational approaches to create, evaluate, and apply pharmacokinetics and pharmacodynamics models. The overall goal is to predict exposure and therapeutic response in vulnerable patient populations and identify sources of variability among populations to improve pharmacotherapy and, thus, clinical outcomes. His research track focuses on immunosuppressants in transplant patients and immunomodulators in patients with inflammatory bowel diseases." "Model-informed drug development: application to drug-induced cholestasis" "Pieter Annaert" "Drug Delivery and Disposition" "Drug-induced liver injury (DILI) may impair liver function and lead to liver failure or even fatality, resulting in a considerable burden on the healthcare system. In addition, drug candidates that injure the liver may terminate clinical trials, be disapproved, or be withdrawn from the market, either of which causes appreciable losses for the pharmaceutical companies. To improve drug safety and minimise the attrition during drug development, developing approaches to detect the risk of DILI at an early stage is essential. As cholestasis typically associates with altered bile acid homeostasis, drug interactions that modulate the disposition of bile acids are considered a major underlying mechanism of DILI. Consistently, early detection of disturbed bile acid homeostasis may inform the potential of DILI caused by a drug (candidate). In silico modeling and simulation can translationally integrate the findings from in vitro, in vivo animal to clinical studies and allow the bottom-up prediction of in vivo risk. Therefore, the aim of this PhD project is (1) to develop a bottom-up Physiologically-based (pharmaco)kinetic (PB(P)K) modeling strategy for bile acids and drugs in special populations; (2) to deal with patients’ variability in predicting the drug exposure; (3) to integrate mechanistic knowledge on DIC and PB(P)K modeling to predict in vivo DIC risk. Eventually, this PhD project is expected to inform drug safety at the early stage of drug development." "Computer-assisted dosing recommendation framework, feasibility study and proof of concept implementation for tacrolimus" "Pieter Annaert" "Drug Delivery and Disposition, Nephrology and Renal Transplantation Research Group" "An overwhelming number of medicinal products are marketed with the same fixed dose for every patient. Adapting the dose for each patient should result in superior efficacy and safety, at least in theory. The gold standard of dosing individualization is model-informed precision dosing (MIPD). An extensive dataset of many patients is used to identify a population pharmacokinetic/pharmacodynamic model (popPK/PD). This is composed of a mathematical model predicting outcomes (drug concentration, biomarkers, or clinical outcome) over time, the variability of parameters for that model between individuals, and any predictive covariates for these individually variable parameters. By then using observations of an individual patient, the model parameter values for that individual patient can be estimated. These parameter values are subsequently used to accurately predict future outcomes for a candidate dose, and select the most optimal future dose: model-informed precision dosing.This thesis aims to pave the road towards MIPD by exploring two key aspects. First, we show how to predict the effect of precision dosing in silico. Similar to how model-informed drug development has rationalized the drug development process, quantifying the effect of MIPD allows us to make well-informed choices, optimize investment into high-value opportunities for clinical improvement, develop better models, design better dosing strategies, and design better trials to show benefit. Second, we simplify building MIPD software tools through reusable software. Such a reusable software framework and accompanying scientific methodology reduces MIPD implementation time and cost. To show these goals are achieved, we apply this methodology to clinical use cases: infliximab induction therapy for ulcerative colitis patients, and tacrolimus immunosuppressive therapy for kidney transplant recipients.We first developed the tdmore software package, integrating pharmacometric models with individual parameter estimation and future dose optimization. The mathematical routines are accompanied by debugging tools, likelihood profile visualization, and population simulation. This software package and simulation methodology was applied to investigate precision dosing of infliximab induction therapy in ulcerative colitis. In silico, a gradual reduction in outcome variability was predicted when moving from fixed dosing to covariate-based MIPD and concentration-based MIPD. Surprisingly, average mean dose per patient was predicted to increase, without an associated improvement to mean outcome. This important negative case-study predicted that precision dosing, contrary to popular belief, may not be appropriate for infliximab induction therapy, at least in the proposed implementation. This software and simulation methodology was also applied to tacrolimus dosing for kidney transplant recipients. We showed how early simulation of predictive performance can inform modeling decisions, leading us to discard covariates in favor of the base model, as well as implementing a new estimation technique to account for parameter drift. Population simulation of MIPD showed a clinically relevant improvement in probability of target attainment, speed of target attainment and -for patients not in target- distance to target window. Clinical trial simulation informed the clinical team to expand enrollment from 100 to 200 patients, reducing the probability of an expensive but ultimately inconclusive clinical study. Both use cases demonstrate the overarching goal of rational MIPD development. Based on these simulations, a precision dosing tool was developed. First, general-purpose user interface components were developed. These were combined with an automated exchange of patient data with the electronic patient record database, and extensive business rules for automated conversion of clinical data to pharmacometric data. This system is undergoing clinical trial testing at Leuven University Hospitals since April 2021.In conclusion, this thesis has advanced the domain of MIPD. To the best of our knowledge, this is the first scientific work proposing a clear roadmap to perform informed development of MIPD: we showed how to develop a model fit-for-purpose, how to simulate whether MIPD would outperform standard of care, and which clinical trial can demonstrate this. From an engineering point of view, we greatly simplified the transformation from pharmacometric model to precision dosing tool. Finally, we showed clinical results: our work allowed future infliximab MIPD efforts to refocus their aims, and showed improved tacrolimus target attainment in silico. We developed a tacrolimus precision dosing tool in a cost-effective manner, and designed a prospective randomized clinical trial which is currently ongoing at University Hospitals Leuven." "Mold-active Azoles: Development, Validation and Implementation of strategies for Safe and Effective Dosing (M-ADVISED)" "Isabel Spriet" "Laboratory of Intensive Care Medicine, Laboratory for Clinical Infectious and Inflammatory Disorders, Clinical Pharmacology and Pharmacotherapy" "Infections, including severe bacterial infections and invasive fungal infections, are a major cause of morbidity and mortality in critically ill patients and other patient populations (i.e. patients with hematological malignancies). Therapeutic exposure to antibacterial or antifungal drugs at the site of infection (or in plasma as a surrogate matrix) is crucial for successful treatment of severe bacterial and fungal infections. However, it has been shown that critically ill patients are at risk of subtherapeutic exposure to antimicrobial drugs, mainly due to pathophysiological changes (i.e. augmented renal clearance, fluid shifts and hypoalbuminemia) that alter pharmacokinetics (PK) of commonly used antibiotic and antifungal agents (i.e. beta-lactams and azoles). In order to overcome suboptimal exposure to antimicrobials different dose optimization strategies have been developed, including personalized and covariate-based dosing regimens. Population PK (popPK) analysis is a widely applied method to guide individualized dosing strategies as it allows for a better understanding of covariates impacting PK variability in a specific patient population. Simulations based on popPK modeling can lead to different dosing strategies aiming to optimize (in silico) target attainment. These effective dosing solutions might include 1) higher doses for a broad population, 2) stratified dosing based on specific patient characteristics (e.g. renal function) or 3) model-informed precision dosing (MIPD) based on both patient characteristics (a priori information) and monitored concentrations (a posteriori information). The impact of these optimized dosing strategies, including MIPD, on pharmacokinetic-pharmacodynamic target attainment and clinical outcomes should be further scrutinized. Therefore, the major objective of this PhD research is to formulate effective dosing strategies for different antibacterial (i.e. ceftriaxone, meropenem and amikacin) and antifungal (i.e. voriconazole) drugs and to evaluate their impact on clinically relevant outcomes in special patient populations. Additionally, this PhD thesis aims to document the exposure and target attainment to isavuconazole in a real-life clinical setting, to identify covariates that may influence isavuconazole concentrations in different patient populations and to evaluate the impact of extracorporeal membrane oxygenation on the PK of isavuconazole." "A Pharmacometrics Approach to Improve Dose Individualisation Methods of Biologicals in Patients with Chronic Inflammatory Diseases" "Erwin Dreesen" "Clinical Pharmacology and Pharmacotherapy, Therapeutic and Diagnostic Antibodies, Translational Research in GastroIntestinal Disorders" "In clinical drug development, “one dose fits all” is a key objective. However, variability in exposure and thus response is common and can result in suboptimal treatment of individual patients. To hit a predefined exposure target in each patient, “therapeutic drug monitoring” (TDM) is often implemented. TDM helps improving attainment of a desired exposure target by guiding individualised drug dosing based upon drug concentrations. “Population models” can be employed to further maximise the success of TDM. These models can be applied to predict what will happen in the future and dosing can be adapted accordingly. The dictum of “one dose fits all” has been shown problematic in patients with chronic inflammatory diseases receiving biological therapies. Particular pathophysiological conditions in these patients often result in underexposure, making it difficult to properly treat these patients using standard dosing. With data from clinical trials, the applicant will develop population (and physiologically-based) models to characterise the dose-exposure- response relationship and to investigate dose optimisation opportunities (incl. model-informed precision dosing), thereby aiming to improve outcomes of (1) patients with ulcerative colitis or Crohn’s disease receiving infliximab, ustekinumab or vedolizumab therapy. (2) patients with psoriasis receiving adalimumab or guselkumab therapy." "Joint pharmacometrics modeling of antimicrobial exposure, biomarkers, and clinical outcome assessments to improve the in silico exploration of dose optimization strategies in critically ill patients" "Erwin Dreesen" "Clinical Pharmacology and Pharmacotherapy" "Dosage regimens of antimicrobial drugs predominantly stem from in vitro and animal studies. Critically ill patients display altered, highly variable drug concentration-time profiles in their bodies (i.e., pharmacokinetics; PK). Therefore, therapeutic drug monitoring (TDM) has been used to individualize dosing in this vulnerable patient group. TDM guides dosing based on drug concentration measurements, thereby maximizing the chance to meet desired exposure targets. However, the successful attainment of an exposure target is not necessarily reflected in a favorable clinical outcome. Despite the growing interest in TDM in the last decade, the quality of evidence remains low. We believe that dose optimization practices will only reach their optimal success when combining TDM with the monitoring of biomarkers and clinical markers of surrogate response such as disease activity scores (i.e., pharmacodynamics; PD). Therefore, we will develop state-of-the-art pharmacometrics models to quantitatively describe, understand, and predict the relationship between antimicrobial drug dose, drug exposure, biomarker/surrogate responses, and clinically relevant endpoints. We propose a disease/PD-oriented modeling and simulation approach based on real-world data of critically ill patients on antimicrobial treatments. We hypothesize that our population PKPD models will facilitate more efficient drug dosing, including their application in PKPD model-informed precision dosing." "Master protocol methodological pharmacometrics research" "Erwin Dreesen" "Clinical Pharmacology and Pharmacotherapy" "Background and rationale: Pharmacometrics (mixed effects) modelling and simulation is increasingly used to characterise, understand, and predict the dose-exposure-response relationships of drugs. Consequently, model-informed drug development (MIDD) has become an established business value, facilitating a cost-efficient drug development process. Population-level dosing is the preferred dosage strategy, followed by group-level dosing (e.g., adjusting for body weight, or interacting drugs) when one dose does not fit all real-word patients. If not possible to achieve safe and effective group-level dosing, individual-level dosing is the sole remaining option. Individual-level dosing can be done relying on individual patient data gathered through therapeutic drug monitoring (TDM), biomarker monitoring, response monitoring, etc. Bayesian forecasting model-informed precision dosing (MIPD) software tools have been proposed for guiding individual-level dosing. The pharmacometrics toolkit involves theoretical, mathematical/statistical modelling and simulation constructs to facilitate MIDD and MIPD. While pharmacometrics method development staggers and the toolkit may seem saturated, not all pharmacometrics research questions have been answered. Objective: To perform exploratory methodological pharmacometrics research, aiming to expand the pharmacometrics toolkit with model building/evaluation/simulation options, thereby providing a basis for continued growth of pharmacometrics modelling and simulation approaches to address currently unanswered questions regarding safety and efficacy, dosage strategy, and study design and interpretation. Research hypothesis: A flexible toolkit for developing pharmacometrics models with adequate descriptive and predictive performance will facilitate more efficient drug dosing. Trial design: This master protocol spans a continuously changing battery of exploratory, methodological (application-oriented) pharmacometrics studies. The protocol serves as a common ‘screening platform’ for pharmacometrics methodology. Since pharmacometrics is data-driven (top-down), the availability of a large, heterogeneous library of clinical and nonclinical data is a basic requirement to facilitate the methodological research. Therefore, data are a means, whilst method development is the goal. Data will be retrospectively collected from other studies. Study procedures: This is an exploratory, monocentre study at KU Leuven.Data handling: Data will be coded prior to sharing for exploratory methodological pharmacometrics analyses. Data files will be stored in the KU Leuven’s secure servers with a copy on a local computer." "Personalized pharmacotherapy in neonates: from (patho)physiology to innovative pharmacokinetic and pharmacodynamic tools" "Anne Smits" "Woman and Child" "In Flanders 8834 of all 63899 live-born neonates (14%) needed a neonatal or neonatal intensive care unit admission in 2021, because of prematurity, adaptation, critical illness, infections, or congenital malformations. Drugs play a pivotal role in the care of these highly vulnerable patients, but have been introduced without standard regulatory drug development process. Consequently the neonate remains a ‘therapeutic orphan’. Lack of evidence-based drug dosing and physiological immaturity make it challenging to predict pharmacokinetics (PK, drug concentration-time relation) and pharmacodynamics (PD, drug concentration–effect relation) in the individual neonate. This puts neonates at risk for toxicity or therapy failure. The goal of my proposal is to reach personalized pharmacotherapy, by developing and applying innovative, predictive PK and PD modeling tools for 3 clinical settings: 1) a translational physiology-based PK model for perinatal asphyxia treated with cooling, 2) an electronic-health record embedded model-informed precision dosing tool for vancomycin in neonatal sepsis, and 3) a bedside neuromonitoring PD tool for integrated PKPD models in neonatal respiratory failure. These new tools have in common that implementation of documented key PK and PD covariates and biomarkers in dose predictions will result in improved target attainment and clinical outcomes in neonates. The workflow generated can also serve to support dosing for other drugs or neonatal subpopulations" "Multi-modal image analysis for selective internal radiation therapy dosimetry" "Johan Nuyts" "Nuclear Medicine & Molecular Imaging" "The role of external beam radiation therapy in liver cancer management remains restricted because of poor tolerance of normal liver parenchyma to radiation. One solution is to follow the Paul Ehrlich (1854-1915) proposal, “we must learn to shoot microbes with magic bullets'”, to develop a radionuclide magic bullet to maximize the tumor irradiation while sparing healthy liver parenchyma as much as possible. The liver has an dual blood flow mechanism; the difference in blood supply between liver malignancies and the normal liver parenchyma, which is predominantly arterial and portal, respectively. Selective internal radiation therapy (SIRT) which is utilizing microspheres loaded with a high-energy ß-emitting radioisotope (e.g. yttrium-90 or holmium-166) benefits from this mechanism; the microspheres target the tumors passively, when infused into the hepatic artery, and consequently deliver lethal tumor irradiation while sparing a significant portion of the non-tumoral liver tissue.As mentioned before, despite the advantageous targeting of the targeted tumors, a fraction of the microspheres can be accumulated within the non-targeted tissues. In Europe, to perform a successful treatment, quantifying the tumor and non-tumor tissue irradiation is compulsory for treatment planning and for treatment verification. Because of a considerable inter- and intra-patient variation in tumor and liver tissue vascular anatomy, classical models that assume “the same relative tracer uptake in the tumor and the normal liver parenchyma in all patients” are over-simplistic for this task.Radionuclide therapies are historically prescribed in a (semi-)empirical manner and some evidence shows personalizing treatment planning could significantly enhance the therapeutic outcomes. As a result, in each individual patient, a careful treatment planning by employing a simulation workup to estimate the distribution of the therapeutic microspheres is essential. In addition, a more precise treatment evaluation is necessary to accurately determine the localization of the radionuclide in the patient’s body and to identify potential adverse effects in terms of treatment efficacy and safety. The tumor and non-tumor irradiation are usually represented by absorbed dose or absorbed energy per unit of mass; this scheme is called dosimetry.The existing dosimetric tools do not adequately extract all required information. The most commonly used method, initially developed for diagnostic applications in nuclear medicine, is widely accepted to be insufficient for internal radionuclide therapy due to several questionable assumptions: (i) the person is represented by a standard mathematical model, and the morphology of each person is not taken into account, (ii) activity is assumed to be distributed uniformly in the source organ (or sub-organ).In contrast, voxel-level dose calculation addresses the patient-specific morphology and activity heterogeneity. Voxel-level dose estimation also could be employed in treatment planning to determine a maximum injectable activity tailored for each patient based on healthy tissue tolerance criteria and tumor dose coverage. One drawback of voxel-level dosimetry is the requirement for sophisticated image registration and segmentation to obtain detailed information about activity distribution and the patient’s liver and tumor anatomy.The objective of this study was to develop a personalized dosimetric tool that answers the needs of SIRT for hepatic tumors. In this manuscript, a quantitative multi-modal image processing framework for SIRT was developed, evaluated, and applied to improve dose prediction for treatment planning, and evaluation of the treatment. The design of our procedure enables the treatment team to practice voxel-level dosimetry in a busy clinical routine. The largest part of this study was dedicated to developing registration and segmentation techniques for reporting an accurate and comprehensive absorbed dose distribution in clinically relevant volumes of interest."