@misc{WichaKeesSolmsetal.2015, author = {Wicha, Sebastian G. and Kees, Martin G. and Solms, Alexander Maximilian and Minichmayr, Iris K. and Kratzer, Alexander and Kloft, Charlotte}, title = {TDMx: A novel web-based open-access support tool for optimising antimicrobial dosing regimens in clinical routine}, series = {International journal of antimicrobial agents}, volume = {45}, journal = {International journal of antimicrobial agents}, number = {4}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0924-8579}, doi = {10.1016/j.ijantimicag.2014.12.010}, pages = {442 -- 444}, year = {2015}, language = {en} } @article{WichaHuisingaKloft2017, author = {Wicha, Sebastian G. and Huisinga, Wilhelm and Kloft, Charlotte}, title = {Translational pharmacometric evaluation of typical antibiotic broad-spectrum combination therapies against staphylococcus aureus exploiting in vitro information}, series = {CPT: pharmacometrics \& systems pharmacology}, volume = {6}, journal = {CPT: pharmacometrics \& systems pharmacology}, publisher = {Wiley}, address = {Hoboken}, issn = {2163-8306}, doi = {10.1002/psp4.12197}, pages = {512 -- 522}, year = {2017}, abstract = {Broad-spectrum antibiotic combination therapy is frequently applied due to increasing resistance development of infective pathogens. The objective of the present study was to evaluate two common empiric broad-spectrum combination therapies consisting of either linezolid (LZD) or vancomycin (VAN) combined with meropenem (MER) against Staphylococcus aureus (S. aureus) as the most frequent causative pathogen of severe infections. A semimechanistic pharmacokinetic-pharmacodynamic (PK-PD) model mimicking a simplified bacterial life-cycle of S. aureus was developed upon time-kill curve data to describe the effects of LZD, VAN, and MER alone and in dual combinations. The PK-PD model was successfully (i) evaluated with external data from two clinical S. aureus isolates and further drug combinations and (ii) challenged to predict common clinical PK-PD indices and breakpoints. Finally, clinical trial simulations were performed that revealed that the combination of VAN-MER might be favorable over LZD-MER due to an unfavorable antagonistic interaction between LZD and MER.}, language = {en} } @article{WeineltStegemannTheloeetal.2022, author = {Weinelt, Ferdinand Anton and Stegemann, Miriam Songa and Theloe, Anja and Pf{\"a}fflin, Frieder and Achterberg, Stephan and Weber, Franz and D{\"u}bel, Lucas and Mikolajewska, Agata and Uhrig, Alexander and Kiessling, Peggy and Huisinga, Wilhelm and Michelet, Robin and Hennig, Stefanie and Kloft, Charlotte}, title = {Evaluation of a meropenem and piperacillin monitoring program in intensive care unit patients calls for the regular assessment of empirical targets and easy-to-use dosing decision tools}, series = {Antibiotics : open access journal}, volume = {11}, journal = {Antibiotics : open access journal}, number = {6}, publisher = {MDPI}, address = {Basel}, issn = {2079-6382}, doi = {10.3390/antibiotics11060758}, pages = {17}, year = {2022}, abstract = {The drug concentrations targeted in meropenem and piperacillin/tazobactam therapy also depend on the susceptibility of the pathogen. Yet, the pathogen is often unknown, and antibiotic therapy is guided by empirical targets. To reliably achieve the targeted concentrations, dosing needs to be adjusted for renal function. We aimed to evaluate a meropenem and piperacillin/tazobactam monitoring program in intensive care unit (ICU) patients by assessing (i) the adequacy of locally selected empirical targets, (ii) if dosing is adequately adjusted for renal function and individual target, and (iii) if dosing is adjusted in target attainment (TA) failure. In a prospective, observational clinical trial of drug concentrations, relevant patient characteristics and microbiological data (pathogen, minimum inhibitory concentration (MIC)) for patients receiving meropenem or piperacillin/tazobactam treatment were collected. If the MIC value was available, a target range of 1-5 x MIC was selected for minimum drug concentrations of both drugs. If the MIC value was not available, 8-40 mg/L and 16-80 mg/L were selected as empirical target ranges for meropenem and piperacillin, respectively. A total of 356 meropenem and 216 piperacillin samples were collected from 108 and 96 ICU patients, respectively. The vast majority of observed MIC values was lower than the empirical target (meropenem: 90.0\%, piperacillin: 93.9\%), suggesting empirical target value reductions. TA was found to be low (meropenem: 35.7\%, piperacillin 50.5\%) with the lowest TA for severely impaired renal function (meropenem: 13.9\%, piperacillin: 29.2\%), and observed drug concentrations did not significantly differ between patients with different targets, indicating dosing was not adequately adjusted for renal function or target. Dosing adjustments were rare for both drugs (meropenem: 6.13\%, piperacillin: 4.78\%) and for meropenem irrespective of TA, revealing that concentration monitoring alone was insufficient to guide dosing adjustment. Empirical targets should regularly be assessed and adjusted based on local susceptibility data. To improve TA, scientific knowledge should be translated into easy-to-use dosing strategies guiding antibiotic dosing.}, language = {en} } @inproceedings{SteenholdtEdlundAinsworthetal.2015, author = {Steenholdt, Casper and Edlund, Helena and Ainsworth, Mark A. and Brynskov, Jorn and Thomsen, Ole Ostergaard and Huisinga, Wilhelm and Kloft, Charlotte}, title = {Relationship between measures of infliximab exposure and clinical outcome of infliximab intensification at therapeutic failure in Crohn's disease}, series = {JOURNAL OF CROHNS \& COLITIS}, volume = {9}, booktitle = {JOURNAL OF CROHNS \& COLITIS}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {1873-9946}, pages = {S330 -- S330}, year = {2015}, language = {en} } @article{StachanowNeumannBlankensteinetal.2022, author = {Stachanow, Viktoria and Neumann, Uta and Blankenstein, Oliver and Bindellini, Davide and Melin, Johanna and Ross, Richard and Whitaker, Martin J. J. and Huisinga, Wilhelm and Michelet, Robin and Kloft, Charlotte}, title = {Exploring dried blood spot cortisol concentrations as an alternative for monitoring pediatric adrenal insufficiency patients}, series = {Frontiers in pharmacology}, volume = {13}, journal = {Frontiers in pharmacology}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1663-9812}, doi = {10.3389/fphar.2022.819590}, pages = {8}, year = {2022}, abstract = {Congenital adrenal hyperplasia (CAH) is the most common form of adrenal insufficiency in childhood; it requires cortisol replacement therapy with hydrocortisone (HC, synthetic cortisol) from birth and therapy monitoring for successful treatment. In children, the less invasive dried blood spot (DBS) sampling with whole blood including red blood cells (RBCs) provides an advantageous alternative to plasma sampling. Potential differences in binding/association processes between plasma and DBS however need to be considered to correctly interpret DBS measurements for therapy monitoring. While capillary DBS samples would be used in clinical practice, venous cortisol DBS samples from children with adrenal insufficiency were analyzed due to data availability and to directly compare and thus understand potential differences between venous DBS and plasma. A previously published HC plasma pharmacokinetic (PK) model was extended by leveraging these DBS concentrations. In addition to previously characterized binding of cortisol to albumin (linear process) and corticosteroid-binding globulin (CBG; saturable process), DBS data enabled the characterization of a linear cortisol association with RBCs, and thereby providing a quantitative link between DBS and plasma cortisol concentrations. The ratio between the observed cortisol plasma and DBS concentrations varies highly from 2 to 8. Deterministic simulations of the different cortisol binding/association fractions demonstrated that with higher blood cortisol concentrations, saturation of cortisol binding to CBG was observed, leading to an increase in all other cortisol binding fractions. In conclusion, a mathematical PK model was developed which links DBS measurements to plasma exposure and thus allows for quantitative interpretation of measurements of DBS samples.}, language = {en} } @article{ScharfWeineltSchroederetal.2022, author = {Scharf, Christina and Weinelt, Ferdinand Anton and Schroeder, Ines and Paal, Michael and Weigand, Michael and Zoller, Michael and Irlbeck, Michael and Kloft, Charlotte and Briegel, Josef and Liebchen, Uwe}, title = {Does the cytokine adsorber CytoSorb (R) reduce vancomycin exposure in critically ill patients with sepsis or septic shock?}, series = {Annals of intensive care}, volume = {12}, journal = {Annals of intensive care}, number = {1}, publisher = {Springer}, address = {Heidelberg}, issn = {2110-5820}, doi = {10.1186/s13613-022-01017-5}, pages = {8}, year = {2022}, abstract = {Background: Hemadsorption of cytokines is used in critically ill patients with sepsis or septic shock. Concerns have been raised that the cytokine adsorber CytoSorb (R) unintentionally adsorbs vancomycin. This study aimed to quantify vancomycin elimination by CytoSorb (R) . Methods: Critically ill patients with sepsis or septic shock receiving continuous renal replacement therapy and CytoSorb (R) treatment during a prospective observational study were included in the analysis. Vancomycin pharmacokinetics was characterized using population pharmacokinetic modeling. Adsorption of vancomycin by the CytoSorb (R) was investigated as linear or saturable process. The final model was used to derive dosing recommendations based on stochastic simulations. Results: 20 CytoSorb (R) treatments in 7 patients (160 serum samples/24 during CytoSorb (R)-treatment, all continuous infusion) were included in the study. A classical one-compartment model, including effluent flow rate of the continuous hemodialysis as linear covariate on clearance, best described the measured concentrations (without CytoSorb (R)). Significant adsorption with a linear decrease during CytoSorb (R) treatment was identified (p <0.0001) and revealed a maximum increase in vancomycin clearance of 291\% (initially after CytoSorb (R) installation) and a maximum adsorption capacity of 572 mg. For a representative patient of our cohort a reduction of the area under the curve (AUC) by 93 mg/L*24 h during CytoSorb (R) treatment was observed. The additional administration of 500 mg vancomycin over 2 h during CytoSorb (R) attenuated the effect and revealed a negligible reduction of the AUC by 4 mg/L*24h. Conclusion: We recommend the infusion of 500 mg vancomycin over 2 h during CytoSorb (R) treatment to avoid subtherapeutic concentrations.}, language = {en} } @article{NassarHohmannMicheletetal.2022, author = {Nassar, Yomna M. and Hohmann, Nicolas and Michelet, Robin and Gottwalt, Katharina and Meid, Andreas D. and Burhenne, J{\"u}rgen and Huisinga, Wilhelm and Haefeli, Walter E. and Mikus, Gerd and Kloft, Charlotte}, title = {Quantification of the Time Course of CYP3A Inhibition, Activation, and Induction Using a Population Pharmacokinetic Model of Microdosed Midazolam Continuous Infusion}, series = {Clinical Pharmacokinetics}, volume = {61}, journal = {Clinical Pharmacokinetics}, number = {11}, publisher = {Springer}, address = {Northcote}, issn = {0312-5963}, doi = {10.1007/s40262-022-01175-6}, pages = {1595 -- 1607}, year = {2022}, abstract = {Background Cytochrome P450 (CYP) 3A contributes to the metabolism of many approved drugs. CYP3A perpetrator drugs can profoundly alter the exposure of CYP3A substrates. However, effects of such drug-drug interactions are usually reported as maximum effects rather than studied as time-dependent processes. Identification of the time course of CYP3A modulation can provide insight into when significant changes to CYP3A activity occurs, help better design drug-drug interaction studies, and manage drug-drug interactions in clinical practice. Objective We aimed to quantify the time course and extent of the in vivo modulation of different CYP3A perpetrator drugs on hepatic CYP3A activity and distinguish different modulatory mechanisms by their time of onset, using pharmacologically inactive intravenous microgram doses of the CYP3A-specific substrate midazolam, as a marker of CYP3A activity. Methods Twenty-four healthy individuals received an intravenous midazolam bolus followed by a continuous infusion for 10 or 36 h. Individuals were randomized into four arms: within each arm, two individuals served as a placebo control and, 2 h after start of the midazolam infusion, four individuals received the CYP3A perpetrator drug: voriconazole (inhibitor, orally or intravenously), rifampicin (inducer, orally), or efavirenz (activator, orally). After midazolam bolus administration, blood samples were taken every hour (rifampicin arm) or every 15 min (remaining study arms) until the end of midazolam infusion. A total of 1858 concentrations were equally divided between midazolam and its metabolite, 1'-hydroxymidazolam. A nonlinear mixed-effects population pharmacokinetic model of both compounds was developed using NONMEM (R). CYP3A activity modulation was quantified over time, as the relative change of midazolam clearance encountered by the perpetrator drug, compared to the corresponding clearance value in the placebo arm. Results Time course of CYP3A modulation and magnitude of maximum effect were identified for each perpetrator drug. While efavirenz CYP3A activation was relatively fast and short, reaching a maximum after approximately 2-3 h, the induction effect of rifampicin could only be observed after 22 h, with a maximum after approximately 28-30 h followed by a steep drop to almost baseline within 1-2 h. In contrast, the inhibitory impact of both oral and intravenous voriconazole was prolonged with a steady inhibition of CYP3A activity followed by a gradual increase in the inhibitory effect until the end of sampling at 8 h. Relative maximum clearance changes were +59.1\%, +46.7\%, -70.6\%, and -61.1\% for efavirenz, rifampicin, oral voriconazole, and intravenous voriconazole, respectively. Conclusions We could distinguish between different mechanisms of CYP3A modulation by the time of onset. Identification of the time at which clearance significantly changes, per perpetrator drug, can guide the design of an optimal sampling schedule for future drug-drug interaction studies. The impact of a short-term combination of different perpetrator drugs on the paradigm CYP3A substrate midazolam was characterized and can define combination intervals in which no relevant interaction is to be expected.}, language = {en} } @misc{MuellerSchoellKloppSchulzeHuisingaetal.2019, author = {M{\"u}ller-Sch{\"o}ll, A. and Klopp-Schulze, Lena and Huisinga, Wilhelm and J{\"o}rger, M. and Neven, P. and Koolen, S. L. and Mathijssen, R. H. J. and Schmidt, S. and Kloft, Charlotte}, title = {Patient-tailored tamoxifen dosing based on an increased quantitative understanding of its complex pharmacokinetics: A novel integrative modelling approach}, series = {Annals of Oncology}, volume = {30}, journal = {Annals of Oncology}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0923-7534}, pages = {1}, year = {2019}, language = {en} } @article{MuellerSchoellGroenlandScherfClaveletal.2020, author = {Mueller-Schoell, Anna and Groenland, Stefanie L. and Scherf-Clavel, Oliver and van Dyk, Madele and Huisinga, Wilhelm and Michelet, Robin and Jaehde, Ulrich and Steeghs, Neeltje and Huitema, Alwin D. R. and Kloft, Charlotte}, title = {Therapeutic drug monitoring of oral targeted antineoplastic drugs}, series = {European journal of clinical pharmacology}, volume = {77}, journal = {European journal of clinical pharmacology}, number = {4}, publisher = {Springer}, address = {Heidelberg}, issn = {0031-6970}, doi = {10.1007/s00228-020-03014-8}, pages = {441 -- 464}, year = {2020}, abstract = {Purpose This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed. Methods A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted. Results OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy. Conclusion Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.}, language = {en} } @article{MinichmayrRobertsFreyetal.2018, author = {Minichmayr, Iris K. and Roberts, Jason A. and Frey, Otto R. and Roehr, Anka C. and Kloft, Charlotte and Brinkmann, Alexander}, title = {Development of a dosing nomogram for continuous-infusion meropenem in critically ill patients based on a validated population pharmacokinetic model}, series = {Journal of Antimicrobial Chemotherapy}, volume = {73}, journal = {Journal of Antimicrobial Chemotherapy}, number = {5}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0305-7453}, doi = {10.1093/jac/dkx526}, pages = {1330 -- 1339}, year = {2018}, abstract = {Background: Optimal antibiotic exposure is a vital but challenging prerequisite for achieving clinical success in ICU patients. Objectives: To develop and externally validate a population pharmacokinetic model for continuous-infusion meropenem in critically ill patients and to establish a nomogram based on a routinely available marker of renal function. Methods: A population pharmacokinetic model was developed in NONMEM (R) 7.3 based on steady-state meropenem concentrations (C-ss) collected during therapeutic drug monitoring. Different serum creatinine-based markers of renal function were compared for their influence on meropenem clearance (the Cockcroft-Gault creatinine clearance CLCRcG, the CLCR bedside estimate according to Jelliffe, the Chronic Kidney Disease Epidemiology Collaboration equation and the four-variable Modification of Diet in Renal Disease equation). After validation of the pharmacokinetic model with independent data, a dosing nomogram was developed, relating renal function to the daily doses required to achieve selected target concentrations (4/8/16 mg/L) in 90\% of the patients. Probability of target attainment was determined for efficacy (C-ss >= 8 mg/L) and potentially increased likelihood of adverse drug reactions (C-ss >32 mg/L). Results: In total, 433 plasma concentrations (3.20-48.0 mg/L) from 195 patients (median/P-0.05 - P-0.95 at baseline: weight 77.0/55.0-114 kg, CLCRCG 63.0/19.6-168 mL/min) were used for model building. We found that CLCRCG best described meropenem clearance (CL = 7.71 L/h, CLCRCG = 80 mL/min). The developed model was successfully validated with external data (n = 171, 73 patients). According to the nomogram, daily doses of 910/1480/2050/2800/ 3940 mg were required to reach a target C-ss = 8 mg/L in 90\% of patients with CLCRCG = 20/50/80/120/180 mL/min, respectively. A low probability of adverse drug reactions (<0.5\%) was associated with these doses. Conclusions: A dosing nomogram was developed for continuous-infusion meropenem based on renal function in a critically ill population.}, language = {en} } @article{MicheletBindelliniMelinetal.2023, author = {Michelet, Robin and Bindellini, Davide and Melin, Johanna and Neumann, Uta and Blankenstein, Oliver and Huisinga, Wilhelm and Johnson, Trevor N. and Whitaker, Martin J. and Ross, Richard and Kloft, Charlotte}, title = {Insights in the maturational processes influencing hydrocortisone pharmacokinetics in congenital adrenal hyperplasia patients using a middle-out approach}, series = {Frontiers in Pharmacology}, volume = {13}, journal = {Frontiers in Pharmacology}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1663-9812}, doi = {10.3389/fphar.2022.1090554}, pages = {14}, year = {2023}, abstract = {Introduction: Hydrocortisone is the standard of care in cortisol replacement therapy for congenital adrenal hyperplasia patients. Challenges in mimicking cortisol circadian rhythm and dosing individualization can be overcome by the support of mathematical modelling. Previously, a non-linear mixed-effects (NLME) model was developed based on clinical hydrocortisone pharmacokinetic (PK) pediatric and adult data. Additionally, a physiologically-based pharmacokinetic (PBPK) model was developed for adults and a pediatric model was obtained using maturation functions for relevant processes. In this work, a middle-out approach was applied. The aim was to investigate whether PBPK-derived maturation functions could provide a better description of hydrocortisone PK inter-individual variability when implemented in the NLME framework, with the goal of providing better individual predictions towards precision dosing at the patient level. Methods: Hydrocortisone PK data from 24 adrenal insufficiency pediatric patients and 30 adult healthy volunteers were used for NLME model development, while the PBPK model and maturation functions of clearance and cortisol binding globulin (CBG) were developed based on previous studies published in the literature. Results: Clearance (CL) estimates from both approaches were similar for children older than 1 year (CL/F increasing from around 150 L/h to 500 L/h), while CBG concentrations differed across the whole age range (CBG(NLME) stable around 0.5 mu M vs. steady increase from 0.35 to 0.8 mu M for CBG (PBPK)). PBPK-derived maturation functions were subsequently included in the NLME model. After inclusion of the maturation functions, none, a part of, or all parameters were re-estimated. However, the inclusion of CL and/or CBG maturation functions in the NLME model did not result in improved model performance for the CL maturation function (\& UDelta;OFV > -15.36) and the re-estimation of parameters using the CBG maturation function most often led to unstable models or individual CL prediction bias. Discussion: Three explanations for the observed discrepancies could be postulated, i) non-considered maturation of processes such as absorption or first-pass effect, ii) lack of patients between 1 and 12 months, iii) lack of correction of PBPK CL maturation functions derived from urinary concentration ratio data for the renal function relative to adults. These should be investigated in the future to determine how NLME and PBPK methods can work towards deriving insights into pediatric hydrocortisone PK.}, language = {en} } @article{MelinHartungParraGuillenetal.2019, author = {Melin, Johanna Stina Elisabet and Hartung, Niklas and Parra-Guillen, Zinnia Patricia and Whitaker, Martin J. and Ross, Richard J. and Kloft, Charlotte}, title = {The circadian rhythm of corticosteroid-binding globulin has little impact on cortisol exposure after hydrocortisone dosing}, series = {Clinical endocrinology}, volume = {91}, journal = {Clinical endocrinology}, number = {1}, publisher = {Wiley}, address = {Hoboken}, issn = {0300-0664}, doi = {10.1111/cen.13969}, pages = {33 -- 40}, year = {2019}, abstract = {Context Optimization of hydrocortisone replacement therapy is important to prevent under- and over dosing. Hydrocortisone pharmacokinetics is complex as circulating cortisol is protein bound mainly to corticosteroid-binding globulin (CBG) that has a circadian rhythm. Objective A detailed analysis of the CBG circadian rhythm and its impact on cortisol exposure after hydrocortisone administration. Design and Methods CBG was measured over 24 hours in 14 healthy individuals and, employing a modelling and simulation approach using a semi-mechanistic hydrocortisone pharmacokinetic model, we evaluated the impact on cortisol exposure (area under concentration-time curve and maximum concentration of total cortisol) of hydrocortisone administration at different clock times and of the changing CBG concentrations. Results The circadian rhythm of CBG was well described with two cosine terms added to the baseline of CBG: baseline CBG was 21.8 mu g/mL and interindividual variability 11.9\%; the amplitude for the 24 and 12 hours cosine functions were relatively small (24 hours: 5.53\%, 12 hours: 2.87\%) and highest and lowest CBG were measured at 18:00 and 02:00, respectively. In simulations, the lowest cortisol exposure was observed after administration of hydrocortisone at 23:00-02:00, whereas the highest was observed at 15:00-18:00. The differences between the highest and lowest exposure were minor (<= 12.2\%), also regarding the free cortisol concentration and free fraction (<= 11.7\%). Conclusions Corticosteroid-binding globulin has a circadian rhythm but the difference in cortisol exposure is <= 12.2\% between times of highest and lowest CBG concentrations; therefore, hydrocortisone dose adjustment based on time of dosing to adjust for the CBG concentrations is unlikely to be of clinical benefit.}, language = {en} } @article{MelinParraGuillenHartungetal.2018, author = {Melin, Johanna and Parra-Guillen, Zinnia Patricia and Hartung, Niklas and Huisinga, Wilhelm and Ross, Richard J. and Whitaker, Martin J. and Kloft, Charlotte}, title = {Predicting Cortisol Exposure from Paediatric Hydrocortisone Formulation Using a Semi-Mechanistic Pharmacokinetic Model Established in Healthy Adults}, series = {Clinical Pharmacokinetics}, volume = {57}, journal = {Clinical Pharmacokinetics}, number = {4}, publisher = {Springer}, address = {Northcote}, issn = {0312-5963}, doi = {10.1007/s40262-017-0575-8}, pages = {515 -- 527}, year = {2018}, abstract = {Background and objective Optimisation of hydrocortisone replacement therapy in children is challenging as there is currently no licensed formulation and dose in Europe for children under 6 years of age. In addition, hydrocortisone has non-linear pharmacokinetics caused by saturable plasma protein binding. A paediatric hydrocortisone formulation, Infacort (R) oral hydrocortisone granules with taste masking, has therefore been developed. The objective of this study was to establish a population pharmacokinetic model based on studies in healthy adult volunteers to predict hydrocortisone exposure in paediatric patients with adrenal insufficiency. Methods Cortisol and binding protein concentrations were evaluated in the absence and presence of dexamethasone in healthy volunteers (n = 30). Dexamethasone was used to suppress endogenous cortisol concentrations prior to and after single doses of 0.5, 2, 5 and 10 mg of Infacort (R) or 20 mg of Infacort (R)/hydrocortisone tablet/hydrocortisone intravenously. A plasma protein binding model was established using unbound and total cortisol concentrations, and sequentially integrated into the pharmacokinetic model. Results Both specific (non-linear) and non-specific (linear) protein binding were included in the cortisol binding model. A two-compartment disposition model with saturable absorption and constant endogenous cortisol baseline (Baseline (cort),15.5 nmol/L) described the data accurately. The predicted cortisol exposure for a given dose varied considerably within a small body weight range in individuals weighing < 20 kg. Conclusions Our semi-mechanistic population pharmacokinetic model for hydrocortisone captures the complex pharmacokinetics of hydrocortisone in a simplified but comprehensive framework. The predicted cortisol exposure indicated the importance of defining an accurate hydrocortisone dose to mimic physiological concentrations for neonates and infants weighing < 20 kg.}, language = {en} } @article{MaierWiljesHartungetal.2022, author = {Maier, Corinna Sabrina and Wiljes, Jana de and Hartung, Niklas and Kloft, Charlotte and Huisinga, Wilhelm}, title = {A continued learning approach for model-informed precision dosing}, series = {CPT: pharmacometrics \& systems pharmacology}, volume = {11}, journal = {CPT: pharmacometrics \& systems pharmacology}, number = {2}, publisher = {London}, address = {Nature Publ. Group}, issn = {2163-8306}, doi = {10.1002/psp4.12745}, pages = {185 -- 198}, year = {2022}, abstract = {Model-informed precision dosing (MIPD) is a quantitative dosing framework that combines prior knowledge on the drug-disease-patient system with patient data from therapeutic drug/ biomarker monitoring (TDM) to support individualized dosing in ongoing treatment. Structural models and prior parameter distributions used in MIPD approaches typically build on prior clinical trials that involve only a limited number of patients selected according to some exclusion/inclusion criteria. Compared to the prior clinical trial population, the patient population in clinical practice can be expected to also include altered behavior and/or increased interindividual variability, the extent of which, however, is typically unknown. Here, we address the question of how to adapt and refine models on the level of the model parameters to better reflect this real-world diversity. We propose an approach for continued learning across patients during MIPD using a sequential hierarchical Bayesian framework. The approach builds on two stages to separate the update of the individual patient parameters from updating the population parameters. Consequently, it enables continued learning across hospitals or study centers, because only summary patient data (on the level of model parameters) need to be shared, but no individual TDM data. We illustrate this continued learning approach with neutrophil-guided dosing of paclitaxel. The present study constitutes an important step toward building confidence in MIPD and eventually establishing MIPD increasingly in everyday therapeutic use.}, language = {en} } @article{MaierHartungdeWiljesetal.2020, author = {Maier, Corinna and Hartung, Niklas and de Wiljes, Jana and Kloft, Charlotte and Huisinga, Wilhelm}, title = {Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy}, series = {CPT: Pharmacometrics \& Systems Pharmacology}, volume = {XX}, journal = {CPT: Pharmacometrics \& Systems Pharmacology}, publisher = {Nature Publ. Group}, address = {London}, issn = {2163-8306}, doi = {10.1002/psp4.12492}, pages = {12}, year = {2020}, abstract = {An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model-based predictions of therapy outcomes. Current Bayesian forecasting tools typically rely only on the most probable model parameters (maximum a posteriori (MAP) estimate). This MAP-based approach, however, does neither necessarily predict the most probable outcome nor does it quantify the risks of treatment inefficacy or toxicity. Bayesian data assimilation (DA) methods overcome these limitations by providing a comprehensive uncertainty quantification. We compare DA methods with MAP-based approaches and show how probabilistic statements about key markers related to chemotherapy-induced neutropenia can be leveraged for more informative decision support in individualized chemotherapy. Sequential Bayesian DA proved to be most computationally efficient for handling interoccasion variability and integrating TDM data. For new digital monitoring devices enabling more frequent data collection, these features will be of critical importance to improve patient care decisions in various therapeutic areas.}, language = {en} } @misc{MaierHartungdeWiljesetal.2020, author = {Maier, Corinna and Hartung, Niklas and de Wiljes, Jana and Kloft, Charlotte and Huisinga, Wilhelm}, title = {Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, number = {827}, issn = {1866-8372}, doi = {10.25932/publishup-44550}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445500}, pages = {14}, year = {2020}, abstract = {An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model-based predictions of therapy outcomes. Current Bayesian forecasting tools typically rely only on the most probable model parameters (maximum a posteriori (MAP) estimate). This MAP-based approach, however, does neither necessarily predict the most probable outcome nor does it quantify the risks of treatment inefficacy or toxicity. Bayesian data assimilation (DA) methods overcome these limitations by providing a comprehensive uncertainty quantification. We compare DA methods with MAP-based approaches and show how probabilistic statements about key markers related to chemotherapy-induced neutropenia can be leveraged for more informative decision support in individualized chemotherapy. Sequential Bayesian DA proved to be most computationally efficient for handling interoccasion variability and integrating TDM data. For new digital monitoring devices enabling more frequent data collection, these features will be of critical importance to improve patient care decisions in various therapeutic areas.}, language = {en} } @misc{KrauseKloftHuisingaetal.2019, author = {Krause, Andreas and Kloft, Charlotte and Huisinga, Wilhelm and Karlsson, Mats and Pinheiro, Jos{\´e} and Bies, Robert and Rogers, James and Mentr{\´e}, France and Musser, Bret J.}, title = {Comment on Jaki et al., A proposal for a new PhD level curriculum on quantitative methods for drug development}, series = {Pharmaceutical statistics : the journal of applied statistics in the pharmaceutical industry}, volume = {18}, journal = {Pharmaceutical statistics : the journal of applied statistics in the pharmaceutical industry}, number = {3}, publisher = {Wiley}, address = {Hoboken}, organization = {ASA Special Interest Grp Stat Phar ASA Special Interest Grp Stat Phar}, issn = {1539-1604}, pages = {278 -- 281}, year = {2019}, language = {en} } @article{KnoechelKloftHuisinga2018, author = {Kn{\"o}chel, Jane and Kloft, Charlotte and Huisinga, Wilhelm}, title = {Understanding and reducing complex systems pharmacology models based on a novel input-response index}, series = {Journal of pharmacokinetics and pharmacodynamics}, volume = {45}, journal = {Journal of pharmacokinetics and pharmacodynamics}, number = {1}, publisher = {Springer Science + Business Media B.V.}, address = {New York}, issn = {1567-567X}, doi = {10.1007/s10928-017-9561-x}, pages = {139 -- 157}, year = {2018}, abstract = {A growing understanding of complex processes in biology has led to large-scale mechanistic models of pharmacologically relevant processes. These models are increasingly used to study the response of the system to a given input or stimulus, e.g., after drug administration. Understanding the input-response relationship, however, is often a challenging task due to the complexity of the interactions between its constituents as well as the size of the models. An approach that quantifies the importance of the different constituents for a given input-output relationship and allows to reduce the dynamics to its essential features is therefore highly desirable. In this article, we present a novel state- and time-dependent quantity called the input-response index that quantifies the importance of state variables for a given input-response relationship at a particular time. It is based on the concept of time-bounded controllability and observability, and defined with respect to a reference dynamics. In application to the brown snake venom-fibrinogen (Fg) network, the input-response indices give insight into the coordinated action of specific coagulation factors and about those factors that contribute only little to the response. We demonstrate how the indices can be used to reduce large-scale models in a two-step procedure: (i) elimination of states whose dynamics have only minor impact on the input-response relationship, and (ii) proper lumping of the remaining (lower order) model. In application to the brown snake venom-fibrinogen network, this resulted in a reduction from 62 to 8 state variables in the first step, and a further reduction to 5 state variables in the second step. We further illustrate that the sequence, in which a recursive algorithm eliminates and/or lumps state variables, has an impact on the final reduced model. The input-response indices are particularly suited to determine an informed sequence, since they are based on the dynamics of the original system. In summary, the novel measure of importance provides a powerful tool for analysing the complex dynamics of large-scale systems and a means for very efficient model order reduction of nonlinear systems.}, language = {en} } @article{KluweMicheletMuellerSchoelletal.2020, author = {Kluwe, Franziska and Michelet, Robin and M{\"u}ller-Sch{\"o}ll, Anna and Maier, Corinna and Klopp-Schulze, Lena and van Dyk, Madele and Mikus, Gerd and Huisinga, Wilhelm and Kloft, Charlotte}, title = {Perspectives on model-informed precision dosing in the digital health era}, series = {Clinical pharmacology \& therapeutics}, volume = {109}, journal = {Clinical pharmacology \& therapeutics}, number = {1}, publisher = {Wiley}, address = {Hoboken}, issn = {0009-9236}, doi = {10.1002/cpt.2049}, pages = {29 -- 36}, year = {2020}, language = {en} } @article{HenrichJoergerKraffetal.2017, author = {Henrich, Andrea and Joerger, Markus and Kraff, Stefanie and Jaehde, Ulrich and Huisinga, Wilhelm and Kloft, Charlotte and Parra-Guillen, Zinnia Patricia}, title = {Semimechanistic Bone Marrow Exhaustion Pharmacokinetic/Pharmacodynamic Model for Chemotherapy-Induced Cumulative Neutropenia}, series = {Journal of Pharmacology and Experimental Therapeutics}, volume = {362}, journal = {Journal of Pharmacology and Experimental Therapeutics}, number = {2}, publisher = {American Society for Pharmacology and Experimental Therapeutics}, address = {Bethesda}, issn = {0022-3565}, doi = {10.1124/jpet.117.240309}, pages = {347 -- 358}, year = {2017}, abstract = {Paclitaxel is a commonly used cytotoxic anticancer drug with potentially life-threatening toxicity at therapeutic doses and high interindividual pharmacokinetic variability. Thus, drug and effect monitoring is indicated to control dose-limiting neutropenia. Joerger et al. (2016) developed a dose individualization algorithm based on a pharmacokinetic (PK)/pharmacodynamic (PD) model describing paclitaxel and neutrophil concentrations. Furthermore, the algorithm was prospectively compared in a clinical trial against standard dosing (Central European Society for Anticancer Drug Research Study of Paclitaxel Therapeutic Drug Monitoring; 365 patients, 720 cycles) but did not substantially improve neutropenia. This might be caused by misspecifications in the PK/PD model underlying the algorithm, especially without consideration of the observed cumulative pattern of neutropenia or the platinum-based combination therapy, both impacting neutropenia. This work aimed to externally evaluate the original PK/PD model for potential misspecifications and to refine the PK/PD model while considering the cumulative neutropenia pattern and the combination therapy. An underprediction was observed for the PK (658 samples), the PK parameters, and these parameters were re-estimated using the original estimates as prior information. Neutrophil concentrations (3274 samples) were over-predicted by the PK/PD model, especially for later treatment cycles when the cumulative pattern aggravated neutropenia. Three different modeling approaches (two from the literature and one newly developed) were investigated. The newly developed model, which implemented the bone marrow hypothesis semiphysiologically, was superior. This model further included an additive effect for toxicity of carboplatin combination therapy. Overall, a physiologically plausible PK/PD model was developed that can be used for dose adaptation simulations and prospective studies to further improve paclitaxel/ carboplatin combination therapy.}, language = {en} }