@misc{WeisserStueblerMatheisetal.2017, author = {Weisser, Karin and St{\"u}bler, Sabine and Matheis, Walter and Huisinga, Wilhelm}, title = {Towards toxicokinetic modelling of aluminium exposure from adjuvants in medicinal products}, series = {Regulatory toxicology and pharmacology : official journal of the International Society for Regulatory Toxicology and Pharmacology}, volume = {88}, journal = {Regulatory toxicology and pharmacology : official journal of the International Society for Regulatory Toxicology and Pharmacology}, publisher = {Elsevier}, address = {San Diego}, issn = {0273-2300}, doi = {10.1016/j.yrtph.2017.02.018}, pages = {310 -- 321}, year = {2017}, abstract = {As a potentially toxic agent on nervous system and bone, the safety of aluminium exposure from adjuvants in vaccines and subcutaneous immune therapy (SCIT) products has to be continuously reevaluated, especially regarding concomitant administrations. For this purpose, knowledge on absorption and disposition of aluminium in plasma and tissues is essential. Pharmacokinetic data after vaccination in humans, however, are not available, and for methodological and ethical reasons difficult to obtain. To overcome these limitations, we discuss the possibility of an in vitro-in silico approach combining a toxicokinetic model for aluminium disposition with biorelevant kinetic absorption parameters from adjuvants. We critically review available kinetic aluminium-26 data for model building and, on the basis of a reparameterized toxicokinetic model (Nolte et al., 2001), we identify main modelling gaps. The potential of in vitro dissolution experiments for the prediction of intramuscular absorption kinetics of aluminium after vaccination is explored. It becomes apparent that there is need for detailed in vitro dissolution and in vivo absorption data to establish an in vitro-in vivo correlation (IVIVC) for aluminium adjuvants. We conclude that a combination of new experimental data and further refinement of the Nolte model has the potential to fill a gap in aluminium risk assessment. (C) 2017 Elsevier Inc. All rights reserved.}, language = {en} } @article{EhmannZollerMinichmayretal.2017, author = {Ehmann, Lisa and Zoller, Michael and Minichmayr, Iris K. and Scharf, Christina and Maier, Barbara and Schmitt, Maximilian V. and Hartung, Niklas and Huisinga, Wilhelm and Vogeser, Michael and Frey, Lorenz and Zander, Johannes and Kloft, Charlotte}, title = {Role of renal function in risk assessment of target non-attainment after standard dosing of meropenem in critically ill patients}, series = {Critical care}, volume = {21}, journal = {Critical care}, publisher = {BioMed Central}, address = {London}, issn = {1466-609X}, doi = {10.1186/s13054-017-1829-4}, pages = {14}, year = {2017}, abstract = {Background: Severe bacterial infections remain a major challenge in intensive care units because of their high prevalence and mortality. Adequate antibiotic exposure has been associated with clinical success in critically ill patients. The objective of this study was to investigate the target attainment of standard meropenem dosing in a heterogeneous critically ill population, to quantify the impact of the full renal function spectrum on meropenem exposure and target attainment, and ultimately to translate the findings into a tool for practical application. Methods: A prospective observational single-centre study was performed with critically ill patients with severe infections receiving standard dosing of meropenem. Serial blood samples were drawn over 4 study days to determine meropenem serum concentrations. Renal function was assessed by creatinine clearance according to the Cockcroft and Gault equation (CLCRCG). Variability in meropenem serum concentrations was quantified at the middle and end of each monitored dosing interval. The attainment of two pharmacokinetic/pharmacodynamic targets (100\% T->MIC, 50\% T->4xMIC) was evaluated for minimum inhibitory concentration (MIC) values of 2 mg/L and 8 mg/L and standard meropenem dosing (1000 mg, 30-minute infusion, every 8 h). Furthermore, we assessed the impact of CLCRCG on meropenem concentrations and target attainment and developed a tool for risk assessment of target non-attainment. Results: Large inter-and intra-patient variability in meropenem concentrations was observed in the critically ill population (n = 48). Attainment of the target 100\% T->MIC was merely 48.4\% and 20.6\%, given MIC values of 2 mg/L and 8 mg/L, respectively, and similar for the target 50\% T->4xMIC. A hyperbolic relationship between CLCRCG (25-255 ml/minute) and meropenem serum concentrations at the end of the dosing interval (C-8h) was derived. For infections with pathogens of MIC 2 mg/L, mild renal impairment up to augmented renal function was identified as a risk factor for target non-attainment (for MIC 8 mg/L, additionally, moderate renal impairment). Conclusions: The investigated standard meropenem dosing regimen appeared to result in insufficient meropenem exposure in a considerable fraction of critically ill patients. An easy-and free-to-use tool (the MeroRisk Calculator) for assessing the risk of target non-attainment for a given renal function and MIC value was developed.}, 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{EhmannZollerMinichmayretal.2019, author = {Ehmann, Lisa and Zoller, Michael and Minichmayr, Iris K. and Scharf, Christina and Huisinga, Wilhelm and Zander, Johannes and Kloft, Charlotte}, title = {Development of a dosing algorithm for meropenem in critically ill patients based on a population pharmacokinetic/pharmacodynamic analysis}, series = {International journal of antimicrobial agents}, volume = {54}, journal = {International journal of antimicrobial agents}, number = {3}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0924-8579}, doi = {10.1016/j.ijantimicag.2019.06.016}, pages = {309 -- 317}, year = {2019}, abstract = {Effective antibiotic dosing is vital for therapeutic success in critically ill patients. This work aimed to develop an algorithm to identify appropriate meropenem dosing in critically ill patients. Population pharma-cokinetic (PK) modelling was performed in NONMEM (R) 7.3 based on densely sampled meropenem serum samples (n(patients) = 48; n(samples) =1376) and included a systematic analysis of 27 pre-selected covariates to identify factors influencing meropenem exposure. Using Monte Carlo simulations newly considering the uncertainty of PK parameter estimates, standard meropenem dosing was evaluated with respect to attainment of the pharmacokinetic/pharmacodynamic (PK/PD) target and was compared with alternative infusion regimens (short-term, prolonged, continuous; daily dose, 2000-6000 mg). Subsequently, a dosing algorithm was developed to identify appropriate dosing regimens. The two-compartment population PK model included three factors influencing meropenem pharmacokinetics: the Cockcroft-Gault creatinine clearance (CLCRCG ) on meropenem clearance; and body weight and albumin on the central and peripheral volume of distribution, respectively; of these, only CLCRCG was identified as a vital influencing factor on PK/PD target attainment. A three-level dosing algorithm was developed (considering PK parameter uncertainty), suggesting dosing regimens depending on renal function and the level (L) of knowledge about the infecting pathogen (L1, pathogen unknown; L2, pathogen known; L3((-MIC)), pathogen and susceptibility known; L3((+MIC)), MIC known). Whereas patients with higher CLCRCG and lower pathogen susceptibility required mainly intensified dosing regimens, lower than standard doses appeared sufficient for highly susceptible pathogens. In conclusion, a versatile meropenem dosing algorithm for critically ill patients is proposed, indicating appropriate dosing regimens based on patient- and pathogen-specific information. (C) 2019 Published by Elsevier B.V.}, language = {en} } @article{FuhrmannKloftHuisinga2017, author = {Fuhrmann, Saskia and Kloft, Charlotte and Huisinga, Wilhelm}, title = {Impact of altered endogenous IgG on unspecific mAb clearance}, series = {Journal of pharmacokinetics and pharmacodynamics}, volume = {44}, journal = {Journal of pharmacokinetics and pharmacodynamics}, publisher = {Springer}, address = {New York}, issn = {1567-567X}, doi = {10.1007/s10928-017-9524-2}, pages = {351 -- 374}, year = {2017}, abstract = {Immunodeficient mice are crucial models to evaluate the efficacy of monoclonal antibodies (mAbs). When studying mAb pharmacokinetics (PK), protection from elimination by binding to the neonatal Fc receptor (FcRn) is known to be a major process influencing the unspecific clearance of endogenous and therapeutic IgG. The concentration of endogenous IgG in immunodeficient mice, however is reduced, and this effect on the FcRn protection mechanism and subsequently on unspecific mAb clearance is unknown, yet of great importance for the interpretation of mAb PK data. We used a PBPK modelling approach to elucidate the influence of altered endogenous IgG concentrations on unspecific mAb clearance. To this end, we used PK data in immunodeficient mice, i.e. nude and severe combined immunodeficiency mice. To avoid impact of target-mediated clearance processes, we focussed on mAbs without affinity to a target antigen in these mice. In addition, intravenous immunoglobulin (IVIG) data of immunocompetent mice was used to study the impact of increased total IgG concentrations on unspecific therapeutic antibody clearance. The unspecific clearance is linear, whenever therapeutic IgG concentrations, i.e. mAb and IVIG concentrations are lower than FcRn; it can be non-linear if therapeutic IgG concentrations are larger than FcRn and endogenous IgG concentrations (e.g., under IVIG therapy). Unspecific mAb clearance of immunodeficient mice is effectively linear (under mAb doses as typically used in human). Studying the impact of reduced endogenous IgG concentrations on unspecific mAb clearance is of great relevance for the extrapolation to clinical species, e.g., when predicting mAb PK in immunosuppressed cancer patients.}, language = {en} } @article{FrontonPilariHuisinga2014, author = {Fronton, Ludivine and Pilari, Sabine and Huisinga, Wilhelm}, title = {Monoclonal antibody disposition: a simplified PBPK model and its implications for the derivation and interpretation of classical compartment models}, series = {Journal of pharmacokinetics and pharmacodynamics}, volume = {41}, journal = {Journal of pharmacokinetics and pharmacodynamics}, number = {2}, publisher = {Springer}, address = {New York}, issn = {1567-567X}, doi = {10.1007/s10928-014-9349-1}, pages = {87 -- 107}, year = {2014}, abstract = {The structure, interpretation and parameterization of classical compartment models as well as physiologically-based pharmacokinetic (PBPK) models for monoclonal antibody (mAb) disposition are very diverse, with no apparent consensus. In addition, there is a remarkable discrepancy between the simplicity of experimental plasma and tissue profiles and the complexity of published PBPK models. We present a simplified PBPK model based on an extravasation rate-limited tissue model with elimination potentially occurring from various tissues and plasma. Based on model reduction (lumping), we derive several classical compartment model structures that are consistent with the simplified PBPK model and experimental data. We show that a common interpretation of classical two-compartment models for mAb disposition-identifying the central compartment with the total plasma volume and the peripheral compartment with the interstitial space (or part of it)-is not consistent with current knowledge. Results are illustrated for the monoclonal antibodies 7E3 and T84.66 in mice.}, language = {en} } @article{GopalakrishnanMontazeriMenzetal.2014, author = {Gopalakrishnan, Sathej and Montazeri, Hesam and Menz, Stephan and Beerenwinkel, Niko and Huisinga, Wilhelm}, title = {Estimating HIV-1 fitness characteristics from cross-sectional genotype data}, series = {PLoS Computational Biology : a new community journal}, volume = {10}, journal = {PLoS Computational Biology : a new community journal}, number = {11}, publisher = {PLoS}, address = {San Fransisco}, issn = {1553-734X}, doi = {10.1371/journal.pcbi.1003886}, pages = {14}, year = {2014}, abstract = {Despite the success of highly active antiretroviral therapy (HAART) in the management of human immunodeficiency virus (HIV)-1 infection, virological failure due to drug resistance development remains a major challenge. Resistant mutants display reduced drug susceptibilities, but in the absence of drug, they generally have a lower fitness than the wild type, owing to a mutation-incurred cost. The interaction between these fitness costs and drug resistance dictates the appearance of mutants and influences viral suppression and therapeutic success. Assessing in vivo viral fitness is a challenging task and yet one that has significant clinical relevance. Here, we present a new computational modelling approach for estimating viral fitness that relies on common sparse cross-sectional clinical data by combining statistical approaches to learn drug-specific mutational pathways and resistance factors with viral dynamics models to represent the host-virus interaction and actions of drug mechanistically. We estimate in vivo fitness characteristics of mutant genotypes for two antiretroviral drugs, the reverse transcriptase inhibitor zidovudine (ZDV) and the protease inhibitor indinavir (IDV). Well-known features of HIV-1 fitness landscapes are recovered, both in the absence and presence of drugs. We quantify the complex interplay between fitness costs and resistance by computing selective advantages for different mutants. Our approach extends naturally to multiple drugs and we illustrate this by simulating a dual therapy with ZDV and IDV to assess therapy failure. The combined statistical and dynamical modelling approach may help in dissecting the effects of fitness costs and resistance with the ultimate aim of assisting the choice of salvage therapies after treatment failure.}, language = {en} }