1.
Alskär, Oskar
(author)
Mechanism-Based Modelling of Clinical and Preclinical Studies of Glucose Homeostasis
2018
Doctoral thesis (other academic/artistic) abstract
Glucose is an important nutrient and energy source in the body. However, too high concentration in the blood is harmful and may lead to several complications developing over time. It was estimated that 5 million people in the world died from complications related to diabetes during 2015. Several hormones and physiological factors are involved in the regulation of glucose homeostasis. To evaluate different aspects of glucose homeostasis and the effect of interventions, such as pharmacological treatment, glucose tolerance tests can be performed. In a glucose tolerance test glucose is administered either orally or intravenously, blood is sampled frequently and analyzed for different biomarkers. Mechanism-based pharmacometric models is a valuable tool in drug development, which can be applied to increase the knowledge about complex systems such as glucose homeostasis, quantify the effects of drugs, generate more information from clinical trials and contribute to more efficient study design. In this thesis, a new comprehensive mechanism-based pharmacometric model was developed. The model is capable of describing the most important aspects of glucose homeostasis during glucose tolerance test in healthy individuals and patients with type 2 diabetes, over a wide range of oral and intravenous glucose doses. Moreover, it can simultaneously describe regulation of gastric emptying and glucose absorption, regulation of the incretin hormones GLP-1 and GIP, hepatic extraction of insulin and the incretin effect, regulation of glucagon synthesis and regulation of endogenous glucose production. In addition, an interspecies scaling approach was developed by scaling a previously developed clinical glucose insulin model to describe intravenous glucose tolerance tests performed in mice, rats, dogs, pigs and monkeys. In conclusion, the developed mechanism-based models in this thesis increases the knowledge about short term regulation of glucose homeostasis and can be used to investigate combination treatments, drugs with multiple effects, and translation of drug effects between species, leading to improved drug development of new antidiabetic compounds.
2.
Bouchene, Salim, 1984-, et al.
(author)
A Whole-Body Physiologically Based Pharmacokinetic Model for Colistin and Colistin Methanesulfonate in Rat
2018
In: Basic & Clinical Pharmacology & Toxicology. - : Wiley. - 1742-7835 .- 1742-7843. ; 123:4, s. 407-422
Journal article (peer-reviewed) abstract
Colistin is a polymyxin antibiotic used to treat patients infected with multidrug-resistant Gram-negative bacteria (MDR-GNB). The objective of this work was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model to predict tissue distribution of colistin in rat. The distribution of a drug in a tissue is commonly characterized by its tissue-to-plasma partition coefficient, K-p. Colistin and its prodrug, colistin methanesulfonate (CMS) K-p priors, were measured experimentally from rat tissue homogenates or predicted in silico. The PK parameters of both compounds were estimated fitting invivo their plasma concentration-time profiles from six rats receiving an i.v. bolus of CMS. The variability in the data was quantified by applying a nonlinear mixed effect (NLME) modelling approach. A WB-PBPK model was developed assuming a well-stirred and perfusion-limited distribution in tissue compartments. Prior information on tissue distribution of colistin and CMS was investigated following three scenarios: K-p was estimated using in silico K-p priors (I) or K-p was estimated using experimental K-p priors (II) or K-p was fixed to the experimental values (III). The WB-PBPK model best described colistin and CMS plasma concentration-time profiles in scenario II. Colistin-predicted concentrations in kidneys in scenario II were higher than in other tissues, which was consistent with its large experimental K-p prior. This might be explained by a high affinity of colistin for renal parenchyma and active reabsorption into the proximal tubular cells. In contrast, renal accumulation of colistin was not predicted in scenario I. Colistin and CMS clearance estimates were in agreement with published values. The developed model suggests using experimental priors over in silico K-p priors for kidneys to provide a better prediction of colistin renal distribution. Such models might serve in drug development for interspecies scaling and investigate the impact of disease state on colistin disposition.
3.
Brekkan, Ari, et al.
(author)
A Population Pharmacokinetic-Pharmacodynamic Model of Pegfilgrastim
2018
In: AAPS Journal. - : SPRINGER. - 1550-7416. ; 20:5
Journal article (peer-reviewed) abstract
Neutropenia and febrile neutropenia (FN) are serious side effects of cytotoxic chemotherapy which may be alleviated with the administration of recombinant granulocyte colony-stimulating factor (GCSF) derivatives, such as pegfilgrastim (PG) which increases absolute neutrophil count (ANC). In this work, a population pharmacokinetic-pharmacodynamic (PKPD) model was developed based on data obtained from healthy volunteers receiving multiple administrations of PG. The developed model was a bidirectional PKPD model, where PG stimulated the proliferation, maturation, and margination of neutrophils and where circulating neutrophils in turn increased the elimination of PG. Simulations from the developed model show disproportionate changes in response with changes in dose. A dose increase of 10% from the 6 mg therapeutic dose taken as a reference leads to area under the curve (AUC) increases of similar to 50 and similar to 5% for PK and PD, respectively. A full random effects covariate model showed that little of the parameter variability could be explained by sex, age, body size, and race. As a consequence, little of the secondary parameter variability (C-max and AUC of PG and ANC) could be explained by these covariates.
4.
Brekkan, Ari, et al.
(author)
Sensitivity of Pegfilgrastim Pharmacokinetic and Pharmacodynamic Parameters to Product Differences in Similarity Studies
2019
In: AAPS Journal. - : Springer. - 1550-7416. ; 21:85
Journal article (peer-reviewed) abstract
In this work, a previously developed pegfilgrastim (PG) population pharmacokinetic-pharmacodynamic (PKPD) model was used to evaluate potential factors of importance in the assessment of PG PK and PD similarity. Absolute neutrophil count (ANC) was the modelled PD variable. A two-way cross-over study was simulated where a reference PG and a potentially biosimilar test product were administered to healthy volunteers. Differences in delivered dose amounts or potency between the products were simulated. A different baseline absolute neutrophil count (ANC) was also considered. Additionally, the power to conclude PK or PD similarity based on areas under the PG concentration-time curve (AUC) and ANC-time curve (AUEC) were calculated. Delivered dose differences between the products led to a greater than dose proportional differences in AUC but not in AUEC, respectively. A 10% dose difference from a 6 mg dose resulted in 51% and 7% differences in AUC and AUEC, respectively. These differences were more pronounced with low baseline ANC. Potency differences up to 50% were not associated with large differences in either AUCs or AUECs. The power to conclude PK similarity was affected by the simulated dose difference; with a 4% dose difference from 6 mg the power was approximately 29% with 250 subjects. The power to conclude PD similarity was high for all delivered dose differences and sample sizes.
5.
Garcia-Prats, Anthony J., et al.
(author)
Pharmacokinetics and safety of high-dose rifampicin in children with TB : the Opti-Rif trial
2021
In: Journal of Antimicrobial Chemotherapy. - : Oxford University Press. - 0305-7453 .- 1460-2091. ; 76:12, s. 3237-3246
Journal article (peer-reviewed) abstract
Background: Rifampicin doses of 40 mg/kg in adults are safe and well tolerated, may shorten anti-TB treatment and improve outcomes, but have not been evaluated in children. Objectives: To characterize the pharmacokinetics and safety of high rifampicin doses in children with drug-susceptible TB. Patients and methods: The Opti-Rif trial enrolled dosing cohorts of 20 children aged 0-12 years, with incremental dose escalation with each subsequent cohort, until achievement of target exposures or safety concerns. Cohort 1 opened with a rifampicin dose of 15 mg/kg for 14 days, with a single higher dose (35 mg/kg) on day 15. Pharmacokinetic data from days 14 and 15 were analysed using population modelling and safety data reviewed. Incrementally increased rifampicin doses for the next cohort (days 1-14 and day 15) were simulated from the updated model, up to the dose expected to achieve the target exposure [235 mg/L.h, the geometric mean area under the concentration-time curve from 0 to 24h (AUC(0-24)) among adults receiving a 35mg/kg dose]. Results: Sixty-two children were enrolled in three cohorts. The median age overall was 2.1 years (range=0.4-11.7). Evaluated doses were similar to 35 mg/kg (days 1-14) and similar to 50 mg/kg (day 15) for cohort 2 and similar to 60 mg/kg (days 1-14) and similar to 75mg/kg (day 15) for cohort 3. Approximately half of participants had an adverse event related to study rifampicin; none was grade 3 or higher. A 65-70 mg/kg rifampicin dose was needed in children to reach the target exposure. Conclusions: High rifampicin doses in children achieved target exposures and the doses evaluated were safe over 2 weeks.
6.
Lacroix, Brigitte, 1978-, et al.
(author)
A Pharmacodynamic Markov Mixed-Effects Model for Determining the Effect of Exposure to Certolizumab Pegol on the ACR20 Score in Patients With Rheumatoid Arthritis
2009
In: Clinical Pharmacology and Therapeutics. - : Nature Publishing Group. - 0009-9236 .- 1532-6535. ; 86:4, s. 387-395
Journal article (peer-reviewed) abstract
The American College of Rheumatology 20% preliminary definition of improvement of rheumatoid arthritis (ACR20) is widely used in clinical trials to assess response to treatment. The objective of this analysis was to develop an exposure-response model of ACR20 in subjects treated with certolizumab pegol, and to predict clinical outcome following various treatment schedules. At each visit, subjects were classified as being ACR20 responders, ACR20 non-responders, or having dropped out. A Markov mixed-effect model was developed to investigate the drug effect on the transitions between the 3 defined states. Increasing certolizumab pegol exposure predicted an increasing probability of becoming a responder and remaining a responder, as well as a reduced probability of dropping out of treatment. Simulations of the ACR20 response rate support dosing regimens of 400 mg at weeks 0, 2 and 4 followed by 200 mg every 2 weeks, or alternative maintenance regimen of 400 mg every 4 weeks.
7.
Wallin, Johan E., et al.
(author)
A tool for neutrophil guided dose adaptation in chemotherapy
2009
In: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 93:3, s. 283-291
Journal article (peer-reviewed) abstract
Chemotherapy dosing in anticancer treatment is a balancing act between achieving concentrations that are effective towards the malignancy and that result in acceptable side-effects. Neutropenia is one major side-effect of many antitumor agents, and is related to an increased risk of infection. A model capable of describing the time-course of myelosuppression from administered drug could be used in individual dose selection. In this paper we describe the transfer of a previously developed semi-mechanistic model for myelosuppression from NONMEM to a dosing tool in MS Excel, with etoposide as an example. The tool proved capable to solve a differential equation system describing the pharmacokinetics and pharmacodynamics, with estimation performance comparable to NONMEM. In the dosing tool the user provides neutrophil measures from a previous treatment course and request for the dose that results in a desired nadir in the upcoming course through a Bayesian estimation procedure.
8.
Centanni, Maddalena, 1994-
(author)
Model-based evaluation of biomarkers for dose-individualization in oncology
2024
Doctoral thesis (other academic/artistic) abstract
In contemporary cancer care, several issues are garnering increasing attention. First, significant inter-individual variability among patients challenges the effectiveness of a uniform dosing approach. Second, the escalating costs of treatments necessitate careful consideration when selecting doses and other clinical modalities, including biomarkers, while balancing economic constraints. The objective of this thesis was to evaluate techniques for tailoring doses and guiding clinical decisions for cancer patients through the development and implementation of various models, with the aim of improving treatment outcomes in terms of both efficacy and safety. Through a model-based framework integrating sunitinib pharmacokinetics (PK), adverse events, biomarkers, tumor dynamics and their correlation with overall survival, different treatment schedules and biomarkers for dose individualization were explored. Based on the proposed threshold values, neutrophil count (ANC) and the biomarker sVEGFR-3 were identified as offering the best balance between safety and efficacy for sunitinib in gastro-intestinal stromal tumors (GIST) and could thus serve as viable guides for dose individualization in clinical practice. Given its routine measurement, dose adjustments guided by ANC may be preferable in clinical settings. The feasibility of utilizing diastolic blood pressure (dBP) for personalized dose optimization of tyrosine-kinase inhibitors in clinical settings is constrained due to its reliance on repeated measurements taken at consistent intervals. For axitinib and sunitinib, model-based predictions using multiple clinical measurements were more accurate than single sample measurements. For drugs with high unexplained inter-individual variability (IIV), low residual variability (RUV), and low inter-occasional variability (IOV), therapeutic drug monitoring (TDM) provided a more accurate measure of exposure. Conversely, for drugs with low IIV and high RUV and IOV, pharmacogenetic profiling was more suitable. However, the prevalence of pharmacogenetic subtypes and the challenge of measuring exposure metrics like AUC through limited sampling also influence these approaches.This research further emphasizes how model structure affects the outcomes of cost-effectiveness analyses and consequently the potential implications for regulatory decisions. Although creating mechanistic models for these analyses demands substantial initial effort, the growing need for model-based analyses in drug approval is likely to make these models more accessible for future compounds. Moreover, such models are expected to be more biologically plausible and therefore more reflective of reality and offer flexibility for exploring alternative dosages with limited additional effort.Using model-based assessments, the relationship between the PK and PK-pharmacodynamic (PKPD) profiles of adverse events arising from therapies for acute lymphocytic leukemia were established. For PEG-asparaginase, the PK model categorized 93% of patients who experienced inactivation against PEG-asparaginase as having an increased clearance, and 86% of patients who did not experience hypersensitivity as maintaining stable clearance throughout their asparaginase treatment. This approach marks a potential method for predicting inactivation by identifying early changes in clearance. For vincristine, model-informed precision dosing was shown to reduce the incidence of vincristine-induced peripheral neuropathy (VIPN) from 62.1% to 53.9%, though the clinical impact remains modest.
9.
Ahn, Jae Eun, et al.
(author)
Likelihood based approaches to handling data below the quantification limit using NONMEM VI
2008
In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 35:4, s. 401-421
Journal article (peer-reviewed) abstract
PURPOSE: To evaluate the likelihood-based methods for handling data below the quantification limit (BQL) using new features in NONMEM VI. METHODS: A two-compartment pharmacokinetic model with first-order absorption was chosen for investigation. Methods evaluated were: discarding BQL observations (M1), discarding BQL observations but adjusting the likelihood for the remaining data (M2), maximizing the likelihood for the data above the limit of quantification (LOQ) and treating BQL data as censored (M3), and like M3 but conditioning on the observation being greater than zero (M4). These four methods were compared using data simulated with a proportional error model. M2, M3, and M4 were also compared using data simulated from a positively truncated normal distribution. Successful terminations and bias and precision of parameter estimates were assessed. RESULTS: For the data simulated with a proportional error model, the overall performance was best for M3 followed by M2 and M1. M3 and M4 resulted in similar estimates in analyses without log transformation. For data simulated with the truncated normal distribution, M4 performed better than M3. CONCLUSIONS: Analyses that maximized the likelihood of the data above the LOQ and treated BQL data as censored provided the most accurate and precise parameter estimates.
10.
Alskär, Oskar, et al.
(author)
Semi-mechanistic model describing gastric emptying and glucose absorption in healthy subjects and patients with type 2 diabetes
2016
In: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 56:3, s. 340-348
Journal article (peer-reviewed) abstract
The integrated glucose-insulin (IGI) model is a previously published semi-mechanistic model, which describes plasma glucose and insulin concentrations after glucose challenges. The aim of this work was to use knowledge of physiology to improve the IGI model's description of glucose absorption and gastric emptying after tests with varying glucose doses. The developed model's performance was compared to empirical models. To develop our model, data from oral and intravenous glucose challenges in patients with type 2 diabetes and healthy control subjects were used together with present knowledge of small intestinal transit time, glucose inhibition of gastric emptying and saturable absorption of glucose over the epithelium to improve the description of gastric emptying and glucose absorption in the IGI model. Duodenal glucose was found to inhibit gastric emptying. The performance of the saturable glucose absorption was superior to linear absorption regardless of the gastric emptying model applied. The semi-physiological model developed performed better than previously published empirical models and allows for better understanding of the mechanisms underlying glucose absorption. In conclusion, our new model provides a better description and improves the understanding of dynamic glucose tests involving oral glucose.
