| 1. |
- Brekkan, Ari, et al.
(författare)
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A Population Pharmacokinetic-Pharmacodynamic Model of Pegfilgrastim
- 2018
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Ingår i: AAPS Journal. - : SPRINGER. - 1550-7416. ; 20:5
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Tidskriftsartikel (refereegranskat)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.
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| 2. |
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| 3. |
- Brekkan, Ari, et al.
(författare)
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Characterization of anti-drug antibody dynamics using a bivariate mixed hidden-markov model by nonlinear-mixed effects approach
- 2024
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer. - 1567-567X .- 1573-8744. ; 51:1, s. 65-75
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Tidskriftsartikel (refereegranskat)abstract
- Biological therapies may act as immunogenic triggers leading to the formation of anti-drug antibodies (ADAs). Population pharmacokinetic (PK) models can be used to characterize the relationship between ADA and drug disposition but often rely on the ADA bioassay results, which may not be sufficiently sensitive to inform on this characterization.In this work, a methodology that could help to further elucidate the underlying ADA production and impact on the drug disposition was explored. A mixed hidden-Markov model (MHMM) was developed to characterize the underlying (hidden) formation of ADA against the biologic, using certolizumab pegol (CZP), as a test drug. CZP is a PEGylated Fc free TNF-inhibitor used in the treatment of rheumatoid arthritis and other chronic inflammatory diseases.The bivariate MHMM used information from plasma drug concentrations and ADA measurements, from six clinical studies (n = 845), that were correlated through a bivariate Gaussian function to infer about two hidden states; production and no-production of ADA influencing PK. Estimation of inter-individual variability was not supported in this case. Parameters associated with the observed part of the model were reasonably well estimated while parameters associated with the hidden part were less precise. Individual state sequences obtained using a Viterbi algorithm suggested that the model was able to determine the start of ADA production for each individual, being a more assay-independent methodology than traditional population PK. The model serves as a basis for identification of covariates influencing the ADA formation, and thus has the potential to identify aspects that minimize its impact on PK and/or efficacy.
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| 4. |
- Brekkan, Ari, et al.
(författare)
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Handling underlying discrete variables with bivariate mixed hidden Markov models in NONMEM
- 2019
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 46:6, s. 591-604
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Tidskriftsartikel (refereegranskat)abstract
- Non-linear mixed effects models typically deal with stochasticity in observed processes but models accounting for only observed processes may not be the most appropriate for all data. Hidden Markov models (HMMs) characterize the relationship between observed and hidden variables where the hidden variables can represent an underlying and unmeasurable disease status for example. Adding stochasticity to HMMs results in mixed HMMs (MHMMs) which potentially allow for the characterization of variability in unobservable processes. Further, HMMs can be extended to include more than one observation source and are then multivariate HMMs. In this work MHMMs were developed and applied in a chronic obstructive pulmonary disease example. The two hidden states included in the model were remission and exacerbation and two observation sources were considered, patient reported outcomes (PROs) and forced expiratory volume (FEV1). Estimation properties in the software NONMEM of model parameters were investigated with and without random and covariate effect parameters. The influence of including random and covariate effects of varying magnitudes on the parameters in the model was quantified and a power analysis was performed to compare the power of a single bivariate MHMM with two separate univariate MHMMs. A bivariate MHMM was developed for simulating and analysing hypothetical COPD data consisting of PRO and FEV1 measurements collected every week for 60 weeks. Parameter precision was high for all parameters with the exception of the variance of the transition rate dictating the transition from remission to exacerbation (relative root mean squared error [RRMSE] > 150%). Parameter precision was better with higher magnitudes of the transition probability parameters. A drug effect was included on the transition rate probability and the precision of the drug effect parameter improved with increasing magnitude of the parameter. The power to detect the drug effect was improved by utilizing a bivariate MHMM model over the univariate MHMM models where the number of subject required for 80% power was 25 with the bivariate MHMM model versus 63 in the univariate MHMM FEV1 model and > 100 in the univariate MHMM PRO model. The results advocates for the use of bivariate MHMM models when implementation is possible.
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| 5. |
- Brekkan, Ari, et al.
(författare)
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Model-based evaluation of low dose factor VIII prophylaxis in haemophilia A
- 2019
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Ingår i: Haemophilia. - : John Wiley & Sons. - 1351-8216 .- 1365-2516. ; 25:3, s. 408-415
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Tidskriftsartikel (refereegranskat)abstract
- Introduction The optimal treatment modality for haemophilia A is lifelong prophylaxis which is expensive and may not be implementable everywhere where factor VIII (FVIII) availability is limited. A less costly alternative to prophylaxis is low-dose prophylaxis (LDP) which was compared to conventional prophylaxis in this model-based simulation study. Aim To explore whether LDP is motivated where standard prophylaxis is not implementable, including evaluating LDP efficacy compared to high-dose prophylaxis and investigating the potential economic benefit of individualized dosing. Methods For a virtual adult haemophilia A population, FVIII activity levels were simulated following alternative treatment regimens, based on a published population PK model. The regimens included very LDP, LDP and conventional prophylaxis twice and thrice weekly. The annual probability of bleeding was predicted based on the weekly time spent below 1 IU/dL, using a previously published relationship. Additionally, PK-based dose individualization was evaluated to determine FVIII savings using Bayesian forecasting. Results A treatment regimen of 10 IU/kg administered thrice weekly cost 75% less than a standard high-dose regimen and was predicted to have a 5% higher median probability of annual bleeds. PK-based dose individualization may result in further cost-savings, but implementation needs benefit versus feasibility consideration. Conclusion Based on simulations, a promising LDP regimen was identified that decreased treatment costs compared with standard high-dose prophylaxis at a small increase in bleeding risk. The results indicate that LDP is advocated where the standard-of-care is on-demand treatment; however, the results should be considered in the context of any limitations of the applied models.
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| 6. |
- Brekkan, Ari
(författare)
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Pharmacometric models in the development of biological medicinal products
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Biological medicinal products (BMPs) are a successful class of drugs that are indicated in numerous diseases. Common among them is that complexities associated with their manufacture and analysis lead to a high cost compared to small-molecular weight drugs. If the development cost can be brought down and the use of BMPs optimized, these drugs may reach more patients at more affordable prices. Further, there are a number of knowledge gaps related to the characterization of their disposition, immunogenicity and use which can be filled through the development and application of novel methods for data analysis. In this thesis work, pharmacometric models and methods were developed and applied to aid BMP development and clinical use.Model-based optimal design (OD) methodology was employed to reduce and optimize a published sampling schedule for a monoclonal antibody (mAb) displaying target-mediated drug disposition. Thus, illustrating that current sampling strategies for mAbs can be excessive from an economic and patient burden perspective.A novel hidden-Markov model was developed to characterize anti-drug antibody (ADA) response which can plague many biologics throughout clinical development and post-approval. The developed model accounted for ADA assay inaccuracies by utilizing information from the assay and the pharmacokinetics (PK) of the therapeutic in question and allowed for an objective assessment of immunogenicity.Model-based dose individualization and evaluation of low-dose prophylaxis (LDP) for coagulation factors were investigated in this work to improve treatment and lower costs. Individual doses were found to outperform standard-of-care while LDP was indicated as a viable treatment option in countries with limited coagulation factor access.Biosimilar development is yet another method to reduce the costs of biologics. The development of a PKPD model for a pegylated granulocyte colony stimulating factor (GCSF) allowed for model simulations to demonstrate PK sensitivity to small differences in delivered dose between a reference and potential biosimilar product. The sensitivity of the system may be one of the reasons for difficulties associated with the development of biosimilar pegylated GCSFs.In conclusion, the pharmacometric methods developed and applied in this thesis work can be used to improve BMP development.
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| 7. |
- Brekkan, Ari, et al.
(författare)
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Population Pharmacokinetics of Plasma-Derived Factor IX : Procedures for Dose Individualization
- 2016
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Ingår i: Journal of Thrombosis and Haemostasis. - : Elsevier BV. - 1538-7933 .- 1538-7836. ; 14:4, s. 724-732
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Tidskriftsartikel (refereegranskat)abstract
- Background: Population pharmacokinetic (POPPK) models describing factor IX (FIX) activity levels in plasma, in combination with individual FIX measurements, may be used to individualize dosing in the treatment of hemophilia B. Objectives: The aim was to reevaluate a previously developed POPPK model for FIX activity and to explore the number and timing of FIX samples required in pharmacokinetic (PK) dose individualization. Methods: The POPPK model was reevaluated using an extended data set. Several sampling schedules, varying with respect to the timing and number of samples, were evaluated in a simulation study with relative dose errors compared between schedules. The performance of individually calculated doses was compared with commonly prescribed FIX doses with respect to the number of patients with a trough FIX activity > 0.01 U mL(-1). Results and conclusions: A three-compartment PK model best described the FIX activity levels. The number and timing of samples greatly influenced imprecision in dose prediction. Schedules with single samples taken on both day 2 and day 3 were identified as being convenient schedules with an acceptable performance level. Individually calculated doses performed better with respect to patient target attainment than a fixed 40 U kg(-1) dose regardless of how many samples were available to calculate individual doses. The results of this study suggest that PK dose tailoring with limited sampling may be applicable for plasma-derived FIX products.
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| 8. |
- Brekkan, Ari, et al.
(författare)
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Reduced and optimized trial designs for drugs described by a target mediated drug disposition model
- 2018
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : SPRINGER/PLENUM PUBLISHERS. - 1567-567X .- 1573-8744. ; 45:4, s. 637-647
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Tidskriftsartikel (refereegranskat)abstract
- Monoclonal antibodies against soluble targets are often rich and include the sampling of multiple analytes over a lengthy period of time. Predictive models built on data obtained in such studies can be useful in all drug development phases. If adequate model predictions can be maintained with a reduced design (e.g. fewer samples or shorter duration) the use of such designs may be advocated. The effect of reducing and optimizing a rich design based on a published study for Omalizumab (OMA) was evaluated as an example. OMA pharmacokinetics were characterized using a target-mediated drug disposition model considering the binding of OMA to free IgE and the subsequent formation of an OMA-IgE complex. The performance of the reduced and optimized designs was evaluated with respect to: efficiency, parameter uncertainty and predictions of free target. It was possible to reduce the number of samples in the study by 30% while still maintaining an efficiency of almost 90%. A reduction in sampling duration by two-thirds resulted in an efficiency of 75%. Omission of any analyte measurement or a reduction of the number of dose levels was detrimental to the efficiency of the designs (efficiency ae 51%). However, other metrics were, in some cases, relatively unaffected, showing that multiple metrics may be needed to obtain balanced assessments of design performance.
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| 9. |
- Brekkan, Ari, et al.
(författare)
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Sensitivity of Pegfilgrastim Pharmacokinetic and Pharmacodynamic Parameters to Product Differences in Similarity Studies
- 2019
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Ingår i: AAPS Journal. - : Springer. - 1550-7416. ; 21:85
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Tidskriftsartikel (refereegranskat)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.
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