Mathematical analysis of the pharmacokinetic–pharmacodynamic (PKPD) behaviour of monoclonal antibodies: Predicting in vivo potency

Aston, Philip J.; Derks, Gianne; Raji, Adewale; Agoram, Balaji; Graaf, Piet H. van der

doi:10.1016/j.jtbi.2011.04.030

Cited by 45 publications

(51 citation statements)

References 18 publications

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“…Assuming that the rate constants are strictly positive and that k out ≪ k on L 0 (hence k on large or L 0 large compared to k out ), the dynamics of the receptor can be described as follows: After the injection of the ligand, the receptor initially reduces rapidly (Aston et al, 2011;Peletier and Gabrielsson, 2012a,b) and then gradually increases on a slower time scale and finally returns back to the steady state. Rebound occurs if the receptor levels y ever exceeds the steady state value y = 1.…”

Section: Reboundmentioning

confidence: 99%

“…As shown by Aston et al (2011), by going to the fast time τ = t/µ, initially the total drug concentration u and the total receptor concentration v will stay approximately constant, while the receptor quickly adapts such that the right hand side of theẏ equation nearly vanishes, i.e.,…”

Section: Magnitude Of the Reboundmentioning

confidence: 99%

“…More about this fast-slow process and the minimal receptor value, can be found in the paper by Aston et al (2011). We are interested in the maximal y value, so we would like to keep the y variable in our slow system.…”

Section: Magnitude Of the Reboundmentioning

confidence: 99%

“…We consider when a simple protein-antibody interaction results in rebound in protein levels in a target-mediated drug disposition (TMDD) model, the same one as we considered previously (Aston et al, 2011) to predict potency. Defining receptor rebound as the post-dose rise in receptor levels to higher than pre-dose (baseline), we show that, under the assumptions of the basic TMDD model, rebound will happen if and only if the elimination rate of the target-drug complex is slower than both the elimination rate of the drug and the elimination rate of the target.…”

Section: Introductionmentioning

confidence: 99%

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A mathematical analysis of rebound in a target-mediated drug disposition model: I.Without feedback

Aston

Derks

Agoram³

et al. 2013

J. Math. Biol.

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We consider the possibility of free receptor (antigen/cytokine) levels rebounding to higher than the baseline level after one or more applications of an antibody drug using a target-mediated drug disposition model. Using geometry and dynamical systems analysis, we show that rebound will occur if and only if the elimination rate of the drug-receptor product is slower than the elimination rates of the drug and of the receptor. We also analyse the magnitude of rebound through approximations and simulations and demonstrate that it increases if the drug dose increases or if the difference between the elimination rate of the drug-receptor product and the minimum of the elimination rates of the drug and of the receptor increases.

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Section: Reboundmentioning

confidence: 99%

Section: Magnitude Of the Reboundmentioning

confidence: 99%

Section: Magnitude Of the Reboundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A mathematical analysis of rebound in a target-mediated drug disposition model: I.Without feedback

Aston

Derks

Agoram³

et al. 2013

J. Math. Biol.

Self Cite

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“…A one‐compartment PK with TMDD model 16, 17 (Figure 1) was developed using the observed GSK2330811 plasma concentration and total OSM (free plus complex) serum concentration to assess the in vivo affinity of GSK2330811 for OSM. Free target was assumed to be synthesized at a zero‐order rate and degraded at a first‐order rate.…”

Section: Methodsmentioning

confidence: 99%

In vivo affinity and target engagement in skin and blood in a first‐time‐in‐human study of an anti‐oncostatin M monoclonal antibody

Reid

Zamuner

Edwards

et al. 2018

Brit J Clinical Pharma

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AimsThe oncostatin M (OSM) pathway drives fibrosis, inflammation and vasculopathy, and is a potential therapeutic target for inflammatory and fibrotic diseases. The aim of this first‐time‐in‐human experimental medicine study was to assess the safety, tolerability, pharmacokinetics and target engagement of single subcutaneous doses of GSK2330811, an anti‐OSM monoclonal antibody, in healthy subjects.MethodsThis was a phase I, randomized, double‐blind, placebo‐controlled, single‐dose escalation, first‐time‐in‐human study of subcutaneously administered GSK2330811 in healthy adults (NCT02386436). Safety and tolerability, GSK2330811 pharmacokinetic profile, OSM levels in blood and skin, and the potential for antidrug antibody formation were assessed. The in vivo affinity of GSK2330811 for OSM and target engagement in serum and skin blister fluid (obtained via a skin suction blister model) were estimated using target‐mediated drug disposition (TMDD) models in combination with compartmental and physiology‐based pharmacokinetic (PBPK) models.ResultsThirty subjects were randomized to receive GSK2330811 and 10 to placebo in this completed study. GSK2330811 demonstrated a favourable safety profile in healthy subjects; no adverse events were serious or led to withdrawal. There were no clinically relevant trends in change from baseline in laboratory values, with the exception of a reversible dose‐dependent reduction in platelet count. GSK2330811 exhibited linear pharmacokinetics over the dose range 0.1–6 mg kg–1. The estimated in vivo affinity (nM) of GSK2330811 for OSM was 0.568 [95% confidence interval (CI) 0.455, 0.710] in the compartmental with TMDD model and 0.629 (95% CI 0.494, 0.802) using the minimal PBPK with TMDD model.ConclusionsSingle subcutaneous doses of GSK2330811 were well tolerated in healthy subjects. GSK2330811 demonstrated sufficient affinity to achieve target engagement in systemic circulation and target skin tissue, supporting the progression of GSK2330811 clinical development.

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Issues, challenges, and opportunities in model-based drug development for monoclonal antibodies

Hansen

2013

Journal of Pharmaceutical Sciences

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Mathematical analysis of the pharmacokinetic–pharmacodynamic (PKPD) behaviour of monoclonal antibodies: Predicting in vivo potency

Cited by 45 publications

References 18 publications

A mathematical analysis of rebound in a target-mediated drug disposition model: I.Without feedback

A mathematical analysis of rebound in a target-mediated drug disposition model: I.Without feedback

In vivo affinity and target engagement in skin and blood in a first‐time‐in‐human study of an anti‐oncostatin M monoclonal antibody

Issues, challenges, and opportunities in model-based drug development for monoclonal antibodies

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