2009 - St. Petersburg - Russia

PAGE 2009: Applications- Biologicals/vaccines
Philip Lowe

On the ability to predict free ligand suppression when free ligand assays are not available or impossible

Philip Lowe, Aurelie Gautier

Novartis Pharma AG, 4002 Basel, Switzerland

Objectives: Monoclonal antibodies are often used to capture soluble target ligands when excess expression causes disease symptoms. Ideally, as in the case of free IgE with omalizumab, one should measure the free ligand and correlate the suppression of this with clinical endpoints. However, in many instances, the free ligand is present at concentrations too low to be assayed directly. The objective of this analysis was to assess whether it is possible to predict the suppression of a free target soluble ligand using the drug and total (captured) ligand concentrations using a binding model.

Methods: Omalizumab pharmacokinetic, free and total IgE biomarker data were used in a one compartment binding model. The first clinical trial, the original purpose for which was bioquivalence was richly sampled and used data from 152 atopic but otherwise healthy volunteers. The second clinical trial used data from 440 severe atopic asthmatics, both omalizumab treated and placebo controls. The model parameters were estimated on either i) the PK, free and total IgE, or ii) just the PK and total IgE. In the latter case, the model was used to predict the suppressed concentrations of free IgE, then the predictions compared with the observed data.

Results: Both estimations converged successfully, with FO also completing the covariance step. The residual errors for the control model were 18% for omalizumab, 22% for total IgE and 21% for free IgE. For the test model, the residual errors were 17% for omalizumab and 20% for total IgE. The diagnostic plots were well centred with few outliers. There were only slight differences in the PK parameter values between the two models. For example, the estimate of clearance of omalizumab was 0.259 ± 0.00878 L/d per 70 kg for the control model, 0.259 ± 0.00798 L/d for the test. The volume of distribution was also comparable at 10.8 ± 0.341 L with the free IgE data, 10.5 ± 0.348 L without. For the PD, IgE production was estimated to be greater when using only the total IgE data, 1680 ± 121 µg/d versus 1180 ± 63.6, and the binding constant, 0.857 ± 0.0359 nM when using the free IgE data, was somewhat higher, 3.12 ± 0.754 nM, when the free IgE was ignored. Plots of the individuals’ predictions for the test model compared with that including the free IgE data showed that there appeared to be a slight bias to overprediction of free IgE levels at the later timepoints during the washout phase, but peak suppression was very well predicted.

Conclusions: A mathematical model describing omalizumab binding to and thereby reducing levels of free IgE described the pharmacokinetics and the observed increase in total IgE. Through the use of the binding reaction and LeChatelier’s Principle cast into a PKPD setting, it was demonstrated that it was possible to predict the suppression of free unbound IgE from omalizumab PK and total IgE.




Reference: PAGE 18 (2009) Abstr 1595 [www.page-meeting.org/?abstract=1595]
Poster: Applications- Biologicals/vaccines
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