Improving Anti-CD45 Antibody Radioimmunotherapy Using a Physiologically Based Pharmacokinetic Model

Kletting, Peter; Bunjes, Donald; Reske, Sven N.; Glatting, Gerhard

doi:10.2967/jnumed.108.054189

Cited by 38 publications

(41 citation statements)

References 31 publications

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“…It describes all major physiologic and physical mechanisms-that is, distribution via blood flow, extravasation, specific binding, internalization, degradation and release, physical decay, and clearance (supplemental data). The model consists of 2 systems, 1 for labeled and 1 for unlabeled peptide (6). The systems are coupled by the competition for binding to free receptors and by physical decay (6).…”

Section: Pbpk Model Structurementioning

confidence: 99%

“…The model consists of 2 systems, 1 for labeled and 1 for unlabeled peptide (6). The systems are coupled by the competition for binding to free receptors and by physical decay (6). All physiologic parameters are assumed equal for the labeled and unlabeled substance.…”

Section: Pbpk Model Structurementioning

confidence: 99%

“…The effect of peptide amount was investigated in animal studies (4,5). In humans, a strong effect of substance amount on the therapeutic index has been observed in previous work with monoclonal antibodies (6)(7)(8) but also peptides (9,10). Sabet et al showed that saturation of tumor-binding sites requires considerably higher amounts of peptide than for those in normal tissue (10).…”

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Optimized Peptide Amount and Activity for ⁹⁰Y-Labeled DOTATATE Therapy

et al. 2015

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In peptide receptor radionuclide therapy with 90 Y-labeled DOTATATE, the kidney absorbed dose limits the maximum amount of total activity that can be safely administered in many patients. A higher tumor-to-kidney absorbed dose ratio might be achieved by optimizing the amount of injected peptide and activity, as recent studies have shown different degrees of receptor saturation for normal tissue and tumor. The aim of this work was to develop and implement a modeling method for treatment planning to determine the optimal combination of peptide amount and pertaining therapeutic activity for each patient. Methods: A whole-body physiologically based pharmacokinetic (PBPK) model was developed. General physiologic parameters were taken from the literature. Individual model parameters were fitted to a series (n 5 12) of planar γ-camera and serum measurements ( 111 In-DOTATATE) of patients with meningioma or neuroendocrine tumors (NETs). Using the PBPK model and the individually estimated parameters, we determined the tumor, liver, spleen, and red marrow biologically effective doses (BEDs) for a maximal kidney BED (20 Gy 2.5 ) for different peptide amounts and activities. The optimal combination of peptide amount and activity for maximal tumor BED, considering the additional constraint of a red marrow BED less than 1 Gy 15 , was individually quantified. Results: The PBPK model describes the biokinetic data well considering the criteria of visual inspection, the coefficients of determination, the relative standard errors (,50%), and the correlation of the parameters (,0.8). All fitted parameters were in a physiologically reasonable range but varied considerably between patients, especially tumor perfusion (meningioma, 0.1-1 mLÁg −1 Ámin −1 , and NETs, 0.02-1 mLÁg −1 Ámin −1 ) and receptor density (meningioma, 5-34 nmolÁL −1 , and NETs, 7-35 nmolÁL −1 ). Using the proposed method, we identified the optimal amount and pertaining activity to be 76 ± 46 nmol (118 ± 71 μg) and 4.2 ± 1.8 GBq for meningioma and 87 ± 50 nmol (135 ± 78 μg) and 5.1 ± 2.8 GBq for NET patients. Conclusion: The presented work suggests that to achieve higher efficacy and safety for 90 Y-DOATATE therapy, both the administered amount of peptide and the activity should be optimized in treatment planning using the proposed method. This approach could also be adapted for therapy with other peptides.

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Section: Pbpk Model Structurementioning

confidence: 99%

Section: Pbpk Model Structurementioning

confidence: 99%

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confidence: 99%

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Optimized Peptide Amount and Activity for ⁹⁰Y-Labeled DOTATATE Therapy

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“…The application of pharmacokinetic models has helped to elucidate the most important influences for favorable antibody biodistribution (14). Physiologically based pharmacokinetic (PBPK) models (15,16) have the great advantage that the parameters used represent a physiologically meaningful quantity, and the experimental conditions can be related to the effect (on a specific parameter) in the patient (17)(18)(19). For radioimmunotherapy with anti-CD45 antibody (18), the application of a PBPK model demonstrated that the amount of unlabeled antibody, administered as a preload, is a main determinant of favorable biodistribution.…”

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confidence: 99%

“…For radioimmunotherapy with anti-CD66 antibody, the influence of the amount of antibody on the biodistribution has not yet been quantified. The use of an optimal amount of antibody for 111 In and 90 Y labeling might considerably improve the biodistribution (18) and therefore enhance the efficacy and reduce the side effects such as nephrotoxicity (10,20).…”

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Radioimmunotherapy with Anti-CD66 Antibody: Improving the Biodistribution Using a Physiologically Based Pharmacokinetic Model

Kletting¹,

Kull²,

Bunjes³

et al. 2010

J Nucl Med

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To improve radioimmunotherapy with anti-CD66 antibody, a physiologically based pharmacokinetic (PBPK) model was developed that was capable of describing the biodistribution and extrapolating between different doses of anti-CD66 antibody. Methods: The biodistribution of the 111 In-labeled anti-CD66 antibody of 8 patients with acute leukemia was measured. The data were fitted to 2 PBPK models. Model A incorporated effective values for antibody binding, and model B explicitly described mono-and bivalent binding. The best model was selected using the corrected Akaike information criterion. The predictive power of the model was validated comparing simulations and 90 Y-anti-CD66 serum measurements. The amount of antibody (range, 0.1-4 mg) leading to the most favorable therapeutic distribution was determined using simulations. Results: Model B was better supported by the data. The fits of the selected model were good (adjusted R 2 . 0.91), and the estimated parameters were in a physiologically reasonable range. The median deviation of the predicted and measured 90 Y-anti-CD66 serum concentration values and the residence times were 24% (range, 17%231%) and 9% (range, 1%264%), respectively. The validated model predicted considerably different biodistributions for dosimetry and therapeutic settings. The smallest (0.1 mg) simulated amount of antibody resulted in the most favorable therapeutic biodistribution. Conclusion: The developed model is capable of adequately describing the anti-CD66 antibody biodistribution and accurately predicting the time-activity serum curve of 90 Yanti-CD66 antibody and the therapeutic serum residence time. Simulations indicate that an improvement of radioimmunotherapy with anti-CD66 antibody is achievable by reducing the amount of administered antibody; for example, the residence time of the red marrow could be increased by a factor of 1.9 6 0.3 using 0.27 mg of anti-CD66 antibody.

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