Dataset Information

Quantitative Systems Pharmacology Model of a Masked, Tumor-Activated Antibody.

ABSTRACT: PROBODY therapeutics (Pb-Tx) are protease-activatable prodrugs of monoclonal antibodies (mAbs) designed to target tumors where protease activity is elevated while avoiding normal tissue. They are composed of a parental mAb, a mask that inhibits antibody binding to target, and a protease-cleavable substrate between the mask and the mAb. We report a quantitative systems pharmacology model for the rational design and clinical translation of Pb-Tx. The model adequately described monkey pharmacokinetic data following the administration of six anti-CD166 Pb-Tx of varying mask strength and substrate cleavability and captured the trend of decreasing Pb-Tx systemic clearance with increasing mask strength. Projections to humans suggested both higher levels of Pb-Tx in tumor relative to parental mAb and an optimal mask strength for maximizing tumor receptor-mediated uptake. Simulations further suggested the majority of circulating species in humans would be intact/masked Pb-Tx, with no significant flux of cleaved/activated species from tumor to the systemic compartment.

SUBMITTER: Stroh M

PROVIDER: S-EPMC6765697 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Quantitative Systems Pharmacology Model of a Masked, Tumor-Activated Antibody.

Stroh Mark M Sagert Jason J Burke John M JM Apgar Joshua F JF Lin Lin L Millard Bjorn L BL Michael Kavanaugh W W

CPT: pharmacometrics & systems pharmacology 20190726 9

PROBODY therapeutics (Pb-Tx) are protease-activatable prodrugs of monoclonal antibodies (mAbs) designed to target tumors where protease activity is elevated while avoiding normal tissue. They are composed of a parental mAb, a mask that inhibits antibody binding to target, and a protease-cleavable substrate between the mask and the mAb. We report a quantitative systems pharmacology model for the rational design and clinical translation of Pb-Tx. The model adequately described monkey pharmacokinet ...[more]

PMID: 31250966

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Project description:BackgroundPsoriasis is a chronic immune-mediated inflammatory systemic disease with skin manifestations characterized by erythematous, scaly, itchy and/or painful plaques resulting from hyperproliferation of keratinocytes. Certolizumab pegol [CZP], a PEGylated antigen binding fragment of a humanized monoclonal antibody against TNF-alpha, is approved for the treatment of moderate-to-severe plaque psoriasis. Patients with psoriasis present clinical and molecular variability, affecting response to treatment. Herein, we utilized an in silico approach to model the effects of CZP in a virtual population (vPop) with moderate-to-severe psoriasis. Our proof-of-concept study aims to assess the performance of our model in generating a vPop and defining CZP response variability based on patient profiles.MethodsWe built a quantitative systems pharmacology (QSP) model of a clinical trial-like vPop with moderate-to-severe psoriasis treated with two dosing schemes of CZP (200 mg and 400 mg, both every two weeks for 16 weeks, starting with a loading dose of CZP 400 mg at weeks 0, 2, and 4). We applied different modelling approaches: (i) an algorithm to generate vPop according to reference population values and comorbidity frequencies in real-world populations; (ii) physiologically based pharmacokinetic (PBPK) models of CZP dosing schemes in each virtual patient; and (iii) systems biology-based models of the mechanism of action (MoA) of the drug.ResultsThe combination of our different modelling approaches yielded a vPop distribution and a PBPK model that aligned with existing literature. Our systems biology and QSP models reproduced known biological and clinical activity, presenting outcomes correlating with clinical efficacy measures. We identified distinct clusters of virtual patients based on their psoriasis-related protein predicted activity when treated with CZP, which could help unravel differences in drug efficacy in diverse subpopulations. Moreover, our models revealed clusters of MoA solutions irrespective of the dosing regimen employed.ConclusionOur study provided patient specific QSP models that reproduced clinical and molecular efficacy features, supporting the use of computational methods as modelling strategy to explore drug response variability. This might shed light on the differences in drug efficacy in diverse subpopulations, especially useful in complex diseases such as psoriasis, through the generation of mechanistically based hypotheses.

Dataset Information

Quantitative Systems Pharmacology Model of a Masked, Tumor-Activated Antibody.

Publications

Quantitative Systems Pharmacology Model of a Masked, Tumor-Activated Antibody.

Similar Datasets

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