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Berkhout J, Fairman D, van Noort M, van Steeg TJ. A model-based approach using GSK3772847, an anti-interleukin-33 receptor monoclonal antibody, as a showcase to predict SC administration PK and free target dynamics based on PK and total target measurements after IV administration. CPT Pharmacometrics Syst Pharmacol 2024. [PMID: 39258338 DOI: 10.1002/psp4.13234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/12/2024] Open
Abstract
Integrated modeling of the pharmacokinetic (PK) and target binding, by means of a TMDD model, can provide valuable insights into the expected pharmacodynamic (PD) effects of monoclonal antibodies (mAbs). Optimal characterization of the human PK and target binding for mAbs requires data obtained after intravenous (IV) administration which can be combined with subcutaneous (SC) data to further this characterization. Integration of free and/or total target measurements in a population TMDD model will allow quantification of target engagement which is the first step in the cascade leading to efficacy. However, the assays for determination of free target concentrations are analytically challenging and are inherently biased to overpredict the true concentrations in the presence of mAb:target complexes. For that reason, the objective of the current research was to evaluate the predictive value of free target concentrations in a TMDD model developed using PK and total target observations only. Further, a secondary objective was to demonstrate that prediction of SC data is feasible, based on an existing IV model and typical values of mAb parameters reported for SC absorption. GSK3772847, a human immunoglobulin G2 sigma isotype (IgG2f) mAb that binds to the extracellular domain of the interleukin-33 receptor (IL-33R or ST2) and neutralizes IL-33-mediated ST2 signaling, was used as a model compound for mAbs in this study.
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Affiliation(s)
- Jan Berkhout
- Leiden Experts on Advanced Pharmacokinetics and Pharmacodynamics (LAP&P), Leiden, The Netherlands
| | - Dave Fairman
- Clinical Pharmacology Modelling and Simulation, GSK, Stevenage, Hertfordshire, UK
| | - Martijn van Noort
- Leiden Experts on Advanced Pharmacokinetics and Pharmacodynamics (LAP&P), Leiden, The Netherlands
| | - Tamara J van Steeg
- Leiden Experts on Advanced Pharmacokinetics and Pharmacodynamics (LAP&P), Leiden, The Netherlands
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Fairman D, Tang H. Best Practices in mAb and Soluble Target Assay Selection for Quantitative Modelling and Qualitative Interpretation. AAPS J 2023; 25:23. [PMID: 36759378 DOI: 10.1208/s12248-023-00788-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 01/22/2023] [Indexed: 02/11/2023] Open
Abstract
Biologics, especially monoclonal antibodies (mAbs), are an increasingly important part of the drug discovery and development portfolio across the pharmaceutical industry. To enable robust demonstration of pillars 1 and 2 [1] for mAbs, specialised assays are required to measure the complex interactions between mAb and target. This is especially important for the interpretation of soluble target interactions. In some instances, multiple assays with overlapping purposes (e.g., developing both complex and total assays) have been developed. In retrospect, these efforts may have led to excessive time and resources spent in assay development and the generation of data that is contradictory or misleading. Our recommendation is to invest resources early into the development of total assays for both mAb and target. Free target assay data may be inaccurate and report higher levels of free target than are present in the sample at collection due to re-equilibrium during measurement. Total assay formats are inherently less sensitive to the effects of sample preparation, assay conditions, and re-equilibration than free or complex assays. It is acknowledged that pathology/pharmacology is ultimately driven by the free target and knowledge of its dynamics are critical. However, generation of appropriate total target data and using model-based estimation of free target concentrations is a more robust approach than utilisation of direct assay derived estimates. Where free data are utilised, the potential biases should be prospectively considered when developing the assay and utilising the data for quantitative analyses.
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Affiliation(s)
- David Fairman
- Clinical Pharmacology Modelling and Simulation, GSK Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire, SG1 2NY, UK
| | - Huaping Tang
- Bioanalysis Immunogenicity and Biomarkers, GSK Research, 1250 South Collegeville Road, Pennsylvania, 19426, Collegeville, USA.
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Tao X, Liu H, Xia J, Zeng P, Wang H, Xie Y, Wang C, Cheng Y, Li J, Zhang X, Zhang P, Chen S, Yu H, Wu H. Processed product (Pinelliae Rhizoma Praeparatum) of Pinellia ternata (Thunb.) Breit. Alleviates the allergic airway inflammation of cold phlegm via regulation of PKC/EGFR/MAPK/PI3K-AKT signaling pathway. JOURNAL OF ETHNOPHARMACOLOGY 2022; 295:115449. [PMID: 35688257 DOI: 10.1016/j.jep.2022.115449] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 06/01/2022] [Accepted: 06/06/2022] [Indexed: 06/15/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Pinelliae Rhizoma Praeparatum (PRP) is a traditional processed product of Pinellia ternata (Thunb.) Berit., which mainly used for treating cold asthma (CA). However, the mechanism of action of PRP for treating CA have not been fully elucidated. AIM OF THE STUDY To investigate the core active constituents and the pharmacological mechanism of PRP against CA. MATERIALS AND METHODS Ovalbumin (OVA) and cold water-induced cold asthma model were established in male mice. The effects of water extract from PRP were evaluated by general morphological observation, expectorant activity, airway hyperresponsiveness, mucus hypersecretion, inflammatory cytokines, etc. Additionally, the mRNA and protein expression of mucin 5AC (MUC5AC) and aquaporin 5 (AQP5) in vivo and in vitro were detected by immunohistochemistry (IHC), qRT-PCR, and western blotting. The mechanisms of action were investigated through network pharmacology and transcriptomic, and validated through western blotting and molecular docking. RESULTS PRP exhibited a favorable expectorant activity, and significantly reduced the airway inflammation, mucus secretion, and hyperresponsiveness in cold asthma model. It also reduced the levels of IL-4, IL-5, IL-8, and IL-13 in bronchoalveolar lavage fluid (BALF) and IL-4 and total IgE in serum, while obviously increased the levels of IL-10 and IFN-γ in serum for asthmatic mice. Meanwhile, PRP also attenuated the pathological changes and mucus production in cold asthmatic mice. Moreover, the downregulation of MUC5AC and upregulation of AQP 5 were detected by western blotting and qRT-PCR after administration with PRP both in vivo and in vitro. PRP expectedly inhibited the protein expression of PKC-α, SRC, p-EGFR, p-ERK1/2, p-JNK, p-p38, p-PI3K, and p-Akt levels in vivo. CONCLUSIONS These combined data showed that PRP suppressed the allergic airway inflammation of CA by regulating the balance of Th1 and Th2 cytokines and the possible involvement of the PKC/EGFR/MAPK/PI3K-Akt signaling pathway. Pentadecanoic acid, licochalcone A, β-sitosterol, etc. were considered as main active ingredients of PRP against CA. This study provides a novel perspective of the classical herbal processed product PRP in the treatment of CA.
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Affiliation(s)
- Xingbao Tao
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Hongbo Liu
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jie Xia
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Ping Zeng
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Hepeng Wang
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yuwei Xie
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Caixia Wang
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yanqiu Cheng
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jiayun Li
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Xingde Zhang
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Ping Zhang
- National Institutes for Food and Drug Control, State Food and Drug Administration, Beijing, 100000, China
| | - Shengjun Chen
- Jiangyin Tianjiang Pharmaceutical Co., Ltd., Jiangyin, 214400, China
| | - Hongli Yu
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China; Jiangsu Key Laboratory of Chinese Medicine Processing, Nanjing University of Chinese Medicine, Nanjing, 210023, China; Engineering Center of State Ministry of Education for Standardization of Chinese Medicine Processing, Nanjing, 210023, China; State Key Laboratory Cultivation Base for TCM Quality and Efficacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
| | - Hao Wu
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China; Jiangsu Key Laboratory of Chinese Medicine Processing, Nanjing University of Chinese Medicine, Nanjing, 210023, China; Engineering Center of State Ministry of Education for Standardization of Chinese Medicine Processing, Nanjing, 210023, China; State Key Laboratory Cultivation Base for TCM Quality and Efficacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
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