Your browser doesn't support javascript.
loading
Physiologically Based Absorption Modelling to Explore the Formulation and Gastric pH Changes on the Pharmacokinetics of Acalabrutinib.
Zhou, Diansong; Chen, Buyun; Sharma, Shringi; Tang, Weifeng; Pepin, Xavier.
Afiliação
  • Zhou D; Clinical Pharmacology & Quantitative Pharmacology, AstraZeneca, BioPharmaceuticals R&D, Boston, Massachusetts, USA. diansong.zhou@astrazeneca.com.
  • Chen B; AstraZeneca, 35 Gatehouse Dr., Waltham, Massachusett, 02451, USA. diansong.zhou@astrazeneca.com.
  • Sharma S; Clinical Pharmacology & Quantitative Pharmacology, AstraZeneca, BioPharmaceuticals R&D, South San Francisco, California, USA.
  • Tang W; Clinical Pharmacology & Quantitative Pharmacology, AstraZeneca, BioPharmaceuticals R&D, South San Francisco, California, USA.
  • Pepin X; Clinical Pharmacology & Quantitative Pharmacology, AstraZeneca, BioPharmaceuticals R&D, Gaithersburg, Maryland, USA.
Pharm Res ; 40(2): 375-386, 2023 Feb.
Article em En | MEDLINE | ID: mdl-35478298
Acalabrutinib, a selective Bruton's tyrosine kinase inhibitor, is a biopharmaceutics classification system class II drug. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to mechanistically describe absorption of immediate release capsule formulation of acalabrutinib in humans. Integration of in vitro biorelevant measurements, dissolution studies and in silico modelling provided clinically relevant inputs for the mechanistic absorption PBPK model. The batch specific dissolution data were integrated in two ways, by fitting a diffusion layer model scalar to the drug product dissolution with integration of drug substance laser diffraction particle size data, or by fitting a product particle size distribution to the dissolution data. The latter method proved more robust and biopredictive. In both cases, the drug surface solubility was well predicted by the Simcyp simulator. The model using the product particle size distribution (P-PSD) for each clinical batch adequately captured the PK profiles of acalabrutinib and its active metabolite. Average fold errors were 0.89 for both Cmax and AUC, suggesting good agreement between predicted and observed PK values. The model also accurately predicted pH-dependent drug-drug interactions between omeprazole and acalabrutinib, which was similar across all clinical formulations. The model predicted acalabrutinib geometric mean AUC ratios (with omeprazole vs acalabrutinib alone) were 0.51 and 0.68 for 2 batches of formulations, which are close to observed values of 0.43 and 0.51~0.63, respectively. The mechanistic absorption PBPK model could be potentially used for future applications such as optimizing formulations or predicting the PK for different batches of the drug product.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Omeprazol / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Omeprazol / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article