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Quantitation and pharmacokinetic modeling of therapeutic antibody quality attributes in human studies

A thorough understanding of drug metabolism and disposition can aid in the assessment of efficacy and safety. However, analytical methods used in pharmacokinetics (PK) studies of protein therapeutics are usually based on ELISA, and therefore can provide a limited perspective on the quality of the dr...

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Detalles Bibliográficos
Autores principales: Li, Yinyin, Monine, Michael, Huang, Yu, Swann, Patrick, Nestorov, Ivan, Lyubarskaya, Yelena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4968108/
https://www.ncbi.nlm.nih.gov/pubmed/27216574
http://dx.doi.org/10.1080/19420862.2016.1186322
Descripción
Sumario:A thorough understanding of drug metabolism and disposition can aid in the assessment of efficacy and safety. However, analytical methods used in pharmacokinetics (PK) studies of protein therapeutics are usually based on ELISA, and therefore can provide a limited perspective on the quality of the drug in concentration measurements. Individual post-translational modifications (PTMs) of protein therapeutics are rarely considered for PK analysis, partly because it is technically difficult to recover and quantify individual protein variants from biological fluids. Meanwhile, PTMs may be directly linked to variations in drug efficacy and safety, and therefore understanding of clearance and metabolism of biopharmaceutical protein variants during clinical studies is an important consideration. To address such challenges, we developed an affinity-purification procedure followed by peptide mapping with mass spectrometric detection, which can profile multiple quality attributes of therapeutic antibodies recovered from patient sera. The obtained data enable quantitative modeling, which allows for simulation of the PK of different individual PTMs or attribute levels in vivo and thus facilitate the assessment of quality attributes impact in vivo. Such information can contribute to the product quality attribute risk assessment during manufacturing process development and inform appropriate process control strategy.