ISPRI-HCP: CHO protein impurity immunogenicity risk prediction for improving biosimilar product development and assessing product interchangeability

点击翻译按钮获取中文摘要

ABSTRACT The identification and removal of host cell proteins (HCP) from biologic products is a critical step in biosimilar drug development. While the sequence of a biosimilar may be identical to the innovator, the process used to produce the biosimilar will be different, and as a result, new HCPs may be introduced into the product. Despite recent improvements to purification processes, biologics that are manufactured in different cell lines and purified using different processes contain variable HCP impurities, making it necessary to identify and quantify impurities for each product, be it a reference innovator product or a proposed biosimilar product. In this U01 program, we propose to develop a predictive model for HCP immunogenicity that can facilitate assessment of clinically meaningful immunogenicity risk for biologics and assess interchangeability risk between a biosimilar and an innovator product. We have developed a web-based tool called ISPRI-HCP (formerly called CHOPPI) that predicts the immunogenic potential of HCP sequences by evaluating T cell epitope count and density, and relative conservation with other epitopes in the human genome. Building on previous studies of monoclonal antibody and biologic protein immunogenicity using silico methods and our FDA generic peptide immunogenicity research experience, we hypothesize that ISPRI-HCP can accurately classify candidate HCP impurities according to their immunogenicity risk. To address this hypothesis, we will train, test and cross-validate an immunogenicity prediction model for Chinese hamster ovary (CHO) HCPs using a T cell immunogenicity dataset generated for 87 common CHO HCP impurities in licensed monoclonal antibody products with our method for stimulating de novo T cell responses in vitro, named In Vitro Immunization Protocol (Aim 1). We will also test the quality of the antigen stimulation strategy that is used to stimulate de novo T cell immunogenicity data for development of the ISPRI-HCP predictive model (Aim 2). This research program will improve the accuracy of the ISPRI-HCP platform, providing drug developers with a rapid and efficient means to reduce HCP-associated immunogenicity risk to address this critical quality attribute in biosimilar development.