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A survey conducted by the Therapeutic Product Immunogenicity (TPI) community within the American Association of Pharmaceutical Scientists (AAPS) posed questions to the participants on their immunogenicity risk assessment strategies prior to clinical development. The survey was conducted in 2 phases spanning 5 years, and queried information about in silico algorithms and in vitro assay formats for immunogenicity risk assessments and how the data were used to inform early developability effort in discovery, chemistry, manufacturing and control (CMC), and non-clinical stages of development. The key findings representing the trends from a majority of the participants included the use of high throughput in silico algorithms, human immune cell-based assays, and proteomics based outputs, as well as specialized assays when therapeutic mechanism of action could impact risk assessment. Additional insights into the CMC-related risks could also be gathered with the same tools to inform future process development and de-risk critical quality attributes with uncertain and unknown risks. The use of the outputs beyond supporting early development activities was also noted with participants utilizing the risk assessments to drive their clinical strategy and streamline bioanalysis., (© 2023. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

All therapeutic proteins are potentially immunogenic. Antibodies formed against these drugs can decrease efficacy, leading to drastically increased therapeutic costs and in rare cases to serious and sometimes life threatening side-effects. Many efforts are therefore undertaken to develop therapeutic proteins with minimal immunogenicity. For this, immunogenicity prediction of candidate drugs during early drug development is essential. Several in silico, in vitro and in vivo models are used to predict immunogenicity of drug leads, to modify potentially immunogenic properties and to continue development of drug candidates with expected low immunogenicity. Despite the extensive use of these predictive models, their actual predictive value varies. Important reasons for this uncertainty are the limited/insufficient knowledge on the immune mechanisms underlying immunogenicity of therapeutic proteins, the fact that different predictive models explore different components of the immune system and the lack of an integrated clinical validation. In this review, we discuss the predictive models in use, summarize aspects of immunogenicity that these models predict and explore the merits and the limitations of each of the models. [ABSTRACT FROM AUTHOR]

Therapeutic protein products (TPPs) are of considerable value in the treatment of a variety of diseases, including cancer, hemophilia, and autoimmune diseases. The success of TPP mainly results from prolonged half-life, increased target specificity and decreased intrinsic toxicity compared with small molecule drugs. However, unwanted immune responses against TPP, such as generation of anti-drug antibody, can impact both drug efficacy and patient safety, which has led to requirements for increased monitoring in regulatory studies and clinical practice, termination of drug development, or even withdrawal of marketed products. We present an overview of current knowledge on immunogenicity of TPP and its impact on efficacy and safety. We also discuss methods for measurement and prediction of immunogenicity and review both product-related and patient-related risk factors that affect its development, and efforts that may be taken to mitigate it. Lastly, we discuss gaps in knowledge and technology and what is needed to fill these. [ABSTRACT FROM AUTHOR]