治疗性单克隆抗体及其衍生物是全球生物制药行业临床管道的关键组成部分。抗体序列的大数据集的可用性,结构,和生物物理特性正日益促进抗体候选药物的“可开发性评估”的预测模型和计算工具的开发。这里,我们概述了适用于预测稳定性等可开发性问题的抗体信息学工具,聚合,免疫原性,和化学降解。我们进一步评估了使用生物制药信息学进行药物发现和优化的机遇和挑战。最后,我们讨论了基于可用于评估抗体稳定性和可制造性的计算机模拟指标的开发指南的潜力。
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the \"developability assessment\" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability
guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.