Antibody disulfide bond reduction has been a challenging issue in monoclonal antibody manufacturing. It could lead to a decrease of product purity and failure to meet the targeted product profile and/or specifications. More importantly, disulfide bond reduction could also impact drug safety and efficacy. Scientists across the industry have been examining the root causes and developing mitigation strategies to address the challenge. In recent years, with the development of high titer mammalian cell culture processes to meet the rapidly growing demand for antibody biopharmaceuticals, disulfide bond reduction has been observed more frequently. Thus, it is necessary to continue evolving the disulfide reduction mitigation strategies and developing novel approaches to maintain high product quality. Additionally, in recent years as more complex molecules (such as bispecific and trispecific antibodies) emerge, the molecular heterogeneity due to incomplete formation of the interchain disulfide bonds becomes a more imperative challenging issue. Given the disulfide reduction challenges that biotech industry is facing, in this review, we provide a comprehensive scientific summary of the root cause analysis of disulfide reduction during process development of antibody therapeutics, mitigation strategies and its potential remediated recovery based on published papers. First, this paper intends to highlight different aspects of the root cause for disulfide reduction. Secondly, to provide a broader understanding of the disulfide bond reduction in downstream process, this paper discusses disulfide bond reduction impact on product stability, associated analytical methods for disulfide bond reduction detection and characterization, process control strategies as well as their manufacturing implementation. In addition, brief perspectives on the development of future mitigation strategies are also reviewed, including platform alignment, mitigation strategy application for the emerging new modalities such as bispecific and trispecific antibodies as well as using machine learning to identify molecule susceptibility of disulfide bond reduction. The data in this review are originated from the published papers.