Kim Jeremiah Y, Rosenberger Matthew G, Rutledge Nakisha S, Esser-Kahn Aaron P
Pritzker School of Molecular Engineering, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA.
Pharmaceutics. 2023 Jun 8;15(6):1687. doi: 10.3390/pharmaceutics15061687.
Adjuvants are a critical component of vaccines. Adjuvants typically target receptors that activate innate immune signaling pathways. Historically, adjuvant development has been laborious and slow, but has begun to accelerate over the past decade. Current adjuvant development consists of screening for an activating molecule, formulating lead molecules with an antigen, and testing this combination in an animal model. There are very few adjuvants approved for use in vaccines, however, as new candidates often fail due to poor clinical efficacy, intolerable side effects, or formulation limitations. Here, we consider new approaches using tools from engineering to improve next-generation adjuvant discovery and development. These approaches will create new immunological outcomes that will be evaluated with novel diagnostic tools. Potential improved immunological outcomes include reduced vaccine reactogenicity, tunable adaptive responses, and enhanced adjuvant delivery. Evaluations of these outcomes can leverage computational approaches to interpret "big data" obtained from experimentation. Applying engineering concepts and solutions will provide alternative perspectives, further accelerating the field of adjuvant discovery.
佐剂是疫苗的关键组成部分。佐剂通常靶向激活先天免疫信号通路的受体。从历史上看，佐剂的研发既费力又缓慢，但在过去十年中已开始加速。当前的佐剂研发包括筛选激活分子、将先导分子与抗原进行配方组合，以及在动物模型中测试这种组合。然而，获批用于疫苗的佐剂非常少，因为新的候选佐剂常常由于临床疗效不佳、无法耐受的副作用或配方限制而失败。在此，我们考虑使用工程学工具的新方法来改进下一代佐剂的发现与研发。这些方法将创造新的免疫结果，并使用新型诊断工具进行评估。潜在的改善后的免疫结果包括降低疫苗反应原性、可调的适应性反应以及增强佐剂递送。对这些结果的评估可以利用计算方法来解读从实验中获得的“大数据”。应用工程学概念和解决方案将提供不同的视角，进一步加速佐剂发现领域的发展。
