Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305-5454, USA.
Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305-5454, USA.
Cardiovasc Res. 2022 Jan 7;118(1):20-36. doi: 10.1093/cvr/cvab115.
Manifestations of cardiovascular diseases (CVDs) in a patient or a population differ based on inherent biological makeup, lifestyle, and exposure to environmental risk factors. These variables mean that therapeutic interventions may not provide the same benefit to every patient. In the context of CVDs, human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an opportunity to model CVDs in a patient-specific manner. From a pharmacological perspective, iPSC-CM models can serve as go/no-go tests to evaluate drug safety. To develop personalized therapies for early diagnosis and treatment, human-relevant disease models are essential. Hence, to implement and leverage the utility of iPSC-CMs for large-scale treatment or drug discovery, it is critical to (i) carefully evaluate the relevant limitations of iPSC-CM differentiations, (ii) establish quality standards for defining the state of cell maturity, and (iii) employ techniques that allow scalability and throughput with minimal batch-to-batch variability. In this review, we briefly describe progress made with iPSC-CMs in disease modelling and pharmacological testing, as well as current iPSC-CM maturation techniques. Finally, we discuss current platforms for large-scale manufacturing of iPSC-CMs that will enable high-throughput drug screening applications.
心血管疾病（CVDs）在患者或人群中的表现因固有生物构成、生活方式和暴露于环境风险因素而异。这些变量意味着治疗干预措施可能不会为每个患者提供相同的益处。在 CVDs 方面，人类诱导多能干细胞衍生的心肌细胞（iPSC-CMs）为以患者特异性方式模拟 CVDs 提供了机会。从药理学的角度来看，iPSC-CM 模型可用作去留测试，以评估药物安全性。为了开发早期诊断和治疗的个性化疗法，人类相关疾病模型至关重要。因此，为了实施和利用 iPSC-CM 进行大规模治疗或药物发现，关键是：（i）仔细评估 iPSC-CM 分化的相关限制，（ii）建立定义细胞成熟状态的质量标准，以及（iii）采用允许可扩展性和高通量的技术，同时最小化批次间变异性。在这篇综述中，我们简要描述了 iPSC-CMs 在疾病建模和药理学测试方面取得的进展，以及当前的 iPSC-CM 成熟技术。最后，我们讨论了用于大规模制造 iPSC-CMs 的当前平台，这些平台将能够实现高通量药物筛选应用。
