Pluripotent stem cells, in the recent years, have been demonstrated to mimic different aspects of metazoan embryonic development in vitro. This has led to the establishment of synthetic embryology: a field that makes use of in vitro stem cell models to investigate developmental processes that would be otherwise inaccessible in vivo. Currently, a plethora of engineering-inspired techniques, including microfluidic devices and bioreactors, exist to generate and culture organoids at high throughput. Similarly, data analysis and deep learning-based techniques, that were established in in vivo models, are now being used to extract quantitative information from synthetic systems. Finally, theory and data-driven in silico modeling are starting to provide a system-level understanding of organoids and make predictions to be tested with further experiments. Here, we discuss our vision of how engineering, data science and theoretical modeling will synergize to offer an unprecedented view of embryonic development. For every one of these three scientific domains, we discuss examples from in vivo and in vitro systems that we think will pave the way to future developments of synthetic embryology.

近年来，多能干细胞已被证明可以模拟体外后生动物胚胎发育的不同方面。这导致了合成胚胎学的建立：该领域利用体外干细胞模型来研究在体内无法进行的发育过程。目前，存在大量受工程启发的技术，包括微流体装置和生物反应器，以高通量生成和培养类器官。同样，在体内模型中建立的数据分析和基于深度学习的技术现在正用于从合成系统中提取定量信息。最后，理论和数据驱动的计算机建模开始提供对类器官的系统级理解，并做出预测以通过进一步的实验进行测试。在这里，我们讨论了我们对工程、数据科学和理论建模将如何协同作用以提供前所未有的胚胎发育观点的愿景。对于这三个科学领域中的每一个，我们讨论了来自体内和体外系统的例子，我们认为这些例子将为合成胚胎学的未来发展铺平道路。