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Automation of Personal Food Computers for Research in Drug Development and Biomedicine

机译：用于药物开发和生物医药研究的个人食品计算机自动化

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Plant secondary metabolites are critical factors that aid plants in adaptation to their environment and are important sources of pharmaceuticals. Growth environment chambers nowadays are employed only to improve the overall production of the plant, while paying less attention to its quality. Automated strategies can be applied to attune the existing model, making it compatible for precisely controlling the environmental factors, which are the significant effectors of changes in the metabolic pathways of secondary metabolites. Previously, MIT has developed a Personal Food Computer (PFC) to control the growth environment of plants to maintain uniformity in their production in an urban setting. However, several challenges remained untouched, especially when the PFC was used in a research setting. One such instance was that an increase in the daylight negatively impacted the level of humidity, which could be undesirable and requires manual intervention to maintain grow-condition stability. To overcome the shortcomings of the existing model we have modified MIT's PFC by implementing cloud-based flexible automation techniques along with robotics to develop a Cost-Effective Automated Food Computer (CEAFC). The present article is aimed at addressing the automated features of CEAFC and its eloquent use in the production of secondary metabolites of therapeutic value.
机译：植物次生代谢物是帮助植物适应环境的关键因素，并且是药物的重要来源。现在，生长环境室仅用于改善工厂的整体生产，同时对其质量的重视不太关注。自动化策略可以应用于调度现有模型，使其与精确控制环境因素相容，这是次级代谢物代谢途径的变化的显着效应。此前，麻省理工学院开发了一种个人食品计算机（PFC），以控制植物的生长环境，以保持城市环境中生产的均匀性。然而，几个挑战仍然保持不变，特别是当PFC用于研究环境时。一个这样的例子是，日光的增加负面影响湿度水平，这可能是不希望的并且需要手动干预以保持生长条件稳定性。为了克服现有模型的缺点，我们通过实施基于云的灵活自动化技术以及机器人来制定经过修改麻省理工学院的PFC，以开发一种经济高效的自动化食品计算机（Ceapc）。本文旨在解决Ceafc的自动特征及其在治疗价值的次级代谢产物中使用的雄辩。

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