Raj M Kiran, Priyadarshani Jyotsana, Karan Pratyaksh, Bandyopadhyay Saumyadwip, Bhattacharya Soumya, Chakraborty Suman
Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu 600036, India.
Department of Mechanical Engineering, Biomechanics Section (BMe), KU Leuven, Celestijnenlaan 300, 3001 Louvain, Belgium.
Biomicrofluidics. 2023 Sep 27;17(5):051503. doi: 10.1063/5.0161809. eCollection 2023 Sep.
Biomicrofluidics, a subdomain of microfluidics, has been inspired by several ideas from nature. However, while the basic inspiration for the same may be drawn from the living world, the translation of all relevant essential functionalities to an artificially engineered framework does not remain trivial. Here, we review the recent progress in bio-inspired microfluidic systems via harnessing the integration of experimental and simulation tools delving into the interface of engineering and biology. Development of "on-chip" technologies as well as their multifarious applications is subsequently discussed, accompanying the relevant advancements in materials and fabrication technology. Pointers toward new directions in research, including an amalgamated fusion of data-driven modeling (such as artificial intelligence and machine learning) and physics-based paradigm, to come up with a human physiological replica on a synthetic bio-chip with due accounting of personalized features, are suggested. These are likely to facilitate physiologically replicating disease modeling on an artificially engineered biochip as well as advance drug development and screening in an expedited route with the minimization of animal and human trials.
生物微流体学作为微流体学的一个子领域，其灵感来源于自然界的几个理念。然而，尽管其基本灵感可能源自生物界，但要将所有相关的基本功能转化为人工工程框架并非易事。在此，我们通过利用实验和模拟工具的整合来深入研究工程与生物学的界面，回顾受生物启发的微流体系统的最新进展。随后将讨论“芯片上”技术的发展及其多种应用，以及材料和制造技术的相关进步。我们还建议了研究的新方向，包括将数据驱动建模（如人工智能和机器学习）与基于物理的范式进行融合，以便在充分考虑个性化特征的情况下，在合成生物芯片上构建人类生理复制品。这些可能有助于在人工工程生物芯片上进行生理复制疾病建模，并以加快的速度推进药物开发和筛选，同时尽量减少动物和人体试验。
