AI and Automation in Organ-on-a-chip Technology: Advancing Personalized Medicine and Disease Modeling
Organ-on-a-Chip (OoC) technology is an advanced platform that replicates human organ functioning on a microfluidic chip, offering a more precise and moral substitute for conventional in vitro and animal testing. They re-create intricate tissue interfaces, mechanical signs and biochemical environments, making them of great utility for disease modeling, drug discovery and toxicity testing. With recent advancements, the use of Artificial Intelligence (AI) and robotic automation, the interpretation of real-time biosensor signals, facilitating accurate detection of tissue responses, early indicators of toxicity and predictive modeling of disease progression will be augmented in the healthcare industry. Robotic automation enables OoC platforms utility to advance through the high-throughput fabrication, fluid manipulation and maintenance of chip cultures with minimal human involvement. This enhances consistency and decreases the possibility of human errorIn medicine, these OoCs are utilized in personalized medicine for drug screening and optimization of therapy using patient- derived cells. They are also used to model intricate medical conditions like cancer, cardiovascular disease, and neurological disorders. This review underscores the upcoming trends of automated and AI-based OoC systems with a focus on their increasing influence on clinical research, personalized medicines, diagnostics and future healthcare provisions.
Authors
- Vinothini Vijayaragavan
- Kavitha Karunakaran
- Rajkumar Densingh Samuel Raj (ORCID: https://orcid.org/0000-0003-2868-0776)
- Manju Vijayakumar (ORCID: https://orcid.org/0000-0003-2585-7345)
- K. Kesavan
- Priya Dharshini
Institutions
- Dr. M.G.R. Educational and Research Institute (IN)
- Kursk State Medical University (RU)
- Bharath University (IN)
- Ragas Dental College & Hospital (IN)
Publication Details
- Published
- 2025-08-20
- DOI
- https://doi.org/10.1109/roma66616.2025.11155313
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00