AI-Driven Acoustofluidics: A New Era for Biomedical Research
Researchers at the Indiana University Luddy School of Informatics, Computing and Engineering are blending acoustofluidics with artificial intelligence to accelerate biomedical discovery. Acoustofluidics, the manipulation of cells and chemical components in liquids using sound waves, sits at the intersection of physics, engineering and biology. Led by Feng Guo, an associate professor of intelligent systems engineering, the team recently secured a $1.5 million grant from the National Institutes of Health to push this technology toward real-world medical applications.
“The goal of our lab is to leverage artificial intelligence and organoid computing—what we call biological intelligence—to further advance or innovate biomedical systems to address the challenges for medicine, healthcare and the pharmaceutical industry,” Guo explained. As director of the Intelligent Biomedical Systems Lab, he emphasizes a broad mission: transform how experiments are designed, monitored and interpreted by combining AI with lab-on-a-chip platforms.
What is Acoustofluidics—and Why It Matters?
Acoustofluidics uses principles of fluid dynamics to steer and organize biological material in solution with sound. Often termed “acoustic tweezers,” the technique offers distinct advantages over traditional liquid handling: it is contactless, reduces cross-contamination risks, and is largely label-free. Guo notes that the approach is harmless to living cells and does not require fluorescent dyes or radioactive labels, making it inherently biocompatible. The technology holds promise across infectious disease research, cancer studies and regenerative medicine, where delicate handling of cells and molecules is essential.
Microscopic views of acoustofluidic experiments reveal striking transformations: chaotic cell suspensions can be guided into orderly, programmable patterns, with particles spinning and forming structured arrays under the influence of carefully tuned sound fields. This precise control is what makes AI integration so compelling: it can interpret rapid changes and adjust experimental parameters in real time, something that’s challenging for human operators who must pause between steps.
AI as Real-Time Co-Pilot for Complex Experiments
The infusion of artificial intelligence opens the door to real-time monitoring and dynamic feedback. AI could optimize protocols on the fly, enabling faster protein analysis and high-throughput screening of candidate drug compounds. In personalized medicine, where therapies must be tuned to an individual’s unique biology, AI-guided acoustofluidics could dramatically shorten development timelines by predicting optimal conditions and accelerating decision-making during experiments.
Guo envisions AI as a co-pilot that not only accelerates experiments but also expands what researchers consider feasible. He notes, “AI can help you generate the best protocol. It can provide dynamic feedback and dynamic monitoring to control fast, quick chemical reactions.” The goal is to translate laboratory insights into therapies and devices that could be deployed clinically, bridging the gap between basic science and patient care.
Towards Translational Impact and Broad Applications
The NIH grant supports a larger effort to push acoustofluidics from the bench toward real-world use. Guo plans to recruit a new postdoctoral researcher and several undergraduates to the Intelligent Biomedical Systems Lab, joining nine current students. Beyond the NIH grant, Guo is a co-lead on a $16.5 million Alzheimer’s project with IU School of Medicine and a $2 million NSF grant exploring brain organoid computing. These collaborations underscore a shared emphasis on organ-on-a-chip systems that fuse intelligent algorithms with microfluidic platforms to study brain health, neurodegeneration and related diseases.
Industry interest is already blooming. Several healthcare startups have approached Guo’s team about licensing aspects of acoustofluidics technology, signaling promising translational potential. Guo stresses that the lab’s ambition extends beyond technical novelty: the focus is on practical challenges that can be translated into clinical tools or commercially viable devices. He frames the mission simply: scientists seek to understand the world; engineers aim to change it—and AI helps accelerate that transformation by turning rapid data into actionable insight.
Looking Ahead
As the work progresses, the IU team will continue to refine acoustofluidic control and expand AI-enabled decision-making in organoid and chip-based systems. The convergence of sound, biology and intelligent computing could redefine how we approach drug discovery, disease modeling and regenerative medicine—providing faster routes to therapies that are precisely tailored to individual patients.
