genetics

Thematic Center for Intelligence Bioengineering

aboutTCIB1
aboutTCIB2
The objective of this thematic center is to explore innovative manufacturing and emerging materials in order to expedite the development and implementation of sustainability technologies for realization carbon neutral society.

Vision and Mission

Our mission is to drive significant advancements in biotechnology and clinical applications,
focusing on innovative solutions that promise substantial potential for transformation.
With a robust team of experts and strategic partnerships,
we aim to push the boundaries of current medical technologies to create impactful and sustainable improvements in healthcare.

Research Focus

Research Focus
Advanced Imaging and Sensing Technologies
  • We are leaders in developing sophisticated imaging methods such as lightsheet expansion microscopy, which provides resolutions comparable to electron microscopes, and the application of advanced mass spectrometry techniques for studying complex biological materials.
Artificial Intelligence in Bioengineering
  • Our center has developed groundbreaking AI applications, including an AI-driven non-invasive blood glucose meter, which has received several national recognitions. We also employ AI to enhance computational methods for biomolecular interaction analysis and drug discovery.
Innovative Drug Delivery Systems
  • We are pioneering new drug delivery methods, including hydrogel systems for the controlled release of therapeutic compounds, offering new approaches to treat chronic diseases like obesity.

Focusing project

Automated Intelligence-Empowered Biology Lab: from Drug Discovery to Advanced in vitro Model and Analysis
Automated Intelligence-Empowered Biology Lab: from Drug Discovery to Advanced in vitro Model and Analysis

Drug development is a complex, time-consuming, and expensive process. To lower the barriers to drug discovery before animal testing and clinical trials, this project aims to develop an integrated, cross-disciplinary technology platform to establish an automated, intelligent biological laboratory to assist in drug discovery and testing. In this system, we will first employ artificial intelligence methods, including deep learning neural network models, to efficiently and accurately perform virtual screening of large-scale chemical databases, preliminarily identifying compounds with high binding affinity to target proteins. After selecting candidate compounds, the project will develop an intelligent chemical synthesis system to automatically synthesize these compounds. This system will feature fully automated design combined with real-time Raman spectroscopy monitoring to achieve highly reproducible and reliable synthesis outcomes. In addition, surface plasmon resonance (SPR) sensing chips with high throughput and sensitivity will be used to confirm the affinity between the synthesized compounds and target proteins, as well as to study interactions between the compounds and living cells. To further evaluate drug efficacy in tissue models that more closely mimic in vivo conditions, the project will also establish patient-centered cell and organoid models. The processes of cell culture, drug testing, and analysis will be automated to achieve unbiased, intelligent analysis.

Development and Application of Multiscale Multimodal Biomedical Imaging Technologies
Development and Application of Multiscale Multimodal Biomedical Imaging Technologies

With the rapid advancement of biomedical technologies, biomanufacturing and bioimaging technologies have become critical core technologies in the biomedical field. In particular, the latest developments in nanoscale imaging now enable the resolution of the three-dimensional spatial positioning and structures of individual protein molecules within cells or tissues. However, developing such new technologies requires collaboration among interdisciplinary experts in fields such as optics, electron microscopy, ion beam technology, and biological sample preparation. This project will first focus on developing novel biomaterials and sample preparation techniques for application in biomedical imaging, aiming to enhance the accuracy and efficiency of diagnosis and treatment. Secondly, it will work to overcome the limitations of traditional imaging methods by developing higher-resolution, single-molecule-level imaging analysis tools to enable precise dynamic monitoring of biological systems. To drive technological innovation and promote the translation of research outcomes, the project will integrate various resources to build an efficient research platform and collaborate closely with medical institutions to shorten the time from research to clinical application. By developing high-value biomaterials and imaging technologies, the project will contribute to enhancing the international competitiveness of the domestic biomedical industry. Additionally, the project aims to provide a leading research platform for academic institutions both domestically and internationally, attracting collaborations with global scholars and professionals, and opening new frontiers in biomaterials and bioimaging technologies.

Thematic Center for Intelligence Bioengineering

Our Members

This team's combined expertise spans the entire spectrum of bioengineering,
from molecular biology to nano-fabrication technologies,
ensuring a comprehensive approach to research and development.
This diverse expertise ensures a comprehensive and multi-disciplinary approach to our research projects.
Collaboration is a key pillar of our operational philosophy,
involving close ties with Academia Sinica’s Life Science Division and numerous medical institutes across Taiwan,
facilitating a seamless integration of academic research and practical application.

Research Content

contract
Creating an integrated platform for high-performance drug discovery

This platform encompasses intelligent computation, efficient chemical synthesis, digital biosensing, and patient-derived organoid models for drug testing. In an era where personalized medicine is rapidly gaining traction, this project is both timely and significant. The marriage of cloud computing and artificial intelligence can expedite drug discovery, potentially enabling new treatments to reach patients more rapidly. Meanwhile, the development of patient-derived organoid models aligns with global regulatory efforts to reduce animal testing, contributing to more ethical and accurate drug testing methods.
contract
Revolutionize optical microscopy by achieving spatial resolution comparable to electron microscopy (EM), while retaining chemical information and the capacity for 3D imaging

This endeavor could fundamentally change our understanding of biological structures like synapses, a key area of focus in neurology and related fields. By enhancing the resolution and capabilities of optical microscopy, we can facilitate more comprehensive research into synaptic connectivity and advance our understanding of how information flows within the brain.

Achievements

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Field of Imaging and Sensing

  • Innovated lightsheet expansion microscopy to match the resolution of electron microscopes.
  • Applied cluster ion beams and secondary ion mass spectrometry to investigate organic-inorganic composites.
  • Created a high-throughput drug screening platform that utilizes cellular traction forces.
  • Developed a surface plasmon resonance (SPR)-based digital nanoplasmonmetry (DiNM) method for the sensitive detection of biomolecules, eliminating the need for labeling.
  • Employed a 3D cell co-culture system to evaluate the synergistic effects of anti-fibrotic and anti-cancer drugs on lung cancer cells and cancer-associated fibroblasts. Through this research, we've identified four genes in fibroblasts that could potentially be suppressed by the anti-fibrotic drug nintedanib.
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Field of Artificial Intelligence Integration

  • Our "AI Deduction Learning Non-Invasive Blood Glucose Meter” earned the National Innovation Award.
  • Introduced a unique computational approach to calculate the standard free energy of binding based on the statistical mechanics of biomolecular interactions in an all-atom explicit solvent description.This method has proven useful in protein-protein, protein-peptide, and protein-small molecule systems.
  • Applied machine learning to Raman image spectra categorization for illicit drug detection.
  • To aid in the development of biomedical sensors for pesticide molecules, we've synthesized various oligopeptide fragments and composite metal nanostructures.
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Field of Drug Delivery

  • Creating delivery systems for cold-mimetic and heat-mimetic compounds. We've designed a dissolving hydrogel system to release the cold-mimetic compound menthol gradually. This release mechanism triggers adipocyte browning, presenting a potential solution for obesity and associated metabolic disorders.
  • Developed in vitro cell culture models based on microfluidics to examine blood vessel formation processes, like vasculogenesis and angiogenesis, in more life like microenvironments