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Research Direction
AI × Regenerative Medicine × Industry-Academia-Research Collaborative Innovation Ecosystem
Building an engineered, verifiable, and translatable life science innovation system
Kuqi Labs uses artificial intelligence as its core engine to reshape the research and development paradigm of regenerative medicine.
By leveraging algorithms, bioengineering modeling, and cross-border experimental collaboration, a complete closed loop is constructed, from basic research to industrial validation.
We focus not only on the research itself, but also on how research results can truly be applied in real-world scenarios.
Core Research Matrix
①
AI-powered biocomputation and intelligent drug design
We will build a platform for biological data analysis and molecular design with algorithms at its core.
• AI-powered protein structure prediction and optimization • Small molecule/peptide screening models • Biological data modeling and research support systems
Target:
Establish a sustainable and iterative intelligent R&D system.
②
Regenerative Medicine and Cell Engineering
A regenerative medicine technology system is being built around tissue repair and microenvironment regulation.
• Stem cell and exosome research • Tissue repair and anti-aging mechanisms • Engineering applications of growth factors
Target:
To promote regenerative medicine from experimental verification to translational pathways.
③
Genetic Engineering and Synthetic Biology Systems
Build an engineerable and controllable life system platform.
• CRISPR and gene expression regulation • Synthetic pathway design • mRNA/DNA construction and delivery technology
Target:
To develop biological system models with engineering expression capabilities.
④
Tumor Metabolism and Precision Medicine
Focusing on the disease microenvironment and metabolic reprogramming mechanisms.
• Lactic acid metabolism and microenvironment regulation • Precision detection and personalized pathway design • Construction of tumor metabolic models
Target:
Promoting precision medicine research from a systems perspective.
⑤
Scientific research education and achievement incubation system
Construct a research-driven talent training and achievement incubation model.
• Collaborative development of real scientific research projects • International competition incubation channels (iGEM / ISEF, etc.)
• Closed-loop model from scientific research to results publication
Target:
Establish an innovative talent development path that integrates scientific research and education.
⑥
Technology Verification and Industrial Transformation Platform
Connecting laboratory findings with real-world industry scenarios.
• Technology verification and application testing • Collaborative enterprise R&D • Cross-border resource integration network
Target:
Promote the application of scientific research results in real-world scenarios.