(Press-News.org) The future of gene therapy is arriving in the form of intelligent genetic circuits. Diego di Bernardo, Genomic Medicine Program Coordinator at the Telethon Institute of Genetics and Medicine (TIGEM) and Professor of Biomedical Engineering at the University of Naples “Federico II,” has been awarded a prestigious €2.5 million ERC Advanced Grant for DIMERCIRCUITS — a project that merges synthetic biology, artificial intelligence, and biomedical engineering to transform how we treat genetic disorders.
At the heart of this high-impact research lies a bold technological ambition: to develop programmable DNA-based circuits that can dynamically and reversibly control gene expression in human cells. These next-generation tools are designed to fine-tune gene dosage with precision, offering a powerful solution to one of gene therapy’s most pressing challenges — balancing safety and efficacy.
Engineering biology: a new frontier for personalized medicine
DIMERCIRCUITS aims to develop an innovative modular platform based on engineered transcription factors (MAD-TFs) and their inhibitors (ΔTFs). These components act like molecular building blocks to design genetic circuits with a variety of different functions, akin to electronic ones, which instead use transistors — but encoded directly in biological material. Controlled by computational design and responsive to cellular conditions, they offer unprecedented flexibility and customization for therapeutic interventions.
This platform technology, compact and adaptable for clinical use, represents a leap beyond current gene therapy paradigms. It enables real-time modulation of therapeutic gene expression — a game-changer for treating complex or dosage-sensitive conditions.
Rare diseases as launchpads for innovation
The project’s translational focus is Friedreich’s ataxia, a rare neurodegenerative disorder of genetic origin. Using brain organoids derived from patient cells, developed in collaboration with Vania Broccoli, Group leader of the Stem cells and neurogenesis Unit at San Raffaele Hospital and director of the Research Institute of Neuroscience (CNR) in Milan, the team will test the efficacy and safety of these synthetic circuits in a setting that closely mimics human brain tissue..
“Rare genetic diseases are more than urgent clinical challenges,” said di Bernardo. “They are fertile ground for innovation. Their genetic simplicity and well-defined molecular targets make them ideal testbeds for technologies with much broader therapeutic potential.”
This strategic approach — using rare disease models to develop platform technologies — is a hallmark of TIGEM’s scientific vision. Once validated, the circuits developed in DIMERCIRCUITS can be adapted to more complex and widespread disorders, from cancer to metabolic syndromes.
AI-guided design meets systems biology
By integrating artificial intelligence into the design phase, the project leverages in silico simulations to accelerate the development of optimal circuit configurations. This fusion of computational modeling and experimental validation enhances both speed and precision — delivering smarter therapies, faster.
DIMERCIRCUITS also builds on decades of systems biology, applying its network-based principles not just to understand disease, but to engineer cures. This is translational systems biology in action — reshaping medicine from the inside out.
The project is enabled by the unique research ecosystem at TIGEM, where computational biology, cell engineering, high-throughput screening, and clinical research converge. With 18 ERC grants secured to date, TIGEM continues to serve as a European leader in biomedical innovation.
END
ERC awards €2.5 million to TIGEM scientist for project on programmable genetic circuits
Di Bernardo’s DIMERCIRCUITS integrates AI and synthetic biology to advance precision gene therapy
2025-06-17
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[Press-News.org] ERC awards €2.5 million to TIGEM scientist for project on programmable genetic circuitsDi Bernardo’s DIMERCIRCUITS integrates AI and synthetic biology to advance precision gene therapy