GeneNet Technology is a synthetic biology startup founded by a Cambridge-based academic researcher, with a mission to revolutionize the life sciences industry through AI-powered genetic engineering. With a focus on innovation and translational impact, we have secured major international grants including Innovate UK, the British Office in Taipei, CPI, Medicines Discovery Catapult, and ITRI Taiwan. To date, we have filed three international patents to protect our proprietary gene circuit technologies across key markets in the US, UK, and EU.

Our patented technology is designed for broad application across medicine, synthetic biology, and pharmaceutical research. We provide genetic circuit design services, R&D consultation, and patent licensing for academic and industry partners. Our solutions are especially relevant for high-throughput drug discovery, cell and gene therapy, and advanced biomolecule sensing—empowering pharmaceutical companies and contract research organizations (CROs) worldwide.

We have developed a growing suite of applications built on our core technologies, including CHO cell-based bioproduction platforms, next-generation gene sequencing kits, and AI-powered analytics for biological data interpretation. Recently, we have expanded into the organoid-on-chip space, starting with a cardiac model to enhance precision, efficiency, and ethical standards in biopharmaceutical research.

In synthetic biology, gene circuit is a synthetic gene which can fine-tune the control of expression of transcription factors in the manner of electronic circuits. However the current biocomputing method is still based on the logic gate genetic circuits (AND/OR/NOT) which can only accept simple Boolean inputs and outputs, thus the function of the gene circuit is limited to just classification of input.

Our technology integrates deep learning into the gene circuit design. Artificial neural network (ANN) has been emerging in recent years and is a fundamental part of deep learning. ANN allows regression or classification which makes quantification prediction of input becomes possible: We proposed a de novo biocomputing method, using genetic circuits to mimic ANNs and this unleashes the potential of the gene circuit design into the blue ocean applications that were impossible with gene circuit design using the simple logic gates. Our novel algorithm will be a revolutionary and ground-breaking technology which allows the gene circuit to be designed as if a deep neural network used by state-of-art computer scientists.