Our patented technology can be applied to any field that needs genetic engineering (eg. medicine, synthetic biology and pharmaceutical industries). We plan to offer genetic circuit design service, consultation service and patent licensing to academic or industrial research units. Our product could worldwidely cover research units (including pharmaceutical companies and contract research organisation) with focus at high throughput drug discovery, CAR-T therapy and biomolecules detection.

There are many pain points in traditional biopharmaceutical research. For example, the high cost of research, time-consuming processes of drug development, and difficulties in treating complicated diseases. These problems not only harm the development of the biopharmaceutical industry, but also generate traumatic problems, such as COVID-19 pandemic, to our world. Genenet Technology provides a one-stop solution to address all these problems, in hope of taking the biopharmaceutical industry to the next level.

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.