Bioreactors have significantly been applied for biological research and manufacturing, such as bioplastic and biologics. The increasing use of bioplastic and biologics heralds a new era of production, where the specific use of AI prediction are rapidly tailored to advance manufacturing. However, current bioreactor on the market wouldnt provide inline examination of cell viability or support cell line adapting production related stress. Mammalian cells, e.g. CHO cell line are one of the most highly employed cell lines in bio-manufacturing. In CHO cells, the intracellular accumulation of misfolded and unfolded proteins in CHO cells triggers the unfolded protein response (UPR). Although immediate activation of this protective mechanism restores cell balance, UPR may trigger cell apoptosis under prolonged stress stimuli. Current commercial CHO cell lines lack environmental sensing elements for these cellular stresses. Chronic stress-induced apoptosis remains a pain point in CHO bio-manufacturing with limited solutions. To overcome this challenge, Genenet Technology, in collaboration with its subcontractors, CPI (Centre for Process Innovation) and The University of Edinburgh, is employing its proprietary AI technologies to develop a new bio-manufacturing tool that will demonstrate intelligent cellular response to bio-manufacturing stress and a real-time AI bioreactor monitoring system to improve bio-manufacturing yield. Therefore, unlike the current options, we can de-risk our client's innovation and operation process, reducing their financial burden.

Cardiotoxicity is a major contributor for safety concerns in drug and vaccine development. In this project, we are building a Cardiac Organoid-on-Chip solution to address these problems. Currently, there are limited cardiac organoid related products on the market, whilst organoid technology has been favourably adopted in the biotech industry by pharmaceuticals and likes. With the expertise from Genenet, VasoDyanmics, and our Taiwanese partners (Darwin, Pythia, Anntong and ITRI), in the fields of cell biology, synthetic biology, machine learning, Organ-on-Chip, etc., we are establishing a real-time monitoring system to observe the effects of drugs on cardiac organoids on a chip, and to use AI-assisted analysis. We will develop an innovative system that uses AI algorithms to process real-time signals to ensure continuous and accurate monitoring of the beating rate, beating amplitude, and changes in biochemical indicators of cardiac organoids. With advanced auto-control, this system resolves 1) the poor prediction result from the current 2D cell model in drug discovery for toxicity and efficacy; and 2) the lack of an in-line method to monitor the actual cell viability of organoid development in Organ-on-Chip. By developing this organoid-based system, we would provide a new accurate, high-throughput, and user-friendly product for biotech users, be beneficial to the general public by increasing the successful rate of drug development (via reducing the drug failure rate due to cardiotoxicity), reduce the waiting time for new drug candidate screening, and, at the same time, reduce the usage of lab animals. In this project, we also take advantage of collaborating with VasoDyanmics to test their drug candidate in our new platform. VasoDyanmics has been focusing on drug discovery for antitumor treatment side effects. Chemotherapy induced alopecia (CIA) is a condition that affects 65% of cancer patients. From a patient's point of view, CIA is the most traumatic aspect of chemotherapy, causing about 8% of patients to refuse to receive chemotherapy (Rossi A et al. 2017). To date, there are no approved drugs to effectively prevent/reduce the anticancer therapy-induced dermatology side effects, including hair-loss. There is a large unmet need to develop safe and effective drugs to improve cancer patients' quality of life sooner. The success of VasoDyanmics' chemotherapy-related alopecia drug candidate would allow us to further promote our Organoid-on-Chip solution and the need to reduce animal usage in drug discovery.

Although CHO cells are one of the most highly employed cell lines in bioproduction (with \>£100 Billion market), current commercially available CHO cells inability to adapt and restore cell balance leads to stress-induced apoptosis and undesirable protein modifications. Further, the biotechnology industry lacks in-line methods to examine the actual cell viability during production in small or large-scale experiments. These pain points limit CHO-based recombinant protein production's efficiency and yield, leading to a considerable waste of resources, time and materials in manufacturing. GeneNet Technology, in collaboration with CPI (Centre for Process Innovation) and Taiwan based Cytena BPS and Instant NanoBiosensor, is here to engineer a stress sensing genetic circuit and AI cell embedded to current bioproduction (incubator) in real-time testing method. Combining cutting edge technology from Cytena BPS' next-generation bioreactor, which allows culture fine-tuning and real-time data collection from culturing and physiological conditions, and Instant NanoBiosensors' Fiber Optic Particle Plasmon Resonance technology which detects biomarker expression, we will gather comprehensive culturing, physiological and biomarker data during CHO cell bioproduction. This comprehensive data will be fed into GeneNet's ground-breaking technology, Artificial neural network (ANN) genetic circuits. ANN genetic circuits are the cutting-edge technology in synthetic biology and genetic engineering. In the past decade, synthetic genetic circuits only apply simple logic (AND/OR/NOT) gates to biocomputing. GeneNet's ground-breaking technology makes genetic circuits analogous to deep learning computers, turning CHO cells into smarter AI computers. All this will enable us to engineer smart, stress-sensing CHO cells to maximise protein production efficiency and yield, benefiting our downstream clients and wider industry and society as a whole.