Feasibility study for an automated Machine Learning analytics platform applied to muscle tissue chips in-space manufacturing process control

G-SPACE proposes a new process that integrates microgravity and artificial intelligence (AI) into a real-time analysis solution with potential future endeavors to become a predictive capability. This process will allow informed experimental tests and ultimately drug therapy decisions to be systematically discovered.nbsp; The platform#39;s user interface will allownbsp;researchers to easily design and execute experiments, monitor results, and refine their hypotheses. The platform#39;s capabilities will significantly reduce drug discovery timelines, increase the success rate of drug candidates, and ultimately improve patient outcomes.In partnership with Micro-gRx, G-SPACE proposes this feasibility study to demonstrate its platform use to thenbsp;simulation of sarcopenia conditions both terrestrially and in-space, which have been shown to enhance cellular functions relevant to drug discovery and eventual FDA approval. Currently there are No FDA approved drugs for sarcopenia. A hallmark of sarcopenia is a progressive pathology characterized by the loss of muscle mass and strength in those over 60 years old. The age-related effects on muscle tissue is difficult to model in cell systems because of genetic differences and tissue heterogeneity in patients and it is most desirable to eliminate reliance on animal studies. The unmet medical need is a standardized platform that can provide a solid reference and evaluate patient-specific tissue pathophysiological responses to potential therapeutics in real time.