In brief, we are conducting large-scale screens tying promoter sequences to gene expression levels to then feed into a machine learning model to generate new sequences for experimental validation. We propose this discovery service to companies seeking to fine-tune their gene expression.

The ability to optimize gene output would have high impact within the biotechnology sector, with immediate medical, environmental, agricultural, and industrial applications. We are developing early partnerships with such organizations to engineer and validate synthetic promoters tailored to their specific needs, which would not only help us to develop our processes and iterative pipeline, but also provide an initial revenue stream and guide the development of our internal/commercial software. Therefore, we operate as a business-to-business company to customers such as cell therapy and therapeutic protein companies, where output efficiencies directly influence production and sales. Data generated from m...
In brief, we are conducting large-scale screens tying promoter sequences to gene expression levels to then feed into a machine learning model to generate new sequences for experimental validation. We propose this discovery service to companies seeking to fine-tune their gene expression.

The ability to optimize gene output would have high impact within the biotechnology sector, with immediate medical, environmental, agricultural, and industrial applications. We are developing early partnerships with such organizations to engineer and validate synthetic promoters tailored to their specific needs, which would not only help us to develop our processes and iterative pipeline, but also provide an initial revenue stream and guide the development of our internal/commercial software. Therefore, we operate as a business-to-business company to customers such as cell therapy and therapeutic protein companies, where output efficiencies directly influence production and sales. Data generated from massive high-throughput screens are fed back into our predictive model, allowing us to more rapidly identify subsequent target promoters. Machine learning has transformed the field of drug and small molecule discovery within the last decade; we plan on applying similarly powerful models to sequence discovery and design, founded and validated on high volumes of high-quality experimental data generated for the purposes of machine learning.
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Victoria Mo
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Victoria Mo CEO Machine learning engineer, early-stage software engineer, and prior CTO of a B2B software company. Div I National Champion in epee fencing.