FORMsightAI enables cell and gene therapy developers to explore new derivatives of their constructs to ensure the greatest predicted likelihood of manufacturing success, while ensuring cost efficiency.
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Easily build the specific elements for your new construct, including the type of therapeutic gene, the promoter and enhancer sequences to control gene expression and viral vector.
Leverage deep learning technology to minimize truncation propensity and improve reproducibility of the manufacturing process, reducing the potential for batch variability.
Apply FORMsightAI’s breakthrough machine learning models to improve predicted full reads and increase the consistency and quality of the therapeutic output.
Further algorithmic modeling, including codon optimization, CpG island detection and hairpin analysis, can predict likelihood of manufacturing success and cost efficiency.
Improve safety & dose yield by ensuring optimal capsid fill rate
Extend IP protection by filing fresh patents on optimized construct derivatives
Reduce costs by avoiding expensive bioreactor runs on suboptimal constructs
Save time by reducing the number of test manufacturing cycles for a therapeutic candidate
Compare an array of constructs with different design characteristics to find the most promising versions
Fully understand constructs with automated AAV characterization reporting
Predict manufacturing results relating to truncations and other issues
