Nanograb

Nanograb is an AI-driven platform designed to optimize the delivery of genetic material—such as DNA, RNA, or CRISPR components—into a wide variety of cell types. It leverages machine learning to predict and recommend optimal delivery parameters, including lipid nanoparticle formulations, electroporation settings, and viral vector designs, thereby reducing the trial-and-error typically associated with gene delivery. The platform is intended for researchers and biotechnologists working in gene therapy, cell engineering, and synthetic biology. By integrating experimental data with predictive models, Nanograb helps users design more efficient transfection and transduction protocols, potentially accelerating the development of cell and gene therapies. Nanograb's AI models are trained on a large corpus of published and proprietary transfection data. Users input target cell type and desired payload, and the system returns recommended delivery methods and parameters. The platform also offers a collaborative workspace for teams to share protocols and results. What sets Nanograb apart is its focus on generalization across diverse cell types, including hard-to-transfect primary cells and stem cells. The AI continually improves as more data is fed into the system, making it a dynamic tool that adapts to the evolving needs of the gene delivery community.