Background: Clinical Limitations of Existing DNA Double-Strand Cleavage-Based Editing and Specific Genetic Polymorphism Data Bottlenecks in Craniosynostosis R&D

• Conventional CRISPR-Cas9 and other first-generation genome editing models, which rely on DNA double-strand cleavage (DSB), have inherent limitations, including genomic sequence loss, large-scale chromosomal translocations, on-target/off-target indel noise, and p53-induced cell death feedback. Craniosynostosis, in particular, is a complex disorder involving over 60 genes (including FGFR1, FGFR2, FGFR3, TWIST1, TCF12, and EFNB1) that form intricate networks. It is characterized by abnormal gain-of-function mutations in the cranial suture microenvironment during fetal development. Existing models fail to fully control the dissociation of cells in this developmental stage and the changes in microenvironmental signals through in silico computational methods, leading to poor in vivo efficacy and failure to maintain effective therapeutic concentrations. This has created significant data barriers and R&D bottlenecks in the development of long-term rare skeletal disease therapeutics.

Discovery: Machine Learning-Based pegRNA Tensor Synchronization and In Silico Docking Free Energy Prediction for Downstream Pathway Editing

• This architecture employs a next-generation genome editing modality, Prime Editing, and integrates it with a precision deep learning design algorithm (e.g., PRIDICT2 and PrimeDesign, DOI: 10.1038/s41587-020-0610-z) to perfectly synchronize a multidimensional tensor that analyzes pegRNA structure and the accessibility of target sites. By performing in silico predictive calculations of the local binding free energy of the Prime Editor protein complex based on differential equations and computational design, the platform mathematically eliminates unwanted cell batch effects observed in ex vivo cell cultures. This platform demonstrates ultra-precise target editing that surpasses the off-target rates of conventional gene editing tools and completely restores developmental mutations in the FGFR2 gene (e.g., S252W) to the normal wild-type (WT) sequence. Consequently, the topological variation curve of the downstream transcriptional regulatory network of FGFR (RAS-ERK/MAPK and PI3K-AKT pathways) returns to the normal baseline, fully demonstrating the molecular integrity of osteogenesis.

Establishment of a Model for Fine-Tuning the FGFR Signaling Pathway and Reversible Osteogenic Homeostasis

• This model integrates large-scale multi-omics matrix data with individual patient genetic molecular phenotypes and family-specific mutation patterns to perfectly implement precision stratification. By numerically modeling the rate-limiting step constant of FGFR2 signal transduction strength, the model artificially up-regulates or down-regulates specific transcriptional activation constants to reset over-activated bone development signals. This establishes a framework for reversibly modulating cell-autonomous osteogenic homeostasis even in aberrant, physically stressed bone microenvironments. This goes beyond single-molecule target editing to provide a patient-specific therapeutic backbone that computationally modulates and induces homeostatic dynamics throughout the developmental cycle.

Prospects: Establishing a Standard for Programmable Genome Editing Medicine and Launching a Next-Generation IND Digital Governance System

• This achievement transforms genome medicine R&D governance from a static, post-hoc symptomatic treatment system to a fully programmable digital infrastructure based on AI-powered multidimensional tensors. In line with the expansion of Prime Medicine and other global biotech companies' Prime Editing clinical pipelines (e.g., Phase 1/2 trials of PM359), a computational moat has been established that links high-throughput screening (HTS) stage micro-gradient correction coefficients to the genome architecture to completely eliminate batch-to-batch variation. As a result, this platform fully meets companion diagnostic (CDx) requirements, drastically shortens the timeline for clinical trial protocol (IND) approval by global regulatory agencies (FDA, EMA), and significantly increases the rate of cGMP manufacturing approval, making it a master asset.