Moving oncology from a stochastic "cell-kill" model to a deterministic "state-steering" paradigm using vector-field topography.
The current standard of care for glioblastoma (GBM) is analogous to carpet-bombing the mountain. We are changing the physics of the treatment.
Somatic Mutation Theory & Cytotoxicity. We've historically viewed cancer as uncontrollably dividing cells. Therapy aims for "cell-kill" (radiation, chemo). However, surviving cells exhibit lineage plasticity. They climb out of their differentiated valleys, escaping cytotoxic stress by adopting resistant, stem-like states.
Epigenetic Landscapes & State-Steering. Cancer is cells climbing the Waddington landscape. We don't want to destroy the cell; we want to force it to mature. Differentiation therapy uses specific directional pushes to guide Glioblastoma Stem Cells (GSCs) back down into stable, post-mitotic valleys.
Reverse-Engineering Malignancy via Attractor Perturbation. Integrating scRNA-seq, RNA velocity, and massive perturbation databases.
Using Single-Cell Multiomics (scRNA-seq + scATAC-seq) and Waddington-OT, we reconstruct the patient-specific epigenetic landscape from patient-derived organoids.
Deploying scVelo and Dynamo to calculate real-time RNA velocity. We map the continuous vector field to identify the precise paths cells take to become resistant (v_escape).
Top predicted 'Shifter' compounds are rigorously validated using automated, high-content imaging of 3D patient-derived organoids to confirm morphological maturation.
VECTR-Match bridges the gap between static drug signatures and dynamic cellular fate. It screens the LINCS L1000 database (>1.3M profiles) not for cytotoxicity, but for mathematical force-field alignment.
ScoreP = (FP · vtarget) - λ * (FP · vescape)
Glioblastoma represents a $3B+ annual market with zero significant survival improvements in 20 years. E.sapiens is built to disrupt this stagnation.
Integration of spatial transcriptomics for microenvironment-aware steering.
In-vivo validation of top 3 'Shifter' candidates in orthotopic GBM models.
Safety profiling and clinical trial design for first-in-human differentiation therapy.
Our approach is guided by world-class experts in computational biology, oncology, and regenerative medicine.
Pioneering the application of vector-field topography to cellular state transitions.
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