WHAT IF YOU COULD PREDICT MOLECULES TO MAKE THE CAUSE OF DISEASE DISAPPEAR?
Differentiated Therapeutics (DXTX) has built the first end-to-end discovery engine for Targeted Protein Degradation (TPD) which drives the discovery and optimization of novel protein degraders designed to eliminate the genetically defined drivers of disease.
Due to the highly heterogeneous nature of pharmaceutical development, our field has yet to experience an organization built from the ground up with an end-to-end platform that deploys a custom toolkit of applications for specific problems in the drug development process. DXTX fills this gap. We believe our organization can only be successful by discovering differentiated therapeutic development strategies for which our platform drives significant value.
The vast complexity of biological signaling requires protein-protein interactions to impart post-translational modifications and molecules that induce proximity gave us paradigm-shifting medicines like rapamycin, lenalidomide, and pomalidomide. Yet, 95% of nature’s E3-substrate chemical space remains unmapped for its enormous potential - until now. At Differentiated Therapeutics we’re combining breakthroughs in biophysics, chemoproteomics, molecular simulation, artificial intelligence (AI), and automation to map the conformational basis of induced proximity and to use that map to design novel degrader therapeutics.
Our Automatic Differentiation (AutoDX) platform consists of a suite of tools that enable differentiable portfolio planning by screening our proprietary Differentiated Therapeutic Knowledge Graph (DTKG) to identify protein degradation strategies for targets with indications of high unmet need. AutoDX significantly reduces time reviewing the literature, assessing patents, and manually designing molecules providing our scientists more time to focus on experimental design and high-quality data collection. To compute protein degradation strategies, AutoDX precision engineers compound design leveraging molecular dynamics to assess platform performance and predict the likelihood of successful strategy execution. Key components of our platform include biological discovery, multiobjective design, and translational studies.
Our carefully engineered systems combine advanced differentiable design with experimental validation to rapidly progress our protein degradation strategies. The AutoDX platform is better at learning which degrader molecules meet the complex project-specific criteria required for successful clinical development than traditional human-led design, enabling a more efficient and effective trajectory to a development candidate. Every program in our pipeline represents hope for an important segment of patients in need of treatment. By targeting the known drivers of disease, we are engineering the integration of AI, molecular simulation, and biomedical informatics to develop drugs that show promise of becoming safe, effective protein degrader therapeutics.