SBIR Phase I: Determination of the Mechanisms Driving Diseases at the Molecular Network Level to Develop Disruptive Drug Candidates

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a platform of drugs with therapeutic effects that cannot be achieved otherwise, such as disease modifying effects for neurodegeneration or universal treatments for cancer. The project aims to determine the biological laws of molecular networks driving diseases and programing these into an efficient, scalable algorithm for drug target discovery.

The understanding of network biology may enable the rapid design and development of a high number of therapeutic programs and their commercialization with high predictability. It may also inform the field on how molecular networks operate and initiate a new research field. The societal impact of the innovation is to address high unmet medical needs, such as stopping the progression of neurodegenerative diseases or providing universal treatments for cancer.

The platform has the potential for broad impact as it can expand to most cancers, neurodegenerative diseases and beyond, including fibrosis or cardiac disorders.

The proposed project of identifying how of molecular networks drive diseases and programing their laws into a drug target discovery algorithm represents a potential technological leap to develop revolutionary therapies. Current treatments focus on single targets, providing variable therapeutic effects. What is advanced here is the opposite approach: reprogramming molecular networks to produce safe, profound and consistent therapeutic effects.

Specifically, transcription factors (TFs) are dominant proteins controlling all gene expression and cell fate. Because TFs act in networks, algorithms are built to map TF networks and identify the TFs controlling diseased networks. Oligo-based drugs will be developed with the unique ability to inhibit multiple TFs to drive therapeutic effects beyond single target approaches.

The technical objectives of the proposal are the demonstration that oligo efficacy is a function of TF network reprogramming using a well-established breast cancer cell line, building a computational model to select TF targets to reprogram networks toward therapeutic effects and demonstrate the scalability of the model in a second cancer cell line.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.