Objective

Indication prioritization is the most crucial step for the emerging target to enhance the therapeutic success in clinical trials. We also identify and prioritize the therapeutic indications and patient-segments for emerging drug modality to augment and position the molecule(s) competitively in the market.

Methodology

• AI/ML-based gene prioritization enable us to prioritize disease-associated genes based on biological relevance, level of evidence for gene–disease associations and unmet medical need.
• In addition to the above parameters, we also consider commercial attractiveness of a given target, novelty of MoA, standard of care, etc.
• Extract the disease signature from RxAgentAI, our AI platform to predict a disease modifying property of a given therapeutic agent and its target.
• We apply multiple ML methods such as LLMs and Named Entity Recognition to map all the relevant associations in order to make a rational decision.

Outcomes / Impact

This method allows us to prioritize the therapeutic indications and segment for the emerging drug modality to augment and position the molecule(s) competitively in the market and our ML methods accelerates this process which ultimately helps us in making informed decisions.