Oct 30 2025
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Smart Pipeline Decisions: AI-Powered Indication Prioritization for Oncology TA
Background:
In the current scenario, the competitive landscape of oncology TA, where innovation moves rapidly, pharma companies face intense pressure to optimize their pipeline investments. With hundreds of potential cancers and limited resources, selecting the most promising therapeutic indications for early-stage assets is both critical and complex. Traditional prioritization methods usually rely on manual literature reviews, expert panels, and historical analogs, lagging to keep pace with the dynamic nature of clinical, regulatory, and market data, which in turn delays portfolio actions.
With a goal to address this challenge, one of our key clients sought a solution from us that would provide a systematic, multi-dimensional, and data-centric approach to prioritize oncology indications for their early-stage pipeline assets.
Objective:
The primary objective was to enable evidence-based indication prioritization by integrating epidemiological, clinical, and commercial datasets into a unified, AI-powered decision framework that would:
- Identify high-value oncology indications with optimal market potential and strategic fit.
- Accelerate go or no-go decisions in the asset development stage.
- Balance scientific feasibility, unmet need, competitive intensity, and commercial viability.
Approach:
Thelansis deployed its own AI-powered cloud platform to support structured indication assessment through a combination of epidemiological insights mapping, clinical landscape intelligence, and market attractiveness scoring model.
Our team also developed simulation models to analyse various scenarios from launch to adoption, predicting ROI potential.
Our solution consolidated all the insights into interactive dashboards, providing real-time visualization.
Impact:
Through this technology-enabled framework, the client successfully transitioned from a subjective, time-intensive indication assessment process to a multi-dimensional, data-centric prioritization model. The key outcomes included:
- 30% faster Therapy area/ indication selection cycle, reducing decision turnaround time from months to weeks.
- Freed up over 400 hours of manual research and cross-team alignment.
- Identification of three high-potential oncology indications with strong commercial viability and feasible development timelines.
- Enhanced asset valuation by aligning development plans with high-impact indications.
With this approach, our client not only accelerated their decision-making process but also strengthened their scientific and commercial rationale for every pipeline move.