The Portfolio Strategy team of a prominent mid-size Pharma company had been seeking to implement a systematic way to review the PTRS (Probability of Technical and Regulatory Success) of all its programs. Initial focus was on oncology, but over time, they also expanded this approach to other TAs.

Previously, the company had relied on disparate analysis including the estimates provided by the program teams, analytics performed on internal historic data, and industry- wide historical benchmarks.

Intelligencia’s Porfolio Optimizer applies ML-driven predictive analytics on a rich, expertly curated proprietary database to enable users to:

• Apply a consistent and data-driven probability of success estimate on programs (transition to clinical stage, transition across phases, regulatory approval)
• Evaluate the key drivers behind the PTRS assessments by indication and phase
• Review analogs and benchmarks in a fast, systematic, consistent manner
• Provide a unique data-driven perspective as an input to the semi- annual discussions and decisions of Porfolio Review Committee