Global biopharma company leverages patented Intelligencia Portfolio OptimizerTM to enhance its scientific and business decision-making
Core Challenges
• Reliant on a resource-intensive and inconsistent process for evaluating phase transition and probability of technical and regulatory success (PTRS).
• Limited data and lack of objectivity for drug development portfolio go/no-go and investment decisions.
• Need to support oncology pipeline development with data-backed insights for informing more confident scientific and business decisions.
Key Outcomes and Impact
• Streamlined and improved workflow for PTRS assessments leveraging AI-supported insights and consistent data
• Time savings from months to weeks on the PTRS process
• Access to AI Explainability providing transparency into the why behind the predictions
• Potential saving of an estimated $22M in Phase 31 clinical development costs
Challenges in the Oncology Drug Development Process
A global biopharma company approached Intelligencia AITM with two main objectives: improving the success of its oncology drug development process and fostering more efficient workflows and processes. The company sought assistance from an external solution provider to address internal inconsistencies and inefficiencies in evaluating phase transitions and the probability of technical and regulatory success (PTRS) in early-stage drug development.
With a growing oncology portfolio and complex clinical development pathways, the biopharma company needed to enhance its internal PTRS methodology. At the time, the company relied on data from pharma consortium databases for a phase 2 asset. To obtain statistically significant results and improve decision-making, the company augmented its approach with Intelligenica AI’s AI-driven PTRS process, aiming to establish a more efficient, consistent and unbiased method for informed scientific and business decisions.
Improving the Oncology Drug Development Process with AI
In leveraging Intelligencia Portfolio OptimizerTM, the head biostatistician at the biopharma company discovered a significant discrepancy between the internally calculated PTRS prediction for a leading program and Intelligencia AI’s AI-driven prediction. The internal prediction – at 45% – was significantly more favorable than the Intelligencia AI PTRS assessment, which was below 10%.
Impact on the Oncology Drug Development Process
The biopharma’s oncology program failed during the engagement period with Intelligenica AI. If they had access to the more accurate, AI-powered prediction, the company could have discontinued the program earlier, saving significant resources. Comparing the PTRS assessments, the low PTRS and the approval failure validated the accuracy and credibility of Intelligencia AI’s methodology.
Using insights generated with Portfolio Optimizer, Intelligencia AI could have saved the biopharma organization an estimated $22M of phase 3 development costs.
“I’ve had the opportunity to work with Intelligencia AI for over a year, and I have consistently experienced the thorough thinking behind every assumption and methodology being used. Because of this, I have built great trust in our working relationship and trust and confidence in the data and the processes. The quality of work produced has been overwhelmingly impressive. This was truly the first time I felt I had access to enough data to help me test my theory and draw meaningful conclusion.”
– Portfolio Management and Optimization Leader, Biopharma Company
The results of this study convinced the biopharma company to adjust its current workflow for late-stage assets. They evolved the process to require a triangulation of internal predictions, expert elicitation, and the newly added AI-driven phase transition and PTRS predictions from Intelligencia AI to have a more comprehensive, objective and data-backed approach.
Making Substantial Impacts Both Short-and Long-Term
Through this collaboration, the biopharma company experienced an immediate positive impact of introducing a complementary and enhanced approach to PTRS assessments. By leveraging the new AI-backed process and working collaboratively with the Intelligencia AI team, the company can make better science and data-driven decisions.
The global biopharma company now has greater consistency when assessing phase transition and PTRS as well as a streamlined workflow that reduces the burden on project teams and shortens decision-making timelines from several months to weeks.
“We see Intelligencia AI as an extension of our internal team – a true collaboration. We rely on their expertise, meticulous processes and methodologies to guide us and augment our clinical development risk assessment efforts. They are far more than just another vendor”
– Head of Disease Area Strategy, Biopharma Company