As Novartis transformed to a focused, pure-play innovative medicines company, portfolio management was consolidated across Research, Development, and Commercial to build lasting impact and achieve long-term business success. Since mid-2022, we have focused on building a stronger, focused pipeline, streamlined enterprise governance, centralized long-term revenue forecasts and valuations, and created an aligned strategic framework. Key learnings include importance of change management, flexibility, and streamlined processes and systems.

Decisions in drug development have a substantial influence on the outcome of individual projects and the Research and Development portfolio.  Lilly Decision Sciences and Project Management organizations partner to deliver Decision Quality on decisions across Research and Development and Lilly Research Labs has won the Raiffa-Howard Award from the Society of Decision Professionals for achieving Organizational Decision Quality.  This presentation will discuss what roles the Decision Sciences experts and Project Managers take and what approaches are put in place in those organizations to deliver Decision Quality for individual projects and the portfolio.  

This presentation outlines the intention of waiting for external clinical data prior to investment decision-making. An illustrative example-including an overview of the quantitative inputs needed to generate outputs and insights-is used to frame the decision of invest now or invest later pending external data read-out. While leveraging external data may appear appealing, the presentation will review potential challenges to the decision alternative of waiting.

Over the past 5 years we have explored areas where AIML can be applied to improve decision science in healthcare R&D. We will review our journey with highs and lows, share pros and cons and where we see applicability now and for the future through very practical case studies (from AIDD to indication ideation, to PTRS prediction and development strategy optimization as well as other less expected areas of interest).

There are several theoretical approaches to portfolio prioritization, based on value metrics, costs, and pareto curves. In the real world within the pharma industry, prioritization needs to align with multiple stakeholders who have different priorities, and to address multiple constraints. A framework will be presented that addresses these limitations and provides transparency in order to make tradeoffs within the portfolio.

Traditional statistics analysis discovers correlations while yielding biased results. New techniques, called causal inference and discovery, identify causal relationships. Using these techniques, inspired by how statistics transformed baseball (see the movie Moneyball), we analyze ten years of clinical trial data to identify opportunities to improve trial design and PTRS.

In helping to support decision making on complex opportunities, setting the table for the decision should include some elements that serve as mitigation for any potential bias. Consistently leveraging a process OR building one to generate an aligned set of key inputs can sometimes be challenging. What are the common and not-so-common biases that might be at play for your opportunity? What processes do you have at your disposal (or may need to set up) to leverage? What resources might you leverage to up your own game?

It is well-documented that in-licensed drug projects have higher likelihood of approval than projects developed internally in the biopharmaceutical industry. Using a granular dataset, we show that this result holds when controlling for possible sources of heterogeneity across drug projects. Next, we posit and show that the success rate difference is partly driven by agency problems within companies. Namely, internal R&D teams may bring forward less promising drug projects due to monetary and career incentives. We also show that this mechanism is distinct and coexists with selection effects and contractual inflexibility mechanisms proposed in previous literature.

This session will explore strategic frameworks that drive successful drug development. We will delve into the Target Product Profile (TPP), which delineates a drug's ideal characteristics, serving as a strategic blueprint to align development and regulatory objectives. It ensures a clear vision from concept to market.  Additionally, we'll examine the Stage-Gate Governance model, which structures drug development into distinct phases, with decision points or "gates" to evaluate progress. It promotes systematic review, risk management, and efficient resource utilization, enhancing project success.

The RAID Log is a commonly used tool for capturing project information. However, it lacks key project information, does not link between key artifacts, and it does not allow for feedback loops that enable continuous improvement. The GRIDALL model offers a more comprehensive model for capturing project information. A PMO that uses the GRIDALL method will provide value to project teams by being more complete, connected, and continuous.