With emerging New Science, novel modalities, and a renewed urgency to achieve faster time-to-market, biopharma research and development (R&D) has an opportunity to bring down the total spend for drug discovery and development from billions to millions, with a more fluid organizational blueprint and pipeline process.
First, let’s look at R&D organizational design. Our study shows low variability across the six core dimensions among biopharma R&D organizations. This illustrates an aversion to bold experimentation in favor of minimal change through incremental improvements. While this approach makes sense in terms of risk management and business continuity, it limits the benefits we can realize from high-impact change, and it is not sufficient to sustain R&D investment levels while delivering therapeutic innovation and enabling New Science to scale.
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Second, although each R&D organization is different in scale and strategic priorities, we can still define an overall organizational paradigm for biopharma, the ‘Liquid Pipeline Progression Model,’ which includes:
- Independent and decentralized asset teams: Purpose, mandates, setup, and interactions for drug discovery and development are fundamentally redefined towards more autonomous asset teams.
- Fit-for-purpose development pathways: Interdisciplinary asset teams are fully empowered, equipped, and incentivized to win their individual race to market by choosing fit-for-purpose pathways from bench to bedside.
- Expertise and partnership networks: Asset teams pick and choose discovery, translational, development, and submission services from specialized internal service units as well as from an ecosystem of external partners and service providers.
- Shared learnings and data-driven decision-making: An end-to-end management layer across assets and therapeutic areas drives data-driven portfolio decisions and shares insights across the pipeline via integrated lessons learned, and shared data supports definition of standard pathways based on asset characteristics.
This model shifts power to asset teams, which operate like Product Management Units (PMUs) across all R&D phases. We see these functioning as incubators with a venture capital style of funding and greater accountability for results.
This isn’t entirely new. Specific pieces of the model have already been utilized over the last twenty years. For example, a top-10 European-based pharma company implemented a version of this in the early 2000s starting with Centers for Drug Discovery, and later adding Drug Performance Units and Medical Centers for Phase I-IV development. They also used a venture capital model of competition for budgets on a 3-year cycle instead of the traditional annual budget cycle.
The innovation potential is realized when applying the model end-to-end across the full R&D value chain. Leaders should focus on designing and implementing change across the organization, from real-time portfolio prioritization supported by an R&D data fabric to adaptive workforce models with talent pools that are both internal and external.
Rather than a “big bang” approach, companies can carve out a piece of their pipeline to adopt the new R&D model characteristics as a pilot. Learnings can then be applied to other components of the pipeline in systematic, incremental steps – each continuously refining the overall model, making it better every time. Areas with novel modalities such as Cell & Gene Therapy are primary candidates for a first wave of implementation.
Biopharma leadership is entering a prime time for dramatic change to the R&D landscape, and a new organizational model is available to expedite the discovery, development, and launch of treatments and recognize opportunities for financial improvement.