By Marc P. Philipp and Katie Miinch
Shifting pharma spend from billions to millions requires revisiting R&D organizational design
For decades, biopharma executives have seen operational costs and complexities soar. As commercial pricing, reimbursement, and market access hurdles remain particularly difficult to overcome, CEOs are turning to their R&D leadership to help reconfigure the business economics. In addition, recent experiences with Covid and the subsequent rapid delivery of effective vaccines showed that the operational costs and complexities of a decade-long bench-to-bedside journey does not need to remain the norm.
With emerging New Science, novel modalities, and a renewed urgency to enable faster time-to-market, R&D now has a prime opportunity to find effective means for rapid innovation while also bringing down the total spend for drug discovery and development from billions to millions.
We believe another look at how biopharma R&D is organized and operates can make a major contribution to this effort. The quest for a more fluid and adaptable organizational blueprint that supports the effective progression of the pipeline of lead candidates through proof-of-concept and full-scale clinical development will likely mean an end to the R&D organization as we know it.
The realities of R&D org design
We took a deeper look at the current state of R&D organizations to understand what models are being applied in the marketplace (see Figure 1), and we benchmarked similarities and differences across six core dimensions of R&D organizational design:
- R&D leadership breadth: Integration and leadership oversight across research, development, and medical affairs functions
- R&D governance: Decision-making, provision of strategic guidance, and management of drug pipeline progression
- Hand-off points towards development: Timepoint when ownership of asset progression is handed over from discovery to development
- Degree of centralization: Degree of global versus regional autonomy over portfolio, functional activities, and therapeutic areas
- Large molecule & novel modality capability setup: Degree to which new modality capabilities are established and shared across therapeutic areas
- Degree of clinical externalization: Use of partners (e.g., CROs, FSPs) for clinical development and operational activities
Our benchmarks show low variability across these six core dimensions, with biopharma R&D organizations all operating with similar models. Each dimension shows one clearly dominant option that is deployed by 40-70% of all companies. For example, more than 2/3 of all companies embed new capabilities for large molecules and novel modalities within global functions and share them across TAs. More than 60% of all companies still apply a traditional, vertical stage-gate-focused governance model. More than half of all companies hand over assets to their clinical development organization at or after Proof-of-Concept and steer global R&D activities through HQ functions.
This limited variability in R&D organizational design today is likely a result of approaching change through incremental improvements rather than bold experimentation and novel ways of reconfiguring the organization. While this approach is rational from a risk management and business continuity perspective, it also limits the ability to realize the benefits of high-impact change.
Prime time for change: Inspiration from biotech, software development, and defense
Though the common operating model characteristics across each of the six core dimensions have sustained the industry to date, we believe that the current approach is not sufficient to sustain R&D investment levels while delivering therapeutic innovation and enabling New Science to scale.
As R&D org design can have a powerful impact on competitive differentiation and productivity, what is required instead is holistic change towards a more fluid model. With rising stakeholder pressure and lessons from Covid-19 in hand, the next five years are a window of opportunity for leaders to establish and test fundamentally new models. A successful “first mover” approach to transforming the R&D operating model will not only be hard for competitors to replicate but will also directly improve top- and bottom-line performance. It will radically accelerate the progression of assets without compromising quality or compliance.
Despite the specificities of the large-scale biopharma business model and the unique level of GxP-related scrutiny and compliance, sources of inspiration for new models can be found in biotech companies, software developers, and military defense:
- Mid-sized biotech players take an accentuated asset-based approach to innovation and can make quick changes to adjust their portfolio to strategic needs.
- Software development has impressively demonstrated how to effectively move away from waterfall-driven vertical, functional siloes and towards agile approaches that cut down both costs and timelines for product development, deployment, and adoption.
- The U.S. Defense Advanced Research Project Agency (DARPA) has mastered the ability to formulate and execute highly complex research projects that have provided significant technologies beyond immediate military requirements by effectively collaborating with academia, industry, and government partners.
The patterns of leading practices across these industry sectors can be translated to biopharma, with prominent themes of strategic autonomy, agility, adaptability, and collaborative management.
A new future – the ‘liquid’ blueprint for pipeline progression
Each biopharma R&D organization is different in scale, scientific platform access, pipeline priorities, and capability maturities. Although individual strategic characteristics call for a tailored target operating model for each organization, we can still define an overall organizational paradigm for biopharma, the essential features of what we call the ‘Liquid Pipeline Progression Model’:
- 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 will be 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.
To make this model successful, power will need to shift to asset teams, which will operate like Product Management Units (PMUs) across all R&D phases. These can function as incubators with a venture capital style of funding, and with greater accountability for results. Global functions will need to be transformed into internal service units specialized in delivering against asset-team needs in competition with external partners that are pre-selected and managed in an R&D ecosystem.
Several pieces of this model have already been utilized in practice, with progress that goes back twenty years:
- Some biopharma leaders established autonomous asset teams years ago, although mostly for discovery and pre-clinical research stages. 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.
- Other organizations have already transformed functional cost centers into internal service providers, however most of them are enterprise functions outside of R&D, such as Finance or IT. Over the last 5-10 years, some large and mid-sized players have successfully taken the idea into R&D, creating offshore captive business services for transactional activities across regulatory affairs, pharmacovigilance, and clinical operations.
- Establishing partnership networks to open opportunities beyond the boundaries of the biopharma company has been essential to R&D for a long time, but was mostly restricted to academia in discovery research or clinical development service providers. Just recently have R&D organizations realized how critical cross-functional strategic vendor management capabilities are when external ecosystem partnerships become larger and more mission-critical.
What is different about the Liquid Pipeline Progression Model? We believe the winning model of the future will depend on an organization’s ability to combine these ideas end-to-end across the full R&D value chain. Leadership attention should be directed towards designing and implementing change across all six core dimensions, and aligning the organization from the start on the target ambition of the new model across all dimensions (see Figure 2).
|DESIGN DIMENSION||KEY CONSIDERATIONS||TARGET AMBITION FOR LIQUID PIPELINE PROGRESSION|
R&D Leadership Breadth
|How are key decisions made within executive leadership team (especially investment and resource allocation)?||Collaborative data-driven decisions across full R&D value chain on asset-specific outputs, and subsequent pressure-testing and consolidation across all assets|
|How is accountability assigned, and operational excellence and performance assessed and fostered?||Operational excellence and performance management are part of the model’s fabric, with strong incentives to continuously improve functional service offerings and efficiency enforced collectively across the R&D leadership|
|How are the pipeline and projects prioritized?||Dynamic real-time prioritization based on competitive intelligence and scenario modeling across full asset portfolio|
|How is budget allocated?||Budget allocated to asset teams that provides funding for function based on service delivery/output. Budget allocation on milestones rather than annual basis. Baseline funding for functions centrally provided and continuously challenged.|
|Hand Off to Development||When and how are assets transitioned into Clinical Development organization?||Asset teams align budget/timeline/outcome ambition with Executive Leadership, but gain full authority to decide when and how they work with internal or external development partners based on asset characteristics and development strategy|
|How is data managed to support portfolio asset decision-making?||Integrated data flow across R&D value chain that is standardized and reliable (i.e end-to-end R&D data fabric).|
|How are differences in asset characteristics and resulting R&D requirements accounted for?||Asset teams can choose from different pathways tailored to their therapeutic area from technology partners, CROs, academia|
|Degree of Centralization||How is talent optimized across global/local boundaries?||Global asset teams with worldwide reach, integrated global functions with regional/local country level that allows for variations depending on local clinical footprint (esp. for emerging markets), empowered and flexible workforce to conduct specialized activities|
|How are technology systems managed?||Cloud-based technology platform that supports applications managed by technology partners and CoE service teams with global reach.|
|Large Molecule and Novel Modality Capability Setup||How are new capabilities created and further developed?||Selectively decentralized capability building based on demand/needs from asset teams to improve relevance, trade-off between global cross-TA consistency vs. replication of capabilities to adhere to TA-specific needs determined within global functions – external partnerships can mitigate need for specialization|
|Degree of Clinical Externalization
|How is capacity utilization and flexibility ensured?||Balance of shared resources providing CoE services and flexibility of asset teams to deliver end-to-end. Ecosystem used to flexibly ramp up/down extra capacity as needed|
|How are workforce needs anticipated and planned for?||Adaptive workforce models with talent pools spanning internal and external sources|
Figure 2: Key considerations and target ambition for Liquid Pipeline Progression Model across six core org design dimensions
(Source: Accenture research and client experience)
De-Risking the journey by moving to an interim hybrid R&D model
When it comes to making change happen, R&D leaders have historically taken “big bang” approaches for incremental or targeted improvements. Rightly so, as the smaller the magnitude of expected change, the better and easier it is to minimize transition time and directly introduce new ways of working at full scale.
In contrast, implementing the Liquid Pipeline Progression Model via a big bang to the entire organization could put R&D business continuity, compliance, and ‘in flight’ pipeline delivery at risk. Depending on the current state, such a shift is likely to change too many organizational aspects simultaneously. Introducing the new model will require a new mindset and game plan (see Figure 3). Instead of aiming for the big bang that requires getting things right the first time across the board, 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.
Establishing an interim ‘hybrid’ model between the old and the new is an effective approach. Primary candidates for a first wave are planned pipeline expansions that cater to novel modalities, such as Cell & Gene Therapy, and/or additional therapeutic areas that inherently require changes to the way an R&D organization operates.
This game plan will require R&D leadership to effectively manage expectations in their organization about accepting upfront investment and temporary operational redundancies while running two operating models in parallel. Performance of the new model will need to be analyzed and approaches improved and fine-tuned in an iterative fashion – and leadership must provide end-to-end support for this strategic change. The new model will then scale gradually until the organization fully transitions to the new paradigm.
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.
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About the Authors
Marc P. Philipp is a Managing Director with Accenture Strategy out of the firm’s Berlin office. He leads the firm’s Biopharma R&D Strategy Consulting practice in Europe and serves as a consulting practitioner and senior advisor to executive leaders in shaping and executing strategies for large-scale transformation and productivity improvement. Marc started his career with Accenture in 2004 and re-joined the firm in 2014 after five years as Head of Clinical Research & Trial Management Operations at CHARITÉ BERLIN – one of Europe’s largest University Hospitals and Clinical Research Sites. He holds an MBA with a major in Corporate Finance and an LL.M. in Intellectual Property and Antitrust Law.
Katie Miinch is a Managing Director with Accenture’s Life Sciences R&D Strategy and Consulting group, based out of the firm’s Philadelphia office. She co-leads Accenture’s Biopharma Agile R&D Operating Model team globally and has worked across many R&D functions at various pharmaceutical companies both within Accenture and in previous work locations. She holds a B.S. degree in Kinesiology, an M.S. degree in Sports Healthcare and a Masters certificate in Applied Project Management. She also holds the Project Management Professional certification from the Project Management Institute.
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