Eli Lilly Tops Inaugural Pipeline-to-Patient Productivity Index as Industry R&D Efficiency Faces Mounting Pressure
核心洞察
Eli Lilly ranks first in the new P3i benchmark, rising from 16th place against 2020 metrics, driven by operational improvements beyond its GLP-1 franchise.
Pipeline creation has slowed 32% over five years while R&D spend increased 45%, with median development timelines extending from 8.4 to 9.3 years.
Overall success rates have fallen to 8.2% as companies impose stricter Phase I barriers, with 38% of clinical failures now occurring at this early stage.
Eli Lilly has claimed the top spot in the inaugural Pipeline-to-Patient Productivity Index (P3i), a new benchmark developed by Evaluate Pharma (搜索) and Norstella (搜索) that tracks drug performance across the entire development and commercialization lifecycle. The ranking marks a dramatic ascent for Lilly, which would have placed 16th against 2020 benchmarks, with the report attributing the trajectory to operational improvements across its pipeline rather than solely to the success of its GLP-1 franchise.
The P3i spans the top 25 publicly listed biopharmaceutical companies and provides performance benchmarks across eight key indicators, from early pipeline creation through clinical development and risk, into market access and commercial return. UCB (搜索) has similarly risen sharply, while several companies have dropped out of the top ten.
R&D Costs Climb as Pipeline Output Contracts
The index reveals a troubling divergence: pipeline creation has slowed by 32% over the last five years, even as R&D spend increased by 45% across the cohort. The median development timeline has extended from 8.4 to 9.3 years within the same period, underscoring the growing challenge of translating investment into tangible output.
Overall success rates have fallen to 8.2%, driven by a higher Phase I barrier. Notably, 38% of clinical failures now occur at this early stage, reflecting tighter criteria for advancing assets into costly late-stage development. This stricter portfolio discipline represents a strategic response to the escalating costs and timelines that characterize the current R&D environment.
Launch Performance and Market Access Dynamics
Average revenues at seven years post-launch have risen to $1.6 billion, though this figure is substantially driven by GLP-1 therapies. Excluding Wegovy and Mounjaro, the current cohort average falls to $1.3 billion—on par with five years ago, suggesting that blockbuster performance remains concentrated rather than broadly distributed.
Access to new launches is showing signs of tightening. While one-year coverage stands at 68.3%, in line with the 2020 benchmark, annual data for 2024 and 2025 suggest a downward trend coinciding with more active payer utilization management, including restrictive prior authorization criteria.
Newly launched products account for 25.7% of total prescription revenues, down from 28.9% in 2020. On current projections, that figure falls to 18% by 2030, pointing to a growing need for deal-making to grow beyond the patent cliff.
Three Pathways to Enhanced R&D Efficiency
Naveed Panjwani, pharma R&D consulting lead at PA Consulting (搜索), identifies three major themes for continued progress in improving pipeline delivery efficiency.
The first is optimizing resource utilization. As R&D budgets and specialist talent remain under pressure, leading companies are treating resource utilization as a core productivity lever. Panjwani notes that companies are refining resource deployment models, reducing management layers to decentralize trial decision-making, and pursuing strategic, selective outsourcing rather than all-in or all-out approaches. "As pipelines evolve, an outsourcing strategy must be frequently revisited to test the original value thesis—and companies must not shy away from changing tack when it is no longer sound," he writes.
The second theme is driving technology-enabled operational innovation. Structured digital workflows that span trial tasks end-to-end can reduce repetitive manual effort and cut the FTEs needed in trial start-up, conduct, and reporting. Data integration and analytics, including consolidating tools and establishing a single source of truth from the start of a clinical program, improves downstream document creation, data quality, and amendment speed. Technology-enhanced recruitment using electronic health records, AI-driven outreach, and digital communication platforms enables more precise and efficient patient recruitment and retention.
The third priority is executing with operational discipline. Panjwani emphasizes systematic, data-driven removal of unnecessary procedures and data points to counter protocol complexity that has "long fed cycle time inflation." Critical path management—rethinking sequential activities and converting selected steps into parallel ones—can liberate months or even years of avoidable cycle time. "Dropping a new process or technology into clinical trial work is insufficient on its own and often leads to poor adoption or workarounds," Panjwani cautions, stressing that new workflows require deliberate consideration of how roles and process norms must adapt.
An Ever-Rising Bar
The efficiency bar continues to rise. Economic shocks from trade and geopolitical friction are fueling the already substantial cost of talent, raw materials, and services. Development cycle times creep up as data volumes explode, protocols incorporate ever more endpoints, and narrower inclusion and exclusion criteria constrict already small trial populations.
"The bandwidth of major pharma late-stage pipelines has remained stagnant or even reduced relative to pre-pandemic years, as companies have focused expertise on fewer therapeutic areas and fewer, higher-value, first-in-class new molecular entities," Panjwani observes, citing the Citeline Pharma R&D Annual Review from April 2026.
For R&D leaders, the path forward requires disciplined progress across all three connected priorities: deploying scarce resources more intentionally, translating digital and AI-enabled innovation into practical operational gains, and embedding the execution discipline needed to reduce avoidable complexity and cycle time.