The 2026 Global Biopharmaceutical Leaders Study was carried out during June and July, reaching 400 senior voices from the world’s biggest drugmakers, emerging public and private firms, and leading investment houses. The sample comprised 359 C-level executives and 41 top-tier investors, offering a panoramic view of how the industry perceives its immediate future.
Respondents were asked about market sentiment, financing, regulatory risk, partnership trends, therapeutic focus, and the impact of emerging technologies. Their answers reveal a nuanced picture: optimism tempered by macro-economic uncertainty, an evolving pricing landscape, and a shifting balance of power toward China and artificial intelligence.
Equity sentiment, pricing policies and macro-risk outlook
For the first time in several years, a plurality of executives believes the biotech public equity market is fairly priced. This newfound confidence is linked to expectations that both public and private financing streams will remain robust, driven by steady M&A activity and efficiency gains from AI-enabled drug discovery. Nevertheless, respondents flagged three principal threats: lingering macro-economic volatility, political turbulence, and uncertainties surrounding the U.S. drug-pricing framework. The effectiveness of the FDA also emerged as a top concern, as does the unpredictable trajectory of U.S. pricing reforms.
When asked to project the impact of U.S. pricing policy over the next three years, leaders anticipated a pull-back of ex-U.S. product launches. They also expected biotech firms to retain global commercial rights rather than cede them to partners. Opinions on the direction of U.S. drug prices split along geographic lines: U.S.-based and large-pharma CEOs tended to forecast price declines, while mid-cap, small-cap and European executives leaned toward price increases. Across the board, most participants predicted that European prices would rise, often outpacing inflation, reflecting the belief that recent price erosion has reached its floor.
Deal dynamics, therapeutic priorities and technology bets
Survey data indicate that bolt-on acquisitions and strategic licensing deals are set to grow, especially among mid-cap pharmaceutical leaders. Large-cap consolidation, however, is expected to stay flat at historically low levels, although roughly 30 % of large-cap CEOs foresee modest upticks. The chief obstacles to deal execution span valuation mismatches between buyers and sellers, competitive crowding, and the lingering fog of pricing and reimbursement uncertainty, with FDA regulatory risk trailing closely behind.
Therapeutically, executives continue to focus on autoimmune, inflammation and fibrosis indications, with solid tumours also high on the agenda, particularly for large-pharma decision-makers. Rare diseases, metabolic disorders and neurology follow in priority. On the technology front, priorities are widely dispersed. Next-generation antibodies—including bispecific and multispecific formats—remain the top bet, especially among large pharma and investors. Interest in precision small molecules, antibody-drug conjugates, and protein-degradation platforms has risen, while enthusiasm for data analytics, AI and machine learning has dipped slightly compared with the previous year.
China’s expanding role and the shifting AI/ML landscape
Respondents agree that China’s contribution to the global pipeline will keep expanding, driven now by more than cost and speed. Leaders cite a growing belief that Chinese innovators will deliver both first-in-class and best-in-class therapeutics, intensifying competition in Western markets over the next five years. The perception of China as a “double-edged sword” remains, reflecting both lucrative opportunity and strategic risk.
Artificial intelligence and machine learning continue to reshape drug discovery, but their perceived point of greatest impact is moving forward. While chemistry discovery still registers as the area where AI makes the most noticeable difference, large-pharma executives now anticipate that the technology’s biggest breakthrough will occur in biological discovery and clinical development within the next five years. This shift signals a maturation of AI tools from early-stage molecule design to later-stage validation and trial optimization.
