ADCs, bispecifics, and radiopharma gain traction
After a decade of immunotherapy dominance, oncology’s next wave is defined by targeted precision — antibody-drug conjugates (ADCs), bispecific antibodies, and radiopharmaceuticals.
In 2025, the FDA approved multiple ADCs across solid tumors, with >260 ADCs now in global development — a 40% increase from 2022. Daiichi Sankyo’s TROP-2 programs, ImmunoGen’s Elahere (mirvetuximab), and Seagen’s HER2-directed ADCs have validated the model: better tumor targeting, better tolerability, and growing commercial success. Radiopharma is following suit — Novartis’s Pluvicto (PSMA-targeted) and Lutathera (NETs) continue to expand indications, and more than 30 new radioligand programs entered early-phase trials in 2024–25.
Implication: Oncology pipelines are tilting toward payload precision, with platform competition shifting from “who can target” to “who can deliver.”
Regulatory and Payer Expectations Tighten
As targeted innovation accelerates, regulators and payers are converging on a single demand: proof of differentiated, durable benefit. The FDA’s Oncology Center of Excellence is piloting “Project FrontRunner” to encourage randomized data earlier in metastatic settings, pushing sponsors to produce higher-quality evidence before approval. In Europe, joint HTA assessments under the new EU HTA Regulation (2025) will apply to oncology first, introducing cross-country evidence alignment pressures. Meanwhile, payers are reining in the one-size pricing model. In the U.S., CMS has begun value-based pricing pilots for oncology biologics under the Inflation Reduction Act framework.
Implication: Companies must connect precision to proof early — designing clinical and economic data packages that withstand both regulatory and reimbursement scrutiny.
AI, Real-World Data and the “Digital Twin” Trial Era
AI is quietly reshaping oncology R&D and evidence generation. Real-world data (RWD) and “digital twin” models are being used to simulate control arms, optimize trial design, and accelerate indication expansion. Others project oncology could see a 20–30% reduction in trial duration when AI-assisted adaptive designs and predictive modeling are applied. FDA guidance on RWD use (finalized 2023) now supports synthetic control approaches for rare and high-unmet-need populations. However, adoption remains uneven — many sponsors lack the data infrastructure or validation frameworks to gain regulator confidence.
Implication: 2026 will mark a split between oncology developers that simply “use AI tools” and those that have integrated AI-native data strategies across development, regulatory, and medical affairs functions.
Horizon: Focus, Evidence, and Sustainable differentiation
Commercial oncology is entering a “proof-before-promotion” era. With more than 25 tumor-agnostic indications now on market, competition has intensified — not only scientifically, but also in how companies communicate differentiated value.
Leaders are focusing on:
Smarter indication sequencing (to show early wins where differentiation is clearest)
Companion diagnostics integration (to ensure real-world uptake matches trial intent)
Cross-functional launch planning (linking regulatory, medical, and market access narratives before Phase 3 completion)
Implication: 2026 will reward companies that tell a credible, data-driven story — one that unites precision, evidence, and economics. The oncology revolution continues, but proof will now be its currency.
