Evaluate: Biopharma recovers cautiously with steady FDA, AI use

Biopharma is starting to recover, but companies are cautious and choose only the safest deals, especially in obesity and metabolic drugs. The FDA is more predictable now, making it easier for companies to plan new drug launches. Artificial intelligence is being used more for real work, like picking clinical trial sites and spotting early trends. New treatments for rare and heart diseases are expected soon, and companies are focusing on science that can be used in many ways, not just one-off products. To make AI work well, companies need strong rules and systems to guide its use.

An in-depth Evaluate analysis reveals the biopharma sector recovers cautiously, guided by a steady FDA and the practical use of AI, signaling a new phase of strategic growth. Speaking to investors, analysts detailed a market in qualified recovery, surprisingly predictable regulators, and artificial intelligence graduating from hype to operations. A replay of the webinar is available for those tracking deal flow and upcoming launches.

The analysis synthesizes pipeline data, FDA calendars, and AI deployment case studies to map the next 12 months of biopharma competition and capital allocation.

Three Things we Learned in our 2026 Preview Webinar

Analysis of market data reveals a qualified sector recovery favoring proven assets, increased regulatory predictability from the FDA that simplifies drug launches, and the graduation of artificial intelligence from a concept to an operational tool for forecasting and clinical trial optimization.

Recovery, but with guardrails. Late-2025 M&A activity reached $36 billion, and the first quarter since 2023 saw an average deal size over $1 billion, signaling cautious optimism. Buyers are prioritizing assets with proven biology, particularly GLP-1 programs that challenge Novo Nordisk and Eli Lilly. Obesity and metabolic assets are expected to command premium multiples through 2026.
A steadier FDA. Regulatory continuity is growing. The Commissioner's National Priority Voucher has cut the review window for drugs like orforglipron to two months GoodRx, while the agency's flexible chemistry controls for cell and gene therapies simplify late-stage validation FDA. Fewer political shocks allow companies to model approval dates with more certainty, a key advantage for finance teams managing patent expiries worth $300 billion.
AI graduates to operations. Evaluate's commercial forecasting group showed how machine-learning baselines and centralized governance are already live in top-20 pharma. Key use cases include trial-site selection and early signal detection in real-world data. According to Pharma Forecasting Trends 2026, 83% of life-science leaders plan to increase AI budgets this year, with the market's CAGR expected to exceed 27% through 2035 towardshealthcare.

Pipeline events to watch

Zycubo, the first Menkes disease therapy, is setting the tone for novel approvals in 2026.
Wegovy's HFpEF label expansion could reshape cardiometabolic treatment.
Baxdrostat's priority review for resistant hypertension is nearing a Q2 decision.

Why selective dealmaking dominates

Platform technologies like bispecific T-cell engagers and circular RNA are attracting significant interest. These platforms provide modular innovation that integrates into existing portfolios, lowering the cost of entry compared to single-asset acquisitions. Analysts noted that every major 2025 partnership was linked to a platform, reinforcing the thesis that buyers prefer scalable science over one-off bets.

AI adoption checklist

Companies benchmarking their digital maturity were advised to implement four pillars:

Centralized baselines
Governance protocols
Audit trails
Transparent override rules

Organizations that embed these controls achieve faster scenario planning and reduced forecast bias. The speakers warned that skipping governance leads to flawed decisions driven by black-box AI outputs.