As we advance through 2025, biopharma companies are increasingly using artificial intelligence (AI) and new data tools to improve commercial performance and make research and development (R&D) more efficient. AI is changing the way the industry engages with healthcare professionals (HCPs), allowing for personalised interactions, better content strategies, and useful insights for field teams. In R&D, new methods for handling data and navigating regulations are speeding up clinical trials, shortening approval times, and improving transparency at research sites.
On the commercial side, making the most of AI and data-driven solutions depends on having clean, organised data and investing in systems that are scalable and compliant. Companies focusing on data quality, following regulations, and using AI-driven insights will be better prepared for long-term success. Key improvements include AI powered tools for creating and reviewing content, advanced analytics for smarter business decisions, and streamlined operations through integrated quality and regulatory systems.
In R&D, the spotlight is on speeding up approvals through simultaneous submissions, sharing data more openly with contract research organisations (CROs), and automating safety monitoring. Simultaneous submissions can cut approval times significantly, while better data sharing with CROs leads to faster, more informed decisions. Advanced automation, supported by reliable safety data, will simplify pharmacovigilance and reduce operational challenges.
Prediction 1: A Focus on Clean Data Will Fuel Compliant AI Innovation in the EU
The recent wave of AI innovation has fallen short of transforming commercial life sciences. In 2025, European biopharma’s that unlock harmonised internal and external data will start to reap commercial rewards.
Biopharma organisations will combine off-the-shelf AI engines with more harmonised, clean data. The integration of these AI solutions with well-structured, high-quality datasets will enable organisations to achieve deeper insights, enhance operational efficiency, and drive evidence-based decision-making. Acquiring data from trusted, internally verified sources will lead to greater confidence in AI-generated outcomes. By ensuring data integrity and consistency across different functions, companies can minimise biases and inaccuracies, ultimately boosting stakeholder trust. This will make it easier to scale pilots from single-market, single-brand solutions across the enterprise. As these scaled solutions prove their value, biopharma organisations will be better positioned to optimise their supply chains, improve patient outcomes, and streamline regulatory reporting.
The EU recently introduced the Artificial Intelligence Act — the first comprehensive AI regulation by any regulator, designed to ensure that AI is developed and used safely. This landmark legislation establishes clear guidelines on risk categorisation, transparency, and accountability, compelling companies to align their AI strategies with ethical and legal standards. Along with existing European data privacy rules, European biopharma’s will have clear principles to support future investment and innovation. These combined regulations will foster an environment where AI-driven projects are not only innovative but also aligned with societal expectations and legal mandates. Commercial success will come to those that clean up their data, secure new sources, and interrogate them within this regulatory framework. In the long run, organisations that proactively embrace compliance while leveraging AI will gain a competitive advantage, positioning themselves as industry leaders in ethical AI adoption.
