Since 1950, the cost of developing a new drug has doubled every nine years — Eroom's Law. Today, bringing a molecule to market takes 10–15 years and over $2 billion. AI promises to close the loop: analyze clinical, genomic and lab data faster, predict effective compounds. But the raw material — data — sits fragmented inside corporate silos and under divergent regulations. Those who own and process it win. And right now, that's the US and China.
An in-depth report by MIT Technology Review shows that the “data loop” is the key: more data → better models → faster trials → more data. A virtuous cycle that requires infrastructure, investment and agile regulation to sustain.
Why it matters — for Europe and Italy
Europe has world-class basic research: Italy's Menarini, Germany's BioNTech, France's Sanofi. But when it comes to AI-driven drug discovery, the landscape shifts. Health data across EU members is regulated by GDPR, yet each member state interprets it differently. Aggregating datasets for large-scale model training is a regulatory obstacle course. Meanwhile, the US pushes the NIH All of Us initiative, and China runs a national precision medicine program with centralized data.
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For an Italian pharma company or a biotech SME, the choice is stark: either partner with a US big tech (paying in data and royalties) or build proprietary infrastructure at prohibitive cost. The result? Europe risks becoming a customer of others' discoveries, losing strategic control over therapies and pricing.
Our stance
Noi, di Meteora Web, see this every day in the projects we follow: the digital divide isn't just about websites or e-commerce — it's about the ability to use data for innovation. Supporting open-source and controlled data sharing isn't ideology: it's economic pragmatism. Europe must invest in sovereign AI platforms for drug discovery — anonymized datasets, transparent models, equitable access. If it doesn't, the gap won't close on its own. Data security matters, but paralysis is far more dangerous.
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What to do — concrete actions
For those in Italian pharma biotech: join European consortia like the European Health Data Space. Push for common interoperability standards. Invest in open-source AI models (e.g. MolPAL, DeepChem) to avoid vendor lock-in with American firms. And ask your government for tax incentives for shared research. The era of silos is over: those who don't share data today will have no drug discovery tomorrow.
