Artificial intelligence is speeding up the path from the lab to the patient, but in healthcare it must go hand in hand with data security. A conversation with representatives of Redhead and Mama AI showed how robust infrastructure connects with expert AI know-how. We looked at where AI truly saves time and how it protects sensitive information in the process.
Cloud or on‑premise: data security and sovereignty
On‑premise means that data and computations run in the organization’s data center, which has full control over access as well as the location of information. The cloud, by contrast, offers fast access to compute capacity from large providers across Europe or the world, which can be sensitive when it comes to healthcare and research data. Pharmaceutical companies are especially cautious: they protect intellectual property and do not want even the mere “traces” of searching for target molecules or proteins to reveal their direction. Access is therefore guarded at the levels of authentication and network rules, but no model guarantees complete immunity to industrial espionage – the important thing is sensible risk configuration.
AI in practice: from molecule discovery to clinical trials
AI can significantly shorten the initial phases of research. One of Mama AI’s clients needed to sort approximately 40 million molecules by parameters, which normally took around 200 days; after deploying the system, they managed it in two days. In experiments, AI automatically classifies images from bioassays and highlights those that require human attention, reducing work from hours to minutes. An added benefit is more consistent evaluation, as the algorithm reduces differences between individual assessments.
AI does not replace experts, but removes routine and strengthens their decision‑making with additional context. In clinical trials, different techniques are used, for example for more efficient collection of participant feedback, and when bringing a drug to market, automated processing of extensive documentation helps. The choice of infrastructure is pragmatic: the cloud provides instant performance, but with large datasets the costs of transfers grow; on‑premise, by contrast, benefits from intensive utilization of capacity. The Redhead and Mama AI partnership gives companies the freedom to choose the most suitable model for each phase and to take into account regulatory requirements, whose impact varies depending on the specific use.
