From the AboutPharma 2026 Generative AI for Life Sciences event: how digital patients and AI avatars are redefining market access, marketing and patient engagement
Generative AI in Life Sciences is one of the key reference events for pharma management in Italy, organised by AboutPharma. The 2026 edition, held on 26 March at the Enterprise Hotel in Milan, brought together professionals from pharmaceutical companies, consultants, regulatory experts and technology providers to take stock of where GenAI is truly changing the industry’s core processes.
Media Engineering was present both as a sponsor and as a speaker. Antonio Franzese, CEO of Media Engineering, took to the stage alongside Giulio Lorenzo Pacilio, Product Manager Primary Health Care, Vascular at Alfasigma Italia, for the speech “Patient & Treatment Digital Twin: accelerating and improving decision-making in the age of Generative AI”. Two complementary perspectives , strategic use cases and real-world proof — painted a clear picture of where the sector can go. Antonio then took part in the closing roundtable on ROI, lessons learned and the scalability of GenAI in Life Sciences
A territory still largely unexplored
In the life sciences sector, patient digital twins have already demonstrated their value in areas such as medical rep training and medical visit simulation. But the maturity now reached by these technologies opens up far broader scenarios today: market access, marketing, go-to-market strategy, and clinical decision support for HCPs.
Antonio built his speech around this opening: Digital Twins are now ready to become a cross-cutting information layer for the entire pharma organisation. The technology is mature. The real discontinuity lies in the strategic choice of how and where to deploy it
AI-integrated avatars are mature technologies. The true innovation lies in the strategic choice of how to use them. The pharma sector still has a great deal of unexplored territory ahead of it.
Antonio Franzese, CEO — Media Engineering
The Use Cases of Digital Patients
In each of the following areas, the common thread is the same: the digital patient is not valuable as a technological object in and of itself. It becomes valuable when it turns into the information layer on which those working in clinical and commercial settings make faster and more accurate decisions.
🩺 Market Access
An avatar that articulates the patient’s perspective, sensations, emotions, therapeutic experience, as input for those who build dossiers and argue the value of a therapy before HTA bodies
Marketing and go-to-market
The digital patient as an interlocutor for testing messages and positioning before bringing them to market, compressing insight cycles from weeks to hours.
Role play with expert physicians
Avatars that simulate specialists or KOLs to prepare commercial and medical affairs teams for high-scientific-content conversations, featuring realistic objections and a register calibrated to the specific specialty.
Training and onboarding
The most established use case: visit simulations, personalised scenarios and contextual feedback for medical reps and MSLs. With GenAI, no longer fixed scripts but adaptive scenarios.
If Antonio mapped out the boundaries of what is possible, Giulio Pacilio from Alfasigma Italia brought to the stage the tangibility of an already operational project.
USE CASE
Digital Patient for HCP engagement and ISF/MSL training
Alfasigma Italia, in collaboration with Media Engineering, developed a digital patient aimed at physicians and scientific representatives, designed to support interaction between the commercial force and the clinical world.
Not a generic chatbot: an avatar built around a defined therapeutic profile, integrated into the daily workflow of physicians and reps. Its strength lies in its specificity — it responds to the concrete needs of those who must communicate complex therapies to demanding interlocutors, with a level of conversational fidelity that only generative AI makes possible today.
These are not future scenarios. The project addresses real challenges: simulating complex conversations, preparing for specific objections, and training the ability to communicate value in high-scientific-demand contexts.
Does the Digital Patient deliver measurable ROI?
It is the question pharma Marketing Directors ask most often. The answer is clear: a Digital Twin of the patient is worthless if it remains a technological object in and of itself. It is worth a great deal when it becomes the information layer on which the HCP makes faster and more accurate decisions.
That is where ROI is measured: in reduced decision time, in the quality of engagement, in the reduction of follow-up cycles.
Antonio Franzese, CEO — Media Engineering
The value of the technology itself is not what gets measured, but the impact it produces on the physician’s decision-making behaviour. A shift in perspective that moves the digital patient from experimental innovation to tools with concrete clinical and commercial impact.
What changes with Generative AI
Avatars existed before the generative era. The breakthrough introduced by Large Language Models is deep conversational capability: a digital patient that does not respond to predefined scripts, but reasons, contextualises and reacts coherently even to unexpected questions. A generative avatar can simulate a relationship, complete with the emotional nuances and real concerns that make a patient a patient, not an abstract clinical case. It is this qualitative difference that structurally opens the doors to market access, marketing and patient engagement.
The compliance question
EU AI Act & Law 132/2025
Italian Law 132/2025 requires that any AI system interacting with users in professional contexts explicitly declare that it is an artificial intelligence. For a digital patient in the pharma space, this is not a detail — it is a legal requirement with concrete implications.
The EU AI Act classifies AI systems in the healthcare domain as “high risk”: they require transparency, traceability and documented human oversight. Compliance is not added afterwards — it is designed from the start.
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