Aindo

☀️ Summer is calling, but our passion for synthetic data never takes a break! 🧠 Before we log off for the season, we've got one last challenge for you: the Aindo Summer Crossword 🧩 Can you solve all 6 clues on synthetic data, clinical research, and healthcare innovation? 👇 Play and test your solutions here: 🔗 https://lnkd.in/ezh-t7Rd DOWN  1️⃣ The sector where safe data sharing saves lives and speeds up research. (10 letters)  2️⃣ What we all need after a year of intense innovation! ☀️ (8 letters) ACROSS  3️⃣ The systematic pursuit of new knowledge that synthetic data can accelerate. (8 letters) 4️⃣ Data generated from real data to preserve useful patterns while protecting privacy. (9 letters)  5️⃣ Aindo's primary mission: making AI safe, compliant, and _______. (7 letters)  6️⃣ The three-letter acronym for evidence complementing randomized clinical trials. (3 letters) Have fun!😎 The entire Aindo team wishes you a wonderful, safe, and rejuvenating summer break. We'll be back in September, refreshed and ready to generate even bigger things! 🚀☀️ #Aindo #SyntheticData #AI #RealWorldEvidence #HealthcareAI #Crossword #SummerBreak

🚀 Can Synthetic Data transform the future of clinical trials? Recruiting patients for control groups in clinical studies is often one of the biggest bottlenecks in medical research, slowing down breakthroughs and increasing costs. That’s where Synthetic Control Arms (SCAs) come in. By leveraging generative AI and high-fidelity synthetic data, SCAs enable researchers to: ⏱️ Accelerate trial timelines and bring therapies to market faster. 🩺 Reduce patient burden, minimizing the need for placebos in severe conditions. 📊 Strengthen comparative evidence while helping protect patient privacy. In our latest blog post, we dive deep into how Synthetic Control Arms work, their key advantages, and how they are reshaping clinical development. 👉 Read the full article here: https://lnkd.in/eFWx47mU #SyntheticData #ClinicalTrials #HealthTech #AIinHealthcare #Biotech #DataPrivacy #Aindo

AI in Health Technology Assessment (HTA): "How should we use it?"💡 The HTA Coordination Group (HTACG) has published its "General principles on the use of Artificial Intelligence in the preparation of dossiers for Joint Clinical Assessments"📄. The message is clear: AI is welcome, but it does not replace scientific responsibility. Among the key principles: 🔷 Human oversight must be maintained throughout the dossier preparation process. 🔷 Health Technology Developers remain fully accountable for the content, methodology, and conclusions. 🔷 Any AI-assisted activities (e.g., literature screening, data extraction, risk of bias assessment, analysis, reporting) should be transparently documented. 🔷 AI-generated outputs should be traceable, with information on the tool, version, developer, intended use, and even prompts available upon request during the assessment process. This is an important milestone 🎯 because it shifts the discussion from whether AI should be used to how AI can be integrated into HTA in a scientifically robust, transparent, and trustworthy way. As AI becomes increasingly embedded in evidence generation and evidence synthesis, governance, documentation, and validation will become just as important as the technology itself. Read the full principles in the document attached below 📃

🚀 Is your Real-World Data truly ready for regulatory scrutiny? The European Medicines Agency (EMA) recently introduced its Data Quality Framework for RWD, shifting the standard from simply having data to proving its "fitness for use." At the same time, initiatives like the European Health Data Space (EHDS) and DARWIN EU are setting a new bar for data governance, traceability, and interoperability. In our latest blog post, we break down: 🔹 The 3 Data Quality Determinants: Foundational, Intrinsic, and Question-Specific. 🔹 Why data quality is no longer a static property, but a measurable, context-driven process. 🔹 How Generative AI and Synthetic Data enable secure data reusability, imputation, and population rebalancing while fully preserving privacy. Whether you are a data holder, CRO, or life sciences leader, understanding these regulatory shifts is essential for future readiness. 💡 Read the full article here: https://lnkd.in/dHSSsKzX #RealWorldData #RWD #LifeSciences #EMA #EHDS #SyntheticData #HealthData #AIinHealthcare #RegulatoryAffairs #Aindo

Artificial Intelligence is transforming healthcare, but its impact depends not only on the quantity and quality of available data, but also on its relevance to the clinical and decision-making questions it must address. This was the core theme of the lecture delivered by Arianna Bertolani, Clinical & RWE Manager at Aindo, as part of the advanced training course at ALTEMS Università Cattolica del Sacro Cuore, dedicated to evaluating AI applications in healthcare. During the session, key topics included: 🔹 The main barriers limiting the availability of adequate evidence for Health Technology Assessment (HTA), and the gaps that can emerge regarding populations, comparators, timelines, contexts, and data accessibility; 🔹 The role of synthetic data in protecting privacy while making health information more accessible and usable; 🔹 How synthetic data acts as an enabler for the development and evaluation of AI solutions; 🔹 The necessary conditions for AI-generated evidence to support an HTA decision: question relevance, data reliability, method validation, and utility within the specific decision-making context. Discussions like these are a valuable opportunity to share knowledge and contribute to training the professionals who will be tasked with evaluating and driving healthcare innovation using a rigorous, informed, and evidence-based approach. A big thank you to ALTEMS, Dr. Rossella Di Bidino (Scientific Coordinator of the course), and all the participants for their engagement and insightful discussion! 💡 Swipe through the images to check out a few key slides from the presentation!

La sanità ha bisogno di dati per innovare. Ma ha anche il dovere di proteggere la privacy dei pazienti. Come conciliare queste due esigenze? In un'intervista pubblicata da Open, Daniele Panfilo, PhD spiega perché i dati sintetici stanno emergendo come una tecnologia chiave per il futuro della ricerca e dell'intelligenza artificiale in sanità. Generati dall'AI a partire da dati reali, i dati sintetici consentono di condividere e utilizzare informazioni di valore per: 🔹 accelerare la ricerca clinica; 🔹 sviluppare e validare modelli di intelligenza artificiale; 🔹 favorire la collaborazione tra ospedali, istituzioni e aziende; 🔹 ridurre le barriere legate alla tutela della privacy. Nell'intervista si parla anche del ruolo dell'Europa nello sviluppo di un ecosistema digitale competitivo e dell'importanza di costruire un'innovazione che metta al centro sicurezza, qualità dei dati e fiducia. 📖 Leggi qui l’intervista completa: https://lnkd.in/eEzTtdJi #Aindo #SyntheticData #Healthcare #ArtificialIntelligence #HealthData #DigitalHealth #Privacy #Innovation #AI

The TEHDAS2 consortium has recently published its D7.2 Guideline for Health Data Access Bodies on data minimisation, pseudonymisation, anonymisation and synthetic data - formally accepted on 24 March 2026, following a public consultation process that ran through the autumn of 2025, and one of ten implementation documents now released ahead of the Final Conference in Brussels on 16 November 2026. It is, in many ways, one of the most consequential documents to emerge from the EHDS implementation process so far. And not only for the technical content. What strikes us most is a shift in emphasis that runs quietly through the entire document. For years, the conversation around health data governance has centred on protection: how to minimise, pseudonymise, anonymise. How to reduce the risk of harm from data that circulates. The implicit assumption has been that the problem is primarily one of containment. The D7.2 guideline moves somewhere different. It acknowledges - with appropriate care - that synthetic data is a recognised tool for enabling responsible secondary use of health data. But the conditions it sets are precise: documented quality assessment of the generation process, evaluation of residual risk, transparency of methodology. In other words, the question is no longer only whether the data is protected. It is whether the data - and the process that produced it - is demonstrably fit for the specific purpose it is asked to serve. 🎯 Fitness for purpose. Auditable process. Documented risk proportionality. These are not abstract principles. They are the operational requirements that Health Data Access Bodies - which Member States must designate by March 2027 - will apply to every data permit application under the EHDS secondary-use framework . For researchers, data holders, pharma companies and technology providers, this is the compliance standard now being operationalised. Eight months away. The trust that EHDS needs to function does not come from any single technology. It comes from the capacity to demonstrate - transparently, repeatably, in a form an HDAB can audit - that the data is adequate to the purpose, the risk assessed and proportionate, the process traceable end to end . This is the direction the European health data ecosystem is moving.⚙️ It is also the standard we have built to.

Last week, after our corporate Town Hall, we headed to Area Science Park for an intensive, hands-on team workshop! 🛸 We split into 3 cross-functional crews named after space missions: Artemis (Real-World Evidence Studies), Orion (Synthetic Control Arms), and Voyager (Health Technology Assessment). Our goal? To brainstorm, collaborate, and align on the core strategic streams that drive Aindo's healthcare focus. To guide our journey, each of the three groups relied on three Dogmas:  1️⃣ Radical Contamination: "Isolated knowledge is sterile" 🧠  2️⃣ Trust & Collaboration: "In space, we save ourselves together" 🤝  3️⃣ Execution Speed: "Space moves fast" ⚡ By bringing together diverse skills from data science, clinical, regulatory, and business teams, we proved that complex challenges are best solved when we work as a single, united force, channeling our unique strengths and synergies toward a common goal. A huge thank you to all Aindoers for stepping up, sharing your brilliant ideas, and collaborating so passionately on this mission! 💜 Ready for the next launch! 🌍🚀 #Aindo #TeamWorkshop #Brainstorming #AI #Healthcare #RealWorldEvidence #SyntheticControlArms #HTA #CrossFunctional #Collaboration

What an incredible day in Trieste it was! 🌊✨ Last week, the Aindo team gathered in Trieste for our corporate town hall: an intense, high-energy day to align, reflect, and reconnect! Since many of us collaborate from different cities, having the entire Aindo team together in person was a wonderful opportunity to share quality time and fresh perspectives. Our agenda was packed with inspiring moments:  🩺 We mapped out our exciting future evolution into healthcare and clinical evidence generation 👋 Officially welcomed our newest Aindoers to the team 💬 Hosted a highly collaborative Q&A session 🧠 And put our brains and competitive streaks to the test during an epic trivia game (let's just say, some major competitive spirits were revealed!). 🎮👾 At the end of the day, we wrapped up the workday and headed over for a beautiful evening under the sunset, celebrating our team spirit with a seaside aperitivo and dinner. 🍹🌅 Moments like these remind us that behind all the hard work and innovation, there’s an extraordinary, united team making it all happen. 💜 Thank you to everyone who made this Townhall so memorable, and to all the Aindoers who bring our mission to life every single day! 🚀 #Aindo #CompanyTownhall #AIHealthcare #Team #Trieste #Vision

🔍 Trust is the foundation of responsible AI in healthcare. Artificial intelligence has the potential to reshape healthcare, but its success depends on more than advanced algorithms. It requires high-quality data, clear governance, and accountability. In his latest article for Agenda Digitale - Nextwork360, Davide Ruffo explores how Europe's regulatory framework – including the European Health Data Space (EHDS) and the AI Act – is laying the groundwork for trustworthy AI in healthcare. 💡 The article also highlights the role of synthetic data in enabling innovation while protecting privacy, helping researchers and healthcare organizations unlock the value of data responsibly. Building trustworthy AI isn't just about technology—it's about creating the conditions for innovation to deliver real impact. 📖 Read the full article: https://lnkd.in/ec-tsbHd #ArtificialIntelligence #Healthcare #DigitalHealth #SyntheticData #AIAct #EHDS #Privacy #Innovation