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Ambrose Healthcare fortifies rare disease pipeline on AM-Pharma takeover. Ambrose will now enter the race to debut a new medicine on the HPP market as the only approved therapy edges closer to key patent expiries. Ambrose Healthcare has acquired 100% of Dutch pharma company AM-Pharma's shares, absorbing the company and fortifying its pipeline with a rare bone disease drug that's could be set to take on AstraZeneca's blockbuster therapy, Strensiq (asfotase alfa). At the core of this deal is ilofotase alfa, an investigational, Phase II-ready enzyme replacement therapy (ERT) and anti-inflammatory currently in development for an inherited condition called hypophosphatasia (HPP). This rare disease, which impacts approximately one in 100,000 people globally, is characterised by the softening of patients' bones and teeth due to low activity of alkaline phosphatase (ALP) - an enzyme involved in normal skeletal development. Thus far, ilofotase alfa has shown early promise in Phase Ib clinical trials, with the drug having demonstrated its positive safety profile and dose-dependent effect on key biomarkers of disease in HPP across adult patients. On top of securing access to ilofotase alfa, Ambrose's AM-Pharma takeover will also expand the British company's footprint into new territories, as it will now have an established base in the Netherlands - specifically in the central city of Utrecht. According to Toby Wilson Waterworth, CEO of Ambrose, the takeover will also secure the company access to AM's regulatory quality and scientific infrastructure in Europe, offering what he calls "a strong base" from which it can develop the rest of its pipeline. This includes two other acquisition-derived rare disease drugs - namely Val401, a Phase II palliative care and cachexia-targeting medicine for pancreatic cancer, and renzapride, a mid-stage candidate in development to treat gastrointestinal symptoms of cystic fibrosis. Through this acquisition, AM-Pharma's shareholders receive up to €161m (approx. $180m) in upfront and potential milestone payments tied to ilofotase alfa's commercialisation, as well as royalties on potential future sales of the drug. New drugs inch closer to the HPP market. Ambrose's bet on AM-Pharma is the latest in a string of pharma activity in HPP, as companies look to challenge AstraZeneca-owned Alexion Pharmaceuticals' monopoly on the market stemming from ERT, Strensiq, which will start to lose its market exclusivity in 2027. One of the key current players in this race is AstraZeneca itself, which is eyeing a potential place on the HPP market for efzimfotase alfa, despite the drug missing its primary endpoints in the Phase III HICKORY study (NCT06079281). Meanwhile, BioMarin has also hedged its bets on HPP through a $490m acquisition of rare disease drug developer, Alesta Therapeutics - opting to keep only its HPP drug, ALE1. Currently, Strensiq is a blockbuster seller for AstraZeneca, as the drug pulled in more than $1.6bn in sales during 2025. Looking ahead, GlobalData analysts forecast the therapy's sales will peak at $2.1bn in 2027, before taking a hit due to a loss of market exclusivity until the end of the forecast period in 2032. GlobalData is the parent company of Pharmaceutical Technology. Give your business an edge with its leading industry insights.

Health AI Chronicle - October 20, 2026. Hook of the day. 270 European clinical sites are now standardizing AI performance metrics for cancer detection and cardiovascular risk prediction - yet 69% of cancer patients using AI chatbots never tell their doctors about it. Executive summary. October 2026 marks Europe's transition from AI pilot networks to operational infrastructure: 270+ clinical sites across 29 EU nations are integrating standardized AI validation protocols, while €80M in EU Chips funding accelerates supercomputing capacity for health-data AI factories. Simultaneously, patient behavior reveals a critical disconnect - those using AI-enabled digital health tools often hide this from clinicians, despite reporting high trust in physician judgment and preference for physician-recommended AI use. Summary section A: practical AI in healthcare. Summary: European healthcare infrastructure is shifting from isolated pilots to continent-wide, standardized AI validation networks. The EU Screening Network's 270+ sites represent the largest coordinated effort to test cancer detection and cardiovascular risk algorithms in real clinical environments, with a November 2026 implementation summit signaling imminent operational deployment. EU Screening Network launches 270+ site Network with November implementation summit. The EU Screening Network has assembled 270+ clinical sites across 29 EU Member States to standardize performance metrics and validation protocols for AI triage, oncological imaging, and cardiovascular risk prediction systems. This federated approach enables real-world testing while maintaining data sovereignty - raw clinical data stays within national borders using federated EHDS registries. A November 2026 implementation summit will establish operational protocols, creating the continent's first standardized pathway for AI clinical validation at scale. This infrastructure directly addresses the "deployment-to-validation gap" that has slowed European AI adoption compared to other regions. AstraZeneca-insitro partnership launches virtual Human platform - $1.46B milestone deal. AstraZeneca and insitro announced a landmark partnership deploying "Virtual Human" machine learning platforms to identify rare disease sub-phenotypes for metabolic dysfunction-associated fatty liver disease (MASH) and cardiomyopathy. The $40M upfront commitment with up to $1.46B in development milestones represents AI's shift toward precision phenotyping at scale. Virtual Human models integrate patient genomics, clinical data, and real-world outcomes to predict treatment responses before trial enrollment - dramatically accelerating target validation and reducing drug development timelines. This model exemplifies how AI tackles one of healthcare's largest administrative and financial burdens: unnecessary clinical trial failures and extended development cycles. Can AI help healthcare move from treatment to prevention? Governance gaps emerge as adoption surges. European healthcare leaders are asking a critical question: How can AI shift medicine from reactive treatment to proactive prevention? The challenge isn't technological - it's systemic. Healthcare incentive structures reward treatment volume over prevention success, and most European nations (only 1 in 12) have implemented AI governance strategies despite widespread adoption. Healthcare informaticist Ricardo Baptista Leite warns that "retrofitting AI into an inefficient system makes you very efficient at being inefficient." The path forward requires three interventions: (1) regulatory frameworks that maintain oversight post-deployment, not just at launch; (2) incentive restructuring to reward prevention outcomes; and (3) governance bodies with authority to audit active AI systems in clinical use. Without these, scaling AI to population health will amplify existing system inefficiencies rather than transform them. Summary section B: reducing administrative burden. Summary: Administrative infrastructure is accelerating across Europe through federated data registries and €80M in EU Chips funding. These complementary initiatives move healthcare IT from organizational silos to continent-wide, coordinated research ecosystems while maintaining data privacy and national sovereignty. EHDS federated registries and €80M EU Chips funding establish data infrastructure across 29 nations. The European Health Data Space is operationalizing through federated registries that enable data sharing without raw data crossing borders - a breakthrough for privacy-preserving research at continental scale. Simultaneously, €80M in EU Chips Act funding supports construction of AI supercomputing facilities and "health-data AI factories" positioned regionally across Europe. These complementary initiatives address a core administrative burden: duplicative infrastructure and incompatible data systems that force researchers to negotiate bilateral agreements for each cross-border collaboration. The federated approach also reduces compliance overhead - organizations apply standardized HealthDCAT-AP metadata standards once, then participate in multiple research networks without re-certifying for each one. This infrastructure-as-commons model shifts healthcare IT from organizational silos to continent-wide, coordinated research ecosystems. Ireland's EU Presidency advances EHDS implementation through "Data in Motion" Conference. During Ireland's EU Presidency, the "Data in Motion" EHDS conference convened European health leaders (October 13-14, 2026) to accelerate implementation of cross-border health data infrastructure. Central discussions focused on establishing Health Data Access Bodies and Digital Health Authorities - the operational governance structures that will enforce EHDS regulations in practice. Health Minister Jennifer Carroll MacNeill emphasized the goal of delivering health information "when and where it is needed" while maintaining privacy and trust. Sessions covered data quality standards, interoperability protocols, and real-world impact on clinicians, researchers, and patients. This phase - moving from regulatory text to operational governance - directly reduces administrative friction for healthcare organizations by establishing clear, consistent standards across all EU Member States rather than requiring organization-by-organization compliance negotiations. Summary section C: how patients use AI (#patientsuseai). Summary: Patient behavior reveals a critical paradox: those using AI-enabled digital health tools often hide this from clinicians, despite reporting high trust in physicians. Understanding this disconnect is essential for healthcare organizations aiming to safely integrate AI into patient care pathways. Cancer patients silently use AI chatbots, don't disclose to doctors - yet trust physicians' judgment. A Supportive Care in Cancer journal study of 400 cancer patients and caregivers at a Turkish tertiary oncology center revealed a striking paradox: 75% of patients knew about AI-enabled health tools, but only 24% used them - and 69% of those users never told their physicians. The secrecy wasn't driven by distrust of physicians (no patient reported decreased trust from using AI) but by fear of judgment. However, the same cohort showed strong conditional acceptance: 73% would openly use AI if their physician verified and recommended it. The study identified key predictors of AI adoption: university-level education (4.47x odds), age under 55 (2.64x odds), and recent diagnosis (2.16x odds). The clinical implication is clear: oncologists and healthcare providers who non-judgmentally inquire about AI use can identify misinformation, correct knowledge gaps, and guide patients toward reliable tools rather than allowing silent, unvalidated AI use to persist. European Open Science Cloud launches 13 regional nodes with standardized AI training pipelines. The European Open Science Cloud has activated 13 regional nodes across Europe, each equipped with standardized AI training pipelines for health data research. This infrastructure enables patients and research participants to understand how their health data is being used in AI model development - increasing transparency and supporting informed consent. The standardized pipelines also reduce barriers for patient-led research initiatives and citizen science projects that use AI for personal health tracking or community health advocacy. By decentralizing AI infrastructure to regional hubs rather than centralizing in single institutions, the EOSC approach distributes both technical capacity and governance responsibility - empowering healthcare organizations and patient communities to participate in AI development, not just consume it as end-users. So what for you? If you lead patient education, clinical workflows, or healthcare administration: How would you differently guide patients toward trusted AI tools if you knew 69% of them are already quietly using digital health AI without telling you? Daily Health AI Chronicle - Edition 13 October 20, 2026 Curated AI healthcare news focused on Europe, patient perspectives, and reducing administrative burden Book Lucien for your next event. 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Sferical One: Ericsson and partners make AI supercomputing a reality in Sweden. Oct 16, 2026 * Ericsson is among several major Swedish companies who have started to utilise a new sovereign AI supercomputer in Sweden, called Sferical One, officially launched today by the Sferical AI initiative. As a founding member of Sferical AI - alongside AstraZeneca, Saab, SEB and Wallenberg Investments, with SKF as a strategic partner - Ericsson gains access to secure, sovereign Swedish computing capacity to develop, deliver, and deploy advanced AI solutions alongside the partner companies. The initiative aims to deliver direct societal benefits to Sweden as AI use case momentum gathers pace. Shared use of investment, capacity and expertise under the Sferical AI initiative means the partners can scale AI development faster. Ericsson will contribute telecom expertise, drive AI use cases, and jointly develop a secure, sovereign AI platform, while simultaneously using the platform to further develop Ericsson's own network and automation capabilities. The system is an NVIDIA DGX SuperPOD built on NVIDIA DGX GB300 systems. The system has been running since late summer 2026. Sferical AI will also build services based on NVIDIA Nemotron open multimodal AI models. Today's event was attended by senior executives from Sferical AI, the Swedish partner companies, including Ericsson President and CEO, Per Narvinger, and Nvidia founder and CEO, Jensen Huang. Ericsson CTO, Erik Ekudden, who led Ericsson's co-development of Sferical from inception, says: "I envision the future as a 6G/AI intelligent fabric - a universal framework which enables different AI systems to work together securely and with reliable performance, no matter where they are or who built them. Ensuring a robust and secure infrastructure requires best in class AI models. To build those, we need the best compute infrastructure. Through our cooperation with Sferical we get access to sovereign infrastructure for model training and refinement." Addressing the partner companies at the Sferical One launch, Jensen Huang predicted an exciting future. "You have done the hardest part... you have started," he said. Ericsson's Sferical One engagement to date relates to ensuring secure and reliable networks through AI-based network operations. Jenny Nordlöw, CEO, Sferical AI, says: "Sferical One enables the companies to train and run AI models at a larger scale on a sovereign platform. What makes Sferical unique isn't just the technology, but that several of Sweden's largest companies share the same infrastructure, develop solutions together and share knowledge across industries." Marcus Wallenberg, Chair of Wallenberg Investments, says: "AI will be a critical component of Swedish industry's future competitiveness. Sferical One will help some of Sweden's leading companies stay at the forefront of that development. It is a long-term investment in the capabilities and expertise we will need to compete in the future."