AI in Pharmacovigilance: Why Governance Will Define Success
As adoption accelerates, organizations must ensure that the use of AI strengthens and not weakens accountability and patient safety.
Better Models Won’t Fix Pharma’s AI Problem — Better Terminology Will
The bottleneck in AI-enabled real-world data analysis is not computation, model architecture, or training data volume. It is the semantic layer over which the AI is trying to reason – the place where precise clinical meaning lives.
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Inside an Automated Healthcare Practice: Redesigning Care Around People, Not Paperwork
By reducing administrative burden and redesigning workflows around human needs, it creates space for what matters most: connection between clinicians and patients.
AI in Drug Development is Not a Data Problem — It’s An Evidence Problem
Drug development isn't limited by the amount of data we collect, but by our ability to preserve the context, meaning and relationships that transform data into evidence.
Hope Is Not a Soft Concept, It’s a Strategic Imperative in Cancer Innovation
Hope is a catalyst for scientific ambition. It encourages researchers, clinicians, investors, and innovators to pursue solutions where none currently exist. In oncology, many major breakthroughs begin with the belief that a better answer is possible.
Four Ways Health Systems Should Plan for the Next Wave of Breakthrough Therapies
Groundbreaking new therapies have exciting potential to treat and cure diseases while minimizing burden on patients; however, they create major clinical, operational and financial implications that must be planned for years in advance.
Why Pharma Companies Should Look To Social Media For Better Patient Insight
Healthcare decision-makers, especially at pharmaceutical companies, must prioritize patient input. Data collected from social media listening is a significant step in the right direction.
Where Will AI Deployment Benefit Payers the Most?
We are taking a look at how health insurers are using AI, defining success, and managing cybersecurity risks. Give us your opinions by completing our brief, anonymous survey.
The Measurement Problem Behind Two Decades of Neurology Trial Failures
The FDA now treats continuous, real-time data sharing as a regulatory direction of travel rather than a theoretical future. The neurology field should pay close attention.
Healthcare Must Protect Innovation, Not Just Patient Data
Healthcare cybersecurity is no longer just about protecting electronic health records. It is increasingly about protecting the research, algorithms, clinical data, and intellectual property that drive the next generation of medicine.
When Evidence Gap Becomes a Commercial Liability
The MENA evidence gap for selected portfolios is becoming a commercial liability for drugmakers that could have been prevented at the design stage.
Hantavirus Is the Warning Signal America Should Not Ignore
Are we genuinely building long-term preparedness infrastructure, or are we repeatedly improvising our way from one outbreak cycle to the next?
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Closing the Quality-Affordability Gap in Workplace Mental Health
In an interview, Kyan Health Co-Founder and Chief Commercial Officer Konstantin Struck discussed how Kyan gives mid-market and enterprise employers access to premium workforce mental healthcare, at a price point that is affordable.
The AI Drug Discovery Race Is Heating Up, Not In the Way You Think
We should ask a more nuanced question than "does AI work in drug discovery." Rather, we should ask which approaches are about to be proven, and which are about to be exposed, because the field is several bets, and they are not equally sound.
Real-Time Trials Are Here — Now We Need Real-Time Trust
For years the healthcare system has relied on the slow machinery of research — and that system is failing the people it was built for. It was designed for a world that operated with an abundance of caution and lacked the modern tools of today. That world no longer exists.
From Trial-and-Error to Targeted Success: How Computational Disease Models Can Help Patients and Pharma Companies
The in-depth, constantly-changing birds-eye view of disease that computational models provide is an essential next step in linking our ever-expanding clinical knowledge and data with drug development.
Passive Immunization: The Expanding Role of Monoclonal Antibodies in Preventive Medicine
For governments and health systems, monoclonal antibodies represent not just another drug class, but a strategic shift toward precision prevention.
AI Can Accelerate Discovery — Development Still Decides What Advances
AI will continue changing how small molecules are discovered, but the candidates that generate the most interest in silico still have to succeed under real development conditions.