Artificial intelligence has reached a pivotal milestone by successfully creating drug-like antibodies, signaling a potential transformation in the biopharmaceutical industry. This breakthrough prompts the question: how soon will AI-driven antibody design revolutionize drug development and biopharma practices?

As 2026 approaches, the health care sector prepares for critical discussions on financing clinical AI. Industry stakeholders face important decisions about payment models that will shape the future of AI integration in medical treatment.

Doctors are overwhelmed by the sheer volume of new medical research, making it difficult to stay fully informed. Meanwhile, patients are increasingly turning to AI tools for health insights. It's time for medical professionals to adopt AI as a valuable resource to enhance their practice and deliver better care.

The FDA has granted approval for the oral formulation of Novo Nordisk’s Wegovy, originally an injectable treatment for weight management. This marks the first approval of a GLP-1 receptor agonist in pill form for obesity treatment, potentially broadening patient access to this therapy.

A move to relax regulations on AI tools used in healthcare may result in health systems having to take on greater responsibility for evaluating and ensuring the safety and effectiveness of these technologies.

The FDA's fast-track drug review program has evolved into a tool for the White House to steer which medications reach patients most quickly. This initiative influences the timeline for drug approvals, impacting how swiftly critical treatments become available.

Research clearly links nurse overwork to higher patient mortality rates. In response, nurses are mobilizing to push for better working conditions and improved patient care.

Increasing anti-science and anti-vaccine attitudes have significantly altered how healthcare providers and patients interact, impacting trust and communication in clinical settings.

In this edition of our Health Tech newsletter, we explore how the field of radiology is adapting to the integration of artificial intelligence, especially in interpreting X-rays independently. Additionally, we cover the progress of a new app designed to assist schizophrenia patients as it moves toward FDA approval.

This edition of AI Prognosis highlights a critical gap: although patients are central to health care, their voices are often missing in discussions about AI's role in the field. Exploring how health care systems can better include patients in AI development and implementation is essential for truly patient-centered innovation.