Zimmer Biomet will hire 500 professionals over the next three years for its new Bengaluru technology centre, expanding its AI, software engineering, and R&D capabilities as India strengthens its position as a global healthcare innovation hub.
MTI Viewpoints Insights shared by industry relative to healthcare and the advancement of medical technology. Jaimon Jose, senior director of engineering and compliance at CharmHealth, is a software architect and technical leader with more than 18 years of product development experience in the areas of identity and security technologies, distributed systems, cloud security, and data…
By the time most medtech organizations noticed their teams were using AI in regulatory work, the governance conversation was already running behind.. How can your organization move forward? An Operational AI Capability Maturity Model — a five-domain framework built specifically for regulatory affairs and offers a direct way to assess where your organization actually stands. If your team cannot consistently answer who approved the tool, how the output was verified, and what was retained, this framework is a practical place to start.
The most recent AI thought leadership published on MedTechIntelligence.com.
Why is algorithmic transparency becoming an increasingly important consideration in FDA’s review of AI/ML medical devices?
How has AI impacted the way in which companies recruit for senior specialists, particularly in highly niche roles in MedTech, biotech and pharmaceutical development? Finding the right people for these roles has never been harder.
Boston Children’s Hospital physicians say one of the greatest risks in pediatric ICUs is delayed de-escalation of care, which can expose children to prolonged ventilation, sedation, and vasoactive medications. They argue that AI-driven clinical intelligence can help clinicians identify safer timing for weaning and extubation, supporting recovery and improving long-term outcomes.
The agency launched Elsa 4.0, an upgrade to the agency’s internal AI tool available to all FDA staff, from scientific reviewers to investigators.
Without formal policies and governance, MedTech organizations face risks to intellectual property, product quality, and ultimately patient safety. Thoughtful AI governance enables development teams to capture efficiency gains while maintaining the rigor that the industry demands.
Healthcare environments are dynamic with patient populations, clinical practices and data collection methods continuously evolving. Similarly, effective AI systems depend on more than performance at initial deployment. They must be monitored and managed throughout their lifecycle to remain reliable, clinically relevant, and safe.