RPM Cybersecurity 2026: FDA 524B Mandates & SBOM Compliance

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The RPM Cybersecurity Shift: Navigating New FDA Mandates and Software Supply Chain Transparency in 2026 A Senior Cybersecurity Architect's Field Guide — Because "We Think We're Covered" Is No Longer Good Enough May 2026  |  20-minute read  |  Written for C-Suite, Regulatory Affairs, and QA Leadership 📋 Table of Contents The Confidence Paradox: Why 90% Confidence Masks a 50% Coverage Gap The FDA Mandate Reality: Section 524B Is Not a Suggestion Anymore RPM Cybersecurity 2026: How CMS Expansion Created a New Attack Surface SBOM in 2026: From Compliance PDF to Quality System Backbone Comparison Table: Pre-2026 vs. The 2026 Mandatory Framework ISO 14971 as Connective Tissue: Risk Management Meets the Supply Chain Real-World Scenario: How a Mature SBOM Prevented a Class I Recall FDA Inspection Readiness: What Investigators Will Look For Under CP 7382.850 What You Need to Do Right Now: A 7-Poin...
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Big pharma's pre-competitive collaboration

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Big pharma's pre-competitive collaboration


Handshaking Image showing gesture of collaboration between two firms


Merck, Eli Lilly and Pfizer have provided funding to launch Enlight Biosciences, a for-profit venture that aims to advance breakthrough technologies for drug discovery and development.


The lowdown: There has recently been increasing emphasis from industry on participating in non-profit collaborations to address issues in drug development that are considered to be pre-competitive. 

Now, Merck, Eli Lilly and Pfizer, together with the venture capital firm PureTech Ventures and several leading academic researchers, have founded Enlight Biosciences. 


This is a for-profit venture that will aim to tackle critical unmet industry needs with innovations from academia and start-up companies. Enlight Biosciences, based in Boston, USA, will direct up to US$39 million into technologies that strengthen the connection between preclinical research, clinical research and post-market use, such as techniques that could help predict human responses to experimental therapies.


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