John Edson

Designing medical devices is about both well-engineered tech and people. A “perfect” device on paper can still miss the mark if it doesn’t fit the real-world context of its users. Clinical workflows vary. So do cultural norms, training levels, and infrastructure. To build truly effective devices, we need more than technical know-how; we need empathy. That means shadowing clinicians, listening to local experts, and immersing ourselves in the environments where care happens. #MedicalDevices #HealthTech #ProductDesign

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With no affiliation, sharing this as I know it will be good. Peter Merholz's ideas have been instrumental in my shaping of design teams. As iF Design point out here - the right environment around the design team is key to producing a successful team. The role of the leader is to create that environment.

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AI is impacting how we think about sustainable products and packaging. Tools like MechStyle show what’s possible when generative AI is paired with real-world physics: designs that are customized, material-efficient, and structurally sound. Instead of overbuilding “just in case,” AI can identify weak points, reduce waste, and design only what’s needed. That’s a quiet but powerful sustainability win.

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70% of 510(k) submissions receive a deficiency letter on the first review cycle. For Human Factors submissions specifically, that number climbs to 90%. If you're leading a MedTech product through FDA clearance, those aren't the exception. That's the landscape you're operating in. The instinct when a deficiency letter lands is to start fixing things immediately. In our experience, that's exactly what you should not do. Jumping into remediation before you understand the root cause means you’ll fix the wrong things and face a second deficiency letter. Fix the right things in the wrong order, and you'll waste months. Either way, you're back to square one. In our latest article, we lay out the five root causes behind the vast majority of Human Factors deficiencies — from poorly structured URRAs to cross-document inconsistencies that undermine an otherwise credible evidence package — and a structured Phase Zero diagnostic framework for understanding precisely where your submission failed before you spend a dollar on remediation. Whether you're staring at a deficiency notice right now or building the submission that you hope will never get one, this is the diagnostic framework worth adding to your toolbox. Read the full article here: https://hubs.ly/Q046FQXR0 If your team is navigating a 510(k) deficiency and needs expert eyes on the evidence package, reach out directly. We're here to help you get to clearance — efficiently, and the first time. #MedTech #FDA #510k #HumanFactors #RegulatoryAffairs #MedicalDevices #UsabilityEngineering #FDAClearance #ProductDevelopment #HealthcareInnovation #THRIVE

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Sharing the state of the art of #LLMs capabilities for #Design and #Manufacturing. If you are wondering what can currently be done in design with LLMs, keep reading. In a near future, LLMs can potentially become the interface through wich to control and direct computational solutions for design. They will act as a design teammate, transforming designers intent into into structured design representations such as CAD models, scripts (e.g., OpenJSCAD), or vector formats (e.g., SVG). Capable of reasoning across the entire design-manufacturing pipeline—from ideation to optimization—enhancing both creativity and technical feasibility through natural language interfaces, domain integration, and iterative collaboration. Allready, GPT4.0 is starting to contribute in: 1. Design generation – generating initial concepts from descriptions. 2. Design space construction – creating variations and parametric families of designs. 3. Design for manufacturing (DFM) – adapting designs to fit manufacturing constraints and processes. 4. Performance evaluation – assisting in the setup or scripting of performance analyses (e.g., load capacity, sustainability). 5. Design optimization – performing iterative design improvements based on goals and constraints. 6. Enable faster design iterations through conversational refinement. 7. Support interactive debugging and modular design changes. 8. Provide prompt engineering support for guiding design evolution or corrections. 9. LLMs bring a broad knowledge base in design and manufacturing principles. 10. Capable of contextual reasoning, such as suggesting relevant hardware or materials, and adapting designs based on performance or aesthetic requirements. 11. Can generate code for or interface with external DSLs and libraries for integration with external tools: OpenJSCAD / OpenSCAD (CSG modeling) URDF (robot morphology) SVG / DXF (vector design) STEP-NC (CAM programming) FeatureScript (OnShape CAD scripting) Makatura, L., Foshey, M., Wang, B., Hähnlein, F., Ma, P., Deng, B., Tjandrasuwita, M., Spielberg, A., Owens, C., Chen, P. Y., Zhao, A., Zhu, A., Norton, W., Gu, E., Jacob, J., Li, Y., Schulz, A., & Matusik, W. (2024). How Can Large Language Models Help Humans in Design and Manufacturing? Part 1: Elements of the LLM-Enabled Computational Design and Manufacturing Pipeline. Harvard Data Science Review, Special Issue 5. https://lnkd.in/dq79iCMi https://lnkd.in/d5Tk3w-y

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Ready to elevate your product innovation game in 2025? 🚀 . 3D reverse engineering isn’t just about copying old parts anymore—it’s a power move for precision, speed, and nonstop innovation. Thanks to ultra-accurate 3D scanners capturing every detail, paired with advanced design tools, companies today are slashing development time and costs while creating designs that truly impress. From aerospace to automotive, laser scanning and 3D metrology are the secret weapons for top-tier quality control and rapid design iteration. Digitizing your products in 3D isn’t optional anymore—it’s the solid foundation for AI-driven optimization and next-gen manufacturing. With 15 years sharpening our skills and mastering high-end surface modeling, PSH Design is here to help you stay ahead of the curve. Curious to see how? Check this out: https://lnkd.in/gW7_VUGB

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Most deep tech brands lead with complexity. Quantum breakthroughs. AI models. Patents and roadmaps. But luxury brands learned long ago that the story of craft matters more than the craft itself. Taste isn’t about elitism—it’s about restraint. It’s knowing what not to show, what not to say, and when to let silence do the work. As deep technologies like AI and quantum computing move from the lab to the world, the companies that lead will be the ones who communicate with elegance, not excess. Because when everything is powerful, taste becomes the real differentiator.

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Discover why industrial design for startups is essential. Learn 6 reasons it drives growth, attracts investors, and builds customer loyalty.

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