Technical Content Validation

I'll be covering more of my core areas: healthcare AI, disease detection, clinical tools, medical entrepreneurship, and digital health transformation. Each week, I'll share insights from my journey across medicine, tech, and business. Today's topic? The shaky foundation most health startups build upon. Most healthtech startups never get their validation studies right. After reviewing hundreds over 15+ years, I've spotted consistent mistakes that kill otherwise promising technologies. Here are 5 validation pitfalls I've seen repeatedly: 1/ Testing on the wrong population ↳ Using healthy 25-year-old engineers instead of actual patients ↳ Not accounting for age, comorbidities, or tech literacy ↳ Result: Your "93% accuracy" plummets to 62% in real clinical settings 2/ Confusing correlation with clinical utility ↳ Showing your algorithm correlates with an existing test isn't enough ↳ What matters: Does it change clinical decisions or improve outcomes? ↳ Many startups have impressive p-values but zero clinical impact 3/ Biased comparison groups ↳ Cherry-picking "perfect" cases for your technology ↳ Comparing against outdated standards no one uses anymore ↳ Using different protocols for your tech vs. comparator 4/ Ignoring clinical workflow realities ↳ Testing in controlled lab environments only ↳ Not measuring time burden on staff ↳ Forgetting connection/integration requirements 5/ Publishing one study and stopping ↳ Validation isn't a one-and-done event ↳ Real power comes from continuous collection of data ↳ FDA approval ≠ clinical adoption The technologies that succeed don't just validate once - they build validation into their DNA. —----------------------------- ⁉️ Comment below: What's the most frustrating validation mistake you've seen in healthtech as a builder or user? ♻️ Share to help founders avoid these costly missteps. 👉 Follow me (Reza Hosseini Ghomi, MD, MSE) for more like this.

As cybersecurity professionals, it's critical to stay informed about the latest incident analyses and their mitigations. CrowdStrike recently released an in-depth Root Cause Analysis (RCA) for the Channel File 291 incident, detailing the technical issues and steps taken to resolve them. Incident Overview: On July 19, 2024, a mismatch in input parameters in the CrowdStrike Falcon sensor's new IPC Template Type led to system crashes. The incident affected a small percentage of Windows sensors, causing out-of-bounds memory reads and subsequent system failures. Key Findings: Input Parameter Mismatch: The IPC Template Type expected 21 input fields, but only 20 were provided, which went undetected during initial testing and deployments. Missing Runtime Checks: The Content Interpreter lacked runtime array bounds checks, leading to out-of-bounds reads. Insufficient Testing: Testing did not cover a variety of matching criteria, missing potential faults. Content Validator Logic Error: A logic error allowed problematic Template Instances to be deployed. Mitigations Implemented: Validation at Compile Time: Ensuring input fields are validated during sensor compile time to prevent mismatches. Runtime Bounds Checks: Adding bounds checks to the Content Interpreter to prevent out-of-bounds reads. Expanded Testing: Increasing test coverage to include non-wildcard matching criteria and additional scenarios. Enhanced Content Validation: Updating the Content Validator to add checks for Template Instances. Staged Deployments: Implementing staged rollouts for new Template Instances to identify and mitigate potential issues early. Customer Control: Enhancing customer control over Rapid Response Content updates to manage deployment timing and scope. CrowdStrike's commitment to robust cybersecurity practices is demonstrated by engaging independent third-party reviews of their Falcon sensor code and quality assurance processes. Stay vigilant and proactive in securing your systems! #Cybersecurity #IncidentResponse #RootCauseAnalysis #CrowdStrike #Infosec #TechUpdate

Can your idea actually be built with current technology? Sounds like a simple question. It's not. Here's what technical feasibility really means: ▪️ Material Science: Do the required materials exist and are they accessible? ▪️ Manufacturing Processes: Can current production methods achieve your specifications? ▪️ Tolerances & Precision: Are your design requirements technically achievable? ▪️ Integration Complexity: How many systems need to work together perfectly? ▪️ Cost Reality: Can it be built at a price point that allows for profitable sales? We recently evaluated an idea for a new medical device. Brilliant concept. Huge market need. One problem: the precision required was beyond current manufacturing capabilities at affordable costs. Instead of letting the inventor spend $200,000 discovering this, our $900 Innovation Overview identified the technical barriers upfront. The inventor pivoted to a modified design that was actually buildable. Now in prototype phase. That's the power of technical validation before you build. Your idea might be brilliant. But is it technically feasible? Let's find out. #TechnicalValidation #ProductDevelopment #Engineering

"Hope it works" is not a QA testing strategy. You can end up with code that passes every test, but the platform fails to meet actual user needs. I see this pattern repeatedly in complex implementations. Teams run technical tests, check all the boxes, then wonder why their business processes collapse after go-live. Here's what most miss: 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 ≠ 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 ➡️ Technical testing asks: "Are we building the product right?" ➡️ Business validation asks: "Are we building the right product?" Verification confirms that the software meets all technical specifications, which sets a solid foundation for the validation phase. During validation, the software is tested from the user's perspective. Your order-to-cash process might technically function while completely breaking your sales workflow. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝘀: Manual business validation is time-consuming, so teams skip it. Resource constraints push business process validation to "later" (which becomes never). James Bach warns us: "The testing mindset is a sophisticated and difficult thing to achieve. You can't be in the testing mindset while you are in the building mindset. They fight each other." 𝗪𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀 𝗶𝗻𝘀𝘁𝗲𝗮𝗱: ✅ Embed QA throughout development, not as an afterthought. ✅ Test real-world business scenarios, not just code functions. ✅ Automate both technical verification AND business process validation. ✅ Engage stakeholders actively during QA and user acceptance phases. ✅ Foster a culture where quality is everyone's responsibility. But it's the difference between project success and costly failure. Don't let your next implementation fall into the "hope it works" trap. What's your experience with balancing technical testing and business validation? #QualityAssurance #SoftwareTesting #ProjectManagement #DigitalTransformation #SoftwareDevelopment #TechLeadership #BusinessProcesses #QAStrategy #SystemsImplementation #TechnicalLeadership #EnterpriseSoftware #SoftwareQuality #TestingStrategy #BusinessValidation #ProjectSuccess #TechStrategy #SolutionsArchitecture #Consulting #TechConsulting #QAProcess #Excellence #Delivery #ProjectDelivery #Technology #B2B #B2BCommerce #eCommerce #ERP #Integration #Software #SoftwareDevelopment

What is (CSV) ? CSV is the documented process of verifying that a computer-based system performs its intended function accurately and consistently while meeting regulatory standards, such as FDA's 21 CFR Part 11 or EMA Annex 11. It involves assessing systems used in activities like production, quality assurance, clinical trials, and more. Why is CSV Important? 1. Regulatory Compliance 2. Data Integrity 3. Risk Mitigation 4. Operational Efficiency Examples of Computerized Systems Requiring Validation 1. Laboratory Information Management System (LIMS) Tracks samples and associated data during quality control testing. Validation ensures data traceability and accuracy. 2. Enterprise Resource Planning (ERP) Systems Manages manufacturing, inventory, and supply chain. Validation ensures system-generated reports are reliable and accurate. 3. Electronic Batch Records (EBR) Automates batch manufacturing documentation. Validation guarantees proper tracking of deviations, approvals, and compliance. 4. SCADA Systems (Supervisory Control and Data Acquisition) Monitors and controls pharmaceutical production processes. Validation ensures accurate real-time data capture and alarm handling. 5. Environmental Monitoring Systems Tracks conditions like temperature, humidity, and particle counts in cleanrooms. Validation ensures reliable data critical for product quality. Steps in CSV :- 1. Risk Assessment Identify the system's impact on product quality and compliance. 2. Validation Planning Develop a Validation Master Plan (VMP) outlining scope, timelines, and responsibilities. 3. Testing (IQ, OQ, PQ) IQ: Verifies system installation. OQ: Confirms system operation within specified limits. PQ: Ensures performance under actual conditions. 4. Documentation Maintain thorough records, including protocols, test scripts, and deviation reports. 5. Periodic Review Revalidate systems regularly or after significant changes to ensure continued compliance.

Is your website invisible on Google? Even the best content won’t rank if your site has hidden technical issues. Crawl errors, slow speed, or duplicate content can silently kill your SEO. A full technical SEO audit can pinpoint these problems and give your site the boost it deserves. Here’s what to check: ✅ Crawlability: Make sure Google can access your pages. ✅ Site Structure: A clean hierarchy helps users and bots navigate. ✅ Internal Linking: Guide crawlers to your most important content. ✅ Duplicate Content: Consolidate duplicates to protect rankings. ✅ Site Speed: Faster pages = happier visitors + better SEO. ✅ Mobile-Friendliness: Mobile-first is no longer optional. ✅ Code Errors: Fix HTML/CSS issues that block crawlers. ✅ HTTPS: Secure your site to gain trust and rankings. ✅ Status Codes: Resolve 404s and server errors. ✅ Server Logs: See how bots interact with your site. My Go-To SEO Audit Tools: Google Search Console: https://lnkd.in/gWDhrHr7 Screaming Frog : https://lnkd.in/gWyrGJ8u Semrush Site Audit: https://lnkd.in/gSAxqT87 Ahrefs: https://ahrefs.com/ PageSpeed Insights: https://pagespeed.web.dev/ GTmetrix: https://gtmetrix.com/ Small fixes using the right tools can lead to big results in traffic and rankings. Websites that perform a technical audit with these tools see up to 40% faster indexing and better visibility. 🔥 Don’t wait — start your audit today and give Google a reason to love your site! ---- 📌 If you liked this, my weekly newsletter is your next stop 👇 https://lnkd.in/gnvb_ZE4 ♻️Repost if you found it helpful! ✅ Follow Vismaya Vijayan for more straight-up SEO & marketing insights.

Computer System Validation (CSV) is a process used to ensure that computer systems, especially those used in regulated industries like pharmaceuticals or medical devices, function as intended and consistently produce accurate and reliable results. It involves documenting that software and hardware meet their predefined specifications and that they perform correctly in real-world scenarios. Validation is particularly important in environments where data integrity, compliance with regulations (like FDA or GxP), and product safety are critical. The CSV process typically includes planning, risk assessment, requirement definition, testing (such as Installation Qualification, Operational Qualification, and Performance Qualification), and ongoing system maintenance. Proper validation helps prevent system errors, reduces compliance risks, and ensures data traceability and audit readiness. It also supports overall quality assurance by providing documented evidence that the system performs as expected throughout its lifecycle.

Practice Note SC CR 3 Validation of scientific methods The term 'validation' refers to the process by which a scientific method is tested to demonstrate that it produces repeatable, reproducible and accurate results under conditions consistent with how it will be applied in an actual case. A method is only scientifically valid if it can reliably perform in practice, not just in theory. 📄 Practice Note SC CR 3 in Victoria This Practice Note (introduced in June 2025) anticipates that parties calling expert evidence must make appropriate enquiries to ensure that validity can be established (or that limitations are disclosed) so that a trial judge, if asked, can be informed whether the evidence is scientifically valid or not. 🧩 What this means in practice for criminal practitioners When instructing or challenging expert witnesses, you should now expect a declaration relating to validation in every scientific/technical expert report — or a reasoned explanation if validation is not feasible. If an expert fails to provide adequate detail on validation (or the court is left in the dark about error rates, reproducibility, domain of applicability), that may be a ground for challenging admissibility or weight.

Process performance Qualification (PPQ): "establish documented evidence which provides a high de gree of assurance that a specific process will consistently p roduce a product meeting its predetermined specifications and quality attributes." Validation is the documented act of proving that any procedure, process, equipment, material, activity or system actually leads to the expected result. ISO definition: Validation is the confirmation by examination and the provision of objective evidence that the particular requirements for a specific intended use are fulfilled. Phases of Validation: The activities relating to validation studies may be classified into three phases: Phase 1: Pre-Validation Phase or the Qualification Phase, which covers all activities relating to product research and development, formulation, pilot batch studies, scale-up studies, transfer of technology to commercial scale batches, establishing stability conditions, storage and handling of in-process and finished dosage forms, Equipment Qualification, Installation Qualification, Master Production Documents, Operational Qualification, Process Capability. Phase 2: Process Validation Phase (Process Qualification phase) designed to verify that all established limits of the Critical Process Parameters are valid and that satisfactory products can be produced even under the "worst case" conditions. Phase 3: Validation Maintenance Phase requiring frequent review of all process related documents, including validation audit reports to assure that there have been no changes, deviations, failures, modifications to the production process, and that all SOPs have been followed, including Change Control procedures. The types of validation: 1. Process validation 2. Analytical method validation 3. cleaning validation 4. Computer System Validation (facility validation, Utility validation & software validation

You can write the perfect blog… and still lose to a site with worse content. Why? Because Google couldn’t crawl it. Most websites fail before they even get a chance to rank. It’s not your keywords. It’s not your backlinks. It’s your technical SEO. If your site is slow, missing SSL, packed with broken links or duplicate content—search engines don’t care how good your content is. They can’t access it properly. They won’t trust it. They won’t rank it. In 2025, this isn’t optional. Your content strategy won’t work unless your technical foundation is solid. I’ve just updated my Technical SEO Checklist for 2025—it’s the same one I use during audits. Covers everything from crawlability and indexing to JavaScript, canonical tags, and sitemap errors. Want it? Just drop Checklist in the comments and I’ll send it your way. No fluff. No email capture. Just real fixes that move the needle. Let’s make your content actually work.