Quality Assurance Protocols

𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐀𝐬𝐬𝐮𝐫𝐚𝐧𝐜𝐞: 𝐌𝐨𝐫𝐞 𝐓𝐡𝐚𝐧 𝐉𝐮𝐬𝐭 𝐀𝐮𝐝𝐢𝐭𝐬 𝐚𝐧𝐝 𝐏𝐚𝐩𝐞𝐫𝐰𝐨𝐫𝐤⁣ ⁣ When people hear the term “Quality Assurance (QA)”, they often picture audits, checklists, and piles of paperwork.⁣ The reality? QA is much bigger than that. It doesn’t just check boxes—it ensures that your organization runs smoothly, efficiently, and with minimal risk.⁣ ⁣ QA touches almost every aspect of your operations:⁣ ⁣ 🔵 Planning before work starts: Anticipating challenges and setting clear objectives.⁣ ⁣ 🔵 Clear documentation and records: Ensuring transparency and traceability.⁣ ⁣ 🔵 Meaningful metrics and analysis: Turning data into actionable insights.⁣ ⁣ 🔵 Risk thinking, not firefighting: Preventing problems before they occur.⁣ ⁣ 🔵 Audits that improve, not just check boxes: Using audits as tools for growth.⁣ ⁣ 🔵 Defect prevention, not defect detection: Focusing on building quality in, not just finding errors.⁣ ⁣ 🔵 Supplier quality and change control: Maintaining high standards across your supply chain.⁣ ⁣ 🔵 Training, competence, and knowledge sharing: Empowering teams with the right skills and understanding.⁣ ⁣ 🔵 Customer feedback and satisfaction: Listening and adapting to what matters most.⁣ 🔵 Continuous process improvement: Always looking for ways to do better.⁣ ⁣ The beauty of QA is that it works quietly in the background, preventing surprises, stabilizing processes, and building confidence in your products, services, and teams.⁣ ⁣ 𝐖𝐡𝐞𝐧 𝐐𝐀 𝐢𝐬 𝐰𝐞𝐚𝐤, 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐬𝐩𝐞𝐧𝐝 𝐭𝐡𝐞𝐢𝐫 𝐭𝐢𝐦𝐞 𝐫𝐞𝐚𝐜𝐭𝐢𝐧𝐠 𝐭𝐨 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐫𝐚𝐭𝐡𝐞𝐫 𝐭𝐡𝐚𝐧 𝐩𝐫𝐨𝐚𝐜𝐭𝐢𝐯𝐞𝐥𝐲 𝐢𝐦𝐩𝐫𝐨𝐯𝐢𝐧𝐠. 𝐒𝐭𝐫𝐨𝐧𝐠 𝐐𝐀, 𝐨𝐧 𝐭𝐡𝐞 𝐨𝐭𝐡𝐞𝐫 𝐡𝐚𝐧𝐝, 𝐜𝐫𝐞𝐚𝐭𝐞𝐬 𝐚𝐧 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐰𝐡𝐞𝐫𝐞 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐢𝐬 𝐛𝐮𝐢𝐥𝐭 𝐢𝐧, 𝐧𝐨𝐭 𝐚𝐝𝐝𝐞𝐝 𝐥𝐚𝐭𝐞𝐫.⁣ 𝐈𝐧 𝐬𝐡𝐨𝐫𝐭, 𝐐𝐀 𝐢𝐬𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐚 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧—𝐢𝐭’𝐬 𝐚 𝐦𝐢𝐧𝐝𝐬𝐞𝐭.

🔍 Quality Assurance in Pharma: More Than Compliance In the pharmaceutical industry, Quality Assurance (QA) is not just a regulatory requirement—it's the backbone of product integrity and patient safety. QA is a proactive, process-oriented system that ensures every stage of drug development and manufacturing meets rigorous quality standards. Unlike Quality Control (QC), which focuses on detecting defects, QA is all about preventing them by embedding quality into every process—from R&D to distribution. Key QA practices include: ✔️ GMP compliance ✔️ Process validation & documentation ✔️ Internal audits & continuous improvement ✔️ Root cause analysis & risk management tools like FMEA The result? ✅ Reliable, safe, and effective medicines ✅ Fewer recalls and regulatory issues ✅ Stronger reputation and patient trust Common QA Tools and Techniques in the Pharmaceutical Industry - PDCA (Plan-Do-Check-Act) Cycle: For continuous process improvement. - Six Sigma: To reduce process variation and enhance product quality. - Root Cause Analysis (RCA): To investigate and resolve deviations and non-conformances. - Ishikawa (Fishbone) Diagram: For identifying potential sources of problems. - Pareto Analysis: For prioritizing issues based on impact. - Failure Mode and Effect Analysis (FMEA): For proactive risk assessment. - Statistical Process Control (SPC): To monitor and control manufacturing processes using statistical methods. In pharma, quality isn’t just checked—it’s built in. #Pharmaceuticals #QualityAssurance #GMP #Compliance #PharmaManufacturing #PatientSafety #ContinuousImprovement #QA #QC

𝗔 𝗰𝗹𝗶𝗲𝗻𝘁 𝗼𝗻𝗰𝗲 𝘁𝗼𝗹𝗱 𝗺𝗲:  "Our CRO is GLP-certified. We have quality covered." Six months later, their IND was on clinical hold 🛑 The issue? A protocol deviation in their pivotal tox study. The CRO's QA documented it perfectly—followed every SOP, filed the report, archived the records. But no one assessed whether the deviation invalidated their NOAEL. FDA asked that exact question. They couldn't answer confidently. 👇 Here's what they were missing: 𝗖𝗥𝗢 𝗤𝗔 𝗲𝗻𝘀𝘂𝗿𝗲𝘀 𝗚𝗟𝗣 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲:  ✔️ Was the deviation documented? Yes. ✔️ Was corrective action taken? Yes. ✔️ Did they follow SOPs? Yes. 𝗦𝗽𝗼𝗻𝘀𝗼𝗿 𝗼𝘃𝗲𝗿𝘀𝗶𝗴𝗵𝘁 𝗲𝗻𝘀𝘂𝗿𝗲𝘀 𝗿𝗲𝗴𝘂𝗹𝗮𝘁𝗼𝗿𝘆 𝗱𝗲𝗳𝗲𝗻𝘀𝗲:  ❌ Does this affect our NOAEL? No one evaluated. ❌ Can we justify our starting dose with this deviation? No one asked. ❌ Will FDA accept this study? No one assessed. CRO QA did their job perfectly. But no one was doing the Sponsor's job. Big Pharma has teams handling Sponsor-side quality. Biotech usually has no one. 𝗙𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗳𝗶𝗹𝗹𝘀 𝘁𝗵𝗮𝘁 𝗴𝗮𝗽:  → Assesses study design before execution → Ensures data supports your IND, not just generates reports → Reviews deviations for regulatory impact (not just GLP compliance) 📌 If you are running a study at a CRO, but don't have an oversight on the Sponsor side - let's talk. 𝗧𝗼𝗱𝗮𝘆. #toxicology #nonclinicaldevelopment #nonclinical #regulatory #ind #drugdevelopment #biotech #GLP

Deep Dive into Quality Control & Quality Assurance in Food Processing Definition: Quality Control (QC): QC is a reactive process that focuses on detecting and correcting defects in food products. It involves inspecting, testing, and monitoring during various stages of food production — from raw materials to the final packaged product. Quality Assurance (QA): QA is a proactive, systematic approach aimed at preventing defects by ensuring that the entire process is well-designed and controlled. It sets the standards and processes that guarantee quality is built into the product from the beginning. --- What I Learned – Key Concepts: Quality Control (QC) Activities: Raw Material Inspection: Ensuring only safe and high-quality ingredients are accepted. Process Control: Monitoring critical parameters like temperature, pH, pressure during production. In-Process & Final Testing: Checking product quality during and after production (microbial, chemical, sensory testing). Regulatory Compliance: Meeting national and international standards (FSSAI, ISO 22000, Codex Alimentarius). Traceability Systems: Tracking ingredients and processes for quick recall if needed. Labeling & Packaging Check: Ensuring accurate information and sealed, tamper-proof packaging. Technology in QC: Use of sensors, automation, and AI for real-time monitoring. Employee Hygiene & Training: Reducing contamination risks through skilled handling. --- Quality Assurance (QA) Strategies: Setting Quality Standards: Defining safety, nutritional, and sensory expectations. HACCP Implementation: Identifying hazards and controlling critical points in the process. Supplier Quality Management: Auditing and monitoring raw material sources. Standard Operating Procedures (SOPs): Written guidelines for every critical task. Corrective and Preventive Action (CAPA): Finding root causes and preventing repetition. Internal Audits: Regular checks for system performance and compliance. QA-QC Coordination: Ensuring both planning (QA) and execution (QC) work together. Documentation & Records: Maintaining logs for transparency and audit trails. Continuous Improvement: Applying TQM, Six Sigma to enhance efficiency and safety. --- Why It Matters: Ensures safe, high-quality food for consumers Helps meet regulatory and global food standards Reduces recall costs and brand damage Supports innovation and efficient production #QualityControl #QualityAssurance #FoodProcessing #Biotechnology #FoodSafety #HACCP #QAQC #ISO22000 #Microbiology #RegulatoryAffairs #LifeSciences #LinkedInLearning #FunctionalFoods #FoodTech

🔥If Your Audit Report Still Looks Like Last Year’s… It’s Already Non-Compliant "The updated Global Internal Audit Standards establish a more structured and defensible framework for final engagement communications." 1️⃣ Final Communications Now Have a Defined Purpose & Accountability Framework (Principle 15) The new guidance positions final communications as the formal assurance output of the engagement. The CAE’s responsibilities are explicitly stated: 🔹Approval of all final communications 🔹Ensuring consistency with the engagement plan 🔹Distribution to the right stakeholders This raises the bar on review protocols, documentation, approval evidence, and overall quality assurance. 2️⃣ Standard 15.1: Mandatory Content — Zero Flexibility Every final communication must include: • Objectives • Scope (boundaries, exclusions, time period) • Conclusions • Recommendations or action plans For assurance engagements, additional requirements apply: • Prioritized findings based on risk • Scope limitations clearly disclosed • A formal conclusion on governance, risk management, and control effectiveness 🔹Many teams will need to update templates and reporting taxonomies to align. 3️⃣ Standard 11.2 Makes “Quality Communications” Enforceable Quality is now auditable, not subjective. Communications must demonstrate: ✔️ Accuracy ✔️ Objectivity ✔️ Clarity ✔️ Conciseness ✔️ Constructive intent ✔️ Completeness ✔️ Timeliness This affects: 🔹Evidence files 🔹Working paper alignment 🔹Reviewer comments 🔹Version control 🔹Impact statements Expect greater scrutiny if conclusions aren’t fully supported. 4️⃣ Alternative Communication Methods Are Now Standard-Supported 💡 The guidance formally validates: • Executive summaries • Structured presentations • Exit-meeting communications • Dashboards • AI-supported reporting formats The requirement remains: they must fully satisfy Standards 15.1 and 11.2. Functions must show that accuracy, completeness, and approval protocols are intact regardless of format. 5️⃣ Root Cause Analysis Is No Longer Optional 🌳 The guide reinforces the complete finding structure: 🔹Condition 🔹Criteria 🔹Cause 🔹Impact The emphasis on root cause demands: 🔹Consistent methodologies (5 Whys, fishbone, error-type classification, etc.) 🔹Clear rationale for selected causes 🔹Direct linkage between root causes and recommendations Weak causal analysis will be a compliance gap under the new standards. 🔍 Technical Bottom Line These updates require meaningful changes in: • Reporting templates • Working paper structures • Review and approval protocols • QAIP procedures • Training programs • Reporting methodology documentation This is a structural shift, not a stylistic one. If methodology doesn’t evolve, reporting will fall short of the new standards. #InternalAudit #IIA #GlobalInternalAuditStandards #AuditReporting #Assurance #Governance #RiskManagement

🔍 1. Quality Assurance (QA) in the Food Industry Definition: Quality Assurance is a proactive, process-oriented approach that ensures food products are produced to meet defined quality standards. It focuses on preventing defects by designing and implementing effective production processes. Main Objective: To build quality into the process so that the final product is consistently safe and meets consumer expectations. ✅ Key Elements of QA: Good Manufacturing Practices (GMP) Hazard Analysis and Critical Control Points (HACCP) Standard Operating Procedures (SOPs) Supplier Quality Assurance Personnel training and hygiene programs Internal audits and continuous improvement 🏭 Example in Food Industry: Dairy Processing Plant QA ensures that raw milk is sourced from approved farms. QA designs pasteurization procedures and checks that every batch follows SOPs. QA ensures personnel handling milk wear clean uniforms, gloves, and hairnets. QA develops a recall procedure in case contamination is detected. 🧪 2. Quality Control (QC) in the Food Industry Definition: Quality Control is a reactive, product-oriented process that involves testing and inspecting the final product (and sometimes raw materials or in-process samples) to ensure it meets predefined quality and safety standards. Main Objective: To detect and correct defects before the product reaches the consumer. 🔍 Key Activities in QC: Sampling and testing of raw materials, in-process samples, and finished goods Sensory evaluation (taste, smell, texture) Microbiological analysis (e.g., for E. coli, Salmonella) Physical and chemical analysis (e.g., pH, moisture, fat content) Packaging inspection (e.g., seal integrity, label accuracy) 🏭 Example in Food Industry: Snack Food Manufacturing (e.g., Potato Chips) QC tests oil quality (e.g., peroxide value) before frying. QC inspects chips for color, size, and crispiness. QC sends finished packs for microbiological testing. QC checks the packaging date, expiry, and batch number on the label. 📊 3. Quality Management System (QMS) in the Food Industry Definition: QMS is a comprehensive framework that integrates QA and QC activities into a systematic approach to manage and improve quality across the entire food production chain. Main Objective: To achieve consistent product quality and customer satisfaction through systematic planning, documentation, execution, and improvement. 🏗️ Key Components of a QMS: Quality Policy & Objectives Organizational Roles and Responsibilities Document Control and Record Keeping Customer Feedback and Complaint Handling Corrective and Preventive Actions (CAPA) Internal and External Audits Continuous Improvement (PDCA cycle) ✅ Popular QMS Standards in Food Industry: ISO 22000 – Food Safety Management System FSSC 22000 – GFSI-recognized food safety certification scheme BRCGS – British Retail Consortium Global Standard for Food Safety SQF (Safe Quality Food)

This paper provides an in-depth analysis of the critical role that quality assurance (QA) and quality control (QC) measures play in the integration and application of AI tools in the medical field, emphasizing acceptance testing (AT) as a foundational step. It highlights the necessity of robust QA/QC frameworks to ensure the safe, effective, and equitable use of AI technologies in healthcare, drawing attention to the challenges and potential pitfalls of implementing AI without adequate oversight. 1️⃣ The integration of AI tools in healthcare requires comprehensive QA protocols to navigate challenges like limited generalizability and transparency, ensuring patient and provider safety. 2️⃣ A collaborative approach among manufacturers, regulators, healthcare systems, and clinicians is crucial to uphold the quality and safety of AI applications in medicine. 4️⃣ QC as part of QA involves technical procedures to identify and resolve issues with AI tools before impacting patient care, emphasizing guidelines for medical professionals. 5️⃣ Transparency from AI tool manufacturers regarding development, performance metrics, and limitations is vital for informed decision-making and safeguarding patient care. 6️⃣ The paper advocates for ongoing QC and the importance of AT to ensure AI tools perform as expected in clinical settings, highlighting the need for detailed guidelines and tolerance limits from manufacturers. 7️⃣ It emphasizes the significance of user training in the effective deployment of AI tools, ensuring users understand the tool's intended use, capabilities, and limitations, thereby facilitating safe and informed clinical decisions. 8️⃣ The paper suggests that the principles of existing quality and safety protocols in medical imaging, such as the Mammography Quality Standards Act (MQSA), could serve as models for developing QA guidelines for AI tools in healthcare. ✍🏻 Usman Mahmood, Amita Shukla-Dave, Heang-Ping Chan, Karen Drukker, Ravi K Samala, Quan Chen, Daniel Vergara, Hayit Greenspan, Nicholas Petrick, Berkman Sahiner, Zhimin Huo, Ronald M Summers, Kenny H Cha, Georgia Tourassi, Thomas M Deserno, Kevin T Grizzard, Janne J Näppi, Hiroyuki Yoshida, Daniele Regge, Richard Mazurchuk, Ph.D.,Kenji Suzuki, Lia Morra, Henkjan Huisman, Samuel G Armato, Lubomir Hadjiiski. Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing, BJR|Artificial Intelligence, Volume 1, Issue 1, January 2024. DOI: 10.1093/bjrai/ubae003 ✅ Join our community of 29k curious minds! Subscribe to our newsletter for your front-row seat to the latest groundbreaking studies. Get started here: https://lnkd.in/eR7qichj.

🚫 Stop Over-Validating Software in Medical Device Quality Systems I continue to see medical device manufacturers struggling with an overly complex approach to software validation. All too often, GAMP® 5—a framework designed primarily for pharmaceutical manufacturing systems—is applied by default. The result? 🔹 Excessive documentation 🔹 Long validation timelines 🔹 High costs with limited added compliance value 👉 Software validation for medical devices should be risk-based. There are established, regulator-recognized tools specifically designed for medical device quality management systems (QMS), including: ISO/TR 80002-2 (software validation for medical devices) and FDA Computer Software Assurance (CSA) guidance. These approaches align with ISO 13485, 21 CFR Part 820, and FDA expectations—while enabling a far more efficient and pragmatic validation strategy. Are these methods as exhaustive as GAMP® 5? No. Are they appropriate, defensible, and compliant for many medical device software applications? Yes. 📊 Recently, I used these approaches to validate: Temperature monitoring system → validation planning completed in 6 hours. Mid-sized ERP system → validation planning completed in 14 hours. The outcome: compliant software validation, reduced effort, and faster deployment—without compromising patient safety or regulatory expectations. If you’re working in Quality Assurance, Regulatory Affairs, CSV, or Digital Transformation and want to modernize your software validation approach, feel free to connect or reach out.

Every trial has protocol deviations. The statistician's role goes way beyond tabulating them in a report. You need to assess which deviations actually affect the integrity of your analysis. Not all deviations matter equally from a statistical perspective. Evaluate impact on analysis populations. Does this deviation mean exclusion from Per Protocol? These decisions directly affect your primary analysis. Assess data quality. Some deviations compromise specific endpoint reliability. If a patient missed three consecutive visits, can you trust their final measurement? Look for patterns. Are deviations clustered at certain sites or more common in one arm? This might indicate systematic problems that bias results. Use major deviations to inform sensitivity analyses. Show what happens to results if you exclude patients with significant violations. This strengthens regulatory arguments. Partner with data management to catch deviations early. Real-time awareness lets you assess impact while the trial runs instead of discovering problems at database lock. Protocol deviations are critical to ensuring valid, defensible analysis. Be sure you take an active role. Happy Quality Assurance, Happy Monday.

The Procedure Qualification Record (PQR) is a critical document in welding that validates the Welding Procedure Specification (WPS) by recording the actual welding parameters and test results used during a qualification test. Its significance lies in ensuring welds meet specific quality, safety, and performance standards required by codes such as ASME, AWS, or API. Below is a concise discussion of its importance: 1. **Verification of Weld Integrity**: The PQR confirms that the welding procedure produces welds with the required mechanical properties (e.g., tensile strength, toughness) and soundness (e.g., free of defects) through tests like tensile testing, bend testing, or non-destructive examination. 2. **Compliance with Standards**: It ensures the WPS complies with industry codes and standards, providing evidence that the welding process is suitable for the intended application, such as pressure vessels, pipelines, or structural components. 3. **Documentation of Variables**: The PQR records essential welding variables (e.g., material, welding process, filler metal, shielding gas, preheat, and post-weld heat treatment) and test conditions, ensuring repeatability and consistency in production. 4. **Quality Assurance**: It serves as a quality control tool, providing a traceable record that can be reviewed by inspectors, auditors, or clients to verify that the welding procedure meets project or regulatory requirements. 5. **Support for WPS Development**: The PQR is the foundation for creating or modifying a WPS, as it documents the successful qualification of the welding parameters, ensuring they are practical and effective for production. In summary, the PQR is essential for validating the WPS, ensuring weld quality, maintaining compliance, and providing a documented basis for reliable and repeatable welding processes. It’s a cornerstone of welding quality assurance and regulatory adherence.