Regis Technologies’ Post

The United States Pharmacopeia (USP) is preparing to introduce a new general chapter (> 1,000) dedicated to Process Analytical Technology (PAT). This chapter will encapsulate the definition, core attributes, key enablers, and practically applied and modern uses of PAT, with a focus on its timeliness, sampling relevance, regulatory implications, analytical measurement integration, and the production of process- and product-relevant attributes, including Critical Process Parameters (CPPs) and Critical Quality Attributes (CQA). https://lnkd.in/d4wsv3CK

𝐈𝐂𝐇 𝐐𝟐 (𝐑𝟐) 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐚𝐥 𝐩𝐫𝐨𝐜𝐞𝐝𝐮𝐫𝐞𝐬 - 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐟𝐢𝐜 𝐠𝐮𝐢𝐝𝐞𝐥𝐢𝐧𝐞 💡 Everything you need to know about the new update of the ICH Q2 (R2) Guideline for validation of analytical processes in this comprehensive article we have prepared. A complete comparison with the previous version that will clear up all your doubts. The new version of November 2023 came into force in June 2024 in the European Medicines Agency environment. Although at first glance it may be seen as just another regulatory update, this publication is a milestone in the development of analytical processes in a #GMP (Good Manufacturing Practices) environment, especially for the ICH Q2 validation guide, as the current version came into force in 1996, 25 years ago. We hope you find it useful! Please feel free to contact us to find out more about our method development and validation service! #ICHGuideline #ICH #Impurities #ICHQ2 #Validation #AnalyticalProcedures #Accuracy #Precision #Biopharma #Pharma #DrugDevelopment #DrigDiscovery #Drugs #EMA https://lnkd.in/d_G_gQ5Z

Difference between OOS,OOT and OOE Out of Specification (OOS) Results OOS results refer to test results that fall outside the established specifications or acceptance criteria that are present in drug applications, drug master files (DMFs), official compendia or set by the manufacturer. Specifications are typically predefined based on regulatory requirements and scientific rationale. OOS results are immediately alarming as they directly indicate a potential quality issue with the product. They require a thorough investigation to determine the root cause, which could range from sample mishandling and analytical errors to actual product defects. Out of Trend (OOT) Results OOT results, while falling within the product’s specification limits, show an unexpected trend that could indicate a potential problem if not addressed. These results are particularly significant as they can serve as early warning signs of underlying issues in the manufacturing or testing processes. It is of utmost importance to promptly investigate and address these anomalies to preemptively identify these statistically important deviations before they escalate into critical problems. Out of Expectation (OOE) Results Out of Expectation results, also known as atypical/aberrant/anomalous/unexpected results, refer to test outcomes that deviate significantly from what is predicted based on historical data. These are often one-time anomalies that are statistically irrelevant and may not indicate a systemic issue. OOE results are usually characterized as atypical findings that are not consistent with other data, but they don’t necessarily violate specification limits like an OOS result. Depending on the circumstances and potential impact, these results may not require a rigorous multiphase investigation like OOS results.

Difference between OOS,OOT and OOE Out of Specification (OOS) Results OOS results refer to test results that fall outside the established specifications or acceptance criteria that are present in drug applications, drug master files (DMFs), official compendia or set by the manufacturer. Specifications are typically predefined based on regulatory requirements and scientific rationale. OOS results are immediately alarming as they directly indicate a potential quality issue with the product. They require a thorough investigation to determine the root cause, which could range from sample mishandling and analytical errors to actual product defects. Out of Trend (OOT) Results OOT results, while falling within the product’s specification limits, show an unexpected trend that could indicate a potential problem if not addressed. These results are particularly significant as they can serve as early warning signs of underlying issues in the manufacturing or testing processes. It is of utmost importance to promptly investigate and address these anomalies to preemptively identify these statistically important deviations before they escalate into critical problems. Out of Expectation (OOE) Results Out of Expectation results, also known as atypical/aberrant/anomalous/unexpected results, refer to test outcomes that deviate significantly from what is predicted based on historical data. These are often one-time anomalies that are statistically irrelevant and may not indicate a systemic issue. OOE results are usually characterized as atypical findings that are not consistent with other data, but they don’t necessarily violate specification limits like an OOS result. Depending on the circumstances and potential impact, these results may not require a rigorous multiphase investigation like OOS results.

Difference between OOS,OOT and OOE Out of Specification (OOS) Results OOS results refer to test results that fall outside the established specifications or acceptance criteria that are present in drug applications, drug master files (DMFs), official compendia or set by the manufacturer. Specifications are typically predefined based on regulatory requirements and scientific rationale. OOS results are immediately alarming as they directly indicate a potential quality issue with the product. They require a thorough investigation to determine the root cause, which could range from sample mishandling and analytical errors to actual product defects. Out of Trend (OOT) Results OOT results, while falling within the product’s specification limits, show an unexpected trend that could indicate a potential problem if not addressed. These results are particularly significant as they can serve as early warning signs of underlying issues in the manufacturing or testing processes. It is of utmost importance to promptly investigate and address these anomalies to preemptively identify these statistically important deviations before they escalate into critical problems. Out of Expectation (OOE) Results Out of Expectation results, also known as atypical/aberrant/anomalous/unexpected results, refer to test outcomes that deviate significantly from what is predicted based on historical data. These are often one-time anomalies that are statistically irrelevant and may not indicate a systemic issue. OOE results are usually characterized as atypical findings that are not consistent with other data, but they don’t necessarily violate specification limits like an OOS result. Depending on the circumstances and potential impact, these results may not require a rigorous multiphase investigation like OOS results.

On our latest blog, #DigitalCMC expert Lewis Shipp digs into a critical question that’s facing every drug developer with a PAI on the calendar... 🗓🗓🗓 “How exactly do we show a ‘commitment to quality in pharmaceutical development?’” That’s right: as of Objective 4, the FDA’s not just looking for alignment between application and processes at the time of inspection. They want to know – and see – how quality has been embedded in the entire development cycle leading up to the PAI. 😰 As Lewis points out, that puts three big things on the agenda for these critical inspections: holistic knowledge management, effective quality risk management (QRM), and solutions that systematically manage both those vital priorities throughout the development process. Link in comments to learn why Objective 4 moves those systems from “transformation goals” to “must-have program infrastructure.” #QbDVision #QbD #FDA 

Ensuring compliance with ICH guidelines requires a thorough review of the method validation package. This includes providing analytical validation information and experimental data for the procedures used in testing the drug substance. Learn more about analytical validation and how to meet regulatory standards: https://bit.ly/4dhfoBw #AnalyticalValidation #ICHCompliance #PharmaceuticalTesting #DrugDevelopment #DSI

Regulatory Affairs Insights 3.2.P.8 - Stability. The section 3.2.P.8 (Stability) of the Common Technical Document (CTD) provides data and information on the stability of the drug product. It ensures the drug product maintains its intended quality, safety, and efficacy throughout its shelf life. Here’s an insight into what this section typically includes: Key Elements of 3.2.P.8: Stability 1. Stability Summary and Conclusion (3.2.P.8.1): - Summary of the stability studies conducted. - Results demonstrating the stability profile. - Proposed shelf life and storage conditions. 2. Post-Approval Stability Protocol and Commitment (3.2.P.8.2): - Outline of the stability protocol for ongoing studies. - A commitment to perform stability studies on production-scale batches. - Stability commitments for variations, if applicable. 3. Stability Data (3.2.P.8.3): - Detailed results of the studies, including: - Real-time, accelerated, and intermediate conditions. - Testing intervals and conditions (e.g., 25°C/60% RH, 30°C/65% RH, 40°C/75% RH). - Parameters like assay, degradation products, dissolution, physical appearance, etc. - Statistical analyses for trends in stability data. - Bracketing and matrixing approaches, if applicable. - Justifications for extrapolated shelf life. General Expectations: - ICH Guidelines Compliance: Stability data should align with ICH Q1A(R2) and related guidelines (e.g., Q1B for photostability, Q1E for extrapolation). - Batch Details: Include at least three primary batches (pilot or production scale). - Container-Closure System: Data must reflect the intended commercial packaging. - Accelerated and Stress Testing: Demonstrate product behavior under extreme conditions. Challenges and Tips: - Regulatory Alignment: Ensure the data is consistent with local regulatory requirements (e.g., ASEAN for ACTD, EMA/FDA for CTD). - Clear Presentation: Provide well-organized tables and graphical representations for clarity. - Comprehensive Justification: Include scientific rationale for extrapolated shelf life or deviations. #dav #fda #ema #nda #tmda #nafdac #fwa #pharmaceutical #regulatoryaffairs #drug

Unlocking Precision: The Essence of GLP Test Item Characterisation🔓 In the realm of Good Laboratory Practice (GLP), meticulous attention to detail reigns supreme. Together with our dedicated GLP Auditor, Michelle Anderson, we proudly present our latest article: “The Essence of GLP Test Item Characterisation: Ensuring Precision in Non-Clinical Studies.” 🔍 In this comprehensive piece, we delve into the following key aspects: -Significance of Test Item Characterisation in GLP: Understand why this process is crucial for accurate and reliable results. -Methodology: Explore the techniques and protocols employed to characterize test items effectively. -Pivotal Role: Learn how precise test item characterization contributes to the overall quality of non-clinical studies. Read the Article here 👉 https://zurl.co/XIzY #GLP #TestItemCharacterisation #Quality #QualityAssurance #Pharma #LifeSciences #Pharmaceutical

April showers sprout May PERI courses! Seats available for these upcoming live programs: - May 6 & 7: Project Management in the Pharma Industry (BOSTON) - May 15 - 17: Basic Drug Development (ONLINE) Discover the full course line up at https://lnkd.in/gHMSuvQs #projectmanagement #drugdevelopment #FDA #regulatory #clinicaltrials