Supplier or Vendor Qualification

Supplier Qualification Overview 

The "Best practices guide for managing suppliers of API manufacturers" was finalised by the "APIC Supplier Management Task Force" in March 2024 and is now available on the APIC website. It emerged from the document "Supplier Qualification and Management Guideline", which was first published in 2009, and now replaces it in its entirety. The previous document has been completely revised, although the original annexes have been retained and an additional Annex 2 entitled "Commitment declaration (template)" has been added.

The new guide contains the following chapters and sub-chapters:

1. General Section
    1.1 Introduction 
    1.2 Objectives
    1.3 Scope
    1.4 Overall Process for Supplier Management

2. Supplier Management
    2.1 Selection Phase
    2.2 Qualification Phase
    2.3 Operational Phase
    2.4 Termination Phase

3. Risk Management applied to Supplier Management
    3.1 Risk management process
    3.2 Risk Identification and Analysis
    3.3 Risk Evaluation and Risk Review
    3.4 Risk control

4. Auditing
    4.1 General
    4.2 Audit organisation
    4.3 Audit Types
    4.4 Audit rating
    4.5 Refusal of audits

5. Quality agreements
    5.1 General
    5.2 Refusal or partial acceptance of agreements

6. Definitions and abbreviations
7. References
8. Annexes
9. Version History

US FDA Warning Letter 09.04.2024

Your firm failed to have, for each batch of drug product, appropriate laboratory determination of satisfactory conformance to final specifications for the drug product, including the identity and strength of each active ingredient, prior to release (21 CFR 211.165(a)).

Your firm manufactures over-the-counter (OTC) (b)(4) drug products, such as, (b)(4). Your firm failed to adequately test your (b)(4) drug product for identity and strength of active ingredients prior to release and distribution.

In your response, you state that you will perform an assay test of your (b)(4) for (b)(4) with a validated analytical method. Your response is inadequate. You failed to provide sufficient details such as your testing procedures or a risk assessment of products released without appropriate assay testing.

Because you lacked adequate testing of each batch of your drug product, you do not know whether they conform to all appropriate finished product specifications and are suitable for release and distribution.

2. Your firm’s quality control unit failed to exercise its responsibility to ensure drug products manufactured are in compliance with CGMP, and meet established specifications for identity, strength, quality, and purity (21 CFR 211.22).

Your quality unit (QU) did not provide adequate oversight for the manufacture of your drug products. For example, your QU failed to ensure the following:

Appropriate production and process controls, including an adequate process validation program designed to assure drug products manufactured have the identity, strength, quality, and purity purported or represented to possess (21 CFR 211.100(a)).

Scientifically sound and appropriate test methods and standards used for testing your drug products (21 CFR 211.160(b)).

Complete data derived from standard preparation, sample preparation, and assay testing of your drug products was properly documented and retained (21 CFR 211.194(a)).

Adequate investigations and deviations (21 CFR 211.192).

Adequate cleaning and maintenance procedures, including an appropriate cleaning validation program for your non-dedicated manufacturing

Natco Pharma Ltd received a Warning Letter

Natco Pharma Ltd, a leading Indian pharmaceutical company, announced today that it has received a Warning Letter from the United States Food and Drug Administration (USFDA) regarding its manufacturing facility located in Kothur, Telangana.

The letter, dated April 8, 2024, follows a routine current Good Manufacturing Practices (cGMP) inspection conducted by the USFDA at the facility in October 2023.

The Kothur facility produces various pharmaceutical products for the company. While the company did not disclose specific details about the products manufactured at this site, it stated that the warning letter is not expected to disrupt supplies or impact existing revenues from the facility.

However, the letter may result in delays or withholding of pending product approvals from the Kothur site, it added.Hit Follow

Insufficient CAPA turned into Non-compliance

CAPA is a promise from the manufacturer that provide assurance to regulatory over a documentation. Failing to meet such promise will turn into a non compliance report by regulatory authority here is the example.

A follow-up GMP inspection was carried out at Cubit Lifesciences in India by the Malta Medicines Authority (MMA), an EU Competent Authority, early 2024. This inspection was in line with the recommendations from a previous inspection conducted about one year earlier, which had identified "2 critical, 3 major and a total of 17 other observed issues."

The main goal of the recent follow-up inspection was to "assess and validate the effective incorporation, spanning the entirety of the facility and the pharmaceutical quality system, of the documented Corrective and Preventive Actions (CAPAs) and commitments presented by Cubit Lifesciences in response to the February 2023 inspection."

However, the follow-up inspection revealed that some issues identified in the initial inspection were "not fully addressed and implemented," leading to the finding of "two critical, four major and twelve other findings." This indicated a lack of proper implementation of the necessary CAPAs.

As a consequence, the Inspection Review Group (IRG) at the Malta Medicines Authority has decided to issue a "Statement of Non-Compliance with the principles and guidelines of Good Manufacturing Practice laid down in Directive 2003/94/EC" for the site, reflecting ongoing concerns about compliance and quality management at Cubit Lifesciences.

Also for inspection observations, the causes of the problems identified would need to be thoroughly investigated and corrective and preventive actions (CAPA) should be defined to prevent recurrence. The implementation of CAPA following a root cause analysis (RCA) is crucial as it ensures that the identified causes are addressed through appropriate actions. The report emphasises the need for an in-depth root cause analysis and the implementation of effective CAPA.

Understand ICH Q7 S3

Can other departments outside of the quality unit be held responsible for releasing raw materials and intermediates? Yes. The quality unit is responsible for establishing a system Yes. The quality unit is responsible for establishing a system to release or reject raw materials, intermediates, packaging, and labelling materials. This responsibility cannot be delegated [ICH Q7, 2.22(2)]. The system established by the quality unit may allow ‘other departments’ to release raw materials and intermediates (except intermediates that are for use outside the control of the manufacturer [ICH Q7, 2.22(1)]) as long as oversight and the overall responsibility of this system remains with the quality unit. Does ICH Q7 expect that sampling be performed by the quality unit? No. ICH Q7 does not prescribe specifically who should perform the sampling [ICH Q7, 2.22]. However, the quality unit has responsibility for reviewing and approving sampling plans [ICH Q7, 11.12] and procedures. Sampling should be performed by adequately trained personnel [ICH Q7, 3.10] and be appropriately documented as per [ICH Q7, 6.52]. What should be the frequency of a product quality review? A product quality review is generally expected annually. Review timeframes can be appropriately adjusted based upon manufacturing and campaign duration with adequate justification. Even if no manufacturing has occurred in the review period, the quality review should be conducted as per section [ICH Q7, 2.50] and include stability, returns, complaints, and recalls. For example, a product quality review may encompass more or less than 12 months depending upon product campaign duration [ICH Q7, 2.50; ICH Q10, 2.6].

Technical Documents Writing Tips

Know your audience: Before you even start writing, consider who will be reading your document. Are they experts in the field, or do they need a more basic explanation? Tailor your language and level of detail accordingly. Clarity is key: Strive for clear, concise, and easy-to-understand language. Avoid jargon and technical terms whenever possible. If you do need to use them, define them clearly the first time you use them. Structure your document logically: Organize your information in a logical and easy-to-follow way. Use headings, subheadings, bullet points, and numbered lists to break up your text and make it visually appealing. Use visuals effectively: Charts, graphs, diagrams, and screenshots can be powerful tools for explaining complex concepts. Make sure your visuals are clear, well-labeled, and relevant to the text. Write in active voice: Active voice makes your writing more concise and engaging. For example, instead of saying "The experiment was conducted by the researchers," say "The researchers conducted the experiment." Focus on the benefits: When explaining a technical process or product, focus on the benefits for the reader. What problem does it solve? How will it make their life easier? Use examples: Examples can help illustrate complex concepts and make your writing more relatable. Proofread carefully: Once you've finished writing, proofread your document carefully for typos, grammatical errors, and formatting inconsistencies. Get feedback: Ask a colleague or friend to review your document and provide feedback

Understand ICH Q7 S2

Should GMP according to ICH Q7 be applied for manufacturing steps before the defined ‘API starting material' i.e. steps not identified in grey in Table 1? ICH Q7 does not apply to steps prior to the introduction of the API starting material. However, there is an expectation that an appropriate level of controls suitable for the production of the API starting material should be applied [ICH Q7, 1.3]. Normally, the ‘API-starting material’ is defined in the regulatory filing by the applicant and approved in the regulatory reviewing process. Additional guidance is provided to define and justify ‘API starting material’ derived from various sources [ICH Q11, 5]; for master cell banks, see [ICH Q5B; ICH Q5D]

Understand ICH Q7

What is meant by ‘quality unit(s) independent from production The intent of the term ‘independent’ is to prevent any conflict of interest and ensure unbiased decision-making regarding quality-related decisions in the organization structure. The person in the quality unit who is responsible for final decision-making (e.g., batch release decision) should not have responsibilities for production activities [ICH Q7, 2.13]. Does ICH Q7 expect that the quality unit performs API release testing While the quality unit has responsibility for the release of the API, which includes oversight of the testing and results, ICH Q7 does not prescribe specifically who performs testing. ‘Quality control’ in the ICH Q7 Glossary [ICH Q7, 20] refers to the activities, not the organisational structure. For examples of quality responsibility related to testing and release, refer to [ICH Q7, 2.13, 2.22, and 11.12]. Appropriate laboratory controls should be followed [ICH Q7, 11.10, 16.10] regardless of who performs the testing.

Out of Specification (OOS) Results in Pharmaceuticals: A Outline

In the world of pharmaceutical manufacturing, maintaining strict quality control is paramount. Every step of the process is meticulously monitored to ensure the safety and efficacy of the final product. But sometimes, things don't go according to plan, and a test result might fall outside the established specifications, known as an Out-of-Specification (OOS) result. An OOS result can be a cause for concern, but it's crucial to stay calm and follow a systematic investigation process. Here's a breakdown of what to do when you encounter an OOS See the latest updates to the Gemini Apps Privacy HubOpens in a new window Conversation with Gemini profile picture US FDA TODAY news There is no daily news section on the US Food and Drug Administration (FDA) website, but they do have a newsroom section that is updated regularly. Here's what I found for today, April 2nd, 2ˑ024: They have an upcoming public conference on medical device statistical issues (https://www.fda.gov/news-events/fda-meetings-conferences-and-workshops). Looking at their recent press announcements, here are the highlights from March 29th: The FDA warned consumers to avoid certain topical pain relief products (https://www.fda.gov/news-events/press-announcements/fda-warns-consumers-avoid-certain-topical-pain-relief-products-due-potential-dangerous-health). You can find more information on the FDA website https://www.fda.gov/. profile picture EDQM news Here's some recent news from the EDQM (European Directorate for the Quality of Medicines & HealthCare): EDQM celebrating 60 years: 2024 marks their 60th anniversary, and they're hosting a conference on June 11th and 12th in Strasbourg to celebrate their achievements in public health protection [EDQM conference]. New monographs in European Paediatric Formulary: Two new additions were made: Clonidine hydrochloride and Furosemide oral solutions [EDQM news]. EDQM ISO 9001 certification maintained: Their quality management system was successfully audited in November 2023 [EDQM newsroom]. Temporary closure: Due to a recent public holiday, the EDQM was closed from March 29th to April 1st, 2024 [EDQM newsroom]. For more information and the latest updates, you can visit the EDQM website news section [EDQM newsroom]. profile picture What is extra polation Extrapolation is a technique used to estimate what's beyond the data you have. It's like making an educated guess about something that hasn't been observed yet, based on what you already know. Here's a breakdown: Estimating the unknown: Imagine you have data points for something, like temperature measured every day for a month. Extrapolation would be using that data to guess the temperature on a day outside that month. Going beyond the range: Extrapolation extends a trend or pattern in the data beyond the points you actually measured. Comparison to interpolation: It's different from interpolation, which is used to estimate values between known data points. Here are some real-world examples of extrapolation: Weather forecasting: Predicting next week's weather based on data from this week. Population growth: Estimating a city's population in 10 years based on current growth trends. Sales prediction: Projecting future sales figures based on historical sales data. Important to remember: Extrapolation can be risky. The further you go from your existing data, the less reliable your estimates become. New factors can emerge that throw off your predictions. So, it's a useful tool, but use it with caution! profile picture US FDA latest warning letter The FDA website doesn't provide daily updates on warning letters. However, you can find the latest ones yourself by following these steps: Go to the FDA's Warning Letters webpage: https://www.fda.gov/inspections-compliance-enforcement-and-criminal-investigations/compliance-actions-and-activities/warning-letters Look for the "Date Posted" section on the right-hand side. This will show you the dates of the most recently added warning letters. As of today, April 2nd, 2024, the most recent warning letter on the FDA website is dated November 17th, 2023. It was issued to Cipla Limited https://www.fda.gov/inspections-compliance-enforcement-and-criminal-investigations/warning-letters/cipla-limited-660904-11172023. Here are some alternative resources to find the latest FDA news: FDA News & Events: https://www.fda.gov/ This page provides a list of recent press releases and upcoming events. FDA RSS Feed: https://www.fda.gov/about-fda/contact-fda/subscribe-podcasts-and-news-feeds You can subscribe to the FDA's RSS feed to receive automatic updates on new content. FDA Twitter: https://twitter.com/us_fda?lang=en Follow the FDA on Twitter for the latest news and updates. Sources library.weill.cornell.edu/about-us/snake%C2%A0oil%C2%A0-social%C2%A0media-drug-advertising-your-health/modern-drug-advertisements-themes-fda profile picture What is an outlier in stats In statistics, an outlier is a data point that falls significantly outside the overall pattern of the data. It's a single observation that seems very different from the rest of the values in a dataset. Here's a breakdown of what makes a data point an outlier: Extremely high or low value: Outliers are usually on the very high end or very low end of the data spectrum. They deviate considerably from the average (mean) or median of the data set. Doesn't fit the pattern: Outliers disrupt the overall trend or distribution of the data. Imagine a bunch of data points clustered together, and then one point way off by itself - that's an outlier. There are two main ways to identify outliers: Visually: Box plots and scatter plots are useful tools for spotting outliers. In a box plot, outliers appear as points far away from the main box-shaped area. In a scatter plot, they'll be isolated points far from the cloud of other data points. Statistically: There are statistical methods to define outliers based on factors like interquartile range (IQR). These methods set thresholds to determine how far a data point can deviate from the rest before being considered an outlier. Here's some additional information to consider about outliers: Not always errors: While outliers can sometimes indicate errors in data collection, they don't necessarily mean there's a mistake. They could represent genuine variations or exceptions within the data. Impact on analysis: Outliers can significantly affect statistical analyses, especially those that rely on averages or medians. It's important to acknowledge their presence and decide how to handle them (including removing them if justified) before drawing conclusions from your data. profile picture How to download WHO audit observations The World Health Organization (WHO) website doesn't directly offer downloads of individual audit observations. Here are some alternative approaches to find relevant information: List of Internal Audit Reports: The WHO publishes a list of their internal audit reports for each year. This provides an overview of the audits conducted, their titles, dates, and overall conclusions (https://www.who.int/publications/m/item/report-of-the-internal-auditor). While it doesn't include detailed observations, it can be a starting point to see if an audit was conducted in your area of interest. WHO Publications: Search the WHO publications database using keywords related to the specific program or area you're interested in, along with terms like "audit," "evaluation," or "assessment" (https://www.who.int/publications). This might lead you to reports that include summaries of audit findings. WHO Regional Offices: If your focus is on a specific region, explore the websites of the WHO regional offices, as they might publish information on audits conducted within their jurisdiction. Contact WHO: If the above options don't provide what you need, consider contacting the WHO Department of Internal Oversight and Investigations (OIOS) directly. They might be able to advise on how to access specific audit information (https://www.who.int/about/office-of-internal-oversight-services/investigations). Keep in mind: Releasing detailed audit observations might have privacy or confidentiality concerns, so access may be restricted. The WHO website focuses on publishing final reports and recommendations, rather than individual observations. profile picture I need a blog post on how to investigate out of specifications results in pharmaceutical Show drafts Out of Specification (OOS) Results in Pharmaceuticals: A Guide to Investigation In the world of pharmaceutical manufacturing, maintaining strict quality control is paramount. Every step of the process is meticulously monitored to ensure the safety and efficacy of the final product. But sometimes, things don't go according to plan, and a test result might fall outside the established specifications, known as an Out-of-Specification (OOS) result. An OOS result can be a cause for concern, but it's crucial to stay calm and follow a systematic investigation process. Here's a breakdown of what to do when you encounter an OOS result: 1. Initial Response and Documentation: Stop the process: Halt any activity that could potentially affect the product or generate misleading data. Secure the sample: Isolate and quarantine the sample associated with the OOS result to prevent contamination or loss. Document everything: Record all details of the event, including the test name, OOS value, date, time, and any observations about the sample or process. 2. Investigate the Cause: Repeat analysis: Re-run the test according to the established procedure. This helps confirm the initial OOS result and rule out potential errors during the first test. Analyze trends: Review historical data for the same product or test. Have there been any similar OOS occurrences? Identifying trends can help pinpoint potential root causes. Evaluate potential factors: Consider factors that might have influenced the result, such as: Equipment malfunction: Was the testing equipment properly calibrated and functioning correctly? Human error: Did any deviations from the standard operating procedure (SOP) occur during sample collection or testing? Raw material issues: Were there any problems with the starting materials used in the manufacturing process? Environmental factors: Could temperature, humidity, or other environmental conditions have affected the results? 3. Risk Assessment and Corrective Action: Assess the impact: Evaluate the potential health risks associated with the OOS result. How critical is the deviation from specifications? Determine disposition of the batch: Based on the investigation and risk assessment, decide whether to release, rework, or reject the affected batch. Implement corrective actions: Address the root cause of the OOS to prevent future occurrences. This might involve equipment recalibration, additional staff training, or revising SOPs.

FDA warning Letter issued 02.04.2024

Synopsis Identity testing of incoming components: The firm did not conduct adequate testing to verify the identity of each component of its drug products, including active ingredient ethanol for methanol contamination. Finished drug product testing: There was a lack of appropriate laboratory determination of satisfactory conformance to final specifications for drug products before release, including identity and strength of the active ingredients. Stability program: The firm failed to establish and follow an adequate written testing program to assess the stability characteristics for the OTC hand sanitizer drug products. Quality Unit (QU): The QU did not effectively oversee the quality of drug manufacturing operations. Your firm failed to establish an adequate quality control unit with the responsibility and authority to approve or reject all components, drug product containers, closures, in-process materials, packaging materials, labeling, and drug products (21 CFR 211.22(a)). The records and information you provided demonstrate that your quality unit (QU) did not effectively exercise its responsibilities to oversee the quality of your drug manufacturing operations. Your QU is responsible for fully exercising its authority and responsibilities. FDA is concerned that your QU may not be conducting appropriate oversight regarding CGMP operations. See FDA’s guidance document Quality Systems Approach to Pharmaceutical CGMP Regulations for help implementing quality systems and risk management approaches to meet the requirements of CGMP regulations 21 CFR, parts 210 and 211 at https://www.fda.gov/media/71023/download