Affichage des articles du janvier, 2020

WARNING LETTER Sunstar Guangzhou Ltd. MARCS-CMS 592906 — JANUARY 22, 2020

4. Failure to establish an adequate quality control unit and the responsibilities and procedures applicable to the quality control unit are not in writing and fully followed. (21 CFR 211.22(a) and 211.22(d)). Your quality unit (QU) failed to ensure that you have adequate procedures and did not provide adequate oversight of your manufacturing activities. For example: · • You lack adequate control over the issuance, use, and reconciliation of manufacturing batch records and equipment maintenance sheets . Uncontrolled copies of manufacturing batch records and in-process control forms were pre-printed and kept in a room with unrestricted access. • Several test reports of your drug product assay were reviewed and the raw data for the standard curve could not be located. It was noted that scrap pieces of paper were used to record data which was later entered to calculate the  (b)(4)  concentration for the assay test. Link to WL - CLICK HERE

First living robots, called ‘xenobots’, could be used in drug delivery

Using embryonic stem cells from frogs, scientists have created living robots; called xenobots, these organisms are able to heal after injury and could be the future of drug delivery. A team of scientists has repurposed living cells to create 1mm wide living  robots  called ‘xenobots’. By using cells, the researchers made a life form that could move, heal after injury and after seven days, die and completely biodegrade. These new organisms could be used in the future to deliver a drug payload to a specific area in a patient. Link to article - CLICK HERE

WL Zhuhai Aofute Medical Technology Co., Ltd. MARCS-CMS 590945 — JANUARY 09, 2020

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)). You failed to establish an independent and effective quality unit. For example, you failed to adequately perform basic quality unit (QU) responsibilities, including but not limited to: Approval or rejection of all components and drug product containers, closures, in-process materials, packaging materials, labeling, and drug products. Review of all production and control records. Assure establishment of adequate batch records. Approval of procedures and specifications impacting on the identity, strength, purity and quality of all drug products. Notably, you lacked adequate production and laboratory records. Your firm did not demonstrate the appropriate controls to assure drug product batches were manufactured fol

WL Tismor Health and Wellness Pty Limited MARCS-CMS 588104 — DECEMBER 05, 2019

1.   Your firm failed to exercise appropriate controls over computer or related systems to assure that only authorized personnel institute changes in master production and control records, or other records. (21 CFR 211.68(b). Your firm contract manufactures over-the-counter (OTC) topical drug products  (b)(4) . Your firm lacked sufficient controls over your gas chromatography (GC) instrument used to test the drug product prior to release. Specifically, your firm assigned administrative privileges to analysts conducting routine assay tests using your Empower chromatography software data system . During the review of your Empower chromatography audit trail for your drug product, our investigator observed that you deleted more than 100 test results since October 2017. You also aborted more than 100 sample set results during this same period, although you lacked investigations... 3.   Your firm failed to establish laboratory controls that include scientifically sound and appropri

WL Apollo Health And Beauty Care, Inc. MARCS-CMS 593033 — DECEMBER 23, 2019

1. Your firm failed to routinely calibrate, inspect, or check according to a written program designed to assure proper performance and to maintain adequate written records of calibration checks and inspections of automatic, mechanical, electronic equipment, or other types of equipment, including computers, used in the manufacture, processing, packing, and holding of a drug product (21 CFR 211.68(a)). Your firm contract manufactures over-the-counter (OTC) drug products, some of which are labeled to be used for children. During a review of an out-of-specification (OOS) investigation for  (b)(4)  content in your bulk  (b)(4)  lot  (b)(4) , our investigator identified multiple discrepancies between the human machine interface (HMI) data, and the entries made by operators into batch records . For example, the operator recorded  (b)(4)  the batch during Step  (b)(4)  for  (b)(4)  at  (b)(4) . However, HMI data indicated that  (b)(4)  were not operational at that time. Link to documen

iBio aims to cut manufacturing costs and improve data management with AI

by  Gareth Macdonald Wednesday, January 8, 2020  7:50 am iBio will use blockchain tech to cut costs and improve traceability in a deal that may also see Mateon spin-out a biopharma AI specialist. Plant-based biologics CDMO iBio asked EdgePoint AI – a unit of Mateon Therapeutics – to install artificial intelligence (AI) technologies at its manufacturing facility in Bryan, Texas. The idea is that the systems – known as TrustPoint Vision Fabric and TrustPoint Smart Protocols – will monitor production operations conducted and store data in a “blockchain.” Image: iStock/Andy Cost savings A blockchain is a digital record of transactions that can be viewed but not edited. In a drug manufacturing plant, it can track the transfer of raw materials from one unit operation to the next. According to iBio initial deployment will be in raw material supply chain related functions. The system will be used to automate the tracking of materials from time of receipt to manufacturing

Artificial Intelligence Takes Manufacturing Efficiency to the Next Level

Nov 21, 2018 By  Jennifer Markarian Equipment and Processing Report Volume 11, Issue 12 In the pharmaceutical industry, increasing price pressures are driving the need for significant and sustainable improvements in manufacturing efficiency. One of the many areas that can be targeted for efficiency gains is overall equipment effectiveness (OEE). Fortunately, Industry 4.0 tools—including sensors that can connect production equipment to data collection systems via the industrial Internet of Things (IIoT), cloud storage for large data sets, advanced analytics to make sense of the data, and software to make the data understandable and visible to those who can use it—are commercially available.  Link to article - CLICK HERE

How data is changing the pharma operations world

By Thibaut Dedeurwaerder, Daniele Iacovelli, Eoin Leydon, and Parag Patel (Mc Kinsey) Pharma companies have a great opportunity to turn a buzzword into exponential impact. Aircraft today can be fully developed in a digital environment. They are designed using CAD software and tested in a virtual flight simulator, before any physical work happens. Imagine the same in pharma: a COO can model various product portfolios, swap out machines, or model utilization and schedules to optimize agility and cost—all using software and delivering quantifiable answers in seconds. Science fiction? Yes and no. The technology exists today—including predictive analytics, robotic process automation, and AI-based tools, all digitally connected via the Internet of Things (IoT)—but no pharma company has fully leveraged it. Some companies apply point solutions and individual tools, but most get stuck in the pilot phase and struggle to scale up digital across the enterprise. This approach leads to limi

Embracing the Digital Factory for Bio/Pharma Manufacturing

New technologies enhance quality, efficiency, and flexibility. Mar 02, 2019 By  Jennifer Markarian Pharmaceutical Technology Volume 43, Issue 3, pg 16–21 Modern manufacturing technologies are being adopted by pharma and biopharma companies because of the value that they can provide in improving quality, efficiency, and flexibility, as well as profitability. Replacing manual activities with automated systems can remove error and increase the speed and accuracy of activities. Examples of such technologies range from automatic data capture and electronic batch records, which can improve data integrity, to using robots, which removes the potential for human error and reduces the exposure of operators to ergonomic or safety hazards. Connecting manufacturing systems and individual pieces of equipment using the industrial Internet of things (IIoT) improves data flow, so that decisions can be made more quickly and with more information, and data analytics tools create ins

MDCG 2019-16 - Guidance on Cybersecurity for Medical Devices (MDR / IVDR)

The primary purpose of this document is to provide manufacturers with guidance on how to fulfil all the relevant essential requirements of Annex I to the MDR and IVDR with regard to cybersecurity. Link to document - CLICK HERE

Impact of Data Integrity Audits on Pharma Microbial QC Labs

Most people are aware of the requirements of the code of federal regulations 21 CFR Part 11 for computer software security, which have been a major pharmaceutical IT focus for approximately 10 years. However, within the 21 CFR 11 requirements lurked another high-risk component: “Data Integrity”. Simply put, Data Integrity (“DI”) is the assurance that data records are accurate, complete, intact and maintained within their original context so as to make the data trustworthy. In pharmaceutical QC labs, there are often many manual steps in the performance of a routine QC analytic test to release a product (Figure 1). High risk areas were associated with the amount of human input required and how closely that input was monitored and verified. Plus d'information ici .

Google mise sur l'IA pour lutter contre le cancer du sein

Google mise tout sur l'intelligence artificielle (IA). Le géant américain,  qui s'intéresse de près au secteur de la santé , a travaillé avec des partenaires de recherche clinique au Royaume-Uni et aux Etats-Unis pour évaluer si l'intelligence artificielle pouvait être utilisée pour améliorer la détection du cancer du sein. En collaboration avec le Centre impérial de recherche sur le cancer du Royaume-Uni, l'Université Northwestern et le Royal Surrey County Hospital, Google a créé un modèle d'IA pour la lecture des mammographies, qui sont des radiographies du sein, afin d'aider les radiologues à repérer plus précisément les signes du cancer du sein. Selon l'American Cancer Society , les mammographies omettent environ 20 % des cancers du sein aux Etats-Unis, et les faux positifs sont fréquents, ce qui fait que les femmes sont rappelées pour d'autres examens, parfois même des biopsies. Plus d'information ici .

ENISA : Cloud Security

In the past, organizations would buy IT equipment (hardware and/or software) and manage it themselves. Today many organizations prefer to buy IT services from an IT service provider. This trend is generally, and liberally, referred to as ‘going cloud’. Our 2009  cloud security risk assessment  is widely referred to, across EU member states, and outside the EU. Following up on this risk assessment we published   an assurance framework  for governing the information security risks when going cloud. This assurance framework is being used as the basis for some industry initiatives on cloud assurance. In 2011 ENISA published a report on  security and resilience in government clouds ... Plus d'information ici

Nos meilleurs voeux pour 2020 !

Que cette nouvelle année vous garde en bonne santé et vous apporte le succès et le bonheur dans vos projets personnels et professionnels. Que vos projets de mise en oeuvre et de conformité de vos systèmes informatisés se déroulent comme prévus, dans le respect des coûts et des délais et sans remarques d'inspection !

WARNING LETTER Cross Brands Contract Filling, LLC MARCS-CMS 589295 — DECEMBER 17, 2019

2. Your firm lacks an adequate quality control unit with adequate facilities and procedures to ensure that drugs are manufactured in compliance with CGMP regulations and meet established specifications for identity, strength, quality, and purity (21 CFR 211.22). During the inspection, we observed that your Quality Unit (QU) did not provide adequate oversight over the manufacture of your drug products. For example, you lacked adequate written procedures describing your manufacturing operations and you failed to ensure that all batch and laboratory records are complete. Our inspection found that your QU misrepresented results for the absence of  Staphylococcus aureus  and  Pseudomonas aeruginosa  on COA that were released to your customers. Your QU allowed distribution of these products. Without complete laboratory and batch records, and adequate procedures, you cannot ensure the accuracy and reliability of your data . Plus d'information ici .

WARNING LETTER GPT Pharmaceuticals Private Ltd MARCS-CMS 590938 — DECEMBER 17, 2019

3.  Your firm failed to exercise appropriate controls over computer or related systems to assure that only authorized personnel institute changes in master production and control records, or other records (21 CFR 211.68(b)). Our investigator observed your laboratory equipment lacked appropriate controls. For example, from January 1, 2018, to June 25, 2019, audit trails from  (b)(4)  Agilent 1260 Infinity Series II high-performance liquid chromatography (HPLC) instruments showed a pattern of aborted runs and single run entries for testing  (b)(4) . Single run entries included analyses of multiple peaks or split peaks without documented investigations or adequate scientific justifications. Your employees used the Agilent Service Account login, with full administrative privileges, to abort HPLC testing runs without being attributable to a specific individual. Your response identified the number of deleted, aborted, and single runs during your HPLC testing. However, your response did