Affichage des articles du mai, 2020

WL Samchundang Pharm Co., Ltd. MAY 13, 2020

1. Your firm failed to establish and document the accuracy, sensitivity, specificity, and reproducibility of its test methods (21 CFR 211.165(e)). Your firm manufactures and aseptically fills  (b)(4)  drug products for distribution to the U.S. You did not establish the suitability of the sterility test method used for final release testing of  (b)(4)  of your finished drug products. In addition, you did not determine the suitability of the in-process bioburden test performed for each of your drug products. Suitability testing must be performed for each drug product to ensure the sterility test method is valid. Suitability testing establishes that contamination, if present, will be detected. When inhibition is encountered during suitability testing, test method modifications allow for optimized recovery... 2. Your firm failed to establish an adequate system for monitoring environmental conditions in aseptic processing areas (21 CFR 211.42(c)(10)(iv)). You did not routinely ide

WL Altaire Pharmaceuticals, Inc. MARCH 12, 2020

1. Your firm failed to establish an adequate system for monitoring environmental conditions in aseptic processing areas (21 CFR 211.42(c)(10)(iv)). Your firm manufactures sterile ophthalmic drug products which are subject to approved FDA applications for human and veterinary drug products. Additionally, your firm manufactures sterile ophthalmic over-the-counter (OTC) and homeopathic drug products. Our inspection revealed serious data integrity breaches and other serious violations relating to environmental and personnel monitoring. We found that plates taken from ISO 5 areas exceeded action limits, but your firm failed to initiate investigations . Furthermore, laboratory technicians falsified this data which is critical to maintaining an ongoing state of control in your aseptic processing facility. For instance, an environmental monitoring plate was recorded by your technician as “0” on your viable surface monitoring report form. The discarded plate was retrieved that same

La mainmise des données santé en France par Microsoft inquiète Edward Snowden

Technologie :  Le lanceur d'alerte le plus connu de la planète se montre critique à l'égard du choix d'hébergeur des données santé en France. Edward Snowden ne cache pas son indignation en apprenant l'alliance entre la future plateforme de santé française (appelée "Health Data Hub") et Microsoft, qui est devenu  le premier acteur du Cloud public à recevoir la certification hébergeur de données de santé . « Il semble que le gouvernement français capitulera face au cartel du Cloud et fournira les informations médicales du pays directement à Microsoft » a déclaré mardi soir (en français, s'il vous plaît !), le fugitif américain réfugié à Moscou  sur son compte Twitter . « Pourquoi ? C'est plus simple », constate ironiquement le lanceur d'alerte. Le projet controversé "Health Data Hub", dont l'architecte, Jean-Marc Aubert, était  parti rejoindre en décembre dernier la société Iqvia  spécialisée dans l'exploitation des donné

WL Blaine Labs Inc MAY 05, 2020

1. Your firm failed to thoroughly investigate any unexplained discrepancy or failure of a batch or any of its components to meet any of its specifications, whether or not the batch has already been distributed (21 CFR 211.192). A. Your investigations into out-of-specification (OOS) test results were inadequate . For example, you did not adequately investigate the failing viscosity test result obtained at bulk stage of Terpenicol AFC 13% topical cream lot BL2534. Although your Quality Unit (QU) was aware of the drug quality failure, no investigation of manufacturing was performed and the lot was approved for release to customers. Inadequate investigation of viscosity failures was also cited during our November 2015 inspection... 4. Your firm failed to establish an adequate quality unit and the responsibilities, and procedures applicable to the quality control unit were not in writing and fully followed (21 CFR 211.22(a)&(d)). Your QU did not fully exercise its authority

WL International Trading Pharm Lab Inc MARCS - APRIL 24, 2020

1. Failure of your quality unit to ensure that drugs are appropriately tested and the results are reported. Your quality unit did not provide appropriate oversight to laboratory operations. Several chromatographic injections of samples and standards associated with an out-of-specification (OOS) investigation were not included in your investigation, reviewed by your quality unit, and communicated to your clien t. For example, four  (b)(4)  samples tested OOS for assay on October 24, 2017. As part of the OOS investigation, they were all retested on November 11, 2017. One of the four samples you retested as part of your OOS investigation,  (b)(4)  sample ID  (b)(4) , was re-injected in duplicate under a separate series for assay approximately 14 hours later that same day. The second data set was not captured in the analyst’s notebook, it was not included as part of your documented OOS investigation, and your quality unit (QU) was unaware of the sample re-injection. In addition, 

EMA notice to sponsors on validation and qualification of computerised systems used in clinical trials

Note: This notice should be read in conjunction with Q8 and Q9 from the good clinical practice (GCP) Q&As published on the EMA website: Introduction : The integrity, reliability and robustness of data generated in clinical trials, e.g. data submitted to support marketing authorisation applications (MAAs), are essential to regulators. Most clinical trial data supporting MAAs are now collected through computerised data collection tools, e.g. electronic case report forms (eCRFs) and electronic patient reported outcomes (ePROs). In addition, a wide range of computerised media and systems are used in the conduct of a trial, such as safety databases, systems for electronic interactive response technology (eIRT), clinical trial management systems (CTMSs) etc., the use of which will increase in the future. Given recent inspection findings and the impl

Data Integrity In A Cloud-Based World: Regulations & Best Practices

By  Kip Wolf , Tunnell Consulting,  @KipWolf To begin, it is important to understand that data quality and data integrity are not the same thing. Data quality may be defined as the general utility of a data set as a function of its ability to meet the requirements for its use. This definition includes relativity that may also be explained as bias, which simply means that context is necessary to fully interpret and understand the data. Data quality is very specific to the data set and the data itself and, if measured to be poor, may be improved through verification, transformation, and/or cleanup. Data integrity is about trust and is as much about the supporting systems and processes as it is about the data set and the data itself. Data integrity relates to the state of the data or the sensitivity of data to external influence or change... Link to article - CLICK HERE.

WL Bedfont Scientific, Ltd. - FEB 12, 2020

c. Software changes are not adequately documented following your firm’s change control procedure  (b)(4) . The Product/Process Change Request form FRM-01 was not initiated for the change of the firmware  (b)(4)  and  (b)(4) . The adequacy of your firm’s response cannot be determined at this time. Your firm’s Project Manager will arrange for the appropriate documentation to be completed to ensure that a record of the change is held and will train engineers on the importance of recording and approving changes in accordance with procedures. However, documentation of these activities has not been provided for review and you have not provided a timeline for the proposed corrective actions...

WL Shriram Institute for Industrial Research APRIL 15, 2020

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(a)). Your firm serves as a contract testing laboratory analyzing both API and drug products. Your firm had not enabled the audit trail function on high-performance liquid chromatography (HPLC) units until on or about October 11, 2019, when this FDA inspection was announced.Your analyst acknowledged during the inspection that the audit trail function on the HPLCs units was not enabled until October 2019. This was a repeat observation of your August 2016 FDA inspection. Despite written commitments after that inspection to install audit trails, you failed to enable audit trail functions on multiple analytical instruments, including your HPLC units. Customers rely on the integrity of the laboratory data that you generate to make decisions regarding drug quality. It

Bioprocessing 4.0 Accelerates Biological R&D Using Computer-Aided Biology

Computer-aided biology describes a growing ecosystem of tools that augment human capabilities in the laboratory. In this report we give two case study examples of how computer-aided biology has transformed industrial gene therapy bioprocessing. In this Special Report, the authors describe how Synthace’s Antha cloud-based software platform has enabled industrial collaborators Oxford Biomedica and the Cell and Gene Therapy Catapult to harness the power of Bioprocessing 4.0 by: incorporating new process analytical technologies (PAT), such as Raman Spectroscopy, into their unit operations automating the upload, collation, organization, structuring, processing, visualization, and analysis of large bioprocess datasets from various sources precluding the need for data wrangling and reducing the time from data generation to high-value bioprocess insight from weeks to minutes. Link to Article - CLICK HERE

Increasing Transparency And Confidence Through Real-Time Data Sharing

By John Chapin, Senior Automation Engineer, and John Morse, QA Lead, Strategic Growth Investments and Engineering, Lonza Biologics Three industrial revolutions catalyzed by steam, electricity, and the computer, respectively, have occurred over the course of history and drastically changed the landscape of how goods are manufactured. The next transformation taking shape is being dubbed as Industry 4.0, which is the digitization of manufacturing utilizing data, machine learning, and artificial intelligence. Interconnectivity, real-time data sharing, and automation are used to increase transparency across an organization’s people, production line, and in the supply chain, leading to increased efficiency in manufacturing. This movement is fueled by more informed, and eventually autonomous, decision making as automation spreads throughout the business functions. A digitally connected plant is required for this transformation to occur. Link to article - CLICK HERE