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mercredi 12 février 2020

Data Management Practices

Data management is crucial in bio/pharmaceutical laboratory settings from discovery steps through clinical studies and varies based on the development phase.
Feb 01, 2020
Volume 33, Issue 2, pg 35-36







Link to article - CLICK HERE
In nonclinical settings, good laboratory practices (GLPs) ensure the quality of the studies conducted, including the integrity of the data collected. Features needed for compliant data management include detailed final study reports, the proper storing of all raw data, documentation, and protocols, and a responsible archivist to maintain responsibility for the stored data (1).

lundi 10 février 2020

The Evolving Data-Driven Strategic Feasibility Model

How democratization of data is powering a new wave of opportunities

Key Challenges

Today’s clinical research environment is more competitively challenging, has higher costs and takes longer to bring a drug to market than at any other time in history. According to the 2015 Tufts Center for the Study of Drug Development research, from 2005-2015 the average Phase III study saw an increase in the complexity of protocols, driven by the ever-increasing set of inclusion and exclusion criteria (+61%), number of clinical endpoints (+25%), and number of study visits (+25%) and procedures (+70%), are driving more and more protocol amendments and adding to that cost and time. At the same time, the percentage of patients taking part in clinical studies remains at historically low rates, estimated to be less than five percent of the patient population. This contributes to low and non-enrolling sites, further contributing to the cost and time.
One of the common threads across all these challenges, is that data exists that could help address the underlying needs, but that data is often siloed across people, teams and companies, preventing it from helping to drive the right insights at the right time. By breaking down barriers and democratizing data, we are moving towards a future where that data and powerful analytics will come together to help design and execute clinical trials, bending the time cost curve of drug development...

mercredi 29 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.

lundi 27 janvier 2020

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.

mercredi 22 janvier 2020

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

  1. 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 following appropriate written procedures. Because no meaningful production records were available, there is no assurance that, if errors occurred, they were fully investigated before batches were released.  Furthermore, your laboratory technician stated that original raw data is routinely discarded...

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 appropriate specifications, standards, sampling plans and test procedures designed to assure that components, drug products conform to appropriate standards of identity, strength, quality, and purity (21 CFR 211.160(b)).
Your firm failed to validate the Excel spreadsheet used to perform the assay calculation for your “(b)(4).” Your procedures lacked guidance on how to check and manually verify the calculation sheets. During the inspection, our investigator identified a calculation error within the spreadsheet. The incorrect formula for averaging the Internal Standard peak area was used.
There is no assurance that the associated assay results recorded are reliable and accurate...


mercredi 15 janvier 2020

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.

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

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 introduction...

mercredi 8 janvier 2020

Artificial Intelligence Takes Manufacturing Efficiency to the Next Level

Nov 21, 2018
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. 

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 limited results that might excite the CIO but not the CEO.

Link to article - CLICK HERE


Embracing the Digital Factory for Bio/Pharma Manufacturing

New technologies enhance quality, efficiency, and flexibility.
Mar 02, 2019
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 insights that enable improvements in many areas. Whether these technologies are labeled as advanced manufacturing technologies, Industry 4.0 (1), or the digital plant, they are poised to transform bio/pharma manufacturing.

Link to document - CLICK HERE

mardi 7 janvier 2020

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.

lundi 6 janvier 2020

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.

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