Category: Uncategorized

FDA Expands Virtual Audit Guidance

Posted on by Brandon Miller

The US Food and Drug Administration (FDA) has recently expanded on its clarification of a virtual audit, and how new manufacturing protocols in the COVID-19 environment will evolve. Travel constraints continue to impact the industry, especially in countries like India where a tremendous outbreak of COVID cases erupted in April 2021.

 

“This does show that indeed, we are very much interested in doing these remote interactive investigations, you know, especially the ones with video streaming technology.” said Michael Kopcha, director of the Office of Pharmaceutical Quality in the agency’s Center for Drug Evaluation and Research.

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After reviewing recommendations from the European Medicines Agency (EMA) and the UK Medicines and Healthcare Regulatory products Agency (UK MHRA), the FDA continues to address the questions many pharmaceutical companies and partners have voiced during the pandemic. FDA officials commented that, due to these early learnings from other global regulatory bodies, they have recently expanded their recommendations for virtual audit best practices and new criteria of considering when to conduct a remote inspection.

 

Two of the initial primary use cases for virtual pharmaceutical inspections mentioned by the FDA include records requests and on-site inspectional work. While developing the new virtual audit process is still ongoing, one recommendation is Pharmaceutical companies should choose a proven regulatory partner to assist with the audit. Agency executives explained they will not be engaging vendors to perform virtual audits on behalf of the FDA.

virtual audit

 

One looming issue to be remedied is will virtual audits be allowed for facilities with serious good manufacturing practice (GMP) violations. FDA officials have expanded on their risk-based approach to prioritization in deciding which sites may qualify. An expanded virtual audit strategy continues to be a work-in-progress by agency officials including defining which companies qualify for an FDA virtual inspection and, more importantly, in what order the virtual audits may happen.

 

GMP violations involve either FDA warning letters or action-indicated site classifications based on the possible corrective actions needed. If the corrective actions needed for a facility can be successfully addressed remotely, it may become more likely that the number of hybrid virtual inspections authorized by the FDA will continue to grow. However, agency official commentary concluded that each facility will be examined by the FDA team on an individual basis with consideration of potential violations involved being a primary decision-making driver.

 

The good news for Pharmaceutical industry executives is it appears the FDA is willing to learn from international regulatory experiences and potentially even collaborate using technology in new ways to increase the FDA’s ability to continue operations. Global travel limitations will more than likely impact every industry for the foreseeable future in 2021 until the COVID-19 vaccine becomes more widely administered.

 

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FDA Updates Supply Chain Security Guidance

Posted on by Brandon Miller

The U.S. Food and Drug Administration (FDA) recently published multiple new guidance documents to help accelerate supply chain security and new product tracing requirements in the pharmaceutical industry. While most countries have implemented firmer regulations over the last decade, this new guidance is timely as domestic industry executives are reexamining security protocols in the wake of prominent cyberattacks.

 

The Drug Supply Chain Security Act (DSCSA) was originally designed as a framework for manufacturers, wholesalers, and dispensers to comply with laws that accomplish a safer, secure, and entrusted drug supply chain. A primary objective of DSCSA is to develop models and strategies to reduce the distribution of counterfeit, stolen, contaminated, or otherwise harmful drugs. These new FDA guidances include protocols for developing data architecture systems and how industry executives can optimize interoperability during the design and build phase. 

 

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Drug Packaging

 

As part of the DSCSA, pharmaceutical manufacturers and repackagers are required to add a product identifier on drug packaging. The product identifier includes the product national drug code (NDC), serial number, lot number and expiration date for each package. It must be in both human- and machine-readable form (e.g. two-dimensional data matrix barcode). This is designed to help downstream partners (e.g. repackagers, wholesale distributors, and dispensers) associate the information encoded in the barcode with readable text used by Logistics teams. The updated human-readable format includes:

 

  • NDC: [insert product’s NDC]
  • SERIAL: [insert product’s serial number]
  • LOT: [insert product’s lot number]
  • EXP: [insert product’s expiration date]

 

Expiration Date

 

For select products where an expiration date includes only year and month due to space limitations, the drug’s actual expiration date is recommended to be the last day of the calendar month included in the human-readable expiration date on the drug package label.

 

Product Identifier

 

Each finished or unfinished drug is subject to regulatory listing requirements. The product identifier is a standardized graphic composed of an alphanumeric serial number (up to 20 characters) that helps identify the product and package configuration. Product identifiers must be affixed or imprinted on the smallest individual saleable unit of a product, which also includes all product sold to a dispenser.

 

National Drug Code

 

Each product identifier has a unique NDC. The NDC is a FDA-assigned 3-segment format (10 or 11-digit number) to identify its labeler, product, and package size and type. In select instances, the linear barcode requirements from 21 CFR 181 201.25 will stay in effect for additional FDA-regulated products and packaging. This digital fingerprint of data will be used to accelerate the regulatory learning process. 

 

Suspect/Illegitimate Products

 

The revised FDA guidance documents also now provide increased clarity regarding the FDA’s current interpretation of “suspect” and “illegitimate” products. “Suspect” and “illegitimate” products are defined as:

 

  • “counterfeit”
  • “diverted”
  • “stolen”
  • “fraudulent transaction”
  • “unfit for distribution”

 

Artificial Intelligence

 

As artificial intelligence and machine learning modernize the supply chain over time, it’s not unreasonable to imagine the new bar codes could detect medication errors in real time for healthcare professionals and pharmacists. This could provide alerts to validate industry professionals are:

 

  • Giving the right drug,
  • Via the right dose,
  • Via the right route of administration,
  • To the right patient,
  • At the right time.

 

Regulatory Agency Response

 

Specific scenarios designed for risk management of a suspect product entering the pharmaceutical supply chain are also referenced. The guidance provides examples of when manufacturers should notify the FDA of a high risk product that may be or is illegitimate. Industry executives are also encouraged to collaborate with the Agency to help refine existing processes for terminating notifications.

 

This new clarity provides pharmaceutical executives a further glimpse into the FDA’s interpretation of system attributes necessary for secure product tracing inside the marketplace. The language is noticeably more detailed at the package level and provides supporting commentary for avoiding supply chain disruptions and enhanced drug distribution security.

 

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FDA Inspectional Approach

Posted on by Brandon Miller

The US Food and Drug Administration (FDA) is likely going to continue to use remote inspection alternatives in a “hybrid approach” with in-person inspections, supplemented by audit and FDA inspection tools like remote interactive assessments.

 

In a recent Accessible of Accessible Medicine’s (AAM) conference Elizabeth Miller, Assistant Commissioner in FDA’s Office of Medical Products and Tobacco Operations within the Office of Regulatory Affairs (FDA’s inspectorate) stated “Ideally, inspections supplemented by additional tools, including records requests and remote interactive evaluations, would provide FDA with the greatest depth of information”.

 

What is an FDA Inspection “Hybrid Approach”?

 

It is part onsite work and part offsite/remote work to conduct an assessment. The FDA uses tools like video chat for inspection activities like virtual interviews. They also use technology like secure shared online folders for offsite FDA 483 document review.

 

The FDA audit could start with a record request and then come onsite, or vice versa. Remember, FDA doesn’t consider remote evaluations to be a replacement for inspections. Inspections are onsite and will start with the lead FDA investigator providing the most senior ranking person at the site a Form FDA 482, Notice of Inspection.. The Form 482s is not issued for remote interactive evaluations.

 

Instead, your company will receive an FDA Form 4003, FDA Inspection Records Request. Having the term “inspection” in the title of the form can be a little confusing, but it is not considered or counts as an inspection. However, the FDA’s remote work will likely inform their onsite work during the actual inspection. Companies who prepare to manage these FDA  remote evaluations stand the best chance of success in an inspection. This is for all companies, whether you are conducting remediation because you’re having FDA compliance issues or not.

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Will the FDA inspection changes be permanent?

 

Signs currently point to these changes moving down the path to permanency. FDA remote inspections and reviews can and do allow for more efficient onsite inspections. Conducting remote records reviews can help the investigators save time on site by not having to sit in a conference room and read. It also reduces their COVID exposure (and yours) by potentially reducing FDA facility inspection onsite time.

 

It must be pointed out that having a remote review does not immediately equate to a shorter onsite inspection. The onsite time will be dependent on what the investigator is covering and what they are or not finding. For example, an FDA GMP inspection may still take a different amount of time than a FDA surveillance inspection, and so on. 

 

The US Congress has even weighed in on the matter. For example, in a March 2021 Senate Health, Education, Labor and Pensions (HELP) Committee Hearing, Sen. Richard Burr, a member of the HELP Committee, suggested that the technology adoption for FDA virtual inspections should become more permanent in nature.

 

“The pandemic, I believe, has altered the model at FDA and the agency should not go back to its historical approach,” he said.

 

Risk-Based Model used to Identify FDA Inspections

 

The FDA’s risk-based criteria for prioritizing and selecting mission-critical inspections during the pandemic can be found in their Resiliency Roadmap for FDA Inspection Oversight. In the publication, they outline the factors helping to determine whether or not the inspection is mission-critical. These controls help FDA best utilize their already limited resources in protecting public health. The four specific factors the Agency is using are:

 

  • The product receiving a breakthrough therapy or regenerative medicine advanced therapy designation;
  • The product is used to treat a serious disease or medical condition and there is no substitute;
  • The product requires follow-up due to recall or there is evidence of serious adverse events or outbreaks of a foodborne illness; or
  • The product is related to the FDA’s COVID-19 response (e.g., drug shortages).

 

It is expected that this prioritization will be used during the remainder of the pandemic and that some will continue after travel restrictions and other impediments to inspections are eased or lifted.

 

FDA Inspection Hybrid Approach

 

Remote evaluations are time-consuming and take time to prepare and facilitate. Partner this with an onsite inspection and the time and effort quickly compound. Because of these activities are so time-consuming nature companies have had to improve how they efficiently and effectively manage these regulatory interactions.

 

One way to prepare is to look at your overall CGMP and quality system documentation and records to determine what needs to be scanned and uploaded to a secure shared folder prior to the start of the FDA remote review. The scanning process is time-consuming and if done ahead of time helps decrease the cycle time between the investigator’s request and the time you’ll have it ready to present to the investigator.

 

Another helpful hint is to ensure someone reviews the scanned file to ensure the entire document or record is scanned. With auto feeders on scanners, the dreaded folded page or previously stapled page getting jammed and not scanned properly is a common phenomenon. This can slow down any FDA pre-approval process meetings happening in real-time and can be avoided with focused preparation. 

 

The preparation effort can also assist you in being prepared for, as well as hosting your own hybrid internal audits (ex: corporate quality audits), as well as customer and notified body audits (if you’re in medical devices and deal with ISO 9001 and other ISO certification). 

 

What Our Experts Have to Say

 

Speculating on what the world might look like in terms of the use of alternative tools, industry representatives seemed in agreement that a hybrid approach would be most effective going forward.

Steven Lynn, RCA’s Executive Vice President of Pharmaceutical said:

 

“I don’t think the hybrid approach is going FDA Inspectionaway anytime soon. It just makes better sense from a public health efficiency perspective to be able to look at documents and records remotely and then go onsite.”

 

“If I look at it from an FDA perspective, the hybrid approach gives the Agency a way to ensure investigators can review items prior to putting boots on the ground. The remote reviews also enable the Agency to pull in other scientific disciplines easier than it would be, had the investigator been onsite. From the industry perspective, it means we must spend more time preparing in order to successfully host these remote reviews and onsite inspections.”

 

 

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FDA Guidance: Product Lifecycle

Posted on by Brandon Miller

The USA Food and Drug Administration (FDA) recently provided updated regulatory guidance for Product Lifecycle Management in the pharmaceutical industry. The guidance helps pharmaceutical companies and manufacturers better understand the administration of post-approval chemistry, manufacturing, and controls changes.

 

Lifecycle Management

 

The guidance provides new insights into lifecycle management concepts for both new and existing pharmaceutical products, including chemical and biologics. The FDA regulatory team looked to synchronize its updated guidance more closely to ICH guidelines used with other global regulatory agencies.

 

The benefit realized by pharmaceutical companies would be options for reducing duplicate clinical studies and increasing the standardization of safety information reporting. By revising facets of FDA marketing application submissions as well, the Agency appears to be taking a more holistic approach to improving drug development quality and pharmaceutical manufacturing strategy.

 

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Manufacturing Process

 

Changes include language revisions to surrounding regional legal frameworks, an expanded clarification of critical process parameters, and identifying established conditions for manufacturing processes. One important revision for regulatory affairs employees is the new recommended content of the product lifecycle management document and its location within the technical file. Clarity revisions were also made to further expand on the use of available tools described in the guideline for master files.

 

Regulatory Submission

 

The new FDA guidance also expanded its language on post-approval chemistry, manufacturing, and controls changes. With additional tools and principles intended to improve the industry’s management of post-approval changes, FDA leadership is hoping to increase transparency between both industry employees and regulatory authorities.

 

The benefit to pharmaceutical companies should be a deeper understanding of how product and process knowledge will contribute in the real world to post-approval changes that require a regulatory submission. By defining the level of reporting categories, industry experts should experience a deeper understanding of risk compared to product quality.

 

Quality Management System

 

The new tools and principles are designed to improve data input into a company’s quality system. The goal is to enhance the industry’s ability to manage many chemistry, manufacturing, and controls changes that have a lower priority needed of regulatory oversight.

 

At the same time, many at the FDA are hopeful the tools and principles could result in fewer Marketing Authorization Application submissions that increase the associated regulatory burden. The guidance should increase both operational efficiency and regulatory flexibility when implemented with the proper regulatory framework and applied with widely accepted risk management principles in the pharmaceutical industry.

 

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FDA Guidance: Data Integrity

Posted on by Brandon Miller

The Food and Drug Administration (FDA) recently announced a new guidance program for the life science industry regarding data integrity. This FDA guidance draft is currently open & available for the industry to comment on and provide feedback. Additionally, the FDA regulatory process that looks to be initially targeted by the food and drug authority includes:

 

  • Investigational New Drug Application (IND)
  • New Drug Application (NDA)
  • Abbreviated New Drug Application (ANDA)
  • Biologic License Application (BLA)

 

Code of Federal Regulations

 

The guidance draft cites several different code of federal regulation (CFR) that are being reviewed and analyzed during this process. Specific CFR federal regulations mentioned include:

 

  • 21 CFR 11
  • 21 CFR 50
  • 21 CFR 56
  • 21 CFR 58
  • 21 CFR 210
  • 21 CFR 211
  • 21 CFR 312
  • 21 CFR 601
  • 21 CFR 820

 

Data Integrity

 

Specific use cases mentioned by FDA include data integrity throughout the clinical data management process in bioavailability (BA) & bioequivalence (BE) studies. Further, the FDA guidance provides initial suggestions to optimize data integrity success by focusing on three specific drivers:

 

  • Users or applicants in clinical trial
  • Site management of clinical trial
  • Quality management system for clinical trial

 

Finally, FDA provides best practices & recommendations for risk control and risk management. Understanding how to maintain good lab practice & clinical research success is essential for all participants.

 

FDA Guidelines

 

One of the primary objectives of the data integrity draft is to align FDA expectations with the clinical data being submitted in pharmacologic studies. Additionally, clinical data submitted by a drug sponsor for FDA drug approval must be:

 

“accurate, complete, and reliable, and that industry maintain data integrity throughout the data lifecycle of the product(s) or biologic therapeutic(s).”

 

Finally, new concerns are being raised about the evaluation of bioequivalence and bioavailability study data submitted during the FDA regulatory process. FDA highlights specific comments about regulatory concerns during in vivo pharmacology studies. The regulatory documentation lists specific areas adding to the erosion of data integrity based on FDA inspection experiences in the field:

 

  • Patient testing sites
  • Clinical testing sites
  • Analytical testing sites

 

Legal Regulation

 

The FDA guidance begins with reminding drug sponsors that they bear the responsibility of quality assurance even if a contact manufacturing organization (CMO) is engaged. Additionally, confirming a contract development and manufacturing organization (CDMO) has confidentiality processes in place is essential. 

 

For drug sponsors who are submitting a FDA new drug application, ICH guidelines and FDA guidance should be followed by external vendors who are conducting the elements of study-related activity. Finally, clinical data being generated through bioavailability and bioequivalence studies must be durable & reliable in nature, and properly documented in a quality management system (QMS).

 

Testing Site

 

The regulatory guidance goes on to elaborate about the monitoring and oversight strategy needed for clinical testing. Specific drivers listed for analysis when selecting a drug manufacturing partner include:

 

  • Personnel Education
  • Personnel Experience
  • Personnel Training

 

Manufacturing standards and expectations should be documented clearly in a formal agreement. Additionally, FDA highlights that regulatory requirements for clinical study activities should be documented and followed, including:

 

  • Clinical study protocol
  • Clinical study procedure
  • Clinical study process

 

Finally, FDA recommends that bioanalytical analysis should include closer oversight and monitoring. Any CMO or CDMO must have documented analytical methods in their quality management system. Further, all analytical methodologies must follow applicable FDA regulations and be included in the QMS standard operating procedures (SOP).

 

Quality Management System

 

The FDA guidance transitions to describe database integrity and why any clinical services provider you choose must “use a quality management system to help ensure data integrity”. This includes testing sites managing a quality management system and efficacy of “data governance throughout the data lifecycle”.

 

Records Management

 

The operations team supporting the clinical research management should review the QMS using a pre-planned schedule, per the FDA guidance. All data governance used to store and retrieve information in the clinical trial management system should replicate the reliability & durability of the QMS. 

 

Additionally, data integrity across the QMS would focus on each unique phase of the collection process. FDA recommends employees responsible for quality updates consider isolating job responsibilities between the separate data lifecycle phases to help reduce unintentional mishaps.

 

Clinical Technology

 

Using modern technology is recommended for all employees who are responsible & can impact data quality. Specific systems mentioned in the regulatory guidance that can improve data integrity include:

 

  • Computer hardware or related systems
  • 362 software for security or performance
  • Peripheral devices, networks or cloud infrastructure for connectivity
  • Any associated IT documents for usability (e.g. SOP manual)

 

Metadata

 

The guidance goes on to explain more about classification & ensuring that metadata is correct. Metadata, as described by FDA, is “data about data” and provides clarifying information to the agency. Common types of metadata quality concerns are listed as examples:

 

  • Missing date/time stamp for when data was acquired
  • Incorrect measurement units or documentation
  • Missing user ID’s of the team who conducted data testing or data analysis

 

Sample Analysis

 

An important facet of the FDA guidance discusses sample analysis & if the clinical evaluation is completed at a location different from the original testing site. Employees conducting the clinical evaluation should be familiar with good clinical practice & fully understand the study protocol, various test methods that were used, and any quality management system SOPs to follow.

 

Further, different types of instruments & clinical equipment used during the sample analysis should be “calibrated, maintained and serviced” per FDA. The regulatory guidance cites several examples that should follow manufacturer service guidelines, including:

 

  • Balances & pipettes
  • Centrifuges & spectrometers
  • Liquid chromatographs
  • Refrigerators & storage freezers

 

Quality Assurance and Quality Control

 

Managing the risk associated with a QMS is an important facet of the FDA guidance. A quality assurance program should be implemented, including standard operating procedures that limit access control & processes to isolate a data breach. Further, implementing a quality control program can help find and remedy data integrity flaws. An efficient quality control program should include:

 

  • Mapping of standard processes & risk control
  • Employee training & knowledge gaps
  • Difference between unintentional & intentionally compromised data

 

Corrective Action and Preventative Action

 

If data integrity deviations are identified in a quality control analysis, FDA recommends a corrective and preventative action (CAPA) program be launched. Additionally, the CAPA would look at all relevant processes and tasks as a whole rather than isolating a repeat occurrence. The recommended best practices for a quality control plan include:

 

  • Assemble & examine information for review
  • Identify real & possible problems during the review
  • Explore problems & create appropriate CAPA
  • Verify & validate the success of the CAPA
  • Communicate updated CAPA success to applicable teams
  • Document activity & intelligence for management review

 

 

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FDA Machine Learning

Posted on by Brandon Miller

The U.S. Food and Drug Administration (FDA), Health Canada, and the United Kingdom’s Medicines and Healthcare products Regulatory Agency (MHRA) have recently identified 10 guiding principles for the development of Good Machine Learning Practice (GMLP).

 

These guiding software development principles should be used to:

 

  • Adopt good practices that have been proven in other sectors
  • Tailor practices from other sectors so they are applicable to medical technology and the health care sector
  • Create new practices specific for medical technology and the health care sector

 

Need help putting these principles into action? Talk to our Experts →

 

What is Artificial intelligence and FDA machine learning (AI/ML)?

Artificial intelligence and machine learning use software algorithms to learn from real-world use of the device to help improve the product’s performance.

 

Good Machine Learning Practice Guiding Principles

 

  1. Multi-Disciplinary Expertise Is Leveraged Throughout the Total Product Lifecycle. Helps ensure that ML-enabled medical devices are safe and effective and address clinically meaningful needs over the lifecycle of the device.
  2. Good Software Engineering and Security Practices Are Implemented. Implementation with attention to the “fundamentals”: good software engineering practices, data quality assurance, data management, and robust cybersecurity practices.
  3. Clinical Study Participants and Data Sets Are Representative of the Intended Patient Population. Manage bias, promote appropriate and generalizable performance across the intended patient population, assess usability, and identify circumstances where the model may underperform.
  4. Training Data Sets Are Independent of Test Sets. Training and test datasets are selected and maintained to be appropriately independent of one another.
  5. Selected Reference Datasets Are Based Upon Best Available Methods. Using the best available methods for developing a reference dataset ensures that clinically relevant and well-characterized data is collected and the limitations of the reference are understood.
  6. Design Is Tailored to the Available Data and Reflects the Intended Use of the Device. Design is suited to the available data and supports the active mitigation of known risks, like overfitting, performance degradation, and security risks.
  7. Focus Is Placed on the Performance of the Human-AI Team. Human factors considerations and human interpretability are addressed with emphasis on the performance of the Human-AI team.
  8. Testing Demonstrates Device Performance during Clinically Relevant Conditions. Developed and executed statistically sound test plans to generate clinically relevant device performance information independently of the training data set.
  9. Users Are Provided Clear, Essential Information. Users are provided ready access to clear, contextually relevant information that is appropriate for the intended audience.
  10. Deployed Models Are Monitored for Performance and Re-training Risks are Managed. Models have the capability to be monitored in “real world” use with a focus on maintained or improved safety and performance, as well as periodic training after deployment.

 

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