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The EU Parliament voted its position on the Unitary SPC


by Giuliana Miglierini The intersecting pathways of revision of the pharmaceutical and intellectual property legislations recently marked the adoption of the EU Parliament’s position on the new unitary Supplementary Protection Certificate (SPC) system, parallel to the recast of the current Read more

Reform of pharma legislation: the debate on regulatory data protection


by Giuliana Miglierini As the definition of the final contents of many new pieces of the overall revision of the pharmaceutical legislation is approaching, many voices commented the possible impact the new scheme for regulatory data protection (RDP) may have Read more

Environmental sustainability: the EIPG perspective


Piero Iamartino Although the impact of medicines on the environment has been highlighted since the 70s of the last century with the emergence of the first reports of pollution in surface waters, it is only since the beginning of the Read more

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EMA’s reflection paper on AI in the pharmaceutical lifecycle

September 22, 2023 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

by Giuliana Miglierini

The rapidly evolving role of artificial intelligence (AI) and its possible application in the pharmaceutical field led the European Medicines Agency (EMA) to publish a draft Reflection paper on the use of AI along the entire lifecycle of both human and veterinary medicines.

The Reflection paper summarises the current view on the possible use of AI and machine leaning (ML) technologies and is open to public consultation until 31 December 2023. Comments, together with the outcomes of the joint HMA/EMA workshop to be held on 20-21 November 2023, will support its finalisation, as well as the possible development of new guidance. The initiative aims to identify the aspects of AI/ML use that would fall within the remit of EMA or of the single National Competent Authorities (NCAs) in charge of the dossiers’ assessment.

The document is part of the effort to improve the European Medicines Regulatory Network’s capability in data-driven regulation set forth by the joint HMA-EMA Big Data Steering Group (BDSG), and it has been developed in coordination with EMA’s CHMP and CVMP committees.

“The use of artificial intelligence is rapidly developing in society and as regulators we see more and more applications in the field of medicines. AI brings exciting opportunities to generate new insights and improve processes. To embrace them fully, we will need to be prepared for the regulatory challenges presented by this quickly evolving ecosystem” said Jesper Kjær, Director of the Data Analytics Centre at the Danish Medicines Agency and co-chair of the BDSG.

“With this paper, we are opening a dialogue with developers, academics, and other regulators, to discuss ways forward, ensuring that the full potential of these innovations can be realised for the benefit of patients’ and animal health” added Peter Arlett, EMA’s Head of Data Analytics and Methods, co-chair of the BDSG.

The main contents of the Reflection paper

The Reflection paper addresses the use of AI/ML with a dedicated chapter for each one of the steps, part of the overall lifecycle of a medicinal product. The interactions with regulators are then explored, as well as the different technical aspects to be taken into consideration. The final chapters discuss the governance of AI/ML applications, the integrity, and ethical aspects to be considered and how to address data protection.

The increasing use of AI technologies is based on the wide availability of big amounts of data produced and captured in electronic format on a routine basis. This data can be analysed by machine learning algorithms to inform the training of other systems able to analyse data and take actions with some degree of autonomy in order to achieve specific goals. These latter systems are the truly intended AI algorithms, those use is under discussion also in the field of regulatory decision making.

The Reflection paper recalls how the diffusion of these new technologies carries with it also some new risks, due to the “exceptionally great numbers of trainable parameters arranged in non-transparent model architectures”. Measures should thus be taken to ensure the safety of patients and the integrity of data, as well as to avoid the integration of bias into AI/ML applications.

The contents of the Reflection paper may also refer to combinations between a medicinal pro-duct and AI/ML-including medical device, as in such occurrence EMA is involved in the assessment of the characteristics of the device.

In general terms, existing guidelines, best practices, and recommendations relative to model in-formed drug development and biostatistics also apply to AI/ML; the adjacent methodology guidelines which may be relevant to this instance are listed in the document. The Reflection paper warns readers about the differences between the human and veterinary regulatory domains, suggesting that another reflection document specific for veterinary may be developed in future.

A risk-based approach

The usual risk-based approach typical of pharmaceutical development should be used to identify risks throughout the entire AI/ML tool lifecycle, including regulatory impact. According to the Reflection paper, the level of risk may depend also on the context of use and the degree of influence the AI technology exerts.

Developers should always seek early regulatory interaction and scientific advice, especially in cases where the AI/ML system may impact on the benefit-risk ratio of the medicinal product un-der development. To this instance, the EMA Innovation Task Force (ITF) is responsible for pro-viding early interaction on experimental technology, while scientific advice and qualification of novel methodologies in medicines development is provided by the Scientific Advice Working Parties (SAWP) of the CHMP for human medicines and of the CVMP for the veterinary ones.

As for all other steps of pharmaceutical lifecycle, the final responsibility for the suitability and use made of AI/ML algorithms, as well as their compliance to ethical, technical, scientific, and regulatory standards (GxP standards) and to current EMA scientific guidelines falls under the Marketing Authorisation Holders (MAHs) or applicants.

According to the Reflection paper, risks referred to in the discovery step may be limited, but they may impact the final evidence presented for regulatory review, thus principles for non-clinical development should be followed. This second step may include, for example, AI/ML modelling approaches according to the 3R principles. Regulators would expect to receive Standard Operating Procedures (SOPs) for AI/ML applications in preclinical studies; advisory documents on Application of GLP Principles to Computerised Systems and GLP Data Integrity should be also considered where appropriate. A pre-specified analysis plan would be needed for preclinical data potentially relevant for the assessment of the benefit-risk balance.

In the field of clinical trials, ICH E6 and VICH GL9 on human and veterinary GCPs should also be applied to the use of AI/ML. In particular, regulators expect the full model architecture and description of the data processing pipeline would be made fully available for comprehensive assessment should a model be generated for clinical trial purposes, as they would be considered parts of the clinical trial data or trial protocol dossier.

From precision medicine to pharmacovigilance

Particular considerations may be needed for applications of AI/ML in precision medicine, to individualise treatment according to the patient’s characteristics. AI/ML application supporting indication or posology decisions should be referenced in the Summary of product characteristics and their assessment falls under medicines regulation, representing a high-risk use both from the patient and regulatory perspectives. Close human supervision is also expected for AI applications used to draft or translate product information documents.

Many are the possible applications of AI/ML in the manufacturing of medicinal products, where they should follow the usual quality risk management principles (ICH Q8, Q9 and Q10) to guarantee safety, quality, and data integrity. New recommendations are also expected from EMA.

In the post-authorisation phase, AI/ML tools can effectively support efficacy and safety studies and post-marketing surveillance studies for veterinary medicines, as well as pharmacovigilance activities. Good pharmacovigilance practices should always be respected, and the used model should be validated, monitored and documented under the responsibility of the MAH. For conditional marketing authorisations, AI/ML applications should be discussed within a regulatory procedure unless details are agreed already at time of authorisation.


The FDA warns about the manufacture medicinal and non-pharmaceutical products on the same equipment

November 4, 2022 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

by Giuliana Miglierini

A Warning Letter, sent in September 2022 by the US FDA to a German company after an inspection, addresses the possibility to use the same equipment for the manufacturing of pharmaceutical and non-pharmaceutical products. The FDA reject this possibility, that is considered a significant violation of cGMP.

The letter addresses the lack of process validation for the manufacturing of over-the counter (OTC) drugs and of qualification documentation proving acceptance criteria were met and the process was under control. Deficiencies were reflected in the batch records missing important pieces of information. Aspects pertaining cleaning validation were also found critical.

The requests of the FDA

The Warning Letter asks the company to provide the FDA with a full qualification programme of the equipment and facility. This should include a detailed risk assessment for all medicinal products manufactured using shared equipment. Plans are also needed on how to separate the manufacturing areas for pharmaceutical and non-pharmaceutical productions.

Furthermore, the program for cleaning validation should be reviewed to include at least (but not limited to) drugs with higher toxicities or potencies, drugs of lower solubility in their cleaning solvents and that may result difficult to clean. Maximum holding times before cleaning and swabbing locations for areas that are most difficult to clean should be also provided. A retrospective assessment of the cleaning process has to be included in the required CAPA plan; change management for the introduction of new manufacturing equipment or a new product should be also discussed.

The FDA also addressed many other violations, such as the lack of robust laboratory controls, identity testing of incoming raw materials including active ingredients (APIs), and the inability to demonstrate the respect of minimum USP monograph specifications and appropriate microbial limits for drug manufacturing. Management and controls on data integrity were also found deficient.

The European perspective

In the EU, the possibility to use the same equipment and premises for the manufacturing of both pharmaceutical and non-pharmaceutical products can be referred to the provisions set forth by Chapter 3 (Premises and Equipment) of the EU GMPs.

The document clearly states that the “premises and equipment must be located, designed, constructed, adapted and maintained to suit the operations to be carried out. Their layout and design must aim to minimise the risk of errors and permit effective cleaning and maintenance in order to avoid cross-contamination”.

The application of Quality Risk Management principles is used to assess the specific risk of cross-contamination and the consequent measures to be put in place. Dedicated premises and equipment may be needed in some cases, especially if the risk cannot be adequately controlled by operational and/or technical measures, the product has an unfavourable toxicological profile, or relevant residue limits cannot be satisfactorily determined by a validated analytical method. Attention should also be paid to the positioning of equipment and materials, so to avoid confusion between different medicinal products and their components, and to guarantee the correct execution of process controls. Particular provisions are needed in the case dusty materials are used, also with respect to cleaning validation.

All cleaning procedures should be available in written form, designed to allow for an easy and thorough cleaning (including drains, pipework, light fittings, ventilation points and other services). In the case of exposed materials, the interior surfaces of the premises should be smooth and easy to clean and disinfect.

All documentation needed to support the above mention requirements should be prepared according to Chapter 4 (Documentation) of the European GMPs.

EMA’s Guideline on shared facilities

The European Medicines Agency (EMA) published in 2014 a guideline on setting health based exposure limits for use in risk identification in the manufacture of different medicinal products in shared facilities.

Threshold values expressed in terms of Permitted Daily Exposure (PDE) or Threshold of Toxicological Concern (TTC) are the key parameters to be used to run the risk assessment. The so determined threshold levels for APIs can also be used to justify carry over limits used in cleaning validation. EMA’s guideline discusses how to address the determination of the PDE, also with respect to specific types of active substances (e.g. genotoxic, of highly sensitising potential, etc.)

The WHO guidelines

The World Health Organisation released in 2011 its GMP guideline Annex 6 (TRS 961) on the manufacturing of sterile pharmaceutical products. Clean areas are the location of choice for such productions. High-risk operative areas for aseptic manufacturing are classified in Grade A, with Grade B representing their background zones. Grade C and D areas are reserved to less critical steps of the production process.

A frequent and thorough sanitation is important, coupled with disinfection with more than one biocide and/or a sporicidal agent, as appropriate. The effectiveness of the cleaning procedure should be closely monitored to exclude the presence of contaminants, both in the form of vital and not vital particulate.

The guideline specifically mentions the case of preparations containing live microorganisms (such as vaccines), that can be prepared in multiuser facilities only if the manufacturer can demonstrate and validate effective containment and decontamination of the live microorganisms. To transport materials, the conveyor belt should be continuously sterilised as a requirement to pass through a partition between a Grade A/B and a processing area of lower air cleanliness.

A “Comparison of EU GMP Guidelines with WHO Guidelines” was published by the German Federal Ministry for Economic Cooperation and Development (BMZ) to support the understanding of differences between the two approaches, and with a special emphasis to the alleged higher costs of implementation and compliance to EU GMPs.

Analysing the requirements relative to premises and equipment, they aim to guarantee the suitability of rooms to the intended tasks, minimise the risk of failure and cross-contamination and ensure easy cleaning and maintenance. According to the BMZ, EU’s and WHO’s requirements are the same, even if the WHO guideline is more detailed in some aspects (to this instance, the BMZ document was published prior to the release of the new Annex 1 to the GMPs). The theme of equipment is also discussed in other WHO guidelines, i.e. the “WHO good manufacturing practices: starting materials” and the WHO guidelines on transfer of technology in pharmaceutical manufacturing.

Cleaning and sanitation should be addressed according to the provisions set forth by the ISO 14644 family of technical standards. Cleaning validation is also treated in Appendix 3 of the WHO TRS 937 Annex 4. Cleaning validation should be used as the main tool to ensure the removal to pre-established levels of all residues of an API of a product manufactured in any equipment with direct contact to the surface, so that the next product manufactured using the same apparatus would be not cross-contaminated.

According to the BMZ, indications on qualification, process validation and cleaning validation contained in Annex 15 of EU GMPs (paragraph 6) should be integrated with the contents of the ICH Q2 guideline. The only two points of the EU GMPs not covered by the WHO’s guide refer to the allowance that toxic or hazardous substances can be substituted under special conditions for the validation process and the indication that “Test until clean” is not considered an appropriate alternative to cleaning validation.


Revision of the PIC/S GMP Guide: Annex 13 and Annex 16

April 1, 2022 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

by Giuliana Miglierini

The entry into force of EU Regulation 536/2014 “Clinical trials”, at the end of January, resulted in the parallel updating of some international guidelines. In particular, a new version of the GMP Guide PE016 was published by PIC/S (Pharmaceutical Inspection Co-operation Scheme) on 1st February 2022. The revision included Annex 13 on the manufacturing of Investigational Medicinal Products (IMPs), and the new Annex 16 on the certification and batch release to be performed by Authorised Persons (AP) (click here to access all PIC/S guidance related to GMP). The revision of PIC/s guidelines is aimed to reflect the last changes occurred in the corresponding EMA documents, so to maintain the alignment between the two regulatory references (as established by the cooperation agreement between EMA and PIC/S). PIC/S has invited all non- EEA Participating Authorities and applicants to transpose the new Annexes 13 and 16 into their own GMP Guides.

The new Annex 16

Annex 16 represents a completely new addition to the PIC/S GMP guide; the EU Annex 16 (part of the EU GMP Guide) was initially considered to be too EU-specific and difficult to transpose for PIC/S purposes. Following a consultation in 2017, PIC/S Participating Authorities agreed to make an attempt to transpose EU Annex 16, as the adaptation may support a better harmonisation of GMP standards at the international level.

Annex 16 refers to both human and veterinary medicinal products which are subject to the PIC/S Participating Authority or are made for export. Furthermore, the Annex applies to investigational medicinal products for human use, “subject to any difference in the legal provisions and more specific guidance published by PIC/S Participating Authorities under national law”. With reference to imported medicinal products, each PIC/S Participating Authority may independently and voluntary decide whether to adopt the guidance as a legally-binding standard.

Certain types of medicinal products (e.g. blood and immunological products) are not addressed by the Annex, as they are regulated by national laws and fall under the competences of National authorities; to this instance, Annex 16 applies to the certification process performed by the AP and to the subsequent release of the batches.

The marketing authorisation holder (MAH) remains the sole responsible for the safety, quality and efficacy of the marketed products. Authorised Persons are required to check each single batch to verify compliance to national and GMP requirements, as well as to those detailed within the marketing authorisation (MA). After certification by the AP, batches of finished products can be transferred to saleable stock and/or export. Specific and documented agreements are needed should this require transfer to a site different from the certification’s one. Authorised Persons should be clearly identifiable, with reference to any quality defect leading to investigation or batch recall. APs certifying the release of the finished product are responsible for verifying the conditions of storage and transport for the batch and the sample, if sent separately, and of all testing required upon importation (including sampling, where needed).

A formal Quality Risk Management (QRM) process is required when sampling is performed at a manufacturing site located in another jurisdiction; Annex 16 provides detailed guidance on the elements to be considered in this exercise. Documentation of the continuous training received by the AP in charge of certification and batch release should be always available, with specific reference to the product type, production processes, technical advances and changes to GMP.

Annex 16 provides detailed guidance on how to conduct the process of certification of each batch of finished product, independently of the number of sites involved. With reference to specific manufacturing or control steps performed at different sites, their respective AP has to provide confirmation of the performed activities, sharing responsibilities with the AP in charge of the final batch release.

The certification process should take into consideration the entire supply chain of both the active substance and the finished product, including manufacturing sites of the starting and packaging materials. The AP responsible for certification should be able to access results of the audits performed at the sites involved, in order to check the consistency of all activities with those described in the MA and within GMPs. Audits run by third parties should reflect requirements set forth in Chapter 7 of the PIC/S GMP Guide.

In particular, suppliers of active substances should comply with GMP and GDP requirements relating to the supply of the active ingredient used to the finished product manufacturing. Excipients should also fulfil GMP requirements, and be possibly manufactured and supplied in accordance with the PI 045-1 guideline. Specific guidance may also apply for other types of products, i.e. biological active substances and medicinal products for human use or radiopharmaceuticals. Annex 16 provides templates for the confirmation letters to be used for the partial manufacturing of a medicinal product and for the content of Batch Certificates.

The revision of Annex 13

Annex 13 has been revised in order to reflect the contents of the new EU Regulation n. 536/2014 on clinical trials, which will replace EU Annex 13. PIC/S Annex 13 discusses the manufacturing of Investigational Medicinal Products (IMP), apart from the reconstitution phase, which is not considered to be part of the process. Provisions set forth by Annex 13 should be taken into consideration with reference to the re-labelling or re-packaging of IMPs and to the preparation of radiopharmaceuticals used as diagnostic investigational medicinal products, occurring in hospitals, health centres or clinics and performed by pharmacists or other persons legally authorised in the country concerned.

All activities should refer to an appropriate Pharmaceutical Quality System to be in place, according to requirements set forth in Chapter 1 of Part 1 of the PIC/S GMP Guide.

 The characteristics of IMPs may intrinsically evolve along the development process, as new data become available that may require changes to, for example, the formulation or the dosage form. This has to be reflected into the respective product specifications and manufacturing instructions, that should also evolve in parallel and be fully traceable and documented. Annex 13 indicates that all deviations should be registered and investigated, and preventive and corrective actions put in place. The new Annex provides detailed guidance on the different items to be considered within the product specification file, as well as for the proper management of personnel, premises and equipment.

All the documentation generated during the clinical development phases should fulfil requirements specified by the PIC/S GMP Guide, Part I, Chapter 4. To this instance, relevant documentation includes specifications and instructions, orders, manufacturing formulae and processing instructions, packaging instructions and batch records. Detailed guidance is provided also for production, including packaging materials and manufacturing operations, the modification of comparator products, blinding operations, and the packaging and labelling of the IMP. Annex 13 also offers guidance on how to perform quality control and batch release, and how to address outsourced operations, complaints and recalls and or the destruction of batches of IMP products.


The new PIC/S guideline on data integrity

July 30, 2021 , , , , , , , , , , , , , , ,

by Giuliana Miglierini

The long waited new PIC/S guideline PI 041-1 has been finally released on July 1st; the document defines the “Good Practices for Data Management and Data Integrity in regulated GMP/GDP Environments”, and it represents the final evolution of the debate, after the 2nd draft published in August 2016 and the 3rd one of November 2018.
While maintaining the previous structure, comprehensive of 14 chapters for a total of 63 pages, some modifications occurred in the subchapters. The Pharmaceutical Inspection Co-operation Scheme (PIC/S) groups inspectors from more than 50 countries. PIC/S guidelines are specifically aimed to support the inspectors’ work, providing a harmonised approach to GMP/GDP inspections to manufacturing sites for APIs and medicinal products.

Data integrity is a fundamental aspect of inspections
“The effectiveness of these inspection processes is determined by the reliability of the evidence provided to the inspector and ultimately the integrity of the underlying data. It is critical to the inspection process that inspectors can determine and fully rely on the accuracy and completeness of evidence and records presented to them”, states the Guideline’s Introduction.
This is even more true after the transformation impressed by the pandemic, resulting in a strong acceleration towards digitalisation of all activities. The huge amount of data produced every day during all aspects of the manufacturing and distribution of pharmaceutical products needs robust data management practices to be in place in order to provide adequate data policy, documentation, quality and security. According to the Guideline, all practices used by a manufacturer “should ensure that data is attributable, legible, contemporaneous, original, accurate, complete, consistent, enduring, and available”. This means also that the same principles outlined by PIC/S may be used also to improve the quality of data used to prepare the registration dossier and to define control strategies and specifications for the API and drug product.
The guidance applies to on-site assessments, which are normally required for data verification and evidence of operational compliance with procedures. In the case of remote (desktop) inspections, as occurred for example during the pandemic period, its impact will be limited to an assessment of data governance systems. PIC/S also highlights that the guideline “is not intended to provide specific guidance for ‘for-cause’ inspections following detection of significant data integrity vulnerabilities where forensic expertise may be required”.

The impact on the entire PQS
PIC/S defines data Integrity as “the degree to which data are complete, consistent, accurate, trustworthy, and reliable and that these characteristics of the data are maintained throughout the data life cycle”.
This means that the principles expressed by the guideline should be considered with respect to the entire Pharmaceutical Quality System (and to the Quality System according to GDPs), both for electronic, paper-based and hybrid systems for data production, and fall under the full responsibility of the manufacturer or the distributor undergoing the inspection.
The new guidance will represent the baseline for inspectors to plan risk-based inspections relative to good data management practices and risk-based control strategies for data, and will help the industry to prepare to meet the expected quality for data integrity, providing guidance on the interpretation of existing GMP/GDP requirements relating to current industry data management practices without imposition of additional regulatory burden. PIC/S highlights that the new guidance is not mandatory or enforceable under the law, thus each manufacturer or distributor is free to voluntarily choose to follow its indications.

Principles for data governance
The establishment of a data governance system, even if not mandatory, according to PIC/S would support the company to coherently define its data integrity risk management activities. All passages typical of the data lifecycle should be considered, including generation, processing, reporting, checking, decision-making, storage and elimination of data at the end of the retention period.
“Data relating to a product or process may cross various boundaries within the lifecycle. This may include data transfer between paper-based and computerised systems, or between different organisational boundaries; both internal (e.g. between production, QC and QA) and external (e.g. between service providers or contract givers and acceptors)”, warns PIC/S.
Chapter 7 specifically discusses the Good document management practices (GdocPs) expected to be applied, that can be summarised by the acronyms ALCOA (Attributable, Legible, Contemporaneous, Original, Accurate) and ALCOA+ (the previous plus Complete, Consistent, Enduring and Available).
Data governance systems should take into consideration data ownership and the design, operation and monitoring of processes and systems. Controls should include both operational (e.g. procedures, training, routine, periodic surveillance, etc) and technical features (e,g, computerised system validation, qualification and control, automation or other technologies to provide control of data). The entire organisation should commit to the adoption of the new data culture, under a top-down approach starting from the Senior management and with evidence provided of communication of expectations to personnel at all levels. Sections 6 of the guideline provides some examples in this direction. The ICH Q9 principles on quality risk management should be used to guide the implementation of data governance systems and risk minimisation activities, under the responsibility of the Senior management. Efforts in this direction should always be commensurate with the risk to product quality, and balanced with other quality resource demands. In particular, the risk evaluation should consider the criticality of data and their associated risk; the guideline provides an outline of how to approach the evaluation of both these factors (paragraphs 5.4 and 5.5). Indication is also provided on how to assess the effectiveness of data integrity control measures (par. 5.6) during internal audit or other periodic review processes.
Chapter 8 addresses the specific issues to be considered with respect to data integrity for paperbased systems, while those related to computerised systems are discussed in Chapter 9. As many activities typical of the pharmaceutical lifecycle are normally outsourced to contract development & manufacturing organisations (i.e. API manufacturing, formulation, analytical controls, distribution, etc.), PIC/S also considered in the guideline the aspects impacting on the data integrity of the overall supply chain (Chapt. 10). “Initial and periodic re-qualification of supply chain partners and outsourced activities should include consideration of data integrity risks and appropriate control measures”, says the guideline.

The regulatory impact of data integrity
Recent years have seen the issuance of many deficiency letters due to problems with data integrity,. Approx. half (42, 49%) of the total 85 GMP warning letters issued by the FDA in 2018, for example, included a data integrity component.
The new PIC/S guideline provides a detailed cross-reference table linking requirements for data integrity to those referring to the other guidelines on GMPs/GDPs for medicinal products (Chapter 11). Guidance on the classification of deficiencies is also included in the document, in order to support consistency in reporting and classification of data integrity deficiencies. PIC/S notes that this part of the guidance “is not intended to affect the inspecting authority’s ability to act according to its internal policies or national regulatory frameworks”.
Deficiencies may refer to a significant risk for human or animal health, may be the result of fraud, misrepresentation or falsification of products or data, or of a bad practice, or may represent an opportunity for failure (without evidence of actual failure) due to absence of the required data control measures. They are classified according to their impact, as critical, major and other deficiencies.
Chapter 12 provides insight on how to plan for the remediation of data integrity failures, starting from the attention required to solve immediate issues and their associated risks. The guideline lists the elements to be included in the comprehensive investigation to be put in place by the manufacturer, as well as the corrective and preventive actions (CAPA) taken to address the data integrity vulnerabilities. A Glossary is also provided at the end of the guideline.