precision Archives - European Industrial Pharmacists Group (EIPG)

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

How AI is Changing the Pharma Industry and the Industrial Pharmacist’s Role

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Svala Anni, Favard Théo, O´Grady David

The pharmaceutical sector is experiencing a major transformation, propelled by groundbreaking drug discoveries and advanced technology. As development costs in the pharmaceutical industry exceed $100 billion in the U.S. in 2022, there is a pressing need for innovative solutions to accelerate drug development. The urgency stems from a renewed focus on novel approaches, driven by the complexities of advanced therapeutic modalities like mRNA, CGT, and synthorins. This blog delves into the influence of Artificial Intelligence (AI) on overcoming the unique hurdles within the manufacturing domain of the pharmaceutical industry. It specifically emphasizes the crucial partnership between AI and human expertise, shedding light on the vital role of industrial pharmacists in optimizing manufacturing processes.

The demands for precision, quality, and compliance in pharmaceutical manufacturing present challenges, notably in managing rising costs and intricate logistical processes. The adoption of various AI technologies, including generative AI (GenAI), represents a strategic shift, aiming to augment human capabilities while automating routine tasks and facilitating knowledge transfer in the ever-evolving landscape of pharmaceutical production

The fourth industrial revolution is upon us with the development of cyber physical systems and the fifth industrial revolution is on the horizon with the advancement of artificial intelligence (AI) in partnership with humans to enhance workplace processes. The factory of the future is here with digitalization, AI, Big data, robotics and advanced manufacturing becoming the norm rather than the exception in the pharmaceutical industry.

GenAI excels in promoting collaboration while surpassing traditional task automation. It is key in transmitting complex knowledge crucial for maintaining quality, compliance, and safety in pharmaceutical manufacturing. AI empowers experts to document processes using everyday devices, transforming this raw data into straightforward, visual instructional guides.

The pharmaceutical industry confronts distinct manufacturing challenges, including complex processes and rigorous regulatory standards. AI can offer several innovative and compliant solutions. In addition, AI platforms swiftly update training materials, creating dynamic learning environments that keep the workforce informed about the latest developments. These platforms are redefining roles by taking over mundane tasks, thereby freeing human workers to focus on more strategic and creative roles. Furthermore, AI guarantees uniform training across global operations, ensuring consistent processes and fostering global standardization.

Combining humans and AI creates a powerful team that may benefit everyone. AI helps make learning experiences unique for each person, fitting their own way of learning. It also makes it easy for people to get the information they need anytime, thanks to the latest tech advancements. AI is great at helping people from different cultures and who speak different languages work together better. It can give feedback right away, so mistakes don’t spread. Plus, AI holds onto valuable knowledge, reducing the chance of losing important information when people leave or retire. Together, all these benefits show how AI can make a big, notable change also in the pharmaceutical field.

AI – Shaping the Future of Pharmaceutical Industry

AI is transforming the pharmaceutical landscape, particularly in areas vital to industrial pharmacists, such as manufacturing, quality control, and distribution. These professionals play a pivotal role in skillfully integrating AI, serving as the human-in-the-loop to enhance efficiency and ensure safety in pharmaceutical operations.

AI elevates the manufacturing process, forecasts maintenance needs, and sharpens quality control. Industrial pharmacists are pivotal in deploying these AI-driven techniques, ensuring that operations are not only effective but also meet high-quality standards and regulatory requirements.

The Role of Industrial Pharmacists

Industrial pharmacists are essential contributors to this technological revolution, actively collaborating with data engineers and scientists. They play a pivotal role in ensuring regulatory compliance, upholding product quality, and leveraging AI to enhance drug development processes, inventory management, and distribution. Industrial pharmacists:

  • are essential in incorporating AI into manufacturing workflows.
  • ensure AI tools align with regulatory requirements and uphold product quality.
  • utilize AI to accelerate and economize the drug development process.
  • leverage AI for more effective inventory and distribution management.
  • analyze data generated by AI systems for informed decision-making in production and quality control.
  • ensuring the quality of pharmaceutical products, they play a crucial role in safeguarding patient safety.
  • leverage AI to identify eco-friendly manufacturing practices, contributing to sustainable pharmaceutical production.

Risks and Challenges

Using AI in the pharmaceutical environment involves navigating risks such as ensuring data privacy and security, maintaining regulatory compliance, addressing biases and ethical concerns, and dealing with the quality and reliability of data. Additionally, there are challenges related to intellectual property issues, integration with existing systems, scalability and maintenance, and dependence on external vendors. To effectively leverage AI benefits while minimizing these risks, a comprehensive strategy encompassing robust data governance, ethical AI practices, ongoing regulatory engagement, and careful technological and organizational change management is essential.

Conclusion

The pharmaceutical industry stands on the brink of a transformative era, driven by the profound potential of AI to reshape its landscape. The key to unlocking this potential lies in the proactive involvement of industrial pharmacists, who are urged to assume a more strategic and leading role in steering innovation.

Traditionally perceived as followers, industrial pharmacists now face a pivotal moment to transition into drivers of change. This isn’t merely a shift in perception; it is a call to action. The integration of AI offers a unique opportunity for pharmacists to shape the future of pharmaceutical care actively and courageously.

In this evolving landscape, industrial pharmacists are not just guardians of compliance but architects of efficiency, adaptability, and innovation. Collaborating seamlessly with AI technologies, they hold the power to propel the industry forward. Despite certain challenges, this collaboration looks promising – it isn`t just compliant and efficient but also dynamic and inventive.

The call to action is clear – pharmacists, especially those in industrial roles, are not merely spectators in this technological revolution; they are the forerunners, charting a course towards a more responsive and innovative pharmaceutical future.

References:

Artificial trends: intelligence in the pharmaceutical industry: analyzing, innovation, investment and hiring

Insights to the Industrial Pharmacist role for the future: A concept paper from EIPG Advisory Group on Competencies, vol 2, 2023

Pizoń J, Gola A. Human–Machine Relationship—Perspective and Future Roadmap for Industry 5.0 Solutions. Machines. 2023; 11(2):203.

Zheng, S. (2023, Nov. 2). “Empowering the pharma workforce.” Pharma Manufacturing.

Contact for further information:
Anni Svala, Vice-President for European Affairs, European Industrial Pharmacists Group, [email protected]


Comments to the draft ICH guidelines Q2(R2) and ICH Q14

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by Giuliana Miglierini

The public consultation on the two draft guidelines ICH Q2(R2) on the validation of analytical procedures and ICH Q14 on analytical procedure development closed at the end of July 2022.The European Medicines Agency published in August two documents summarising comments received (ICH Q2(R2) and ICH Q14).

Many industrial organisations contributed to the consultation with their point of view on the two draft guidelines. In the next phase of the procedure (step 3 of the ICH process), comments will be reviewed by the ICH Q2(R2)/ICH Q14 Expert Working Group (EWG). We summarise for readers some of the main comments received from industrial stakeholders. A webinar organised byEIPG on the implications and opportunities of the revision of ICHQ2 and the ICHQ14 was presented by Dr Phil Borman, Senior Fellow & Director Product Quality at GSK on 15thJune 2022 (recording and slides are available at the webinars page of EIPG’s website).

Key principles from the EIPG’s webinar

During the webinar, Dr Borman gave a comprehensive picture of the process of Analytical Quality by Design (QbD). The systematic approach to method development starts with the identification of the predefined objectives (Analytical Target Profile, ATP). The understanding and control of the analytical procedure are at the core of the process, and they should be pursued according to principles of ICH Q8. Analytical QbD covers both the drug product (ICH Q8) and the active ingredient (Q11). This means that a similar framework to ICH Q8 and Q11 can be applied also for analytical procedures. The ATP is made up of the sum of performance characteristics, precision, range (including sensitivity), and bias/accuracy.

According to ICH Q2(R1), published in 1994, the objective of validation of an analytical procedure is to demonstrate its suitability for the intended scope. Revision of both guidelines started in 2019, based on a Concept paper published in 2018. ICH Q2(R2) covers the validation of the analytical protocols and reports, while ICH Q14 refers to the development of the analytical procedure and its lifecycle management.

Key features of the new drafts include the fact that no additional expectations / mandated requirements for pharmaceutical analytical scientists are present, the possible use of “enhanced approaches” and the clear link between performance characteristics and their related criteria and the validation study. The Q2(R2) guideline shall apply to both small molecules and biologics and includes the possibility to use prior knowledge (e.g., from development or previous validation) as a part of the validation exercise. Assay for the determination of robustness can be conducted, for example, during development. Other key features highlighted by Dr Borman include the possible use of Platform analytical procedures to reduce the number of validation tests and the possibility to use any type of calibration model (including multivariate calibration).

The expected benefits refer to the possibility to reduce the existing burden associated with post-approval changes to analytical procedures and the use of Established Conditions.

As Dr Borman explained, the ATP could form the basis of a Post Approval Change Management Protocol (PACMP), thus favouring the reporting of changes between technologies at a lower reporting category. A more performance driven and flexible approach to validation is expected following the entry into force of the new ICH Q2(R2) guideline. The selection of validation tests shall be based on the concrete objective of the analytical procedure.

Comments to ICH Q2(R2)

The overview of comments relative to the draft ICH Q2(R2) published by EMA consists of a 72-page document, divided into a first section containing general comments and a second focused on specific comments.

APIC, representing manufacturers of active ingredients and API intermediates, focused on the fact that “uncertainty is not part of the validation whereas it has a reality in practice and part of the discussion between laboratories”. The measurement of uncertainty is also considered linked to the Total analytical error (TAE), a concept that would not be adequately addressed in the guideline.

EFPIA, on behalf of the biopharmaceutical industry, asked for a better connection between the two guidelines ICH Q2 and Q14, starting from the alignment of the respective titles. Improved consistency in the use of some terms was also suggested (e.g. ‘performance criteria’). Improved clarity and greater flexibility should be applied to the concept of working and reportable ranges. The association also asked to provide more examples for multivariate analytical procedures using different models to facilitate the understanding of their validation and lifecycle management.

Medicines for Europe, representing manufacturers of generic and biosimilars, asked to provide a more specific methodology for reportable range validation. The association requested some clarification about the possibility of using the minimal requirements of the performance characteristics for the addendum method validation strategy.

The European Association of Nuclear Medicine (EANM) focused its intervention of radiopharmaceuticals, a class of substances that should be considered a special case and therefore be excluded from the scope of the guidance. The request assumes that other approaches different that those discussed may be applicable and “acceptable with appropriate science-based justification”. The same request also applies to the draft ICH Q14 guideline. The EANM contribution also highlighted aspects specific to radiopharmaceuticals that should be considered, including the strength of the radioactivity content, the unavailability of radioactive standards of the active substance, and the need of specific techniques for radioactivity determination. The suggestion is to refer to the specific guideline on the validation of analytical methods for radiopharmaceuticals jointly developed by the EANM and the EDQM.

According to the International Society for Pharmaceutical Engineering (ISPE), there are many sections of the draft Q2(R2) guideline that may pose challenges due to lack of alignment and fragmentation of contents. A revision of the structure is thus suggested, together with the harmonisation of terms with those listed in the Glossary. ISPE also highlighted the opportunity to better clarify the distinction between validation elements and recommended data applicable to multivariate analytical procedures vs traditional analytical methods.

The ECA Foundation/European QP Association reported a very critical position on the two draft guidelines, clearly stating that ICH Q2 and Q14 should integrate with one another. According to ECA, the corresponding US guideline “USP <1220> is far superior”. Many of the points reported above with respect to the general section of the overview are discussed in more deep detail within the part of the document listing specific comments.

Comments to ICH Q14

The same structure of the document also applies to the 54-page overview summarising the results of the consultation on ICH Q14 guideline.

According to the Plasma Protein Therapeutics Association (PPTA), representing manufacturers of plasma-derived and recombinant analog therapies, the draft would be too focused on chemical methods, with just a residual attention to biological methods.

APIC asked for improved discussion of the capability (and uncertainty) of the method of analysis, a fundamental parameter to assess its appropriateness for the intended use within the defined specification range. According to the association, more specific reference should be made in relation to development data that can be/cannot be used as validation data.

ISPE suggested adopting a more detailed title for the guideline; something similar has also been suggested by EFPIA. ISPE also addressed the issue of reproducibility, that may be influenced by external factors across multiple laboratories. Multivariate analysis is also discussed, suggesting adopting additional requirements for the multivariate elements while maintaining the same approach to other analytical procedures.

EFPIA would prefer to avoid the use of the term “minimal” in favour of other expressions denoted by a less negative connotation (e.g., traditional, suitable/historic, classical, fit for purpose) with reference to the validation approach. The availability of training case studies is considered important to support the alignment between industry and regulatory agencies on expectations for regulatory change management, especially with reference to multivariate models. EFPIA asked that the paragraph discussing the relationship between ICH Q2 and Q14 should not address what should be submitted to regulatory agencies. Discussion of OMICS methods used in quality control of complex biological products should be included in the annexes.

ISPE asked to avoid reference to geographic regions, as the final goal is to reach harmonisation. A clearer statement of the scope would be advisable (a possible example is provided), as well as a better linkage to the ICH Q12 guideline on pharmaceutical product lifecycle management.

Specific comments include the suggestion of the PPTA to define all acronyms at first use in text and to include them in the Glossary. According to Medicines for Europe, it would be advisable to add characterisational assays (other than release/stability) for biosimilars. Furthermore, the scope of the guideline should focus on the risk assessment and availability of the analytical knowledge needed to select the most appropriate method for a specific application. Activities deemed to the submission of the regulatory CTD dossier should remain confined to the complementaryQ2 guideline.