Guest Column | March 22, 2024

Fine-tuning Analytical Development Strategies For Every Phase

By Gerald Gellermann, Stephan Kirsch, and John den Engelsman, Novartis Technical Research and Development

Medical Research, Phases of Vaccine Clinical Trials-GettyImages-1292613072

Product and process understanding are the fundaments for a successful commercial product control strategy. They enable a continuous lean, robust supply and additionally should provide sufficient flexibility for necessary improvements or innovation during long commercial life cycles. Consequently, tailored analytical development strategies are essential throughout the development life cycle of a program.

Most pharmaceutical companies develop multiple drug candidates in parallel. However, drug development is notoriously faced with high attrition rates of candidates, as almost 90% of drugs (all modalities) in clinical development fail.1 Therefore, companies have to make investments with a high uncertainty factor for ultimate market approval and the return on these investments.

For chemistry, manufacturing, and controls (CMC) development, this requires finding the right balance between ensuring clinical supply continuity for multiple drugs and at-risk investments to generate in-depth product and process knowledge to establish a robust analytical commercial control strategy.

In the early phases of drug development, often a multitude of molecular formats exist that need to be evaluated quickly for viability to become a full-blown development candidate. For an analytical development organization, this provides significant challenges to remain sustainable, i.e., how do we balance the available resources to provide only the essential and necessary quality information for a safe first-in-human clinical trial?

In later phases of development, volumes of analytical samples to be tested become a challenge. For analytical development, it is then key to establish robust and smart approaches to determine the actual performance of the analytical methods, which, ultimately, is the basis for filing the control strategy. Especially when an organization is faced with a successful late-phase pipeline, companies typically employ a diversification strategy where part of the portfolio is run internally, while other parts are run in collaboration with strategic partners, giving them a tool to flex the capacity in case of significant demand fluctuations.

Lastly, when a product is launched and enters its commercial life cycle, the performance of the analytical methods needs to be maintained and even improved over time to keep on ensuring appropriate release of commercial batches. However, changing analytical procedures, if required, is a long, tedious, and expensive undertaking.

In summary, across the lifetime of a (potential) drug, analytical development is faced with significant challenges that are different per the phase the drug candidate is in. Therefore, companies must employ smart analytical strategies that balance the available resources with creating enough process and product understanding per (development) phase.

Analytical Approaches To Increase Speed And Efficiency In Early Clinical Phases

Analytical quality control for clinical trial material focuses on demonstrating consistency of manufactured batches to toxicological material and later to the first clinical batches. In this context, the application of analytical platform procedures (i.e., procedures that can be applied to different molecules with little or no modification) is a widely used concept. This significantly lowers the amount of work required for procedure development of a new molecule entering the development pipeline, as only the suitability of the existing well understood and pre-validated platform procedure has to be demonstrated. Therefore, a platform approach should not be limited to applying an existing procedure to a new molecule but rather should be used to translate into a more systematic method development approach and method design that ensures flexibility and broad applicability for future molecules.

This concept can be enabled through the definition of an analytical target profile (ATP) as described in ICH Q142— which the FDA published this month as a final guidance — and USP <1220>.3 The ATP defines the performance requirements and the purpose (e.g., link to the critical quality attribute (CQA)) that is intended for an analytical procedure and a particular molecule.

While product specifications will typically still change through the different steps of clinical development, the platform approach will help to benchmark the performance of a procedure with a new molecule compared to other/further progressed products. On this basis, potential needs for molecule-specific performance improvements can be anticipated and planned for the next project milestones.

A platform focus for analytical procedures also creates synergies for automation and digitalization. A high degree of standardization of procedures across the portfolio is also helpful to increase flexibility to run analyses for different products on the same automated systems in parallel. This also ensures efficient use of available systems and maximized return on investments. At the same time, standardization is also an important element for digitalization. Applying standardized platform technologies improves the harmonization of data generated across different molecules, increases their reusability, and creates opportunities for data mining and empirical modeling over time.    

Nevertheless, the platform approach also comes with certain downsides and risks, especially in early development phases where the characterization and assessment of CQAs is only preliminary. Not all product attributes that have a high risk to become a liability might be covered or individually reported in the respective platform methods.

The application of molecular and structural models as well as “digital twins” is an efficient approach to mitigate and overcome limitations in product understanding. On this basis, the need for more tailored analytical procedures, e.g., to monitor specific sequence motifs that are prone to impact the function or stability of the molecule can be identified and initiated in a data-informed, risk-adjusted, and phase-appropriate manner.

Managing Sample Volumes — And Getting The Best Out Of Them — When Projects Progress

As a project progresses through the development phases, increased process and product understanding is needed and thus sample volumes significantly increase. For analytical development, the key challenges in this phase include:

  1. managing high numbers of analyses and volatile resource demands,
  2. ensuring that increased product and process understanding is continuously feeding into the performance requirements of analytical methods, and
  3. ensuring robustness of analytical procedures for final validation and transfer.

Increasing sample volumes over the different phases of development is generally a challenge. On the other hand, this also presents a great opportunity. Increased throughput translates into increased sample diversity, used instruments, involved operators, used reagent lots, etc. Thorough evaluation of data will improve method understanding and optimization needs and help to address the second and third challenge mentioned earlier (product process understanding informing analytical methods and robust analytical procedures enabling validation and transfer).

Especially in combination with the ATP, these data can ensure the continued balance between performance needs and capabilities of an analytical procedure. The linkage of the ATP to the products’ CQAs thereby ensures that changes in product understanding are addressed by appropriate methods.

The definitions of analytical performance requirements in the ATP are based on analytical specifications, and process capability allows benchmarking with actual method variability derived from trending data. This enables a continuous assessment of method suitability and validation readiness.

Moreover, the ATP can also be useful in the context of procedure development and outsourcing as a typical diversification strategy to cope with increasing sample throughput. The definition of the required analytical procedure performance helps to align on a common goal and therefore can be a part of the contract for outsourced procedure development. However, the selection of work packages to be outsourced should not be driven only by demand. Also, the predictability of certain work packages, the novelty and proprietary knowledge involved in the activities, as well as the flexibility of the partner organization for prioritization of urgent activities and accessibility of raw data should be carefully considered,4 Hence, there is no general blueprint that can be applied as the optimal balance of the different aspects, as it will always depend on a broad spectrum of parameters and the overall company strategy.

Maximizing Flexibility For Commercial Procedures.

For market applications, regulators usually require a very detailed description of analytical procedures. This is primarily needed to judge the suitability of the procedures for their intended purpose of controlling a critical attribute and, secondly, to address potential country requirements to perform testing of incoming goods by the local authorities. Hence, updating an analytical procedure in the common technical document typically requires health authority oversight.

In a complex regulatory landscape, where major therapies are approved in several different countries, changing an analytical procedure is quite cumbersome. Post-approval change (PAC) submissions occur quite frequently and require substantial efforts and costs.

Based on an evaluation of 6,000 changes Novartis conducted on different commercial products, roughly 55% of the changes were categorized as regulatory-relevant. This required a submission of almost 90,000 variations in the different countries where the evaluated products were marketed. Roughly 43% of these variations were related to analytical procedures. The biggest challenge here is if the variation is in the regulatory “high notification” category.5 This category means that a change requires prior approval; however, the outcome and the timing of the approval in different countries is not always predictable. Until approval from all authorities is received, a change cannot be closed. In addition, the submission of more than one change at a time of the high-notification category (e.g., manufacturing and analytical) is often prohibited by country-specific requirements for the same product.

For quality control, it can therefore happen that, in order to measure the same quality attribute, two procedures or technologies must be maintained in parallel over several years. Consequently, changes that are not required to ensure the continuation of the established quality control but rather could provide improvements — e.g., for decreasing the carbon footprint or user-friendliness and robustness — often must be deprioritized.  

ICH Q14 offers potential opportunities for flexibility in this context if the “enhanced procedure development” approach is followed, and appropriate procedure and control strategy understanding can be demonstrated. The fundamentals for this flexibility are already laid out in the initial submission with the definition for those established conditions that are critical for ensuring sufficient procedure performance for a quality batch release decision. In turn, this might offer significantly increased flexibility during the commercial life cycle of all other analytical parameters that do not impact procedure performance or have a well-described control strategy.

The ATP can be regarded as a summary of these measurement requirements for a relevant quality attribute and can be used for communicating the understanding of the performance requirements in the context of the control strategy in the dossier. Changes where adherence to the ATP is demonstrated by respective protocol-assisted bridging studies have low risks and they therefore should be allowed to be implemented without the need to wait for an approval.6 This would help to increase flexibility for changes that are meant to innovate and to decrease the environmental footprint by implementing leaner, faster, or miniaturized methods during the longest commercial phase of a product life cycle.

Conclusion

Analytical development in the pharmaceutical industry is challenged with managing a highly volatile portfolio in a very flexible and phase-appropriate manner. As return on investment only comes with commercialization and brand maximization, it is of high importance for the analytical development unit to meet the right time and decision point for full investments to generate the necessary product and process knowledge for the commercial phase.

The ATP can be used as an anchor point throughout the entire product development life cycle. It helps not only to guide procedure development but can also be used as a contract with an external development partner as well as an agreement of established conditions for the required analytical performance in a regulatory market application. Through this, it enables the needed regulatory flexibility during the commercial phase.

References:

  1. Su, D., Gao, W., Hu, H and Zhou, S. Why 90% of Clinical Drug Development Fails and How to Improve It? 2022 , Acta Pharm Sin B , Vol. 12(6), 3049-3062 doi: 10.1016/j.apsb.2022.02.002
  2. ICHQ14: Analytical Procedure Development, available on internet: ICH_Q14_Guideline_2023_1116.pdf)
  3. <1220> Analytical Procedure Lifecycle [Internet]. United States Pharmacopeia; 2022 [cited 2022 Jul 14]. Available from: https://www.uspnf.com/sites/default/files/usp_pdf/EN/USPNF/usp-nf-notices/gc-1220-pre-post-20210924.pdf
  4. Fahie B, Guggenheim E. The Business Challenges of Externalizing R&D. Scientific Computing 14 December 2015; www. scientificcomputing.com/article/2015/12/business-challenges-externalizing-rd
  5. ICHQ12: Lifecycle Management: Available from: Q12_Guideline_Step4_2019_1119.pdf (ich.org)
  6. Simeoni P, Deissler M, Bienert R, Gritsch M, Nerkamp J, Kirsch S, Roesli C, Pohl T, Anderka O, Gellermann G. Using enhanced development tools offered by analytical Quality by Design to support switching of a quality control method. Biotechnol Bioeng. 2023 Nov;120(11):3299-3310. doi: 10.1002/bit.28517. Epub 2023 Aug 1. PMID: 37526307.)).

About The Authors:

Gerald Gellermann works as a scientific officer at Novartis Analytical Development and, among other activities, leads initiatives related to the implementation of new ICH guidelines, such as ICH Q12 and Q14. Gerald holds a Ph.D. in molecular biology from the University of Jena, Germany.


Stephan Kirsch leads the Scientific Office in Analytical Development and has a strong focus on quality by design, CMC development, and analytical technologies. He holds Ph.D. in biochemistry from the University of Münster, Germany.





John den Engelsman leads the Process Analytical Sciences organization focusing on physicochemical analytical technologies and approaches to generate process and product knowledge. He is trained as a molecular cell biologist and holds a Ph.D. in biochemistry from the University of Nijmegen, The Netherlands.