Timothy J. N. Watson

API Quality by Design Example from the Torcetrapib Manufacturing Process

The concept and application of quality by design (QbD) principles has been and will undoubtedly continue to be an evolving topic in the pharmaceutical industry. However, there are few and limited examples that demonstrate the actual practice of incorporating QbD assessments, especially for active pharmaceutical ingredients (API) manufacturing processes described in regulatory submissions. We recognize there are some inherent and fundamental differences in developing QbD approaches for drug substance (or API) vs drug product manufacturing processes. In particular, the development of relevant process understanding for API manufacturing is somewhat challenging relative to criteria outlined in ICH Q8 (http://www.ich.org/cache/compo/276–254–1.html) guidelines, which are primarily oriented toward application of QbD for drug product manufacturing. This position paper provides a perspective of QbD application for API manufacture using an example from the torcetrapib API manufacturing process. The work includes a risk assessment, examples of multivariate design, and a proposed criticality assessment, all of which coalesce into an example of design space. Torcetrapib was a project in phase III development as a potent and selective inhibitor of cholesteryl ester transfer protein before being terminated in late 2006. The intent of Pfizer was to submit torcetrapib under the QbD paradigm (route selection, robustness, and reagent/solvent selection during phases I to III are significantly important in establishing a manufacturing process that would have the most flexibility in the final design space. For more information on this development phase for torcetrapib see Damon et al., Org Process Res Dev, 10(3):464–71, 2006, Org Process Res Dev, 10(3):472–80, 2006).

Assessment of coronary fractional flow reserve using a monorail pressure catheter: the first-in-human ACCESS-NZ trial.

AIMS FFR measurements have been limited by the handling characteristics of pressure wire (PW) systems, and by signal drift. This first-in-human study evaluated the safety and efficacy of a new monorail catheter (Navvus) to assess coronary FFR, compared to a PW system. METHODS AND RESULTS Resting measurements were acquired with both systems. After initiating IV adenosine, FFR was measured with the PW alone, simultaneously using both systems, and again with PW alone. Any zero offset of PW or Navvus was then recorded. Navvus measured FFR in all patients in whom a PW recording was obtained (50 of 58 patients); there were no complications related to Navvus. Navvus FFR correlated well with PW FFR (r=0.87, slope 1.0, intercept -0.02). Within PW measurement accuracy, in no cases did Navvus FFR classify lesion significance differently from PW FFR. PW signal drift was significantly greater than Navvus (0.06±0.12 vs. 0.02±0.02, p=0.014). CONCLUSIONS Navvus and PW FFR correlated well. Navvus had less sensor drift. This new catheter-based system offers an alternative method for measuring FFR, with some potential advantages over PW.

The Application of Science- and Risk-Based Concepts to Drug Substance Stability Strategies

The International Conference on Harmonization (ICH) has provided practical guidance on the amount and type of drug substance stability data needed to support marketing applications (International Conference on Harmonization 2001, 2002, 2003a, b). Additional guidance has been issued by the World Health Organization (WHO 2009). Recent scientific advances and practices have resulted in improved scientific understanding of the chemical and physical attributes that contribute directly or indirectly to drug substance stability. Combining this improved understanding with the science- and risk-based approaches detailed in ICH Q8, Q9, and Q10 allows for alternative and more scientifically driven approaches to meet the scientific and regulatory objectives for drug substance stability (International Conference on Harmonization 2005, 2008, 2009). In this paper, proposals are presented to more fully leverage enhanced product knowledge to design improved stability strategies. The chemical and physical attributes that potentially impact drug substance stability are discussed, and strategies that leverage accelerated stability studies are presented.

A Science and Risk Based Proposal for Understanding Scale and Equipment Dependencies of Small Molecule Drug Substance Manufacturing Processes

ICH Q8(R2) established general guidelines around the Relationship of a Design Space to Scale and Equipment (Section 2.4.4); however, the guideline is not intended to provide guidance on scientific strategy for the application and implementation. It is widely recognized that drug product processes are typically scale and equipment sensitive; however, the same expectation should not be applied broadly to drug substance processes due to fundamental difference between the disciplines. This paper proposes a scientific perspective and strategy of how to develop design spaces that include scale and equipment knowledge for drug substance processes, and how to use that knowledge to mitigate the risk when changing from laboratory thorough commercial facilities.

A Design Space Verification Protocol for a Small Molecule Drug Substance

Regulatory expectations regarding design space verification in the designated manufacturing facility at commercial scale are not consistent across global markets. The extent and level of verification of design space boundaries are (a) predicated on the degree of risk and impact of that risk for movement within the design space and (b) are continually evaluated over the life cycle of a product and not necessarily defined as a moment in time (such as a submission date). Additionally, accommodations for differences in scientific disciplines are also important when determining design space verification strategies, for example design space verification approaches may vary between large molecule vs. small molecule drug substance, drug product, batch processes, continuous flow processes, or to assess device performance in combination products, etc. Several strategies and guiding principles to illustrate multiple opportunities and possibilities for the different disciplines to achieve design space verification using sound science and riskbased processes and procedures have recently been published [1, 2]. This publication will present a specific case study for assuring consistent quality within a design space for a recent small molecule drug substance example (of which elements are applicable across the other disciplines). It is not practical to execute and/or repeat experiments at commercial scale in a manufacturing facility to verify design space boundaries when the benefits are nebulous and the cost is prohibitive. Based on suggestions from regulatory authorities, a protocol was prepared to describe the life cycle approach and process for demonstrating design space verification. Publishing this protocol is intended to share the results of a successful interaction with regulators while continuing to facilitate open communication and opportunities for addressing the concept of design space verification. The protocol is presented within Appendix 1.

Synthesis of the kappa-agonist CJ-15,161 via a palladium-catalyzed cross-coupling reaction

Syntheses of CJ-15,161 (1) involving intermolecular N-arylation of an appropriately functionalized diamine, obtained from the precursor alpha-amino acids or, more conveniently, from the corresponding 1,2-amino alcohols via 1,2,3-oxathiazolidine-2,2-dioxide 22, are reported.

Misunderstanding Design Space: a Robust Drug Product Control Strategy Is the Key to Quality Assurance

ICH guidelines Q8/11, Q9, and Q10 introduced risk-based approaches and enhanced scientific understanding as an opportunity to encourage continuous process improvement for pharmaceutical manufacturing. Conceptually, Quality by Design (QbD) promised to improve confidence in quality through the lifecycle of pharmaceutical products. A primary incentive for industry is the prospect of global regulatory concordance for new applications and post approval changes. Unfortunately, during the last decade, the industry has experienced regulatory divergence regarding the interpretation of ICH guidelines across geographic regions. Rather than truly harmonized regulatory expectations, localized interpretations of ICH guidance have resulted in different technical requirements posing significant challenges for a global industry. As a result, the increased complexity of manufacturing supply chains and the regulatory burden associated with maintaining compliance with these diverse regulatory expectations serves as a barrier to continual improvement and innovation. The QbD paradigm has effectively demonstrated a risk-based link between a product’s control strategy and patient needs that has prompted meaningful improvement in the industry’s approach to product quality assurance. Divergent interpretations of the concepts and definitions used in the modern QbD approach to product development and manufacturing, however, has led to challenges in achieving a common implementation of design space, control strategy, prior knowledge, proven acceptable range, and normal operating range. While the concept of design space remains an appealing focal point for demonstrating process understanding, the authors suggest that Control Strategy is the most important QbD concept, and one that assures product quality for patients. A focus by both regulators and manufacturers on the significance of Control Strategy could facilitate management of post approval changes to improve manufacturing processes and enhance product quality while also engendering regulatory harmonization.

The Selection and Control of Starting Materials Should be Governed by Science and Risk-Based Approaches

Patient safety and efficacy fundamentally rely on demonstrated assurance of pharmaceutical product quality and consistency. Material and product specifications confirm that critical product quality attributes (CQAs) are controlled. However, a definition of a robust functional relationship between product CQAs and material attributes and/ or process parameters is the most effective means of reducing risk and increasing confidence in quality throughout the lifecycle of the product. In fact, the safety of a product is frequently attributed to its purity, as characterized by its impurity/degradation profile. Some impurities can originate from starting materials used in the manufacture of the active drug substance (API). In recent years, the quality and reliability of the supply chain, particularly the control of starting materials, have increasingly become the focus of industry and regulator concerns. While ICH Q11 provides scientifically justifiable guidance and guiding principles for the selection of starting materials, significant differences in the interpretation of that guidance has not engendered the expected level of global harmonization. ICH Q11 was finalized and adopted in 2012 and provided a long anticipated opportunity to harmonize the selection and justification of starting materials for the manufacture of drug substances. The success or failure of any starting material proposal in a regulatory submission has global implications with respect to current Good Manufacturing Practices (cGMPs), process validation requirements and inspection-related activities (ICHQ7). In addition, the rejection of a proposed starting material can and has resulted in compliance disconnects for qualification of commercial launch supplies. The ICH Q11 guideline recommends a threshold of criteria within themanufacturing process supply chainwhere the risk of upstream change is sufficiently low to pose negligible risk to drug substance quality. In fact, a science and risk based approach can effectively establish this threshold in the manufacturing process for a specific drug substance to adequately characterize the fate and demonstrate purge of upstream impurities. Nevertheless, a perception that a specific number of steps and/ or isolation/purification operations will always be needed to insulate API quality from unknown impurity risks remains and results in a palpable concern of inconsistent application of ICH Q11 principles. The appropriate scientific threshold in a manufacturing process is reflected by a control strategy that effectively manages the supply chain for starting materials by accommodating changes in the source and preparation of starting materials and ensuring the requisite quality of the drug substance has been demonstrated within a company Pharmaceutical Quality System. That control strategy, by definition, is established based on relative risk associated with the detection and control of impurities. ICH Q11 states:

Synthesis of (1‐(Aminomethyl)‐2,3‐dihydro‐1H‐inden‐3‐yl)methanol: Structural Confirmation of the Main Band Impurity Found in Varenicline® Starting Material

Abstract Described here is the synthesis of (1‐(aminomethyl)‐2,3‐dihydro‐1H‐inden‐3‐yl)methanol 1, the previously unidentified impurity found in the synthesis of 2,1 providing a confirmation of the structure. Fabbrica Italiano Sintetici (FIS), working in conjunction with Pfizer Groton, reported an unidentified impurity, referred to as the “main band impurity”, in 2 at levels of 0.4 to 0.8%. The structure was postulated to be 1, the open‐ring product of the lithium aluminum hydride (LAH) reduction of 3 to 2. Although the cis isomer of 1 was previously reported in the literature,2 a much shorter racemic synthesis was developed using intermediates employed for the production of Varenicline®. Several reducing agents were screened for the synthesis of 1, with LiAlH4 followed by basic workup conditions giving optimal results. High performance liquid chromatography (HPLC) analysis ultimately confirmed the structure of 1 as the main band impurity generated during the synthesis of 2.