Control Strategy




The term “control strategy” was coined by the International Conference on Harmonisation (ICH) guidances with the end objective of assuring process performance and product quality.1 A control strategy is composed of a set of controls derived from current product and process understanding that can include parameters, attributes related to drug substance, drug product materials, components, facility and equipment operating conditions, in-process controls, finished product specifications, and the associated methods with frequency of monitoring and control.


Control strategies for drug substance development that focus on the management of impurities generated during its chemical synthesis have been implemented and described in the literature.2 Common to these reports is the inherent challenge offered by the multistep assembly of a drug substance because each step must be developed with the upmost rigor to ensure process performance and product quality.

As a result, multiple control strategies must be put into practice, and an overall control strategy that encompasses the individual strategies from starting materials to drug substance becomes essential. The key elements of a control strategy following a Quality Risk Management approach are provided below:

• Identification of quality attributes (QAs) and critical quality attributes (CQAs) for starting materials, intermediates, and drug substances;

• Establishing acceptance criteria for input materials, reagents, and solvents;

• Determining process parameter criticality and ranges;

• Understanding the fate and purge of impurities; • Defining the in-process controls; and

• Developing specifications.

Development of the control strategy is an iterative process used to ensure quality throughout the lifecycle of a product. If a change in the process is required either in development or continuous improvement, the control strategy should be reevaluated to ensure that the quality of the drug substance is maintained. In general, development of a control strategy begins with identification of drug substance CQAs, determination of the QAs of the corresponding intermediate and starting materials, and a risk assessment of the variables that could impact the quality of the drug substance, e.g., input material attributes and process parameters (critical and noncritical).

These activities rely on an adequate understanding of the overall process and underlying reaction mechanisms and preface experimental studies toward the selection of parameter ranges to ensure consistent quality in concurrence with the quality target product profile (QTPP). The selected ranges can be described by proven acceptable ranges (PARs)3 built upon univariate experimentation or can be presented in terms of a design space that correlates ranges of material attributes with process parameter ranges derived from multivariate experimentation.4 PARs or design space constitute key elements of the control strategy.

Development of a control strategy for the final intermediate during preparation of the asunaprevir drug substance5 is described herein. Designation of the final intermediate as the “quality gate” intermediate6 of the process introduces distinctive challenges that influence the entire strategy. Our approach to control critical impurities is rooted in a detailed understanding of the reaction mechanism as well as the purge capability during workup and crystallization.

The discussion begins with an overview of the process, followed by determination of quality attributes and a process risk assessment. Next, the mechanistic studies of the reactions involved in the generation of the final intermediate, consumption of the corresponding input materials, and impurity formation are described. This knowledge enabled the construction of a mechanistic model for guidance in the selection of a design space and helped to identify the parameters that could impact the impurity profile of the active pharmaceutical ingredient (API).

The defined control strategy was developed utilizing the basis of ICH Q8 (R2) together with the principles in ICH Q11. A riskbased approach (ICH Q9) was used to define the CQAs and the process parameters for the step. On the basis of the mechanistic understanding of impurity formation, a kinetic model was defined (ICH Q10) and used to guide development of the design space. This led to a robust and cost-effective final intermediate process that ensures drug substance quality.



(1) ICH Harmonised Tripartite Guideline: Pharmaceutical Development Q8 (R2); International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use: Geneva, August 2009.

(2) For a recent review, see: Thomson, N. M.; Singer, R.; Seibert, K. D.; Luciani, C. V.; Srivastava, S.; Kiesman, W. F.; Irdam, E. A.; Lepore, J. V.; Schenck, L. Org. Process Res. Dev. 2015, 19, 935−948.

(3) PARs are defined in ICH Q8 R2 as “a characterized range of a process parameter for which operation within this range, while keeping other parameters constant, will result in producing a material meeting relevant quality criteria.”

(4) ICH Q8 R2 defines design space as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality.”

(5) (a) Scola, P. M.; Sun, Li-Q.; Wang, A. X.; Chen, J.; Sin, N.; Venables, B. L.; Sit, S.-Y.; Chen, Y.; Cocuzza, A.; Bilder, D. M.; D’Andrea, S. V.; Zheng, B.; Hewawasam, P.; Tu, Y.; Friborg, J.; Falk, P.; Hernandez, D.; Levine, S.; Chen, C.; Yu, F.; Sheaffer, A.; Zhai, G.; Barry, D.; Knipe, J. O.; Han, Y.-H.; Schartman, R.; Donoso, M.; Mosure, K.; Sinz, M. W.; Zvyaga, T.; Good, A. C.; Rajamani, R.; Kish, K.; Tredup, J.; Klei, H. E.; Gao, Q.; Mueller, L.; Colonno, R. J.; Grasela, D. M.; Adams, S. P.; Loy, J.; Levesque, P. C.; Sun, H.; Shi, H.; Sun, L.; Warner, W.; Li, D.; Zhu, J.; Meanwell, N.; McPhee, F. J. Med. Chem. 2014, 57 (5), 1730− 1752. (b) Wang, X. A., Sun, L.-Q., Sit, S.-Y., Sin, N., Scola, P. M., Hewawasam, P., Good, A. C., Chen, Y., Campbell, J. A. Preparation of peptides as hepatitis C virus inhibitors. PCT Int. Appl. WO 2003099274 A1, 2003. (c) Savage, S. A., Domagalski, N. R., Mack, B., Vemishetti, P., Qiu, Y., Fenster, M., Hallow, D. M., Ferreira, G., Rogers, A., Lou, S., Hobson, L. Preparation of asunaprevir as hepatitis C virus inhibitors. PCT Int. Appl. WO 2015200305 A1, 2015.

(6) The “quality gate”intermediate is defined as the intermediate in the synthesis at which all critical input-related impurities, their corresponding synthetic derivatives, and/or process related impurities are effectively controlled or purged.

(7) Time required to heat the batch from ambient temperature to the target reaction temperature. (8) The solubility of the impurities was measured in the mother liquors to ensure sufficient purging capacity for the process.

(9) For examples of mechanistic models developed to enable design space selection, see: (a) Hallow, D. M.; Mudryk, B. M.; Braem, A. D.; Tabora, J. E.; Lyngberg, O. K.; Bergum, J. S.; Rossano, L. T.; Tummala, S. J. Pharm. Innov. 2010, 5, 193−203. (b) Burt, J. L.; Braem, A. D.; Ramirez, A.; Mudryk, B.; Rossano, L.; Tummala, S. J. Pharm. Innov. 2011, 6, 181−192. (10) The base-mediated deprotection of the primary carbamate, which was experimentally confirmed by in situ IR spectroscopy under the reaction conditions, has been reported: Tom, N. J.; Simon, W. M.; Frost, H. N.; Ewing, M. Tetrahedron Lett. 2004, 45, 905−906.

(11) A radical mechanism involving single electron transfer from tBuOK to input 1, hydrogen abstraction from the solvent, and elimination of KCl is in agreement with impurity formation rates that rise at increased t-BuOK concentrations, the detection of deuterated input 1 in the presence of THF-d8 as solvent, and the inhibitory effect of BHT. For related transformations, see: (a) Shi, Q.; Zhang, S.; Zhang, J.; Oswald, V. F.; Amassian, A.; Marder, S. R.; Blakey, S. B. J. Am. Chem. Soc. 2016, 138, 3946−3949. (b) Roman, D. S.; Takahashi, Y.; Charette, A. B. Org. Lett. 2011, 13, 3242−3245 and references cited therein..

(12) Although other mechanistic pathways are possible, the stated equations accurately predict the observed experimental results.

(13) Prausnitz, J. M.; Lichtenthaler, R. N.; Azevedo, E. G. Molecular Thermodynamics of Fluid-Phase Equilibria; Prentice Hall, Inc.: Englewood Cliffs, NJ, 1986. (14) DynoChem; Scale-up Systems Ltd.: Dublin, Ireland.

(15) Dimensionality reduction was possible because the main effects and interactions of the fixed parameters were unidirectional throughout the space considered, as supported by experimental evidence. See ref 9a. (16) An experimental procedure for a batch can be found in ref 5c.


describes the development of a control strategy for impurities in the final intermediate step of the asunaprevir drug substance utilizing the concepts outlined in the International Conference on Harmonisation guidelines (ICH Q8 (R2), Q9, Q10, and Q11). Detailed mechanistic understanding enabled the construction of a kinetic model that was used in conjunction with a process risk assessment and well-defined quality attributes to guide the development of the reaction design space. Implementation of continuous monitoring of the reaction facilitated the expansion of the design space and provided suitable parameter ranges to enable a robust process for commercial manufacturing.

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