Impurity profile, control

Figure 1.8. Schematic frequency distributions for some independent (reaction input or control) resp. dependent (reaction output) variables to show how non-Gaussian distributions can obtain for a large population of reactions (i.e., all batches of one product in 5 years), while approximate normal distributions are found for repeat measurements on one single batch. For example, the gray areas correspond to the process parameters for a given run, while the histograms give the distribution of repeat determinations on one (several) sample(s) from this run. Because of the huge costs associated with individual production batches, the number of data points measured under closely controlled conditions, i.e., validation runs, is miniscule. Distributions must be estimated from historical data, which typically suffers from ever-changing parameter combinations, such as reagent batches, operators, impurity profiles, etc.

The well documented synthetic method for 37 is chlorination of cyclopropyl-methylketone followed by base treatment [29]. However, this method did not provide a suitable impurity profile. The most convenient and suitable method we found was the one-step synthesis from 5-chloro-l-pentyne (49) by addition of 2equiv of base, as shown in Scheme 1.18 [21, 30]. Two major impurities, starting material 49 and reduced pentyne, had to be controlled below 0.2% each in the final bulk of 37, to ensure the final purity of Efavirenz . Acetylene 37 was isolated by distillation after standard work-up procedure. 

Pluym et al. compared the use of CE to that of HPLC in chemical and pharmaceutical quality control. They stated that CE could be considered as a complementary technique to HPLC because of its large separation capacity, its simplicity, and its economical benefits. Jimidar et al. decided that CE offers high separation efficiency and can be applied as an adjunct in HPLC method validation. Mol et al. evaluated the use of micellar electrokinetic chromatography (MEKC) coupled with electrospray ionization mass spectrometry (ESI—MS) in impurity profiling of drugs, which resulted in efficient separations. 

Although it may not always be possible to control the sources or extraction conditions to produce only a single component, they should be arranged so as to produce, as far as possible, a consistent mixture. Impurity profiles of botanical products are often monitored by a number of anal3hical procedures to ensure product quality. Minor components that have pharmacological activity should not necessarily be viewed as impurities. In some cases, the activity of a botanical or fermentation drug substance may be attributed to a number of components. 

Providing economic and fast generic separation methods that can be applied with confidence in development and control laboratories to a large number of samples of variable composition to provide important information in short time to synthetic chemists, either for fast sample screening, or for generating impurity profiles... 

Ideally all subsequent batches will be prepared by the route and process used for tox and/or Phase 1 batches, so that on-scale impurities and impurity profiles will meet the guidelines above. Of course it is difficult to predict the final optimized process for a dmg candidate. The best approach to control impurities is to determine the optimal starting materials, reagents, process, and final form (salt, polymorph) early ( freeze the final step... 

Maintaining the hydrogenation under kinetic control provides limited alcohol formation and avoids over reduction of product C. The performance of a hydrogenator depends on the gas-liquid mass transfer characteristics Kla (8). Possible operating scenarios with their observed impurity profiles are summarized in Table 5. 

Critical process steps are usually determined by analyzing process parameters (factors in a process that are controllable and measurable) and their respective outcomes. Not all process parameters affect the quality and purity of APIs namely its impurity profile and physical characteristics. For validation purposes, manufacturers should identify, control, and monitor critical process parameters that may influence the critical quality attributes of the API. Process parameters unrelated to quality, such as variables controlled to minimize energy consumption or equipment use, need not be included in process validation. 

Known toxic impurities, however, should be held to a tighter standard (below 0.1%). One of the objectives of a successful validation program for APIs is to maintain control over the impurity profile and to hold contaminants and impurities to an achievable minimum standard. 

An API is closely controlled in terms of crystal form, polymorph identity, particle size, impurity profile and content, solvent, and water levels. All of these quality parameters are defined in creating a drug product that has the desired pharmacological properties (e.g., tablet dissolution rate to give needed blood levels) and desired physical properties (e.g., stability and compatibility with drug delivery systems). 

Assay. The methods for the drug substance and the impurities should be stability indicating. If the identity test is specific and impurities are adequately controlled by other methods, a less specific method to assay the drug substance may be used. If possible, the same procedure should be used to measure both the overall purity of the drug substance and the levels of impurities or degradation products. The limits for purity should be established on the basis of scientific review of the impurity profile of the drug substance and review of results obtained from individual batches. 

In cases where a general QL is required, as in pharmaceutical analysis, it is essential to define a realistic QL (or DL) for the analytical procedure, independently from the equipment used, because this limit has important consequences (e.g., for the consistent reporting of impurities or for method transfer). They may be derived by taking QL (or DL) from various instruments into account ( intermediate QL, during the development process) or can be defined taking the requirements of the control test (specification limits imposed by toxicology or by a qualified impurity profile) into consideration. For example, a QL which... 

Marangoni interfacial stresses which slow the dynamics of wetting. Additional variables which influence adhesion tension include (1) impurity profile and particle habit/morphology typically controlled in the particle formation stage such as crystallization, (2) temperature of granulation, and (3) technique of grinding, which is an additional source of impurity as well. 

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