Product quality confirmation

The computerized systems, both hardware and software, that form part of the GLP study should comply with the requirements of the principles of GLP. This relates to the development, validation, operation and maintenance of the system. Validation means that tests have been carried out to demonstrate that the system is fit for its intended purpose. Like any other validation, this will be the use of objective evidence to confirm that the pre-set requirements for the system have been met. There will be a number of different types of computer system, ranging from personal computers and programmable analytical instruments to a laboratory information management system (LIMS). The extent of validation depends on the impact the system has on product quality, safety and record integrity. A risk-based approach can be used to assess the extent of validation required, focusing effort on critical areas. A computerized analytical system in a QC laboratory requires full validation (equipment qualification) with clear boundaries set on its range of operation because this has a high... 

Figure 9.15. Overview of the production of Refludan (recombinant hirudin). The exact details of many steps remain confidential for obvious commercial reasons. A number of quality control checks are carried out on the final product to confirm the product s structure. These include amino acid composition, HPLC analysis and peptide mapping...

There is a practical distinction between pharmacopoeia standards and manufacturers release specifications, although both comprise sets of tests to which a given product should conform. Release specifications are applied at the time of manufacture of a pharmaceutical product to confirm its appropriate quality but they also need to have a predictive value, to support the notion that the manufacturer is responsible for the product during its entire shelf-life. In many cases pharmacopoeial monographs are based on the specifications developed by the manufacturers of innovator (originator) products. 

Samples are to be taken during and/or after each critical manufacturing step. All control parameters for the manufacturing process have to be monitored and recorded. Each sample analysis will be performed in duplicate using validated or accepted pharmacopeia methods. The sample results will be used to confirm in-process and final product quality attributes as defined by the preestablished specifications. Conformance with specifications will justify the appropriateness of the critical parameters used during the process validation. 

This approach has been confirmed by FDA s guidance on scope and applications. It requires justifying and documenting the rationale behind what and how much to validate We recommend that you base your approach on a justified and documented risk assessment and a determination of the potential of the system to affect product quality and safety, and record integrity. [24]... 

The conversion of 2 to 3 was optimized at full scale in the VRT reactor. In addition to confirming the productivity, safety, product quality, and economic benefit of the process, the robustness of the process was also demonstrated. Finally, this pilot study provided the basis for a full-scale commercial manufacturing design specification. Having fixed the optimum residence time, the process was then transferred into a plant Fixed Residence Time (FRT) cyanation reactor which employed a fixed length of jacketed static mixer for commercial manufacture. This FRT was capable of producing 300 metric tonnes per year of 3, with the same purified step yield of 80% that was achieved in the laboratory capillary reactor. 

Confirm critical process parameters and determine their effects on product quality attributes. 

A fundamental objective of a computer system applied to automate a pharmaceutical GMP operation is to ensure the quality attributes of the drug product are upheld throughout the manufacturing process. It is therefore important that quality-critical parameters are determined and approved early in the validation life cycle. The exercise should be undertaken to a written procedure with base information from the master product/production record file examined and quality-critical parameter values and limits documented and approved for the process and its operation. In addition, the process and instrument diagrams (P IDs) should be reviewed to confirm the measurement and control components that have a direct impact on the quality-critical parameters and data. This exercise should be carried out by an assessment team made up of user representatives with detailed knowledge of both the computer system application and process, and with responsibility for product quality, system operational use, maintenance, and project implementation. This exercise may be conducted as part of an initial hazard and operability study (HAZOP) and needs to confirm the quality-related critical parameters for use in (or referenced by) the computer control system URS. 

That type of fixation on product quality for a single product family might seem excessive, but is certainly preferable to the more prevalent benign neglect that passes for validation of product quality in many firms. Each of the key quality attributes of the product should be established in a validation effort that establishes the consistent conformance to the specifications. As mentioned previously the PQ effort should consist of independent confirmation of process parameters coupled with in-process and finished goods sampling of production materials. The combination of parameter verification with product sampling ties the process to the product. 

Quality assurance may request postapproval stability studies on specific batches of product to confirm that those batches have the same stability profile usually associated with that product. Special stability studies may be requested for batches that experienced manufacturing deviations, exceeded internal alert limits even if they passed regulatory specifications, exhibited... 

Alternately, should a review of the product quality data show that there have been no significant changes in any analytical test results, stability profiles, SPC data trends, etc., the APR may confirm that these changes did not require revalidation individually or collectively. 

The preparation of any pharmaceutical product requires controls over the production operations to assure the end result is a product that meets the required quality attributes. The methods utilized for this control are supported by formalized validation studies in which proof of consistency is demonstrated by appropriately designed experiments. The definition of appropriate operating parameters is the primary objective of the development activities and is further confirmed during scale-up to commercial operations. The validation supports that the routine controls applied to the process are appropriate to assure product quality [36], This is typically accomplished in formalized validation activities in which expanded sampling/testing of the product materials is performed to substantiate their uniformity and suitability for use [30],... 

Complete displacement of a solvent by a higher-boiling solvent, often important to reach the expected yield and product quality from a crystallization. Reaching a target temperature may signify that a distillation is complete. The reactor contents may then be assayed by GC to confirm that the lower-boiling solvent has been reduced to an acceptable level. 

To date, the benefits of the operational improvements have been verified and the improved activity of the second-generation catalyst has been confirmed, along with stability and full activity recovery over multiple HTRs. Representative performance data from the current demo unit operation processing refinery C4 olefins is presented in Figures 12.17 to 12.19 - for alkylate RON, RVP and C5 + yield, respectively. This data, based on automated sampling from the on-line analytical system, show both the high product quality achieved and the stability of the cyclic process over time. 

Having defined process conditions to obtain satisfactory gasoline yield, acceptable product quality, and adequate catalyst life in bench-scale tests, fixed-bed MTG development would normally be considered complete, and the process ready for commercialization. However, to obtain large quantities of gasoline for testing and to confirm scale-up, a demonstration unit with a capacity of 4 B/D of methaijol was built and operated. 

Long term production runs confirmed the high yield and the high quality of the unleaded gasoline. The product quality meets the premium standard for unleaded gasoline. 

A useful approach to process optimisation is to identify all the critical process parameters that could potentially affect product quality or performance and prepare a Process Optimisation Protocol. Typically, data used to identify critical process parameters will be derived from laboratory or pilot-scale batches, and do not need to be confirmed on full-scale batches unless the control of the particular parameter can only be evaluated on a production scale. There is good incentive to use the production facilities at the earliest opportunity, drug availability permitting, to iron out any transfer difficulties. Manufacture of the stability batches to support Phase III studies, and also the Phase III clinical batches, at the final commercial site should minimise any questions from the FDA during PAI about possible differences between R D and Production process used. 

Process validation is documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-deter-mined specifications and quality attributes [48]. For cell culture-derived biopharmaceuticals, important quality attributes to establish include structural integrity and potency of the API and freedom from impurities. Thus, the demonstration of removal of cell culture and process impurities is a key part of process validation. Often, due to practical considerations, some studies are performed at small scale. In these cases, periodic concurrent monitoring of impurities during large-scale production can confirm the results from small-scale studies. 

Equipment shall be periodically repaired, maintained and validated, and these operations shall not have any adverse effect on products quality. Renewed equipment shall be validated, and it can be used when it is confirmed that the products quality is not adversely affected. 

Measures should be taken to confirm that designated Manufacturing and Quality Assurance procedures are being followed by staff at ail levels. To this end appropriate Production, Quality Control and (as necessary) Engineering staff should carry-out periodic inspection and evaluation of the Company s own Quality Assurance systems. This should cover production, warehousing and quality control laboratories, and resulting in a formal written report with recommendations for action. Follow-up action should be recorded. 

Now let us apply the capacity-based approach. Positive and negative 10 percent disturbances are made in the fresh feed flow rate Fg and in the fresh feed composition Zq. Dynamic simulations (confirmed by frequency-domain analysis, to be discussed in Chapter 10) show that the variability in product quality xb is decreased by increasing reactor volume or by decreasing the number of trays in the stripper. 

When a very small change is made in the composition of the Fqb stream (zoB.B changed from I to 0.999 and Zqb,a changed from 0 to 0.001), the process can barely handle it. The steady-state value of in the third column changes 15 percent for this very small disturbance. Thus, the steady-state analysis predicts that this structure will not work. Dynamic simulations confirmed this very small disturbances drive the control valves on / 3 and V3 wide open, and product quality cannot be maintained. 

Trending of process variables is used to refine range limits [3]. Manufacturing data can lead to superseded NORs and/or MORs, which are justified by the associated operational trends and product quality achieved [20]. Extreme parameter values subsequently can become acceptable in process validation if the acceptability of final product has been confirmed by multiple observations [12]. 

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