1、Designation: E2475 10Standard Guide forProcess Understanding Related to PharmaceuticalManufacture and Control1This standard is issued under the fixed designation E2475; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the year of la
2、st revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope1.1 The purpose of this guide is to establish a frameworkand context for process understanding for pharmaceuticalmanufacturi
3、ng using quality by design (QbD) (Juran, 1992;2FDA/ICH Q8). The framework is applicable to both activepharmaceutical ingredient (API) and to drug product (DP)manufacturing. High (detailed) level process understandingcan be used to facilitate production of product which consis-tently meets required s
4、pecifications. It can also play a key rolein continuous process improvement efforts.1.2 Process Analytical Technology (PAT) is one elementthat can be used for achieving control over those inputsdetermined to be critical to a process. It is important for thereader to recognize that PAT is defined as:
5、“a system for designing, analyzing, and controlling manufacturing throughtimely measurements (i.e., during processing) of critical quality and performanceattributes of raw and in process materials and processes, with the goal of en-suring final product quality. It is important to note that the term
6、analytical in PATis viewed broadly to include chemical, physical, microbiological, mathematical,and risk analysis conducted in an integrated manner. The goal of PAT is to en-hance understanding and control the manufacturing process” (U.S. FDA PAT)1.3 This standard does not purport to address all of
7、thesafety concerns, if any, associated with its use. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitations prior to use.2. Referenced Documents2.1 ASTM Standards:3E456 Terminology Relating
8、 to Quality and StatisticsE2281 Practice for Process and Measurement CapabilityIndicesE2474 Practice for Pharmaceutical Process Design Utiliz-ing Process Analytical TechnologyE2617 Practice for Validation of Empirically Derived Mul-tivariate Calibrations2.2 U.S. Government Publications:4FDA/ICH Q8 P
9、harmaceutical DevelopmentFDA/ICH Q10 Pharmaceutical Quality SystemsU.S. FDA PAT Guidance Document, Guidance for IndustryPATA Framework for Innovative PharmaceuticalManufacturing and Quality Assurance3. Terminology3.1 Definitions of Terms Specific to This Standard:3.1.1 critical inputs, ncritical pro
10、cess parameters andcritical raw material attributes for a given process.American Society for Quality53.1.2 empirical, adjany conclusion based on experimentaldata and past experience, rather than on theory.3.1.3 expert system, nan expert system is a computerprogram that simulates the judgment and beh
11、avior of a humanor an organization that has expert knowledge and experience ina particular field.3.1.3.1 DiscussionTypically, such a system contains aknowledge base containing accumulated experience and a setof rules for applying the knowledge base to each particularsituation that is described to th
12、e program. Sophisticated expertsystems can be enhanced with additions to the knowledge baseor to the set of rules.3.1.4 first principles, na calculation is said to be from firstprinciples, or ab initio, if it starts directly at the level ofestablished laws of physics and does not make assumptionssuc
13、h as model and fitting parameters.3.1.5 mechanistic, adj(1) of, or relating to, theories thatexplain phenomena in purely physical or deterministic terms: amechanistic interpretation of nature.3.1.6 process capability, nstatistical estimate of the out-come of a characteristic from a process that has
14、been demon-strated to be in a state of statistical control. E22813.1.7 process inputs, nthe combination of all processparameters and raw material attributes for a given process.1This guide is under the jurisdiction of ASTM Committee E55 on Manufactureof Pharmaceutical Products and is the direct resp
15、onsibility of Subcommittee E55.01on PAT System Management.Current edition approved April 15, 2010. Published August 2010. DOI:10.1520/E2475-10.2Juran, J., Juran on Quality by Design: The New Steps for Planning QualityInto Goods and Services, Free Press, New York, N.Y., 1992.3For referenced ASTM stan
16、dards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.4Available from U.S. Government Printing Office Superintendent of Documents,732 N. Cap
17、itol St., NW, Mail Stop: SDE, Washington, DC 20401, http:/www.access.gpo.gov.5Available from American Society for Quality (ASQ), 600 N. Plankinton Ave.,Milwaukee, WI 53203, http:/www.asq.org.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United S
18、tates.3.1.8 process understanding, vto recall and comprehendprocess knowledge such that product quality can be explainedlogically or scientifically, or both, as a function of processinputs and respond accordingly.3.1.9 residual error, nthe difference between the ob-served result and the predicted va
19、lue (estimated treatmentresponse); Observed Result minus Predicted Value. E4563.1.10 uncertainty, nan indication of the variability asso-ciated with a measured value that takes into account two majorcomponents of error: (1) bias, and (2) the random errorattributed to the imprecision of the measureme
20、nt process.E4564. Process Understanding4.1 From physical, chemical, biological, and microbiologi-cal perspectives, a process is considered to be well understoodwhen:(1) All significant sources of variability in process inputsare identified and explained,(2) The effect of these sources of variability
21、 on productquality attributes can be accurately and reliably estimatedbased on the inputs to the process, and(3) Significant process parameters are continuously man-aged and controlled to ensure that the process must produceproduct which is continuously within required specifications tothe user spec
22、ified required degree or confidence.4.2 A well-controlled process is a process where the risk ofproducing product not meeting required specifications is belowthe maximum acceptable level of risk as predetermined by theuser. Accordingly, process understanding requires the compre-hension and recall of
23、 process knowledge sufficient for thelogical, statistical, or scientific understanding, or combinationthereof, of how significant process parameters and raw materialattributes relate to, or impact the quality attributes of, theproduct being produced. Sufficient process understandingshould be achieve
24、d to reduce risk to an acceptable level for thepatient, manufacturer, or any other stakeholder.4.3 A Lifecycle Commitment (Development and CommercialManufacture):4.3.1 Process understanding is fundamental to QbD. It isimportant to realize that due to commercial realities (forexample, finite resource
25、s, time, and money), a process willtypically be commissioned as soon as the degree of processunderstanding is sufficient to permit operation of the processwith an acceptably low, user specified, level of risk ofproducing out of specification product. While it may beappropriate to commission a proces
26、s once this minimumdegree of process understanding is achieved, the risk that theprocess may transition out of control steadily increases overtime (for example, process drift), and could exceed themaximum acceptable risk without warning, unless an ongoingprogram to enhance process understanding is i
27、n place.4.3.2 Accordingly, the development of process understand-ing should be treated as an ongoing process. Learning shouldcontinue throughout the product and process life cycle toimprove the level of process understanding to include processparameters and other factors (for example, environmental,
28、changes of scale, changes in raw materials, changes in person-nel) which may have changed or which may have newlyemerged since the time the process was first commissioned.Work to enhance process understanding continuously through-out the life cycle of the product and process can provideassurance tha
29、t the process will continue to have an acceptablylow risk of producing out of specification results.4.3.3 Manufacturers are encouraged to continuously moni-tor and improve upon their operations to enhance productquality.4.4 Process Understanding for the Whole Process:4.4.1 For each product, process
30、understanding covers theprocess from the initial design of the chemical or biologicaldrug substance through manufacturing of the unit dose ordevice to final packaging. In addition, the critical qualityattributes of the raw materials will in turn become inputs to thedrug product manufacturing process
31、, as will process param-eters.4.4.2 Fig. 1 schematically illustrates that the performance ofany process output (Y) is a function of the inputs (X), which canbe classified into one of six categories (that is, operator,equipment, measurements, methods, materials, and environ-mental conditions).4.4.3 C
32、omprehensive understanding of the relationships ofthe process inputs and operating parameters to quality at-tributes of the resulting product is fundamental to developing asuccessful risk mitigation or control strategy, or both. Identi-fication of critical process parameters (CPPs) and critical rawm
33、aterial attributes should be carried out using suitable experi-mental and investigative techniques.An understanding of thesecritical inputs (CPPs and critical raw material attributes), andtheir monitoring and control, is essential when designing aprocess that is able to consistently and reliably del
34、iver productof the desired quality.4.4.4 One method for achieving the desired state is throughmultivariate analysis and control. The acceptable operatingrange of the critical inputs defines the relationship between thedesign space, control strategy and operating range(s).4.4.5 Note that for raw mate
35、rials, an additional source ofvariability derives from the potential for adulteration. Thisrequires that manufacturers understand their incoming supplychain and suppliers quality systems, and include methods todetect adulteration of materials in addition to confirmingidentity as necessary, bearing i
36、n mind that adulteration may bedifficult to detect by standard methods. It also requires thatmanufacturers use suppliers that are aware of these concernsand are prepared to implement their own precautionary mea-sures, and to permit transparency into their respective supplysources.4.5 Tools of Proces
37、s Understanding:4.5.1 Process understanding begins with process design(Practice E2474) and usually a structured, small scale devel-opment program which focuses on efficiently delivering aproduct meeting the required specifications. Tools that may beapplied during development and after commercializat
38、ion in-clude:(1) Scientific theory,(2) Prior knowledge,(3) Design of experiments,(4) Simulation of unit operations,E2475 102(5) Selection of a suitable technology platform,(6) Mathematical models,(7) Empirical/statistical models,(8) Appropriate instrumentation, and(9) Appropriate analytical methods.
39、4.5.2 The measurement technologies include but are notlimited to spectroscopic, acoustic, or other rapid sensor tech-nologies. The development of these and other advanced tech-niques will continue to enable or enhance predictive control forcommercial pharmaceutical processes.4.5.3 The ability to mea
40、sure process parameters and qualityattributes inline, online, or atline in real time can contribute toprocess understanding and the ability to control the process.These technologies offer the development scientist, commer-cial production engineer and manufacturing personnel theopportunity for additi
41、onal insight. This is achieved through theincreased measurement frequency and availability of morecomprehensive data.5. Process Knowledge5.1 Process knowledge is the cornerstone of process under-standing. There are various levels of process knowledge, andthese are listed from lowest to highest state
42、 of understanding:(1) Descriptive knowledge (what is occurring?),(2) Correlative knowledge (what correlations are empiri-cally observed?),(3) Causal knowledge (empirical, what causes what?),(4) Mechanistic knowledge (explanations for observedcausality), and(5) First principles knowledge (underlying
43、physical,chemical, and biological phenomena of the mechanistic expla-nations).5.2 Process knowledge is the accumulated facts about theprocess. This accumulated knowledge is generally embodied ina model of the process. Accordingly, process model is oftenused synonymously with process knowledge.5.3 Pr
44、ocess understanding is demonstrated by the extent towhich process knowledge can be used to predict and controlthe process outcomes; a well understood process will combineknowledge from various sources to ensure a well controlledprocess and consistent product quality.5.4 At any point in time for any
45、manufacturing process, thelevel of understanding will likely be a combination of variouslevels of understanding. As more knowledge is obtainedthroughout the lifecycle of a product, the relative contributionto understanding of the various levels is likely to change.5.5 Prior knowledge is any knowledg
46、e that may be availablethrough previous experience. Prior knowledge may come froma number of sources including scientific literature, companyexperience from research and development, and existing com-mercial products such as lab and manufacturing investigations.All knowledge that is available should
47、 be considered andplaced in context in order to optimize the overall level ofunderstanding.FIG. 1 Input, Process, and Output DiagramE2475 1035.6 Within most organizations in the early stages of QbDimplementation, process understanding tends to be basedmainly on descriptive and correlative and scient
48、ific knowledge.The framework outlined in the FDAs “GMPs for the 21stCentury A Risk Based Approach”6should encourage thepharmaceutical industry to enhance understanding by addingprocess knowledge at the causal, mechanistic, and first prin-ciples levels.5.7 Mechanistic and first principles process mod
49、els canoffer advantages over process models which are a combinationof only descriptive, correlative, and causative process knowl-edge. Proper evaluation of risk may be more challenging in theabsence of mechanistic or first principles process knowledge.The user is responsible for determining the level of processknowledge which is appropriate for each specific circumstance.5.8 The subsequent subsections provide greater detail anddiscussion for each state of knowledge.5.9 This guide does not differentiate between programs todevelop understanding for products and pro
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