Verification and validation

"IV&V" redirects here. For NASA's IV&V Facility, see Independent Verification and Validation Facility.

For the software activities, see software verification and validation.

For validation of tests, see Test validity.

Verification and validation (also abbreviated as V&V) are independent procedures that are used together for checking that a product, service, or system meets requirements and specifications and that it fulfills its intended purpose.^[1] These are critical components of a quality management system such as ISO 9000. The words "verification" and "validation" are sometimes preceded with "independent", indicating that the verification and validation is to be performed by a disinterested third party. "Integration verification and validation" can be abbreviated as "IV&V".

In practice, as quality management terms, the definitions of verification and validation can be inconsistent. Sometimes they are even used interchangeably.^[2][3][4]

However, the PMBOK guide, a standard adopted by the Institute of Electrical and Electronics Engineers (IEEE), defines them as follows in its 4th edition:^[5]

• "Validation. The assurance that a product, service, or system meets the needs of the customer and other identified stakeholders. It often involves acceptance and suitability with external customers. Contrast with verification."
• "Verification. The evaluation of whether or not a product, service, or system complies with a regulation, requirement, specification, or imposed condition. It is often an internal process. Contrast with validation."

Overview

Verification

Verification is intended to check that a product, service, or system meets a set of design specifications.^[6][7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results. In the post-development phase, verification procedures involve regularly repeating tests devised specifically to ensure that the product, service, or system continues to meet the initial design requirements, specifications, and regulations as time progresses.^[7][8] It is a process that is used to evaluate whether a product, service, or system complies with regulations, specifications, or conditions imposed at the start of a development phase. Verification can be in development, scale-up, or production. This is often an internal process.^{[citation needed]}

Validation

Validation is intended to ensure a product, service, or system (or portion thereof, or set thereof) results in a product, service, or system (or portion thereof, or set thereof) that meets the operational needs of the user.^[7][9] For a new development flow or verification flow, validation procedures may involve modeling either flow and using simulations to predict faults or gaps that might lead to invalid or incomplete verification or development of a product, service, or system (or portion thereof, or set thereof).^[10] A set of validation requirements (as defined by the user), specifications, and regulations may then be used as a basis for qualifying a development flow or verification flow for a product, service, or system (or portion thereof, or set thereof). Additional validation procedures also include those that are designed specifically to ensure that modifications made to an existing qualified development flow or verification flow will have the effect of producing a product, service, or system (or portion thereof, or set thereof) that meets the initial design requirements, specifications, and regulations; these validations help to keep the flow qualified.^{[citation needed]} It is a process of establishing evidence that provides a high degree of assurance that a product, service, or system accomplishes its intended requirements. This often involves acceptance of fitness for purpose with end users and other product stakeholders. This is often an external process.^{[citation needed]}

It is sometimes said that validation can be expressed by the query "Are you building the right thing?"^[11] and verification by "Are you building it right?".^[11] "Building the right thing" refers back to the user's needs, while "building it right" checks that the specifications are correctly implemented by the system. In some contexts, it is required to have written requirements for both as well as formal procedures or protocols for determining compliance.^{[citation needed]}

It is entirely possible that a product passes when verified but fails when validated. This can happen when, say, a product is built as per the specifications but the specifications themselves fail to address the user's needs.^{[citation needed]}

Activities

Verification of machinery and equipment usually consists of design qualification (DQ), installation qualification (IQ), operational qualification (OQ), and performance qualification (PQ). DQ may be performed by a vendor or by the user, by confirming through review and testing that the equipment meets the written acquisition specification. If the relevant document or manuals of machinery/equipment are provided by vendors, the later 3Q needs to be thoroughly performed by the users who work in an industrial regulatory environment. Otherwise, the process of IQ, OQ and PQ is the task of validation. The typical example of such a case could be the loss or absence of vendor's documentation for legacy equipment or do-it-yourself (DIY) assemblies (e.g., cars, computers, etc.) and, therefore, users should endeavour to acquire DQ document beforehand. Each template of DQ, IQ, OQ and PQ usually can be found on the internet respectively, whereas the DIY qualifications of machinery/equipment can be assisted either by the vendor's training course materials and tutorials, or by the published guidance books, such as step-by-step series if the acquisition of machinery/equipment is not bundled with on- site qualification services. This kind of the DIY approach is also applicable to the qualifications of software, computer operating systems and a manufacturing process. The most important and critical task as the last step of the activity is to generating and archiving machinery/equipment qualification reports for auditing purposes, if regulatory compliances are mandatory.^{[citation needed]}

Qualification of machinery/equipment is venue dependent, in particular items that are shock sensitive and require balancing or calibration, and re-qualification needs to be conducted once the objects are relocated. The full scales of some equipment qualifications are even time dependent as consumables are used up (i.e. filters) or springs stretch out, requiring recalibration, and hence re-certification is necessary when a specified due time lapse.^[12][13] Re-qualification of machinery/equipment should also be conducted when replacement of parts, or coupling with another device, or installing a new application software and restructuring of the computer which affects especially the pre-settings, such as on BIOS, registry, disk drive partition table, dynamically-linked (shared) libraries, or an ini file etc., have been necessary. In such a situation, the specifications of the parts/devices/software and restructuring proposals should be appended to the qualification document whether the parts/devices/software are genuine or not. Torres and Hyman have discussed the suitability of non-genuine parts for clinical use and provided guidelines for equipment users to select appropriate substitutes which are capable of avoiding adverse effects.^[14] In the case when genuine parts/devices/software are demanded by some of regulatory requirements, then re-qualification does not need to be conducted on the non-genuine assemblies. Instead, the asset has to be recycled for non-regulatory purposes.^{[citation needed]}

When machinery/equipment qualification is conducted by a standard endorsed third party such as by an ISO standard accredited company for a particular division, the process is called certification.^[15][16] Currently, the coverage of ISO/IEC 15408 certification by an ISO/IEC 27001 accredited organization is limited; the scheme requires a fair amount of efforts to get popularized.

Categories of validation

Validation work can generally be categorized by the following functions:

• Prospective validation – the missions conducted before new items are released to make sure the characteristics of the interests which are functioning properly and which meet safety standards.^[17][18] Some examples could be legislative rules, guidelines or proposals,^[19][20][21] methods,^[22] theories/hypothesis/models,^[23][24] products and services.^[25][26]
• Retrospective validation – a process for items that are already in use and distribution or production. The validation is performed against the written specifications or predetermined expectations, based upon their historical data/evidences that are documented/recorded. If any critical data is missing, then the work can not be processed or can only be completed partially.^[17][27][28] The tasks are considered necessary if:
  • prospective validation is missing, inadequate or flawed.
  • the change of legislative regulations or standards affects the compliance of the items being released to the public or market.
  • reviving of out-of-use items.

Some of the examples could be validation of:

• ancient scriptures that remain controversial^{[citation needed]}
• clinical decision rules^[29]
• data systems^[30][31]

• Full-scale validation
• Partial validation – often used for research and pilot studies if time is constrained. The most important and significant effects are tested. From an analytical chemistry perspective, those effects are selectivity, accuracy, repeatability, linearity and its range.
• Cross-validation
• Re-validation/locational or periodical validation – carried out, for the item of interest that is dismissed, repaired, integrated/coupled, relocated, or after a specified time lapse. Examples of this category could be relicensing/renewing driver's license, recertifying an analytical balance that has been expired or relocated, and even revalidating professionals.^[32][33] Re-validation may also be conducted when/where a change occurs during the courses of activities, such as scientific researches or phases of clinical trial transitions. Examples of these changes could be
  • sample matrices^[34][35]
  • production scales^[36][37]
  • population profiles and sizes^[38][39]
  • out-of-specification] (OOS) investigations, due to the contamination of testing reagents, glasswares, the aging of equipment/devices, or the depreciation of associated assets etc.^[40][41]

In GLP accredited laboratories, verification/revalidation will even be conducted very often against the monographs of the Ph.Eur., IP to cater for multinational needs or USP and BP etc to cater for national needs.^[42] These laboratories must have method validation as well.^[43]

• Concurrent validation – conducted during a routine processing of services, manufacturing or engineering etc. Examples of these could be
  • duplicated sample analysis for a chemical assay
  • triplicated sample analysis for trace impurities at the marginalized levels of detection limit, or/and quantification limit
  • single sample analysis for a chemical assay by a skilled operator with multiplicated online system suitability testings

Aspects of validation

The most tested attributes in validation tasks may include, but are not limited to

• Sensitivity and specificity
• Accuracy and precision
• Repeatability
• Reproducibility
• Limit of detection – especially for trace elements
• Limit of quantification
• Curve fitting and its range
• System suitability – In a broad way, it usually includes a test of ruggedness among inter-collaborators, or a test of robustness within an organization^[44][45][46] However, the U.S. Food and Drug Administration (FDA) has specifically defined it for its administration, as "System suitability testing is an integral part of many analytical procedures. The tests are based on the concept that the equipment, electronics, analytical operations and samples to be analyzed constitute an integral system that can be evaluated as such. System suitability test parameters to be established for a particular procedure depend on the type of procedure being validated".^[47] In some cases of analytical chemistry, a system suitability test could be rather a method specific than universal. Such examples are chromatographic analysis, which is usually media (column, paper or mobile solvent) sensitive^[48][49][50] However to the date of this writing, this kind of approaches are limited to some of pharmaceutical compendial methods, by which the detecting of impurities, or the quality of the intest analyzed are critical (i.e., life and death). This is probably largely due to:

• their intensive labouring demands and time consumption^{[51][clarification needed][52][53]}
• their confinements by the definition of the term defined by different standards.

To solve this kind of difficulty, some regulatory bodies or methods provide advice on when performing of a specified system suitability test should be applied and compulsory.

Industry references

These terms generally apply broadly across industries and institutions. In addition, they may have very specific meanings and requirements for specific products, regulations, and industries. Some examples:

• Software and computer systems
  Main article: Software verification and validation
• Food and drug manufacturing
  • Pharmaceuticals
  • Main article: Validation (drug manufacture)
    • The design, production, and distribution of drugs are highly regulated. This includes software systems. For example, in the US, the Food and Drug Administration have regulations in Part 21 of the Code of Federal Regulations.^[54] Nash et al. have published a book which provides a comprehensive coverage on the various validation topics of pharmaceutical manufacturing processes.^[55] Some companies are taking a risk-based approach to validating their GAMP system if one understands the regulatory requirements very well while the most of others follows the conventional process^[56][57] It is a part of GxP management. The aspects of validation and verification are even more intense and emphasized if an OOS occurs.^[58] Very often under this circumstance, a multiplicated sample analysis is required for conducting the OOS investigation in a testing laboratory.
  • Medical devices The FDA (21 CFR) has validation and verification requirements for medical devices, as outlined in ASME V&V 40. Also see guidance:^{[54][59][60][61]} and ISO 13485.
    Further information: Validation and verification (medical devices)
  • Manufacturing process and cleaning validation are compulsory and regulated by the U.S. Food and Drug Administration^{[62][63][64][65]}
  • Food hygiene: example ^[66]
  • Clinical laboratory medicine: ISO 15198:2004 Clinical laboratory medicine—In vitro diagnostic medical devices—Validation of user quality control procedures by the manufacturer
• Engineering
  • Engineering in general
    • Engineering validation test
  • Civil engineering
    • Buildings –
    • Roads –
    • Bridges –
• Health care: example^[67]
• Greenhouse gas: ISO 14064 ANSI/ISO: Greenhouse gases – Requirements for greenhouse gas validation and verification bodies for use in accreditation or other forms of recognition
• Traffic and transport
  • Road safety audit
  • Periodic motor vehicle inspection
  • Aircraft noise: example ^[68]
  • Aircraft:
• Model:^[69]
• (Ni-Cd) cells: example ^[70]
• ICT Industry: example ^[71]
• Economics
• Accounting
• Agriculture – applications vary from verifying agricultural methodology and production processes to validating agricultural modeling^{[72][73][74][75][76]}
• Real estate appraisal – audit reporting and authentication^[77]
• Arms control

See also

• Certification of voting machines
• Change control
• Comparability
• Data validation
• Formal verification
• Functional verification
• ISO 17025
• Positive recall
• Process validation
• Software verification and validation
• Statistical model validation
• System testing
• Usability testing
• Validation master plan
• Verification and validation of computer simulation models

Notes and references

1. Global Harmonization Task Force - Quality Management Systems - Process Validation Guidance (GHTF/SG3/N99-10:2004 (Edition 2) page 3
2. Ad Sparrius (2016). (PDF). 12th INCOSE SA Systems Engineering Conference. Archived from the original (PDF) on 6 August 2018. Retrieved 30 April 2018. There are some authors who apparently regard these two terms as synonymous, others who seem to be only vaguely aware of the differences. Some even appear to believe that V&V is one word! ... There is such a fundamental difference between these models that the term validation has many years ago been selected to be different from the term verification. Nevertheless, it is debatable whether the distinction between validation and verification should be continued.
3. James D. McCaffrey (28 April 2006). "Validation vs. Verification". Retrieved 30 April 2018. Two terms that sometimes confuse software test engineers are "validation" and "verification". ... Obviously the two IEEE definitions are so close to each other it's hard to determine the difference.
4. "Difference between Verification and Validation". Software Testing Class. 27 August 2013. Retrieved 30 April 2018. In interviews most of the interviewers are asking questions on "What is Difference between Verification and Validation?" Lots of people use verification and validation interchangeably but both have different meanings.
5. "IEEE Draft Guide: Adoption of the Project Management Institute (PMI) Standard: A Guide to the Project Management Body of Knowledge (PMBOK Guide)-2008 (4th edition)". IEEE P1490/D1, May 2011 (4th ed.). IEEE: 452. June 2011. doi:10.1109/IEEESTD.2011.5937011 (inactive 1 August 2023). Retrieved 28 March 2017.{{cite journal}}: CS1 maint: DOI inactive as of August 2023 (link)
6. "Systems and software engineering - Vocabulary," ISO/IEC/IEEE std 24765:2010(E), 2010. | verification 5. ...product, service, or system complies with a regulation, requirement, specification, or imposed condition.
7. IEEE 1012-2004, IEEE, 2004, p. 9
8. "Systems and software engineering - Vocabulary," ISO/IEC/IEEE std 24765:2010(E), 2010. | verification 6. ...comply with requirements (e.g., for correctness, completeness, consistency, and accuracy) for all life cycle activities during each life cycle process (acquisition, supply, development, operation, and maintenance)
9. "Systems and software engineering - Vocabulary," ISO/IEC/IEEE std 24765:2010(E), 2010. | validation (especially 1. & 2.)
10. Moradi, Mehrdad; Van Acker, Bert; Vanherpen, Ken; Denil, Joachim (2019). "Model-Implemented Hybrid Fault Injection for Simulink (Tool Demonstrations)". In Chamberlain, Roger; Taha, Walid; Törngren, Martin (eds.). Cyber Physical Systems. Model-Based Design. Lecture Notes in Computer Science. Vol. 11615. Cham: Springer International Publishing. pp. 71–90. doi:10.1007/978-3-030-23703-5_4. ISBN 978-3-030-23703-5. S2CID 195769468.
11. Barry Boehm, Software Engineering Economics, 1981
12. Analytical & Precision Balance Co. "Welcome". Retrieved 18 March 2008.
13. Scientech. . Archived from the original on 29 January 2020. Retrieved 18 March 2008.
14. Torres, Rebecca E.; William A. Hyman (2007). "Replacement Parts-Identical, Suitable, or Inappropriate?". Retrieved 29 March 2008.
15. AppLabs. . Archived from the original on 16 February 2008. Retrieved 26 March 2008.
16. AppLabs. . Archived from the original on 12 March 2008. Retrieved 26 March 2008.
17. . U.S. Food and Drug Administration. Archived from the original on 6 June 2009. Retrieved 12 July 2008.
18. . Groupe Novasep. Archived from the original on 15 November 2008. Retrieved 24 September 2008.
19. Quinn, James; McDermott, D; Stiell, I; Kohn, M; Wells, G; et al. (2006). "Prospective Validation of the San Francisco Syncope Rule to Predict Patients With Serious Outcomes". Annals of Emergency Medicine. Elsevier. 47 (5): 448–454. doi:10.1016/j.annemergmed.2005.11.019. PMID 16631985.
20. Sangiovanni, A.; Manini, M; Iavarone, M; Fraquelli, M; Forzenigo, L; Romeo, R; Ronchi, G; Colombo, M; et al. (2007). "Prospective validation of AASLD guidelines for the early diagnosis of epatocellular carcinoma in cirrhotic patients". Digestive and Liver Disease. Elsevier. 40 (5): A22–A23. doi:10.1016/j.dld.2007.12.064.
21. Germing, U.; et al. (2006). . Haematologica. 91 (12): 1596–1604. PMID 17145595. Archived from the original on 12 November 2010. Retrieved 24 September 2008.
22. Sciolla, Rossella; Melis, F; Sinpac, Group; et al. (2008). "Rapid Identification of High-Risk Transient Ischemic Attacks: Prospective Validation of the ABCD Score". Stroke. American Heart Association. 39 (2): 297–302. doi:10.1161/STROKEAHA.107.496612. PMID 18174479.
23. Pfisterer, Matthias; et al. (2008). "Drug-eluting or bare-metal stents forlarge coronary vessel stenting? The BASKET-PROVE (PROspective Validation Examination) trial: Study protocol and design". American Heart Journal. Mosby-Year Book Inc. 115 (4): 609–614. doi:10.1016/j.ahj.2007.11.011. PMID 18371466.
24. Van Geest-Daalderop, Johanna H. H.; Hutten, Barbara A.; Péquériaux, Nathalie C. V.; Levi, Marcel; Sturk, Augueste; et al. (2008). "Improvement in the regulation of the vitamin K antagonist acenocoumarol after a standard initial dose regimen: prospective validation of a prescription model". Journal of Thrombosis and Thrombolysis. Springer. 27 (2): 207–14. doi:10.1007/s11239-008-0203-4. PMID 18270659.
25. Ames, D.; Keogh, A.M.; Adams, J.; Harrigan, S.; Allen, N.; et al. (1996). "Prospective validation of the EBAS-DEP – A short sensitive screening instrument for depression in the physically ill elderly". European Psychiatry. Elsevier. 11 (Supplement 4): 361s. doi:10.1016/0924-9338(96)89148-6. S2CID 58984986.
26. Kidwell, Chelsea S.; Starkman, S; Eckstein, M; Weems, K; Saver, JL; et al. (2000). "Identifying Stroke in the Field: Prospective Validation of the Los Angeles Prehospital Stroke Screen (LAPSS)". Stroke. American Heart Association. 31 (1): 71–76. doi:10.1161/01.str.31.1.71. PMID 10625718. Retrieved 24 September 2008.
27. U.S. Food and Drug Administration. "Ch. 4 PROCESS VALIDATION in Medical Device Quality Systems Manual". Food and Drug Administration. Retrieved 6 August 2009.
28. Groupe Novasep. . Archived from the original on 15 November 2008. Retrieved 24 September 2008.
29. Hart, D.; S.W. Smith (2007). "Retrospective Validation of a Clinical Decision Rule to Safely Rule Out Subarachnoid Hemorrhage in Emergency Department Headache Patients". Annals of Emergency Medicine. 50 (3): S102–S103. doi:10.1016/j.annemergmed.2007.06.388.
30. Kluger, Michael D.; et al. (2001). "Retrospective Validation of a Surveillance System for Unexplained Illness and Death: New Haven County, Connecticut". American Journal of Public Health. 91 (8): 1214–1219. doi:10.2105/AJPH.91.8.1214. PMC 1446748. PMID 11499106.
31. Fine, Leon G.; et al. (2003). "How to evaluate and improve the quality and credibility of an outcomes database: validation and feedback study on the UK Cardiac Surgery Experience". BMJ. 326 (7379): 25–28. doi:10.1136/bmj.326.7379.25. PMC 139501. PMID 12511458.
32. Department of Health. . Archived from the original on 5 October 2012. Retrieved 30 September 2008.
33. Merkur, Sherry (2008). "Physician revalidation in Europe". Clinical Medicine. Royal College of Physicians. 8 (4): 371–6. doi:10.7861/clinmedicine.8-4-371. PMC 4952927. PMID 18724601.
34. Australian Pesticides & Veterinary Medicines Authority (2004). (PDF). Archived from the original (PDF) on 20 February 2011. Retrieved 12 July 2009.
35. Bressolle, Françoise; Brometpetit, M; Audran, M; et al. (1996). "Validation of liquid chromatographic and gas chromatographic methods Applications to pharmacokinetics". Journal of Chromatography B. 686 (1): 3–10. doi:10.1016/S0378-4347(96)00088-6. PMID 8953186.
36. Peptisyntha S.A. (2009). . Archived from the original on 31 May 2009. Retrieved 12 July 2009.
37. del Rosario Alemán, María (2007). "Downstream Processing: A Revalidation Study of Viral Clearance in the Purification of Monoclonal Antibody CB.Hep-1". Retrieved 12 July 2009.
38. El Eman, Khaled; Brown, A; Abdelmalik, P; et al. (2009). "Evaluating Predictors of Geographic Area Population Size Cut-offs to Manage Re-identification Risk". Journal of the American Medical Informatics Association. 16 (2): 256–266. doi:10.1197/jamia.M2902. PMC 2649314. PMID 19074299.
39. Tollman, Stephen M; Kahn, Kathleen; Sartorius, Benn; Collinson, Mark A; Clark, Samuel J; Garenne, Michel L; et al. (2008). "Implications of mortality transition for primary health care in rural South Africa: a population-based surveillance study". Journal of the American Medical Informatics Association. 372 (9642): 893–901. doi:10.1016/S0140-6736(08)61399-9. PMC 2602585. PMID 18790312.
40. United States Department of Health & Human Services (2009). "Warning Letter (WL No. 320-08-04)" (PDF). Food and Drug Administration. Retrieved 12 July 2009.
41. Health Canada (2004). "Validation Guidelines for Pharmaceutical Dosage Forms (GUIDE-0029)". Retrieved 12 July 2009.
42. Food and Drug Administration (May 2001). "Guidance for Industry: Bioanalytical Method Validation" (PDF). Food and Drug Administration. Retrieved 12 July 2009.
43. Method Validation; . Archived from the original on 11 September 2011. Retrieved 19 September 2011.
44. Health Sciences Authority. (PDF). Archived from the original (PDF) on 18 February 2012. Retrieved 29 September 2008.
45. Heyden, Y. Vander; S.W. Smith; et al. (2001). "Guidance for robustness/ruggedness tests in method validation". Journal of Pharmaceutical and Biomedical Analysis. Elsevier. 24 (5–6): 723–753. doi:10.1016/S0731-7085(00)00529-X. PMID 11248467. S2CID 14334288.
46. Ermer, Joachim; John H. McB. Miller (2005). Method Validation in Pharmaceutical Analysis: A Guide to best Practice. Wiley-VCH. p. 418. ISBN 978-3-527-31255-9.
47. "Calibration of dissolution test apparatus (USP apparatus 1 and 2) – SOP". {{cite web}}: Missing or empty |url= (help)
48. Szsz, Gy.; Gyimesi-Forrás, K.; Budvári-Bárány, Zs.; et al. (1998). "Optimized and Validated HPLC Methods for Compendial Quality Assessment. III. Testing of Optical Purity Applying 1-Acid-Glycoprotein Stationary Phase". Journal of Liquid Chromatography & Related Technologies. 21 (16): 2535–2547. doi:10.1080/10826079808003597.
49. Agilent. (PDF). Archived from the original (PDF) on 5 February 2015. Retrieved 29 June 2009.
50. Li, Yong-guo; Chen, M; Chou, GX; Wang, ZT; Hu, ZB; et al. (2004). "Ruggedness/robustness evaluation and system suitability test on United States Pharmacopoeia XXVI assay ginsenosides in Asian and American ginseng by high-performance liquid chromatography". Journal of Pharmaceutical and Biomedical Analysis. 35 (5): 1083–1091. doi:10.1016/j.jpba.2004.04.005. PMID 15336355.
51. 日本药局方. "Japanese Pharmacopoeia". Retrieved 29 June 2009.
52. "Optimizing fault injection in FMI co-simulation through sensitivity partitioning | Proceedings of the 2019 Summer Simulation Conference". dl.acm.org: 1–12. 22 July 2019. Retrieved 15 June 2020.
53. Moradi, Mehrdad, Bentley James Oakes, Mustafa Saraoglu, Andrey Morozov, Klaus Janschek, and Joachim Denil. "Exploring Fault Parameter Space Using Reinforcement Learning-based Fault Injection." (2020).
54. . FDA. May 1987. Archived from the original on 6 June 2009.
55. Nash, Robert A.; et al. (2003). Pharmaceutical Process Validation: An International Third Edition. Informa Healthcare. p. 860. ISBN 978-0-8247-0838-2.
56. De Caris, Sandro; et al. "Risk-based equipment qualification: a user/supplier cooperative approach" (PDF). Retrieved 15 June 2008.
57. Ocampo, Arlene; Lum, Steven; Chow, Frank; et al. (2007). "Current challenges for FDA-regulated bioanalytical laboratories for human (BA/BE) studies. Part I: defining the appropriate compliance standards – application of the principles of FDA GLP and FDA GMP to bioanalytical laboratories". The Quality Assurance Journal. John Wiley & Sons. 11 (1): 3–15. doi:10.1002/qaj.399.
58. "Guidance for Industry: Investigating Out-of-Specification (OOS) Test Results for Pharmaceutical Production" (PDF). Food and Drug Administration. 2006. Retrieved 12 July 2009.
59. "Guidance for Industry: Cybersecurity for Networked Medical Devices Containing Off-the Shelf (OTS) Software" (PDF). Food and Drug Administration. 14 January 2005. Retrieved 12 July 2009.
60. "General Principles of Software validation; Final Guidance for Industry and FDA Staff" (PDF). Food and Drug Administration. 11 January 2002. Retrieved 12 July 2009.
61. "Guidance for Industry and FDA Staff: Medical Device User Fee and Modernization Act of 2002, Validation Data in Premarket Notification Submissions (510(k)s) for Reprocessed Single-Use Medical Devices" (PDF). Food and Drug Administration. 25 September 2006. Retrieved 12 July 2009.
62. . Food and Drug Administration. May 1987. Archived from the original on 20 July 2009. Retrieved 12 July 2009.
63. "Guide to inspections validation of cleaning processes". Food and Drug Administration. July 1993. Retrieved 12 July 2009.
64. Nassani, Mowafak. "Cleaning validation in the pharmaceutical industry". Retrieved 20 March 2008.
65. Bharadia, Praful D.; Jignyasha A. Bhatt. . Archived from the original on 31 May 2012. Retrieved 20 March 2008.
66. (PDF). Archived from the original (PDF) on 11 October 2010. Retrieved 10 February 2011.
67. (PDF). Archived from the original (PDF) on 12 October 2007. Retrieved 14 June 2008.{{cite web}}: CS1 maint: archived copy as title (link)
68. (PDF). Archived from the original (PDF) on 27 September 2007. Retrieved 7 September 2007.{{cite web}}: CS1 maint: archived copy as title (link)
69. . Archived from the original on 13 October 2007.
70. Manzo, M.A.; Strawn, D.M.; Hall, S.W. (7 August 2002). "Aerospace nickel-cadmium cell verification-final report". Sixteenth Annual Battery Conference on Applications and Advances. Proceedings of the Conference (Cat. No.01TH8533). pp. 59–66. doi:10.1109/BCAA.2001.905101. ISBN 978-0-7803-6545-2. S2CID 110489981.
71. "Improving the efficiency of verification and validation". Inderscience.com. Retrieved 19 September 2011.
72. Masako, Tsujimoto. . Archived from the original on 17 February 2012. Retrieved 20 March 2008.
73. Vollmer-Sanders, Carrie Lynn; et al. . Archived from the original on 11 July 2011. Retrieved 20 March 2008.
74. Haboudane, Driss; et al. (2004). "Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture". Accreditation and Quality Assurance. Elsevier. 90 (3): 337–352. Bibcode:2004RSEnv..90..337H. doi:10.1016/j.rse.2003.12.013.
75. Thorp, Kelly; et al. "Using cross-validation to evaluate ceres-maize yield simulations within a decision support system for precision agriculture". Retrieved 20 March 2008.
76. Randolph, Susan; et al. (October 2007). "Monitoring the Realization of the Right to Food: Adaptation and Validation of the U.S. Department of Agriculture Food Insecurity Module to Rural Senegal". Economic Rights Working Papers. 6. Retrieved 20 March 2008.
77. Pruitt, Kirk; Ryan Paul Chamberlain. . Archived from the original on 29 June 2011. Retrieved 15 September 2008.

Further reading

• Majcen, N.; Taylor, P. (2010). Practical examples on traceability, measurement uncertainty and validation in chemistry. Vol. 1. European Union. p. 217. ISBN 978-92-79-12021-3.

External links

• Maturity of verification and validation in ICT companies
• Organisational maturity and functional performance