In plain English
Data integrity is about whether a record can be trusted. A result on a certificate is only as good as the records behind it [1, 2].
Regulators sum up good records as ALCOA+. A record shows who made it and when, is readable, is written at the time, is the first capture (or a checked copy), and is correct. The ”+” adds that the full set is there, hangs together, lasts, and can be reviewed [1, 3, 4].
Computer systems keep an audit trail: a log of who created, changed or deleted a record, when, and why. It works like crossings-out on paper that can still be read [1, 2].
On a certificate of analysis (COA), each number should lead back to an instrument file, a sample, an analyst and a date that someone could check.
The short version
- ALCOA: attributable, legible, contemporaneous, original, accurate [1, 3].
- The ”+”: complete, consistent, enduring, available [1, 3, 4].
- Audit trails record the who, what, when and why of every change [1].
- A printout is not the raw data when the original is an electronic file that can be reprocessed [1, 2].
- Shared logins break attributability [2].
What is data integrity?
The MHRA (the UK medicines regulator) defines data integrity as the degree to which data are complete, consistent, accurate, trustworthy and reliable, and the degree to which those characteristics are maintained throughout the life of the data [1]. The US FDA’s 2018 guidance uses a shorter form: data integrity refers to the completeness, consistency and accuracy of data, and such data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA) [2].
The FDA stresses that it applies at every stage: creation, modification, processing, maintenance, archiving, retrieval, transmission and final disposal [2]. Systems should be designed so that errors, omissions and unusual results are easy to detect [2].
Data integrity is not only an IT matter. The MHRA states that organisational culture and the behaviour of senior management strongly affect whether data governance works [1]. PIC/S calls this a “quality culture” [3].
ALCOA+ explained
The ”+” was added to the original five letters to emphasise the requirements. The MHRA notes there is no difference in expectations whichever acronym is used [1]. The WHO guideline uses ALCOA+ throughout [4].
| Attribute | What PIC/S says it means [3] | Example in a peptide testing laboratory |
|---|---|---|
| Attributable | It is possible to identify the individual or computerised system that performed a task, and when. Changes show who made them, when and why. | Each analyst logs in to the chromatography software under their own account. |
| Legible | Records are readable and unambiguous. Where electronic data are dynamic, the ability to interact with them matters. | The electronic chromatogram can still be opened and examined, not just a faded printout. |
| Contemporaneous | Actions, events and decisions are recorded as they take place. | A balance reading is recorded when it is taken, not copied up at the end of the day. |
| Original | The first capture of information, on paper (static) or electronically (usually dynamic). Information captured in a dynamic state should remain available in that state. | The instrument’s data file is kept, not only the PDF report made from it. |
| Accurate | A truthful representation of facts, supported by qualified and calibrated equipment, validated systems, data review, deviation management and trained staff. | The HPLC system is qualified and the method validated before results are reported. |
| Complete | All information critical to recreating an event is kept, including relevant metadata, and nothing is lost or deleted. | All runs in a sequence are kept, including any that were stopped or repeated. |
| Consistent | Information is created, processed and stored in a logical, defined way: date formats, units, rounding and significant figures. | Purity is reported to one decimal place by the same rounding rule on every COA. |
| Enduring | Records remain intact and accessible as a durable record for the whole retention period. | Data are backed up and can still be read after a software upgrade. |
| Available | Records can be reviewed at any time during the retention period, by those responsible for release decisions, investigations, audits or inspections. | An auditor can retrieve the raw data for a batch tested two years earlier. |
Where the expectations come from
| Document | Issued by | Year | Scope |
|---|---|---|---|
| GXP Data Integrity Guidance and Definitions, Revision 1 | MHRA (United Kingdom) | 2018 | All GxP areas; defines data, raw data, metadata, audit trail [1] |
| Data Integrity and Compliance With Drug CGMP: Questions and Answers | FDA (United States) | 2018 | Drug manufacturing records under CGMP [2] |
| PI 041-1: Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments | PIC/S | 2021 | GMP and good distribution practice inspections [3] |
| TRS 1033, Annex 4: Guideline on data integrity | World Health Organization | 2021 | GxP for medical products; electronic, paper and hybrid systems [4] |
| 21 CFR Part 11, § 11.10 | US Code of Federal Regulations | current | Controls for electronic records in closed systems [5] |
| EudraLex Volume 4, Annex 11: Computerised Systems | European Commission | 2011 | Computerised systems used in GMP [6] |
Regulatory attention is not new. One history traces FDA guidance related to data integrity back to 1963, and describes data integrity as the fundamental reason for 21 CFR Part 11 [9].
“GxP” is shorthand for the good practice codes as a group: good manufacturing practice (GMP), good laboratory practice (GLP), good clinical practice (GCP) and so on [4]. The WHO guideline notes that inspectors have been finding more data integrity problems across all of them [4].
Raw data, metadata and true copies
Raw data
The MHRA defines raw data as the original record: the first capture of information, on paper or electronically. Raw data must allow full reconstruction of the activity. Where data were captured electronically in a dynamic form, paper copies cannot be regarded as raw data [1].
There is one sensible exception. For simple instruments that do not store data, such as some balances and pH meters, the printout is the raw data [1, 2].
Static and dynamic records
The FDA distinguishes static records (a fixed record, such as paper or an electronic image) from dynamic records, which let the user interact with the content. A dynamic chromatographic record, for example, may let the user change the baseline and reprocess the data, so that peaks appear smaller or larger [2]. A printout or PDF of a chromatogram is static and does not preserve that dynamic record, so it cannot replace the original electronic data [2]. See How to Read an HPLC Chromatogram.
Metadata
Metadata are data that describe other data and give them context and meaning. The MHRA gives a simple example: the value “3.5” means nothing by itself, but “sodium chloride batch 1234, 3.5 mg, J Smith, 01 Jul 14” is a usable record [1]. Metadata form an integral part of the original record [1].
True copies
A true copy is a copy of the original record, on any medium, that has been verified, by a dated signature or a validated process, to hold the same information as the original, including the data that describe its context, content and structure [4]. The FDA uses the term “backup” for a true copy of the original record kept securely for the full retention period; a temporary copy made in case of a computer crash does not count [2].
Audit trails
An audit trail is a form of metadata that records the creation, modification or deletion of records, without obscuring or overwriting the original. It allows the history of a record to be reconstructed, including the “who, what, when and why” of each action [1].
The main expectations, side by side:
| Expectation | Source |
|---|---|
| Use secure, computer-generated, time-stamped audit trails to independently record operator entries and actions that create, modify or delete electronic records. Changes must not obscure previously recorded information. Keep the audit trail as long as the records. | 21 CFR 11.10(e) [5] |
| Record GMP-relevant changes and deletions, with the reason documented. Audit trails must be available, convertible to a readable form, and regularly reviewed. | EU GMP Annex 11, section 9 [6] |
| Audit trails identified as required by risk assessment should be switched on. Users should not be able to amend or switch them off. If an administrator does so, a record of that action should be kept. | MHRA [1] |
| Changes should be dated and time-stamped and associated with the person making them, with the reason recorded. | MHRA [1] |
| People who review records should review the related audit trails at the same time. The FDA compares this to assessing cross-outs on paper. | FDA [2] |
Paper records follow the same logic. The PIC/S Guide to GMP, which applies in Australia, requires records to be made at the time each action is taken. Any alteration must be signed and dated, must leave the original information readable, and where appropriate must record the reason [7, 8].
Common data integrity failures
Regulators’ guidance documents describe recurring problems:
- Shared logins. When login credentials are shared, no unique individual can be identified, so actions are not attributable. Shared read-only accounts are acceptable for viewing only [2].
- Testing into compliance. Testing samples repeatedly until a passing result appears is not consistent with CGMP. The FDA considers it a violation to use an actual sample in test, preparation or equilibration runs to disguise this [2].
- Reprocessing until a result “looks right”. Audit trails and retained records should allow all data processing to be reconstructed. If processing was repeated with progressively modified parameters, that should be visible [1].
- Excluding data. Data may be excluded only with a documented, valid scientific justification, and the excluded data must be kept with the original data set so the decision can be checked [1].
- Hybrid systems. A hybrid system uses a combination of electronic and paper records [4]. Such systems need extra controls because they are potentially more vulnerable to manipulation. PIC/S discourages their use and says they should be replaced where possible [3].
These are not rare. A study of FDA drug manufacturing warning letters from 2010 to 2020 found that deficiencies in documentation practices (data integrity) accounted for 21% of CGMP warning letters, behind process validation at 26% [10]. A separate analysis of 300 warning letters from the FDA’s Bioresearch Monitoring Program between 2007 and 2018 found that failure to follow procedures and poor documentation practices were the most common violations [11]. A 2023 review attributed most data integrity problems to poor quality culture, behaviour, leadership, processes or technology, and noted that electronic systems with audit trails can improve compliance over paper [12].
How a COA’s raw data should be traceable
A certificate of analysis (COA) is a summary. The question is whether each number on it leads back to records that meet ALCOA+.
The chain behind one result
For a purity result of, say, 98.6% by HPLC, the chain should look like this:
- COA → names the batch, the laboratory, the method and a report or sample number.
- Sample record → links that sample number to the vial or container received, the date and the person who logged it. See Batch Numbers and Traceability.
- Analytical sequence → the instrument run that included the sample, with its standards and system suitability checks.
- Raw data file → the original electronic chromatogram, which can be reopened and reprocessed [1, 2].
- Processing method and integration → the parameters used to calculate the result, attributable to the analyst [1].
- Audit trail → every change, reprocessing or deletion, with who, when and why [1, 5].
- Review and approval → a second person who checked the data, including the audit trail [2].
If any link is missing, the number on the COA cannot be independently checked.
What regulated buyers do
PIC/S expects manufacturers to have quality agreements with suppliers and contract laboratories that include data integrity provisions, and to verify the source electronic data and metadata during audits [3]. One measure it lists is comparing in-house test results with the supplier’s reported COA and examining discrepancies in accuracy, precision or purity results [3]. The WHO guideline adds that the contract giver is ultimately responsible for the integrity of data provided by contract acceptors [4].
Worked example: two COAs for the same batch
| COA A | COA B | |
|---|---|---|
| Laboratory named | Yes, with report number | Laboratory name only |
| Sample traceable to a batch | Batch and sample numbers match the label | No sample number |
| Chromatogram supplied | Yes, with metadata: file name, acquisition date, analyst, processing method | An image with no file name or date |
| Raw data available on request | Yes | Not stated |
| Analyst and reviewer | Named, with dates | Unsigned |
COA A can be traced back through the chain above. COA B might be accurate, but nothing on it allows that to be checked. See How to Read a Peptide COA.
What data integrity does not tell
- Whether the method was right. Perfect records of an unsuitable method still give an unsuitable answer. See Analytical Method Validation.
- Whether the laboratory is accredited. Accreditation is a separate assessment of competence for specific tests. See ISO/IEC 17025 and NATA.
What this means in Australia
- Medicines. The TGA requires Australian manufacturing of medicines to meet the PIC/S Guide to GMP (PE009-17), which has legal force through the Therapeutic Goods Act 1989 [8]. Its documentation chapter sets the paper-record expectations described above [7]. See Good Manufacturing Practice (GMP).
- PIC/S guidance. The TGA is listed among the members of PIC/S [14], the scheme that publishes PI 041-1 [3].
- Research materials. The TGA has stated that a “research use only” disclaimer does not make supply lawful or change a product’s regulatory status [13]. Good records do not change that.
This is general information, not legal advice. Laws change; check current TGA guidance.
Frequently asked questions
What does ALCOA stand for?
Attributable, legible, contemporaneous, original and accurate. These are the core attributes regulators expect of records [1, 2, 3].
What is the difference between ALCOA and ALCOA+?
ALCOA+ adds complete, consistent, enduring and available. The MHRA states that the expectations are the same whichever acronym is used [1].
What is an audit trail?
An audit trail is a secure, time-stamped record of who created, changed or deleted data, when and why, which does not overwrite the original entry [1, 5].
Is a printed chromatogram raw data?
Not when the original is an electronic file that can be reprocessed. The FDA states that a printout does not preserve a dynamic record. For simple instruments that only print, such as some balances, the printout is the raw data [1, 2].
References
- Medicines and Healthcare products Regulatory Agency (MHRA). ‘GXP’ data integrity guidance and definitions. Revision 1, March 2018. gov.uk. Accessed 25 October 2026.
- US Food and Drug Administration. Data integrity and compliance with drug CGMP: questions and answers. Guidance for industry, December 2018. fda.gov. Accessed 25 October 2026.
- Pharmaceutical Inspection Co-operation Scheme (PIC/S). PI 041-1: Good practices for data management and integrity in regulated GMP/GDP environments. 1 July 2021. picscheme.org. Accessed 25 October 2026.
- World Health Organization. Annex 4: WHO guideline on data integrity. WHO Technical Report Series, No. 1033, 2021. who.int. Accessed 25 October 2026.
- Code of Federal Regulations. Title 21, Part 11: Electronic records; electronic signatures. § 11.10 Controls for closed systems. ecfr.gov. Accessed 25 October 2026.
- European Commission. EudraLex Volume 4, Annex 11: Computerised systems. 2011. health.ec.europa.eu. Accessed 25 October 2026.
- Pharmaceutical Inspection Co-operation Scheme. Guide to Good Manufacturing Practice for Medicinal Products, PE 009-17: Part I, Chapter 4 (Documentation). 25 August 2023. tga.gov.au. Accessed 25 October 2026.
- Therapeutic Goods Administration. Good manufacturing practice (GMP) requirements for medicinal products: PIC/S Guide to GMP PE009-17. tga.gov.au. Accessed 25 October 2026.
- Rattan AK. Data integrity: history, issues, and remediation of issues. PDA J Pharm Sci Technol. 2018;72(2):105–116. doi:10.5731/pdajpst.2017.007765. PMID: 29158286
- Rathore AS, Li Y, Chhabra H, Lohiya A. FDA warning letters: a retrospective analysis of letters issued to pharmaceutical companies from 2010–2020. J Pharm Innov. 2022:1–10. doi:10.1007/s12247-022-09678-2. PMID: 35992018
- Rogers CA, Ahearn JD, Bartlett MG. Data integrity in the pharmaceutical industry: analysis of inspections and warning letters issued by the Bioresearch Monitoring Program between fiscal years 2007–2018. Ther Innov Regul Sci. 2020;54(5):1123–1133. doi:10.1007/s43441-020-00129-z. PMID: 32096103
- Charoo NA, Khan MA, Rahman Z. Data integrity issues in pharmaceutical industry: common observations, challenges and mitigations strategies. Int J Pharm. 2023;631:122503. doi:10.1016/j.ijpharm.2022.122503. PMID: 36529357
- Therapeutic Goods Administration. Understanding your responsibilities when importing, compounding and supplying unapproved peptide products. Safety advisory, 13 April 2026. tga.gov.au. Accessed 25 October 2026.
- Pharmaceutical Inspection Co-operation Scheme (PIC/S). Members. picscheme.org. Accessed 25 October 2026.
