Claims:We claim:

1. A quality tool (CALCULUSTM) used for evaluating the data integrity compliance at pharmaceutical manufacturing site, wherein measurement is based on quantified data.

2. A method of evaluation (CALCULUSTM) of the data integrity compliance at a pharmaceutical manufacturing site which is determined based on regulatory requirements and also internal need for increasing and elevating automation to reduce possibility of errors.

3. The method according to claim 2, wherein the data integrity compliance is provided a score (DI score) computed by considering the sum of a weightage of 85% for a first component including a data integrity checklist score and 15% for a second component including level of automation at site; wherein the pharmaceutical manufacturing site is provided a rating of A+, A, B or C based on the DI score.

4. The method according to claim 3, wherein the first component for measuring the data integrity compliance is based on data integrity checklist consisting of 163 parameters for assessing compliance level of sites with regards to regulatory requirements.

5. The method according to claim 3, wherein the 163 parameters are selected from:
a) Recording and collection of data
b) Original record/ True copy
c) Excluding data,
d) Data Processing
e) Data transfer/mitigation
f) Data Governance
g) Data Integrity Risk Assessment (DIRA)
h) Computerized System transactions
i) Computerized system User access/ System Administrator role
j) Audit Trail
k) Electronic Signatures
l) Data review and approval
m) Data Retention
n) Back up and Archive
o) File structure
p) Validation
q) IT supplier and Service provider
r) Quality Management Systems(QMS)
s) Calibration
t) Quality Control
u) Standalone Systems
v) Trainings
w) Manufacturing

6. The method according to claim 3, wherein the second component for measuring the data integrity compliance is based on the level of automation at site comprising weightage of 5% for Quality Control, 5% for Quality Assurance and 5% for Manufacturing.

7. The method according to claim 2, wherein the data integrity compliance at pharmaceutical manufacturing site requires a threshold value of >70%.

8. The method according to claim 3, wherein:
(i) the rating of A+ is assigned to a site with DI score of >90%;
(ii) the rating of A is assigned to a site with DI score of >70-90%;
(iii) the rating of B is assigned to a site with DI score of 50-70%;
(iv) the rating of C is assigned to a site with DI score of <50%; and
(v) the qualifying rating for the site as data integrity compliant is A+ or A.

Dated this 28th day of November 2019

SRIDEVI KRISHNAN
GENERAL MANAGER – CORPORATE PATENTS
PIRAMAL ENTERPRISES LIMITED
(APPLICANT)

To,

The Controller of Patents
The Patent Office
At Mumbai
, Description:FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
The Patents Rules, 2003

COMPLETE SPECIFICATION
(See section 10 and rule 13)

MONITORING COMPLIANCE OF PHARMACEUTICAL MANUFACTURING SITES

PIRAMAL ENTERPRISES LIMITED, a company incorporated under the Companies Act 1956, of Piramal Ananta, Agastya Corporate Park, Opposite Fire Brigade, Kamani Junction, LBS Marg, Kurla West, Mumbai - 400070, India

The following specification particularly describes the invention and the manner in which it is to be performed.

Field of the Invention
The present invention relates to a method of evaluating data integrity (DI) compliance of a pharmaceutical manufacturing site. The method provides quantified measurement of data Integrity compliance of manufacturing site.

Background of the Invention
Pharmaceutical products due to their nature of use need a high level of quality assurance. This is because they are used either as a prophylactic or curative drugs. While being used as a prophylactic they are expected to not lead to any complication or health hazard, whether short term or a long term. While being used as a curative, since they are used on patients who already have an underlying medical condition, the product is expected to cure the condition and while doing so should not cause any adverse reaction.

Unlike other high risk industries like automotive, aerospace which also play with human and animal lives; pharmaceutical industries take a more conservative approach. The reason behind this conservative approach is a high risk due to delayed detection of hazards to the biological race. To explain this, in case of a technical issue with an automobile or an aircraft, while it risks the lives to the extent of hazard when it crashes etc., the risk is immediate and future hazards can be prevented by a recall. In case of pharmaceutical industry, the knowledge of hazard caused by a drug to the human race could surface out after a few years or a decade and by which time there would be no way to reverse the onset of such damage that will definitely occur in those patients who have already consumed that drug. This is the reason pharmaceutical inventions undergo multiple clinical studies before they are commercialized and require a strict adherence to regulatory guidance on a continued basis.

Unfortunately, pharmaceutical regulatory guidance is still under the phase of harmonization and it varies from country to country. For e.g. CFRs in US, EU annexes in Europe, Orange guide in UK, WHO in rest of the world and so on. For a company of a global standard complying to all the regulations where it markets its product individually is an extremely onerous task and complicates its quality system too. This requires a harmonized approach to one quality system that fits to all the norms. In order to do this, it is important for a company to design a common platform to lay its standards, execute and then it is important to understand the stage at which they are in complying with these standards.

“Write what you do and do what you have written” are golden words in GxP compliance. Assessment of these words though is fairly complicated, runs through a stepwise approach in checking around 800 Standard Operating Procedures (SOPs) in a typical Pharma plant, each SOP running into several pages and steps. Most companies use an internal audit program as dip stick to measure the level of compliance. This however is a sample based check and can miss vital over trivial if not performed by an experienced auditor. It also has some level of variable outcome on assessment from auditor to auditor .Data Integrity compliance is most critical and although a part of GMP compliance and requirements is gaining importance due to rise in integrity non compliances across pharmaceutical industry.

Companies also use various metric to understand where they stand in respect of of data integrity compliance. Key metrics are however individually tracked and do not give an overall inference on a company’s compliance. What it measures is an intangible sense of compliance. This often lead to a pitfall in compliance focus and surprises during regulatory audit leading to import alert or statement of non-compliance leading to high business and reputation impact as well as non-availability of product to the patients.

Therefore there is a need for a tangible value that can sense Data Integrity compliance risk and obtain the required attention from the quality point of view. It also enables channelizing the attention to where it is needed. Additionally it comes as a ready reckoner to preparing for any regulatory inspections. The inventors of the present invention have provided a quality tool to obtain this quantitative measurement.

Summary of the Invention
In one aspect, the present invention provides a quality tool (CALCULUSTM) used for evaluating the data integrity compliance at pharmaceutical manufacturing sites, wherein measurement is based on quantified data and the outcome is useful to interpret the probable outcome of regulatory inspections at a site.

In another aspect, the present invention provides a method of evaluation (CALCULUSTM) of the data integrity compliance at a pharmaceutical manufacturing site which is determined based on regulatory requirements and also internal need for increasing and elevating automation to reduce possibility of errors.

In another aspect, the present invention provides the method, wherein the data integrity compliance is provided a score (DI score) computed by considering the sum of a weightage of 85% for a first component including a data integrity checklist score and 15% for a second component including level of automation at site.

In yet another aspect, the present invention provides the method, wherein the first component for measuring the data integrity compliance is based on data integrity checklist consisting of 163 parameters for assessing compliance level of sites with regards to regulatory requirements as described herein.

In a further aspect, the present invention provides the method, wherein the second component for measuring the data integrity compliance is based on the level of automation at site comprising weightage of 5% for Quality Control, 5% for Quality Assurance and 5% for Manufacturing.

In an aspect, the present invention provides the method, wherein the data integrity compliance at pharmaceutical manufacturing site requires a threshold value of >70%.
In an aspect, the pharmaceutical manufacturing site is provided a rating based on the DI score as described herein.

These and other aspects and advantages of the present invention will be apparent to those skilled in the art from the following description.

Brief Description of Drawings of the Invention
Figure 1 is a Schematic representation of qualifying parameters for Data integrity (CALCULUSTM).

Detailed Description of the Invention
It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art. One skilled in the art, based upon the description herein, may utilize the present invention to its fullest extent. The following specific embodiments are to be construed as merely illustrative, and not limitative of the remainder of the disclosure in any way whatsoever.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs.

Definitions
For the purpose of the disclosure, listed below are definitions of various terms used to describe the present invention. Unless otherwise indicated, these definitions apply to the terms as they are used throughout the specification and the appended claims, either individually or as part of a larger group. They should not be interpreted in the literal sense. They are not general definitions and are relevant only for this application.

It should be noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise.

It should be noted that the term “or” is generally employed in its sense including “and/or” unless the content clearly dictates otherwise.

In an embodiment, there is provided a quality tool (CALCULUSTM) used for evaluation of the data integrity compliance at pharmaceutical manufacturing sites, wherein measurement is based on intangible data and the outcome is useful to interpret the probable outcome of regulatory inspections at a site.

In an embodiment, there is provided a method of evaluation (CALCULUSTM) of the data integrity compliance at a pharmaceutical manufacturing site, which is determined based on regulatory requirements and also internal need for increasing and elevating automation to reduce possibility of errors.

In an embodiment, there is provided a first component for data integrity compliance measurement, which includes assessing compliance level of sites with regards to regulatory requirements (163 parameters) and second component including level of automation at each site.

In an embodiment, the parameters used to evaluate the data integrity compliance of a pharmaceutical manufacturing site are selected from the categories as under:
(a) Recording and collection of data
(b) Original record/ True copy
(c) Excluding data,
(d) Data Processing
(e) Data transfer/mitigation
(f) Data Governance
(g) Data Integrity Risk Assessment (DIRA)
(h) Computerized System transactions
(i) Computerized system User access/ System Administrator role
(j) Audit Trail
(k) Electronic Signatures
(l) Data review and approval
(m) Data Retention
(n) Back up and Archive
(o) File structure
(p) Validation
(q) IT supplier and Service provider
(r) Quality Management Systems(QMS)
(s) Calibration
(t) Quality Control
(u) Standalone Systems
(v) Trainings
(w) Manufacturing

In an embodiment, the data integrity compliance is based on the regulatory (FDA, MHRA, PIC/S etc.) guidance on Data Integrity and is evaluated based on the accuracy, reliability and consistency of the system, process and content. The threshold value for qualifying as data integrity compliant site is >70% as depicted in Figure 1.

Data Integrity score are computed by considering below weightage of score as follows:-
DI Score =Data integrity checklist score (85%) + Level of automation at site (15%)
Level of automation at site is computed as per criteria set out in Table 1:-

Table 1
Level of automation scoring criteria (15%)

Quality Control (5%)
Quality Assurance (5%)
Manufacturing (5%)

Automation within Quality Control labs (HPLC and other instruments) are considered and compliance percentage is allotted
Automation within Quality Assurance (Document management system, training system, aberration handling systems etc.) are considered and compliance percentage is allotted
Automation within Manufacturing (shop floor) is considered (Having PLC, SCADA etc.) are considered and compliance percentage is allotted
Note:- Percentage may vary based on assessment
PLC: Programmable Logic Controller
SCADA: Supervisory Control and Data Acquisition

Modality of implementation:
• The checklist is designed by the Central Quality team based on current regulatory requirements and provides them to the sites.
• Site team does gap assessment based on checklist.
• Central Quality team evaluates and provides scoring.
• Further extent of automation at each site is evaluated by Central quality team and scores are computed.
• Sites falling below qualifying level are given immediate attention for remediation
• Site team works on gaps and improves the scores.

In an embodiment, the pharmaceutical manufacturing site is provided a rating based on the DI score as follows:
(i) the rating of A+ is assigned to a site with DI score of >90%;
(ii) the rating of A is assigned to a site with DI score of >70-90%;
(iii) the rating of B is assigned to a site with DI score of 50-70%;
(iv) the rating of C is assigned to a site with DI score of <50%; and
(v) the qualifying rating for the site as data integrity compliant is A+ or A (as described in Figure 1).

Examples

Example 1:

The score of site “A” for Data Integrity compliance is depicted in table 2, where the scores from DI checklist and the automation are on the lower side. The site is having inadequate data governance, data retention, no audit trail, lack of DI training and undefined review and approval procedures. The site is also lacking in automation in manufacturing, quality control and quality assurance systems.
Table 2
Parameters % Contribution factors used for computation Scores of Site A Total DI Score of Site A
DI checklist score 85 44.3489 48.34
Automation score 15 4

CALCULUSTM Interpretation at Site A:
Based on the computation of above scores, the site “A” is rated as C for compliance to data integrity. This weak condition of site A can be improved by mainly focusing on improvements in record management, data governance, data review and approval, trainings and in automation, which will result in increase of DI compliance score.
Example 2:
The score of site “A” for CALCULUSTM are depicted in table 3, where although the automation score is low but there are improvements in the DI checklist scores. The site has initiated the training programs on data integrity, which is leading to awareness amongst the employees and in turn making them to exercise appropriate methods/controls during data review and approval.
Table 3
Parameters % Contribution Scores of Site A Total DI Score of Site A
DI checklist score 85 58.1725 62.7
Automation score 15 4.0

CALCULUSTM Interpretation at Site A:
Based on the computation of above scores, the site “A” is rated as B for compliance to data integrity. This condition of site A can be improved further by focusing more on improvement in recording and collection of data, data governance and in automation, which will result in increase of DI compliance score.
Example 3:
The score of site “A” for CALCULUSTM are depicted in table 4, and it can be seen that there are improvements in the DI checklist score and automation score. The site has built a data governance mechanism and procedures for handling data integrity incidents. The site has also initiated the data integrity audits at sites and reviews with leadership team to have continuous vigilance. In terms of automation, site has improvised the computerized systems transactions, activated the audit trails for all the computerized systems and automated some of the Quality Control and production functions. The site has also prepared a risk assessment report for all the standalone instruments in use at site.
Table 4
Parameters % Contribution Scores of Site A Total DI Score of Site A
DI checklist score 85 79.5090 86.51
Automation score 15 7

CALCULUSTM Interpretation at Site A:
Based on the computation of above scores, the site “A” is rated as A for compliance to data integrity. The condition of site A can be improved further by focusing more on the importance of validation of computerized systems and increasing the automation at production, quality assurance and control functions.
Example 4:
The improvised scores of site “A” for CALCULUSTM are depicted in table 5. The site has improvised the data integrity compliance in the systems and has increased the automation of the functions of Quality Control, Quality Assurance and production like modules of document management, Quality Management Systems and training management.
Table 5
Parameters % Contribution Scores of Site A Total DI Score of Site A
DI checklist score 85 84.2185 94.21
Automation score 15 10

CALCULUSTM Interpretation at Site A:
Based on the computation of above scores, the site “A” is rated as A+ for compliance to data integrity. The above score can further be improved by maintaining consistent compliance in the processes with respect to data integrity, data governance and by increasing the automated functions in Quality Control, Quality Assurance and production.