A Study of Regulatory Agencies Inspected Global Drug Manufacturers

Sanjay Kumar Jain¹, Rajesh Kumar Jain²

¹Ph.D Scholar, Nirma University, Ahmedabad, Gujarat, India.

²Professor- Operations Management, Nirma University, Ahmedabad, Gujarat.

*Corresponding Author E-mail: sanjaykumarjain@ymail.com, rajeshjain@nirmauni.ac.in

ABSTRACT:

Pharmaceutical industry manufactures various type of pharmaceutical products like drug substances, drug products, medical devices and bio-pharmaceuticals for the treatment of diseased persons, hence product quality and patient safety is paramount vital. This is very reason that this industry is highly regulated industry. In spite of stringent regulations, there is increased number of warning letters which is a matter of concern for the manufacturers, drug authority and society. As a part of this study, 85 warning letters (www.fda.gov) issued to the drug substance and drug product manufacturers for three years (2014 to 2016) were reviewed. The qualitative and quantitative study was undertaken as a part of this study. In qualitative study, six experienced pharma professionals were interacted with an objective to know the reasons for issuance of warning letters. In quantitative study, an instrument was developed to measures the Practices regarding quality system, data integrity management practice, laboratory control and manufacturing control management practices. Instrument consisting of 64 items was circulated to various pharma professionals working in the pharmaceutical companies across the globe. Data collected from qualitative study were compiled and concluded that poor quality system, lack of management overview, right quality culture in the organization, incorrect attitude of employees towards quality and data integrity are the major reasons for non-compliances resulting into issuance of warning letter. Data collected from 317 responsdents was statistically analysed and it revealed the differences in the Good Manufacturing Practices (GMP) among the pharma drug manufacturer of India and Abroad. It also revealed that GMP practices within India are same. There is difference in GMP practices in large and small organizations with respect to based on annual turnover and employee strength. Issuance of warning letter and import alert has significant impact on continuity of the business as there is loss of trust among partners, regulators and customers. There is loss of business opportunity and manufacturer has to spend time and money to revive the quality system meeting Agency’s expectations. There is need for Paradigm shift in quality culture and transparency. Quality, compliance and integrity are the pillars for any pharmaceutical organization to be successful.

KEYWORDS: FDA, cGMP, Warning Letter, Import Alert, Data Integrity, Pharmaceutical Industry, Quality Management.

1. INTRODUCTION:

Pharmaceutical industry manufactures various type of pharmaceutical products like Drug substance, drug products (Tablet, Capsule, injectable etc.), and medical devices for treatment of the diseased persons; hence the product quality and patient safety is paramount vital for these products.

It highlights the importance of pharmaceutical product manufacturers and their reponsibility towards the regulators and end consumers (patients) with respect to Product Efficacy, Quality, and Patient Safety. This is the very reason that this industry is highly regulated industry. USFDA health regulatory agency (hereafter referred to as FDA) from United States of America is responsible to regulate the pharmaceutical manufacturers supplying the drug products for US citizens. Investigators from the agency (FDA) perform inspections of the drug substance and drug product manufacturing sites across the globe conducted for four reasons: (1) Pre-approval inspection (PAI) before approval of the drug product (2) Regular GMP inspection and (3) Post approval and Surveillance and (4) Cause Audit. FDA investigators are instructed to perform the inspection based on six systems categorised as (1) Quality system, (2) Production System, (3) Facilities and Equipment system, (4) Laboratory control system, (5) Materials system and (6) Packaging and Labelling system. They verify compliance to the cGMP requirement, compliance to the SOPs and compliance to data integrity requirement. If any non-compliance is observed during the course of audit, the investigator inform the observation to the responsible person of manufacturing site on form 483 (Objectionable conditions cited by FDA on the Form No 483) and that is why these non-compliance observations are popularly known as “483 observations”. The agency expects to submit the response within 15 business days by the manufacturer explaining the reason for existence of non-compliance, impact of the product quality and appropriate corrective action taken to avoid the recurrence. The agency issues warning letters to the manufacturers when they determine that the response is not satisfactory; non-compliances are critical in nature having direct impact on product quality, patient safety and data integrity. It has been observed that there is significant increase in warning letters issued by the FDA year after year inspite of clarity in the guidance issued by the agency. Significant increase in number of warning letters is matter of concern for the manufacturer, drug authority and consumers¹.

In addition to product quality, data integrity is fundamental in a pharmaceutical quality system which ensures that medicines are of the required quality as decisions on product quality are made based on the data. Electronic data and computerised systems have introduced new challenges to maintain data integrity; hence the data governance system should be integral to the pharmaceutical quality system as required by regulatory authorities².

2. PHARMACEUTICAL INDUSTRY:

Pharmaceutical products-more commonly known as medicines or drugs-are a fundamental component of both modern and traditional medicine. It is essential that such products are safe, effective, and of good quality. Pharmaceutical manufacturer deals in manufacturing of Active pharmaceutical ingredient (API) or Drug substance, finished formulation or Drug product, Medical devices. APIs are used in preparing the finished formulations i.e. tablet, capsule, injectable etc., which is consumed by the patients.

Drug Substance (Active Ingredient) means any component that is intended to furnish pharmacological activity or other direct effect in the diagnosis, cure, mitigation, treatment, or prevention of disease, or to affect the structure or any function of the body of man or other animals. The term includes those components that may undergo chemical change in the manufacture of the drug product and be present in the drug product in a modified form intended to furnish the specified activity or effect.

Drug Product means a finished dosage form, for example, tablet, capsule, solution, etc., that contains an active drug ingredient generally, but not necessarily, in association with inactive ingredients. The term also includes a finished dosage form that does not contain an active ingredient but is intended to be used as a placebo.

A Medical Device is "an instrument, apparatus, implement, machine, contrivance, implant, in vitro reagent, or other similar or related article, including a component part, or accessory which is:

· Recognized in the official National Formulary, or the United States Pharmacopoeia, or any supplement to them,

· Intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease, in man or other animals, or

· Intended to affect the structure or any function of the body of man or other animals, and which does not achieve any of its primary intended purposes through chemical action within or on the body of man or other animals and which is not dependent upon being metabolized for the achievement of any of its primary intended purposes.

Medicines are perhaps as old as Mankind and the understanding how their quality has to be ensured has evolved gradually over the time. Unfortunate events have prompted the development of medicines regulations more than the evolution of a knowledge base. Drugs are not ordinary consumer products and in most of the instances, consumers are not in a position to make decisions about quality of the drugs¹.

Pharmaceutical industry is highly regulated industry and Goal is to ensure that drugs prevent infections, maintain health, and cure diseases. United States Food and Drug Administration (USFDA)/Regulatory Agency of the exporting countries regularly audits the manufacturing facilities. Leading International Regulatory bodies listed below monitor attributes like drug safety, quality, pricing among others.

· World Health Organization (WHO)

· United states Food and Drug Administration (USFDA)

· European Medicines Agency (EMA)

The pharmaceutical industry in India ranks 3^rd in the world in terms of volume and 14^th in terms of value accordingly to Department of Pharmaceuticals, Ministry of Chemicals and Fertilizers. The Country’s pharmaceutical industry is expected to expand at a compound annual growth rate (CAGR) of 22.4% over 2015-20 to reach USD 55 billion. Indian drugs are exported to more than 200 countries in the world, including Unites States of America (USA) as the key market. Generic drugs account for 20% of global exports in terms of volume, making the country the largest provider of generic medicines globally and expected to expand even further in coming years. India’s pharmaceutical exports stood at USD 17.27 billion in 2017-18 (https://www.ibef.org/industry/pharmaceutical-india.aspx)³.

3. FDA INSPECTION SYSTEM AND WARNING LETTERS:

The FDA's Drug Manufacturing Inspection Compliance Program is a system-based approach to inspection, and is very consistent with the robust quality system. FDA investigators are instructed to perform the inspection based on six systems categorised as:

Figure 1: The Six-System Inspection Model

Source: Jain and Jain, Research J. Pharm. and Tech. 11(7): July 2018

The Figure1 shows the relationship among the six systems i.e. the quality system and the five manufacturing systems (1) Production System, (2) Facilities and Equipment system, (3) Laboratory control system, (4) Materials system and (5) Packaging and Labelling system. The quality system provides the foundation for the manufacturing systems that are linked and function within it. One of the important themes of the system based inspection compliance program is that investigator can assess whether each of the systems is in a state of control.

USFDA inspections of pharmaceutical manufacturing plants in the past few years mainly has increased significantly due to increase in manufacturing sites thus increase in number of pre-approval inspections, routine GMP inspections and compliance follow-up activities. It has become clear that effective and efficient inspectional coverage has been crucial to the successful management of their inspection program of FDA being resource-intensive nature and that can be achieved only through maintenance of consistency and uniformity of inspection and enforcement activities. The agency tries to utilize highly qualified Investigators and Analysts for the foreign inspection program who have extensive experience in conducting drug inspections with demonstrated track records of working effectively in a tight time frame and under considerable pressure¹.

Quality system is always part of the inspection along with other system randomly selected by investigator (s) at their own discretion. Implementation of above comprehensive quality systems model will allow manufacturers to support and sustain robust, modern quality systems that are consistent with CGMP regulations. “Quality should be built into the product, and testing alone cannot be relied on to ensure product quality” is predominant philosophy of FDA and in robust modern quality systems. Flexibility of the CGMP regulations laid down by FDA enable manufacturers to implement a quality system in a form that is appropriate for their specific operations. FDA ensures the quality of drug products, medical devices and dietary supplements by carefully monitoring compliance with Current Good Manufacturing Practice (CGMP) regulations. These regulations contain minimum requirements for the methods, facilities, and controls used in the manufacturing, processing and packing of a regulated product. CGMP rules in essence ensure the safety of a product².

When FDA finds that a manufacturer has significantly violated FDA regulations, FDA notifies the manufacturer in the form of a Warning Letter. The Warning Letter identifies the violation, such as poor manufacturing practices, poor laboratory practices, data integrity issues, problems with claims for what a product can do, or incorrect directions for use. The letter also makes clear that the company must correct the problem and provides directions and a timeframe for the company to inform FDA of its plans for correction. Warning letter may result into:

· Import alert/Ban of export of goods to USA market

· Loss of business,

· Creating negative image of the Pharmaceutical product manufacturer.

FDA,during follow up audit,checks and ensures that the company’s corrections are satisfactory and adequate¹.

The FDA provides an electronic reading room on its website that provides access to a great deal of useful information, including copies of Warning Letters issued by the FDA. Reviewing these letters can be useful because they provide insight into the inspection techniques and concerns of FDA inspectors. Understanding common violations mentioned in such notifications can prove beneficial to those firms undergoing inspections. Additionally, they can be used to perform gap analyses of the processes used in other organization in preparation for an FDA inspection.

Authors reviewed the FDA's website to study the Warning Letters issued for 3 years between Jan 2014 and Dec 2016. The review was limited to those referencing drug product and drug substances involving aseptic processing and non-sterile processing, and the data were summarised. Warning letters were divided in three categories based on the nature of products being manufactured at the site:

· Non-sterile Drug Products

· Sterile Drug Products

· Drug Substance/Active Pharmaceutical ingredient

The study revealed that 85 manufacturing sites were issued the warning letters. 17 warning letters were issued in year 2014, 18 warning letters in year 2015 and 50 warning letters in year 2016. There is increase in number of warning letters year after year as focus of the FDA was more on data integrity issues and FDA found serious breaches in the integrity of the documents generated by the firms during manufacturing, analysis of the samples of drug product batches. A few firms manufacturing both drug substance and drug product manufacturing plants were issued warning letters having non-compliance for both type of products. We have separated their non-compliance observations appearing in the warning letters product category wise. The non-compliances appearing in these warning letters and those issued to other manufacturers were then analysed using cause and effect analysis.

There are 3652 FDA registered manufacturing sites in 30 countries. The analysis indicates that non-compliances are not specific to particular country, region or continent but are wide spread. Highest numbers of the warning letters (68%) are issued to manufacturers located in Asia followed by 15% in Europe and 10% in North America.

Import alert is issued to the manufacturer, if the 483-Observations cited by the investigator are critical in nature i.e. having direct impact on product quality, patient safety and breach of data integrity. The manufacturer under import alert cannot export the product to the USA until the import alert is lifted by the agency. Total 26 manufacturers were placed under import alert which is 30.6% of the warning letters issued by the agency. Out of these 26, 46% manufacturers were from China and 34% from India. Before revoking the import alert, the agency verifies cGMP (Current GMP) compliance and ensures that there are no more product quality, patient safety and data integrity issues at the manufacturing site.

The author reviewed all the cited observations (580) in 85 warning letters for last 3 years. Pareto analysis (Figure 2) of the observations revealed that the top four issues among all categories of the plants are contributing 82% of the total observations. These are related to poor quality system (195, 34%), followed by breach of data integrity (142, 24%), poor laboratory controls (76, 13%) and poor production controls (65, 11%). For manufacturing with sterile operation where the risk is high w.r.t. product quality and patient safety, the highest issues were related to poor aseptic behaviour i.e. 31.5% of the total 130 observations cited in the warning letters. This analysis clearly gives a pattern of the observations.

4. LITERATURE REVIEW:

Gough (1989) explained that attainment of an assurance of the quality of a company's products is a function of the attitude of mind of the individuals working within that company, starting with the chief executive and emanating downwards⁴. Goodwin and Jacobs (2013) discussed in their article that FDA warning letters are issued advising drug and device manufacturers about alleged regulatory violations and providing the manufacturer an opportunity to respond and take voluntary corrective action⁵. Yu Lawrence X., and Woodcock Janet (2015) poised the role of the Office of Pharmaceutical Quality (OPQ) to achieve the goals laid out in the FDA’s Twenty first Century Initiative. The establishment of OPQ will result in enhanced transparency and communication between the Agency and industry related to manufacturing technologies, issues, and capabilities, thereby preventing drug shortages and ensuring the availability of high-quality drugs⁶.

Ananth et.al (2018) concluded that there is an increase in warning letters in case of drugs and pharmaceuticals. Their review concluded that warning letters are increasing rapidly for drugs and formulations, whereas they were decreasing for medical devices and biologicals⁷. Khojaet. al (2016) found that Data integrity is main issue raised in most FDA warning letter, followed by failure to have computerized system with sufficient control to prevent unauthorized access or manipulation of data⁸. Unger (2019) in her review of warning letters for FY 2018 concluded that there was continued focus on data integrity and data governance by FDA⁹. Patel (2012) concluded that FDA inspections are mainly focusing on the quality system, as the quality system provides the foundation for the manufacturing systems¹⁰.

5. RESEARCH GAP AND QUESTIONS:

Pharmaceutical product manufacturers are responsible to follow Good Manufacturing Practices and produce consistent product quality to be consumed by the diseased patients, while the regulators are responsible to ensure that they safegaurd health of people in their country with proper checks and balances on the pharma product manufacturer. Ultimately, both of them are responsbile to the consumers i.e. patients. However, there seems to be crevice between manufacturers and regulators as evident from the increased number of non-compliances, warning letters, import alerts issued to manufacturers. It was important to study the best practices in pharmaceuticals industry to determine some metrics to check the health of compliance system internally by the manufacturer. The researcher decided that it would be meaningful to conduct a comparative study of pharmaeceutical manufacturer (s) approved by regulatory agencies and find out GMP practices across the sites.

It is evident from the review of literatures and FDA communique that there is no reseach undertaken on the GMP issues and following research gaps have been identified and researcher did not come across any:

· Study to compare the GMP practices among pharmaceutial manufacturer who are manufacturing the products for regulated markets.

· Study to understand the reasons for recurring quality issues and issuance of warning letters to pharmaceutical industries.

· Study about the role of senior management in maintaining the quality culture.

Research questions shall focus on creating better solutions or creating better knowledge. Based on literature review and research gaps, this study has following research questions:

1. What are the recurring reasons for the issuance of warning letters and/or import alerts to the pharmaceutical organization?

2. Does GMP practices vary in India as compare to overseas countries?

3. Does GMP practices vary within India among the manufacturers?

4. Does GMP practices vary from small to large organizations?

5. Does GMP practices vary from type of manufacturer (Drug Substance, Drug Product and Sterile product)

6. METHODOLOGY:

The Data were collected from both primary and secondary sources. The Primary data were collected with the help of a structured questionnaire through the survey method. The secondary data were collected from the pharmaceutical reports, journals and websites. Based on review of secondary source data i.e. warning letters, literatures, a data collection tool (Questionnaire) was developed to collect the first hand information for the study. Questions were developed based on the recurring findings and major causes of non-compliances as listed in the warning letters issued to the manufacturers. All items were measured on a five point Likert scale, where the lowest point (1) Completely Disagree, point (2) Somewhat Disagree, point (3) Neither Agree nor Disagree, point (4) Somewhat Agree and point (5) Completely Agree.The analysis of warning letters revealed that there are 580 non-compliances reported in 85 warning letters for last 3 years. Pareto analysis of the non-compliance observations revealed that the top four issues among all categories of the plants are contributing 82% of the total non-compliance observations. These are related to poor quality system (195, 34%), followed by breach of data integrity (142, 24%), poor laboratory controls (76, 13%) and poor production controls (65, 11%). The questionnaire consisting 64 items, had the following four parts:

1. Part A – Quality Metrics And Quality System

2. Part B – Data Integrity

3. Part C – Laboratory Control

4. Part D – Production Control

To check the validity of the questionnaire, it was piloted on close associates (three professionals within India and three professionals working abroad) from the pharma industry. The questionnaire was modified based on their feedback related to content of certain items. The final Questionnaire was than sent to different respondents. Professionals working in Pharmaceutical companies both in India and abroad were contacted based on the convenient and snowball sampling method. The questionnaire then was accordingly sent to 867 + pharma professionals working in different functions of different organizations globally with a request to respond to the same. After a close follow-up, we received 317 responses which represented different organizations including manufacturing sterile drug products, non-sterile drug products, active pharmaceutical ingredients and combinations of these types of products.

Statistical analysis of the data obtained from these respondents participated in the survey was conducted. Cronbach’s alpha value is 0.9577; which confirmed the internal consistency reliability of questionnaire. (Cronbach’s alpha value of 0.6 or less generally indicates unsatisfactory internal consistency reliability).

To avoid any biased response, multiple people were chosen from any single organization to make the responses more representative of that organization. 80% of the respondents are working in the organizations located in India and 18% located abroad (e.g. Asia, North America, South America and European countries). Within India, 59% respondents were from organizations located in west India, 14% located in South India, 7% located in North India and 20% located in central India. Majority of the respondents (69%) are having more than 10 years’ experience in pharmaceutical industry of different hierarchical designations like Executive, Manager, General Manager and Vice president. 72% of the organizations were having more than 1200 employees working for them; 55% of the organizations were having a turnover of more than INR 2000 crores (312 Mn USD).

7. HYPOTHESES TESTING, ANALYSIS AND RESULTS:

To address the stated research objectives, hypotheses were developed (Table 1) to study the following issues:

· Country of origin of manufacturers and GMP Practices

· Regional differences among Pharma manufacturers within India with respect to GMP Practices

· Size of organization (Annual turnover) and GMP Practices

· Size of organization (Employees) and GMP Practices

· GMP Practices and Type of products manufacturers (API, NSDP, SDP)

· Data Integrity practices across pharma manufacturers

· Quality Management practices across pharma manufacturers

· Laboratory control management practices across pharma manufacturers

· Manufacturing control practices across pharma manufacturers

· Over all Good Manufacturing Practices across pharma manufacturers

Respondents/organizations were divided in different groups for statistical analysis as mentioned below:

a. India v/s Abroad

b. Different Regions within India (West, North, South and Central India)

c. Different Groups of organizations based on their Annual turnover

d. Different Groups of organizations based on their Employee Strength

e. Organizations with different Product Types

f. Organizations who are issued warning letter / import alert v/s those who are not

8.1. ANOVA and t-test analysis:

One-way analysis of variance (ANOVA) and t-test were performed to test these hypotheses; Microsoft Excel was used for analysing the data.

Table 1: Hypotheses testing results

Null Hypothesis	Result
Ho1: There is no difference in the country of origin (India and Abroad) of the drug manufacturer as far as adhering to the GMP Practices are concerned	The t test returns the p value of 0.016 which signifies that there is a difference in GMP Management practices being followed in the pharmaceutical manufacturing plants located in India and abroad.
Ho2: There is no regional difference (within India) of the drug manufacturer as far as adhering to the GMP Practices are concerned	The analysis of variance (ANOVA) test returns the p value of 0.178 which signifies that there is no regional difference (within India) of the drug manufacturer as far as adhering to the GMP Practices are concerned
Ho3: Size of the organizations (based on annual turnover) does not differentiate a drug manufacturer as far as adhering to the GMP Practices are concerned	The analysis of variance (ANOVA) test returns the p value of 0.015 which signifies that (based on annual turnover) there is a difference among the drug manufacturers as far as adhering to the GMP Practices are concerned
Ho4: Size of the organizations (based on employee strengths) does not differentiate a drug manufacturer as far as adhering to the GMP Practices are concerned	The analysis of variance (ANOVA) test returns the p value of 0.0009 which signifies that Size of the organizations (based on employee strengths) there is a difference among the drug manufacturers as far as adhering to the GMP Practices are concerned
Ho5: There is no difference in the drug manufacturer based on Type of product category (API, Non sterile Drug Product and sterile drug product) as far as adhering to the GMP Practices are concerned	The analysis of variance (ANOVA) test returns the p value of 0.215 signifies that there is no difference in the drug manufacturer based on Type of product category (API, Non sterile Drug Product and sterile drug product) as far as adhering to the GMP Practices are concerned
Ho6: There is no difference in the Data integrity management practices across drug manufacturers based on whether WL/IA is issued or not.	The t-test returns the p value of 0.239 which signifies that there is no difference in the data integrity management practices across drug manufacturers based on whether WL/IA is issued or not
Ho7: There is no difference in the Quality management practices across drug manufacturers based on whether WL/IA is issued or not.	The t - test returns the p value of 0.313 which signifies that there is no difference in the Quality management practices across drug manufacturers based on whether WL/IA is issued or not
Ho8: There is no difference in the Laboratory control and management practices across drug manufacturers based on whether WL/IA is issued or not.	The t - test returns the p value of 0.207 which signifies that there is no difference in the Laboratory control and management practices across drug manufacturers based on whether WL/IA is issued or not
Ho9: There is no difference in the manufacturing control and management practices across drug manufacturers based on whether WL/IA is issued or not.	The t-test returns the p value of 0.258 which signifies that there is no difference in the manufacturing control and management practices across drug manufacturers based on whether WL/IA is issued or not
Ho10: There is no difference in the Good Manufacturing practices across drug manufacturers based on whether WL/IA is issued or not.	The t - test returns the p value of 0.182 which signifies that there is no difference in the Good Manufacturing practices across drug manufacturers based on whether WL/IA is issued or not.

Source: Authors, based on analysis of collected responses

Bartlett’s test for sphericity (x2 - 5615.688 df = 666) suggests that correlation matrix of the 64 items does not behave identically in the matrix i.e. few of the items are inter-correlated. % Variance and Cronbach’s Alpha α (found to be more than.6) of all the 8 factors for best practices in pharma industry is presented in table 2.

8. DISCUSSION AND CONCLUSION:

FDA warning letters are available on FDA website as electronic data and can be accessed by anyone. The investigators are very knowledgeable on US regulatory expectations for API, non-sterile drug product, and aseptic processing operations for sterile products. Expectations of the agency seem to be the same for both aseptic processes and non-sterile manufacturing, irrespective of the size of the manufacturing operation, location of manufacturing site (within or outside of the US). Our study revealed top 4 reasons for warning letters are Poor Quality system, Breach of Data Integrity, Poor Laboratory control and Poor production control. These four causes are responsible for 82% of the observations appearing in the warning letters.

It is recommended that other manufacturers involved in drug product and drug substance should regularly review these warning letters to learn to be proactive and implement the preventive actions to avoid the occurrence in their organizations. It is evident from the review of warning letters that pharmaceutical industry need to improve quality systems specifically investigation system, CAPA system, adherence to SOP compliance and sound stability program. There is a need of paradigm shift in institutionalizing a quality culture and transparency. Firms need to adopt stringent measures on laboratory control system specifically for computerised system to avoid any manipulation and breach of data integrity. Any observation about breach of data integrity will shake the confidence and trust of regulator. Any findings about data integrity breach would result into stoppage of the business for USA market. Quality, compliance and integrity are the pillars for any pharmaceutical organization to be successful.The study concluded that the following are the main reasons for the GMP non-compliances/warning letter observations issued to the pharmaceutical manufacturers:

· Poor quality system

· Breach of data integrity

· Poor laboratory controls

· Poor production controls

Statistical analysis of the responses received reveals that GMP practices are different in the pharma drug manufacturer located in India and abroad. Issuance of warning letters and import alerts have significant impact on continuity of the business, as there is a loss of trust among partners, regulators and customers. There is a loss of business opportunity and the manufacturer has to spend time and money to revive the quality system meeting Agency’s expectations.

GMP practices across all the regions in India are similar and does not have region specific issue which is evident that warning letters are issued by the agency to the Indian manufacturer is not region specific. Data reveals that GMP practices are different among the manufacturers having different size based on employees’ strength and based on annual turnover. It is also found that GMP practices are similar across all type of pharmaceutical manufactures like API, Non- sterile Drug Product and Sterile Drug Products. GMP practices and understanding of the respondents (employees) are similar whether import alert/warning letters are issued or not. Warning letter and Import alerts are issued based on isolated observation related to poor GMP practices. It is possible that Warning letter/Import alert is issued at one site while other sites are compliant and respondents are from compliant site. Factor analysis of the data revealed that there were eight factors influences the best practices in pharmaceutical industry. Researcher proposes the following GMP Compliant Pharma Best Practices Model (Figure 3) for pharmaceutical industries.

Procedure Control in Laboratory (Factor 1) is essential to ensure that data generated in the testing laboratory are original, accurate and reliable. Results published by the laboratory determine the release or reject of the samples. Control by Design and Automation (Factor 2) shall ensure that practices by right design and adequate controls are implemented for robust and consistent product quality of the pharmaceuticals products. Lucidity of Regulatory Requirements – I (Factor 3) and Lucidity of Regulatory Requirements – II (Factor 8) are the factors to ensure that correct regulatory requirements from the regulatory agency are obtained and shall be followed with accurate interpretation to avoid any questions during audits. Electronic Control of Data (Factor 4) is critical in view of multiple data integrity issues due to human intervention and data related to GMP would be captured electronically using software(s) with audit trails. This shall ensure the authenticity of the data, records and would meet ALCOA requirements of Data Integrity. Validity of Methods (Factor 5) factor drives that analytical methods used in testing of the samples in the laboratory are validated and the person performing the testing in the laboratory is qualified. This shall ensure that method used to generate results in the testing laboratory is suitable. Measurement Control – I (Factor 6) and Measurement Control – II (Factor 7) are the metrics revealing the health of various systems in the organization, which shall be measured periodically and shall be discussed during management review meetings. Proactive measures can be initiated in case of any significant drift in the metrics on various parameters.

9. LIMITATIONS AND FUTURE SCOPE:

The study includes the respondents from North America, Europe, Asia and South America continents. Future Study can be conducted involving the participants from countries of Africa, Australia continents. Study includes the review of warning letters from Jan 2014 to Dec 2016 of the pharmaceutical product manufacturers of Active Drug, Non-sterile Drug Product and Sterile Drug Product. Greater period could also be studied for the analysis, and medical device manufacturers can also be included in the future research. The findings have been generalised based on the limited data size of 317 respondents representing 76 companies, from across four continents, including five hierarchical designations of respondents mostly using snowball sampling techniques. Warning letter/Import alert was issued to the organization of the respondent was confirmed from the FDA website, however it is possible that same organization has multiple sites and the site where respondent is employed is not issued warning letter/import alert by the agency. The future study can also involve the interaction with regulators of different countries like USA, UK, Brazil, South Africa, Japan etc.

10. REFERENCES:

1. Jain Sanjay Kumar, and Jain Rajesh Kumar (2018), Review Of FDA Warning Letters To Pharmaceuticals: Cause And Effect Analysis. Research J. Pharm. and Tech. 11(7), 3219-3226

2. Jain Sanjay Kumar, and Jain Rajesh Kumar (2017), Evolution of GMP in pharmaceutical Industry. Research J. Pharm. and Tech. 10(2), 501-506

3. https://www.ibef.org/industry/pharmaceutical-india.aspx (Accessed on 26 Feb 2019)

4. Gough H.F., (1989),"Quality Assurance – Lessons to be Learned from the Pharmaceutical Industry", British Food Journal, 91(9), 10-12

5. Goodwin Paige S. and Jacobs Kevin T., (2013)," A Primer on the admissibility of FDA Warning Letters", Defense Counsel Journal, 36-45

6. Yu Lawrence X., and Woodcock Janet (2015), “FDA pharmaceutical quality oversight”, International Journal of Pharmaceutics, 491, 2-7

7. Ananth L, Gurbani N K., Kumar S, and Gujavarti B (2018), “A retrospective study of Warning Letters issued by US FDA over 2015-2017”, International Journal of Drug Regulatory Affairs; 2018; 6(2); 48-53

8. Khoja SS, Khoja S, Chauhan PH, and Khoja FS (2016) ; “A review on USFDA warning letter and violation observed in Pharmaceutical Industry”, Pharma Tutor; 4(12);33-36

9. Unger Barbara (2019), An Analysis Of FDA FY2018 Drug GMP Warning Letters, (https://www.pharmaceuticalonline.com/doc/an-analysis-of-fda-fy-drug-gmp-warning-letters-0003)

10. Patel DS (2012), FDA Warning Letter Analysis: A Tool for GMP Compliance. Int J Pharm Sci Res. 3(12); 4592-4603.

11. Hair, J.F. Jr., Anderson, R.E., Tatham, R. L. and Black W.C. (1998). Multivariate Data Analysis, New Jersy: Prentice-Hall.

Received on 26.02.2020 Modified on 21.03.2020

Research J. Pharm. and Tech. 2021; 14(2):1008-1016.

DOI: 10.5958/0974-360X.2021.00180.3

Factor	Factor Name	% variance	% Cumulative variance	Cronbach Alpha α
F1	Procedure Control in Laboratory	31.149	31.149	.879
F2	Control by Design and Automation	6.219	37.368	.797
F3	Lucidity of Regulatory Requirements – I	5.484	42.852	.751
F4	Electronic Control of Data	4.755	47.607	.849
F5	Validity of Methods	3.988	51.595	.824
F6	Measurement Control – I	3.505	55.100	.740
F7	Measurement Control – II	3.277	58.377	.787
F8	Lucidity of Regulatory Requirements – II	3.021	61.398	.755