Simultaneous Analytical Methods Development and Validation of for Cleaning Samples Analysis using Total Organic Carbon Analyzer (TOC)

 

Ashish Singh, Pushpendra Sharma

 

Abstract:

Pharmaceuticals produced in a multi-product manufacturing facility can be contaminated by potentially harmful and toxic substances. In such facilities, the equipment is commonly used for manufacturing several different products of varying potencies. Improper equipment cleaning procedures can lead to possible contamination of the products with different types of residues. Although it is theoretically possible to clean equipment to such an extent that it is free from residues of the previous product, this situation is neither practical nor a business-friendly option in today’s competitive environment. The time and cost involved in such cleaning would make it practically impossible to run an economically viable manufacturing unit. The study also included validation of manufacturing unit’s cleaning procedures to demonstrate that the procedures are capable of reducing active ingredient concentrations on equipment surface to levels below the calculated acceptance criteria.

 

 

 

INTRODUCTION:

Validation is not necessary to demonstrate that batch to batch carry-over is acceptable. It is adequate if verification is performed after manufacture of five batches, when thorough cleaning of equipment is done. If, however batch to batch change-over involves batches of lower strengths, impact of strength of the product should be considered. Validation is required when the next batch manufactured is of lower strength, to demonstrate that there is no carry-over of residue from higher to lower strength.

 

Carry-Over to Downstream Process

A batch can be contaminated with carry-over from an upstream process when two or more steps in a production process are performed in the same equipment. This scenario is illustrated in below in Figure 1.

 

 

Figure 1: Carry-over for Common Equipment

The situation described above usually does not have any adverse impact on the final formulation, unless the two processes are designed to be free from residues of either drug in each of the processes. An example of the above would be extended release formulations with components A and B formulated to release in vivo at different times.

 

Validation Requirement for Carry-Over to Downstream Process

Although the above scenario does not affect the patient safety of the formulation in terms of carry-over of residues from one process to the other, it would potentially compromise the bio-availability of formulation.

Validation is necessary in this case to demonstrate that residues from one process are not carried over to the next.

 

Carry-Over to Product during Product Change-Over

Contamination of next product, illustrated in Figure 1.2 below, can come from three sources:

•          Residues from the previous production process

•          Residues from the cleaning process, i.e., residues from the cleaning agent used

 

Figure 2: Carry-over for Product Change-over

 

The situation described above represents a greater risk to the patient as compared to contamination of the formulation during a campaign. There is also a risk of cross contamination of the product during product change-over. Thus, the above situation requires a much greater effort during documentation of the cleaning status of the equipment.

 

Aiming to address the needs of the pharmaceutical industry and current issues regarding cleaning validation and its application in formulation manufacturing and development laboratory, the topic “Implementation of Cleaning Validation Program in Formulation Manufacturing Plant” was selected.

 

This paper work examines the need for pharmaceutical cleaning validation, the various approaches and steps involved and other related considerations. Among the various strategies used for cleaning validation, the worst-case strategy was followed and implemented. The approach to cleaning validation is in compliance with various regulatory guidelines and industrial standards. Validation will demonstrate that the cleaning procedure is adequate and is consistently able to reduce product residues on equipment surfaces to levels that meet the pre-established criteria.

 

The objective was to implement a cleaning validation program in a multi-product pharmaceutical unit manufacturing oral solid dose formulations, providing documentary evidence that gives high degree of assurance, that the equipment cleaning procedures under consideration are capable of reducing product residues to previously determined acceptable levels. Cleaning validation will be carried out at multi-product manufacturing facility to ascertain compliance of the cleaning procedures.

 

MATERIALS AND METHODS:

The cleaning validation program must be initiated with a detailed project plan. This plan may also be termed as cleaning validation master plan. The master plan provides a summary of findings of the literature survey; an overview of the site/facility/area that is governed by the plan, description of the typical manufacturing processes that are to be performed in the manufacturing facility and the dosage forms that are produced, pre-validation considerations such as the development of equipment cleaning on basis of dose details of products manufactured, their batch sizes, physical characteristics of the active ingredient and also equipment design and the types of cleaning that are to be used (e.g., automated Clean-In-Place [CIP] or Clean-Out-of-Place [COP], semi-automated cleaning or manual cleaning). This is followed by finalization of cleaning procedures and levels of cleaning describing the requirements for the cleaning of individual equipment, calculation of worst-case MACO and identification of reference product for cleaning, validating the analytical methods for selected reference product.

 

After completion of above mentioned critical stages of the project plan, execution of the cleaning validation study is undertaken, followed by data analysis, reporting of results and finally conclude the study through summary and conclusions. In the industry, the cleaning validation plan is described in a protocol which must be formally approved by the production, analytical laboratory and quality assurance departments.

 

The key activities involved in executing plan of project are described in the form of a activity flow chart (Figure 2) below.

 

A specific method detects desired compounds in the presence of potential contaminants. Examples of specific methods commonly used are UV spectroscopy and HPLC.

 

High Performance Liquid Chromatography (HPLC) involves injection of the sample into a chromatographic column, separation of the target species from other components in the sample, and then measurement of that target species as it exits the column by ultraviolet (UV) spectroscopy, refractive index of photo-diode array (PDA) detectors.

 

The HPLC and UV methods for detecting residues are normally modified from the routine assay methods to permit detection at low levels. US FDA [4] expects the analytical methods used to be specific and sufficiently sensitive. It also expects that the user is able to demonstrate recovery of contaminants from equipment surfaces at reproducible levels. Generally, HPLC methods are more commonly used in the pharmaceutical industry.

 

RESULTS AND DISCUSSION:

Validation of Method for Selected Reference Products:

The analytical methods for estimation of selected reference products Gliclazide and Mesalamine by UV spectroscopy were validated for specificity, linearity, accuracy & precision and LOD/LOQ, at the acceptance level given in table below:

 

Table 1: Reference Product Acceptance Level

Reference Product for cleaning validation	Acceptance level (μg/ml)
Gliclazide Tablets MR	1 ppm
Mesalamine Granules	1 ppm

 

The Shared Equipment Matrix provides information regarding utilization of common equipment in the manufacture products on site. This information is used in the identification of reference product for any given equipment from the group of products manufactured using the equipment, as indicated in Table 4.2-4.17 below.

 

Table 2: Shared Equipment Matrix, Indicating Products Manufactured Using Common Equipment

S. No	Product	1	2	3	4
	Equipment	Anagrelide tablets	Paracetamol and Tramadol Tablets	Anagrelide Hydrochloride Capsules	Desloratadine tablets
1	Co-mill	ü	ü	û	ü
2	Vibro Sifter - 10'' GMP Model	ü	û	ü	ü
3	Capsule filling m/c.	û	û	ü	û
4	Extruder- Spheronizer	û	û	û	û
5	FBE 25	ü	ü	û	ü
6	RMG 100 L	ü	ü	û	ü
7	Blister Packing Machine	ü	ü	ü	ü
8	Multi mill	ü	ü	ü	ü
9	Cemach Compression machine	ü	ü	û	ü
10	Korsch Compression machine	ü	ü	û	ü
11	Conta Blender 300 L	û	ü	û	û
12	Vibro Sifter - 30'' GMP Model	û	ü	û	û
13	Stick Pack Machine	û	û	û	û
14	Conta Blender 100L	ü	û	ü	ü
15	Tablet Deduster	ü	ü	û	ü
16	Metal Detector	ü	ü	ü	ü

 

 

 

 

Continue Table 2

S. No	5	6	7	8	9
	Betahistine Dihydrochloride tablets	Loperamide and Simeticone Chewable tablets	Mesalazine Granules	Gliclazide MR tablets	Docusate sodium and Sorbitol enema
1	ü	ü	û	ü	û
2	ü	û	û	û	û
3	û	û	û	û	û
4	û	û	û	û	û
5	ü	ü	ü	ü	û
6	ü	ü	ü	ü	û
7	ü	ü	û	ü	û
8	ü	ü	û	ü	û
9	ü	ü	û	ü	û
10	ü	ü	û	ü	û
11	û	ü	ü	ü	û
12	û	ü	ü	ü	û
13	û	û	ü	û	ü
14	ü	û	û	û	û
15	ü	ü	û	ü	û
16	ü	ü	û	ü	û

 

Table 3: Equipment-Product Matrix for Comill (Worst Case)

Equipment	Product A	Product B	Lowest Dose (A)	Batch size (B) (nos)	Batch size (kg)	Max Daily dose
Co-Mill	Any product	Anagrelide tablets	0.5**	100000**	20	10
		Paracetamol/Tram	250/37.5	100000	60	4000/400
		Anagrelide capsules	0.5	100000	20	10
		Desloratadine tablets	5	100000	20	45
		Betahistine tablets	8	100000	36	48
		Loperamide-Simethicone chewable tablets	2/125	100000	100	8/1000
		Mesalamine granules	1000	81818	90	4000
		Gliclazide tablets	60	100000	64	120
		Docusate enema	120	36000	90	500
		Domperidone tablets	10	100000	40	80
		Tramadol HCl tablets	37.5	100000	60	400
		Eletriptan tablets	20	100000	20	80
		Acetylcysteine tablets	200	100000	80	4200
		Metformin granules	500	100000	60	2500
		Ibuprofen tablets	200	100000	90	2000
		Aspirin tablets	250	100000	90	4000
		Flecainide tablets	50	100000	32	400
	Any product processed on co-mill	Products not processed on co-mill	**Lowest dose	**Smallest batch

Continue Table 3

Max Daily dosage (D)	Equipment surface area	MACO factor	MACO mg/ml	MACO µg/ml	MACO for Detergent - mg (Rinse)	Extraction volume (rinse)	Detergent limit μg/ml (rinse)
4	11099	18	0.0016089	2	200	5L	28
16
20
9
6
5
8
2
4
8
8
4
21**
5
10
8
8
**Highest daily dosage

 

Table 4: Equipment-Product Matrix for Sifter 10” (Worst Case)

Equipment	Product A	Product B	Lowest Dose (A)	Batch size (B) (nos)	Batch size (kg)	Max Daily dose	Highest Daily dosage (D)
Sifter 10"	Any product	Anagrelide tablets	0.5**	100000**	20	10	4
		Paracetamol/Tram	250/37.5	100000	60	4000/400	16
		Anagrelide capsules	0.5	100000	20	10	20**
		Desloratadine tablets	5	100000	20	45	9
		Betahistine tablets	8	100000	36	48	6
		Loperamide-Simethicone chewable tablets	2/125	100000	100	8/1000	5
		Mesalamine granules	1000	81818	90	4000	8
		Gliclazide tablets	60	100000	64	120	2
		Docusate enema	120	36000	90	500	4
		Domperidone tablets	10	100000	40	80	8
		Tramadol HCl tablets	37.5	100000	60	400	8
		Eletriptan tablets	20	100000	20	80	4
		Acetylcysteine tablets	200	100000	80	4200	21
		Metformin granules	500	100000	60	2500	5
		Ibuprofen tablets	200	100000	90	2000	10
		Aspirin tablets	250	100000	90	4000	8
		Flecainide tablets	50	100000	32	400	8
	Any product processed on sifter	Products not processed on sifter	**Lowest dose	**Smallest batch			**Highest daily dosage

 

 

Continue Table 4

Equipment surface area	MACO factor	MACO mg/ml	MACO µg/ml	MACO for Detergent - mg (Rinse)	Extraction volume (rinse)	Detergent limit μg/ml (rinse)
2524	19	0.00742868	7	200	5L	28

 

 

Table 5: Equipment-Product Matrix for Capsule Filling Machine (Worst Case)

Equipment	Product A	Product B	Lowest Dose (A)	Batch size (B) (nos)	Batch size (kg)	Max Daily dose	Highest Daily dosage (D)
Capsule filling m/c	Any product	Anagrelide tablets	0.5	100000	20	10	4
		Paracetamol/Tram	250/37.5	100000	60	4000/400	16
		Anagrelide capsules	0.5**	100000	20	10	20**
		Desloratadine tablets	5	100000	20	45	9
		Betahistine tablets	8	100000	36	48	6
		Loperamide-Simethicone chewable tablets	2/125	100000	100	8/1000	5
		Mesalamine granules	1000	81818	90	4000	8
		Gliclazide tablets	60	100000	64	120	2
		Docusate enema	120	36000	90	500	4
		Domperidone tablets	10	100000	40	80	8
		Tramadol HCl tablets	37.5	100000	60	400	8
		Eletriptan tablets	20	100000	20	80	4
		Acetylcysteine tablets	200	100000	80	4200	21
		Metformin granules	500	100000	60	2500	5
		Ibuprofen tablets	200	100000	90	2000	10
		Aspirin tablets	250	100000	90	4000	8
		Flecainide tablets	50	100000	32	400	8
	Any product processed on cap filling mc	Products not processed on Capsule filling m/c	**Lowest dose	**Smallest batch			**Highest daily dosage

 

Continue Table 5

Equipment surface area	MACO factor	MACO mg/ml	MACO µg/ml	MACO for Detergent - mg (Rinse)	Extraction volume (rinse)	Detergent limit μg/ml (rinse)
8986	19	0.00208658	2	200	5L	28

 

CONCLUSION:

Analytical methods for validation of cleaning procedures for gliclazide and mesalamine were developed. The validation studies were carried out as per ICH Q2 guideline. Recovery studies were carried out by Swab sampling technique by spiking known concentration drugs on SS plates. Swab sampling: by this technique recovery of drug was found to be more than 80%. It is a direct method of sampling, compared to the indirect method of rinse sampling. The advantage is that, residues that are insoluble can be sampled by physical removal and equipment areas that are hard to clean can be evaluated. It is expected the swab will pick up all the residues on the surface which can then be assayed. The technique is dependent on individual training and skills. Sampling spiked surfaces with known amounts is often served as a training method. The disadvantages of swabbing methods are inability to access some areas and an assumption that surface is uniformly contaminated; invariably, contamination is not uniform and one must extrapolate sampled area to whole surface. Additionally, calculations also require that the swab location be carefully measured and recorded.

 

Based on the findings, it is concluded that the analytical method for validation of cleaning procedures for active ingredients, gliclazide and mesalamine, and the cleaning agent were successfully validated and may be used for execution of the cleaning validation study.

 

REFERENCES:

1.        PICs Document, PI006-3, Validation Master Plan, Installation and Operational Qualification, Non-Sterile Process Validation, Cleaning Validation, 25 September 2007. https://www.picsscheme.org.

2.        APIC Document, Guidance on Aspects of Cleaning Validation in Active Pharmaceutical Ingredient Plants, May 2014. http://apic.cefic.org/pub/apic_cleaning_validation_2014.pdf

2.S.W. Harder, "The Validation of Cleaning Procedures," Pharm. Technol. 8 (5), 29-34 (1984). www.pharmtech.com.

3.        FDA Guide To Inspections: Validation Of Cleaning Processes, 7/93, 25.11.2014

4.        Mendenhall, D., “Cleaning Validation,” Drug Development and Industrial Pharmacy, 15(13), pp. 2105-2114, 1989.

5.        United States v. Barr Laboratories, Inc., 812 F. Supp. 458 (D.N.J. 1993), U.S. District Court for the District of New Jersey - 812 F. Supp. 458 (D.N.J. 1993) March 30, 1993.

6.        https://law.justia.com/cases/federal/district-courts/FSupp/812/458/1762275/

7.        Health Canada Document, Cleaning Validation Guidelines (GUIDE-0028), 01.01.2008.

8.        Pei Yang, Kim Burson, Debra Feder, and Fraser Macdonald, “Method Development of Swab Sampling for Cleaning Validation of a Residual Active Pharmaceutical Ingredient”, Pharm. Tech. 84, 2005

9.        Sharnez, R., “Setting Rational MAC-Based Limits Part I - Reassessing the Carryover Criterion,” Journal of Validation Technology, Winter 2010, www.gxpandjvt.com.

10.      FDA Document, Guidance for Industry, Q7A Good Manufacturing Practice Guidance for Active Pharmaceutical Ingredients. https://www.fda.gov/ICECI/ComplianceManuals/CompliancePolicyGuidanceManual/ucm200364.htm

11.      PDA Technical Report No. 29, "Points to Consider for Cleaning Validation," PDA J. Pharm. Sci. Technol. 52(6) sup. (1998).

12.      D. Rohsner and W. Serve, "The Composition of Cleaning Agents for the Pharmaceutical Industry," Pharm. Eng. 15(2), 20-29 (1995).

13.      Petropoulos G., Pandazaras C., Davim J. (2010) Surface Texture Characterization and Evaluation Related to Machining. In: Davim J. (eds) Surface Integrity in Machining. Springer, London.

14.      Destin A. LeBlanc, “Systems-Based Inspections for Cleaning Validation”, FDA DG 230, July 17, 2013, Rockville, MD.

15.      WHO Document, “Good manufacturing practices and inspection” in Quality assurance of Pharmaceuticals, Volume 2, 2nd updated edition.

16.      PICs Document, “Validation Master Plan Installation and Operational Qualification, Non-sterile Process Validation, Cleaning Validation”, Sep 25, 2007. www.picscheme.org/.

17.      Food and Drug Administration (FDA) Guidance Document, “ANDAs - Impurities in Drug Products”, Nov 2010.

 

 

 

Received on 08.10.2019       Modified on 25.10.2019 Accepted on 05.11.2019      ©A&V Publications All right reserved Research J. Science and Tech. 2019; 11(4):268-274. DOI: 10.5958/2349-2988.2019.00038.X