Continuous Flow MfgContinuous Flow MfgSkip-Lot SamplingSkip-Lot Sampling

Domenick AmatoDomenick Amato

Frank GomezFrank Gomez

Lynn TorbeckLynn Torbeck

21 CFR 210.321 CFR 210.3

210.3(20) “Acceptance Criteria 210.3(20) “Acceptance Criteria means the product specifications and means the product specifications and acceptance/rejection criteria, such as acceptance/rejection criteria, such as acceptable quality level and acceptable quality level and unacceptable quality level with an unacceptable quality level with an associated sampling plan …”associated sampling plan …”

210.3(21) Representative samples210.3(21) Representative samples

21 CFR 211.8421 CFR 211.84

Requirements:Requirements:1.1. Representative samplesRepresentative samples

2.2. Number of containers to sampleNumber of containers to sample

3.3. Amount of material to be takenAmount of material to be taken

4.4. Variability – Process averageVariability – Process average

5.5. Confidence levelsConfidence levels

6.6. Past quality historyPast quality history

Continuous Flow MfgContinuous Flow Mfg

How to define a continuous How to define a continuous process? Types of processes?process? Types of processes?

How to define a “lot” or “batch” in How to define a “lot” or “batch” in a continuous flow process?a continuous flow process?

Assumption of homogeneity of Assumption of homogeneity of product?product?

Assumptions about defects?Assumptions about defects?

Types of Sampling PlansTypes of Sampling Plans

Variables Plans:Variables Plans:• ANSI/ASQ Z1.9ANSI/ASQ Z1.9

Attribute PlansAttribute Plans• ANSI/ASQ Z1.4ANSI/ASQ Z1.4• ISO 2859ISO 2859

Sampling Plans DefinedSampling Plans Defined

Population of units, lots or batchesPopulation of units, lots or batches AQL: Acceptable Quality LimitAQL: Acceptable Quality Limit LQ: Unacceptable Quality LimitLQ: Unacceptable Quality Limit Sample sizeSample size Accept numberAccept number Reject numberReject number

Risk ManagementRisk Management

““Producer’s Risk” The probability Producer’s Risk” The probability that a good lot is rejected by the that a good lot is rejected by the customer. (Type I error or alpha)customer. (Type I error or alpha)

““Consumer’s Risk” The probability Consumer’s Risk” The probability that a bad lot is accepted by the that a bad lot is accepted by the customer. (Type II error or beta)customer. (Type II error or beta)

Levels not fixed but common Levels not fixed but common values are 5% and 10%.values are 5% and 10%.

Assumptions for SamplingAssumptions for Sampling

Representative samplesRepresentative samples• Beginning, middle and endBeginning, middle and end• Top, middle and bottomTop, middle and bottom• Every 30 minutes or 100 unitsEvery 30 minutes or 100 units• Random Sampling – (difficult)Random Sampling – (difficult)

Defects must be randomly Defects must be randomly distributed !distributed !

Sample inspection is 100%Sample inspection is 100%

Reduced TestingReduced Testing

1.1. Smaller sample size. Using Smaller sample size. Using General Inspection Level I in General Inspection Level I in place of Level II or III in Z1.4.place of Level II or III in Z1.4.

2.2. Not inspecting all characteristics Not inspecting all characteristics on the CoA or listed in the USP.on the CoA or listed in the USP.

3.3. Can use reduced testing in Z1.4.Can use reduced testing in Z1.4.

4.4. Use the switching rules in Z1.4.Use the switching rules in Z1.4.

Skip-Lot SamplingSkip-Lot Sampling

Not all lots are tested.Not all lots are tested. Only a fraction of lots are Only a fraction of lots are

inspected.inspected. Goal is to save money or time and Goal is to save money or time and

still achieve quality products.still achieve quality products.

Types of Skip-Lot SamplingTypes of Skip-Lot Sampling

1.1. Test every “nTest every “nthth” lot, not random.” lot, not random.2.2. Test “i” lots, if all pass go to a Test “i” lots, if all pass go to a

fraction, “f”, of future lots. Select fraction, “f”, of future lots. Select i and f in advance. Lots selected i and f in advance. Lots selected at random. at random.

3.3. ASQ S1ASQ S1, i and f are determined , i and f are determined from the data collected. Lots are from the data collected. Lots are selected at random using dice.selected at random using dice.

Assumptions for Skip-LotAssumptions for Skip-Lot

Supplier and customer agree on a Supplier and customer agree on a plan. Good communications.plan. Good communications.

Faith and trust in an honest Faith and trust in an honest supplier. Good relations.supplier. Good relations.

Proven history of quality with a Proven history of quality with a stable and continuous process.stable and continuous process.

Clear criteria for action plan.Clear criteria for action plan.

Discussion TopicsDiscussion Topics

Compendial requirementsCompendial requirements Regulatory expectationsRegulatory expectations Current state, pro/con/concernsCurrent state, pro/con/concerns Desired state for excipientsDesired state for excipients Fraud, counterfeiting, adulterationFraud, counterfeiting, adulteration Processes “Out of control.”Processes “Out of control.” Changes without notificationChanges without notification

ReferencesReferences

NISTNIST http://www.itl.nist.gov/div898/handbook/pmc/section2/pmc22.htmhttp://www.itl.nist.gov/div898/handbook/pmc/section2/pmc22.htm    http://www.itl.nist.gov/div898/handbook/pmc/section2/pmc27.htmhttp://www.itl.nist.gov/div898/handbook/pmc/section2/pmc27.htm    http://www.itl.nist.gov/div898/handbook/pmc/section2/pmc23.htmhttp://www.itl.nist.gov/div898/handbook/pmc/section2/pmc23.htm    ASQ (1996). ANSI/ASQ S1, “Attribute Skip-Lot Sampling Program.”ASQ (1996). ANSI/ASQ S1, “Attribute Skip-Lot Sampling Program.”    Schilling, E. (1982). Schilling, E. (1982). Acceptance Sampling in Quality ControlAcceptance Sampling in Quality Control, New York, NY: , New York, NY:

Marcel Dekker, pp 443-451Marcel Dekker, pp 443-451    Juran, J. and Godfrey, A. (1999). Juran, J. and Godfrey, A. (1999). Juran’s Quality Handbook, Fifth Edition,Juran’s Quality Handbook, Fifth Edition, pp 46- pp 46-

31, 46-32, New York: McGraw Hill.31, 46-32, New York: McGraw Hill.