Process Drift: When Do We Detect

it?

Richard L. Friedman

Director, DMPQ

CDER/Office of Compliance

PQRI Process Drift Workshop

December 1, 2010

Overview

• Goal of Manufacturing

• Central Question: Why is process output not always predictable?

• Problem detection on stability program...Too late!

• Examples: Why did the failures occur?

– Poorly understood processes = uncontrolled variability

• Testing Reliability

• Recommendations

Goal of a Manufacturing Organization…

• Provide a consistent, defect-free product to the

marketplace via consistent manufacturing operations

• For a Drug Manufacturer, this means…

Assure safety & efficacy every day, every dose.

But not every company has established adequate quality

practices, or achieved this predictable output. Some

companies, products, or processes make more mistakes

and defective units than others. Why?

More questions

• Why due routine stability studies find defects and result in recalls?

• This includes:

– Potency

– Content Uniformity

– Dissolution

– Impurities

– Physical characteristics (e.g., viscosity of ointment)

Impact

• What is the risk to the patient if a lot must be

recalled?

– Incorrect dose, poorly dissolved product, high

impurity ineffective or unsafe

– Shortage product not available

• What are the possible root causes?

– What is the conventional wisdom?

• Degradation!

– What are other possible reasons?

Two Overall Root Causes

1. The classical stability issue is chemical and

physical degradation during storage. • Some products are by nature unstable and have a shorter

shelf life, but are expected to be able to meet their labeled

expiration dating as supported by previous

estimates/predictions.

2. The second issue to be considered is the

inherent manufacturing/process variability• due to inadequate process design and manufacturing.

Examples

8

Importance of Excipients:

Some Examples of Recalls Involving Excipients (2002-2008)

Excipient Product Reason Root Cause

Malt Syrup

Oral Powder

Product

(Granules) Mold

Long excipient storage

period

Sorbitol Syrup OOS Stability Different excipient supplier

Magnesium

Stearate

5, 10, 15, and 30

mg Tablet Product Dissolution Failures

Rendered drug

hydrophobic due to non-

uniform mix issues

(excipient itself was not

defective).

HPMC

Extended

Release Tablet

Dissolution Failure

(Drug release rate

too rapid)

Excipient functionality led

to this Recall

9

Case Study #1

Dissolution Failure (multivariate cause?)

• It was concluded that the cause of the dissolution failure

was a combination of factors, e.g.,

– a formulation change, specifically a 1% increase in lubricant

– a subtle change in the effective density of the tablets which was

apparently affected by the bulk density of microcrystalline

cellulose (another ingredient variable)

– mixer change (different mixing principle)

• Dissolution testing on stability ultimately detected the

problem.

• only 1 batch/year placed on stability, but extra testing

done after the failure

• 3 batches failed

10

Case Study #2

Subpotency (multivariate cause?)

• Tablet product

• Assay failure on Stability (9 months)

• Firm’s investigation concludes that product

stability needs to be improved by:

1.changing to a different API source

2.modification of formula

3.improved container/closure system

Case study #3Assay, Appearance

• Ointment drug product

• NDA sold, and product now being made by contract manufacturer

• Firm receives numerous complaints of product being

“thinner consistency,” “watery,” or “liquidy.”

• Intermittent failures to meet specification for assay,

appearance and/or propylparaben content

• Process involves complex set of process steps:

– melting and mixing, dispersion, dissolving, heating, cooling for

specified times/temps. Transfer of materials to and from 5 different

vessels.

– Product and Process Design flaws. Firm issued WL.

Variability

Variability?

• Have sources of variability been identified

and minimized?

– API, Excipients

– Formulation

– Process

– Container-Closure System

– Sampling and Measurement methods

Development

• Do companies collect enough data, within and between batches, to really understand the stability profile, and transition to typical one lot/year?

• Do companies truly understand first principles–the physicochemical reasons that contribute to stability failure?

• If so, why are batches vulnerable to stability failure during shelflife not routinely identified (prediction capability) prior to distribution?

Formulation Development

• Do companies routinely do sufficient preformulation studies of excipients and API’s to understand their behavior?

• 1975 journal article used DOE for preformulation excipient compatibility.

– Studied 5 factors and 10 two-factor interactions to get the best combination.

• Do companies follow the QbD concepts in ICH Q8 for formulation design?

– Is DOE used routinely?

Raw Material Variability

• Have firms routinely identify all of the raw

material attributes that are important?

• How has the variability been identified,

measured and minimized?

– Many excipients (e.g., cellulose-based) are natural

materials, with unmeasured variability...

• Are incoming ingredient batches sufficiently

analyzed using adequate tests?

– e.g., HPMC

Raw Material Variability

• “Changes in particle size of some excipients, for example, may affect content uniformity. In other cases, a change in the supplier of an excipient or lubricant may affect dissolution or bioavailability.”

• “The failure to specify the amount of granulating solution, resulting in over wetting and dissolution failures of aged batches.”

FDA Guide to Pre/Post-Approval Inspections of Solid Oral Dosage Forms (1994)

Excess Manufacturing Variability?

• The root cause of root causes is often the failure of management to focus on minimizingunwanted variability, differences, and discrepancies throughout the product life cycle.

• There is a need to fully implement 211.110(a). “… to validate the performance of those manufacturing processes that may be responsible for causing variability …”

Management’s Role

• “It is good management to continually

reduce the variation of any quality

characteristic” - Deming

• This builds robustness and ruggedness

into the process and product, increases

product quality, and can reduce costs.

Representative Samples

• The sample must represent the batch

physically. For example, beginning,

middle, end of the batch, and...

• The sample must represent the variability

in the batch

– This applies to all samples, whether raw

material, in-process, QC, or stability...

Representative Samples

• This is a key concept and assumption in

the CGMP’s.

• 210.3(b)(21) Definitions

• 211.84(b) Testing

• 211.122(a) Materials

• 211.134(b) Inspection

• 211.180(e)(1) Review

Testing Programs

QC Release:

Quality System Detection of Variation & Defects

before Distribution

• Test of a firm’s Quality System is if it will promptly catch a problem in a batch vs. discovering only after it is marketed.

1. Mistakes are, in many cases, not caught by the individual making the error, but instead through final inspection or QC test!!

2. QC testing is of limited sample size intended to assess a chemical, microbiological, or physical attribute.

3. To avoid detecting mistakes or defects only after a drug product has been distributed:

• Use Redundancy of Controls or PAT

Testing After Distribution:

How Much is Enough?

• Normally, 3,6,9,12,18,24...

• But based on experiences with some products,

some firms have had to test more often than the

usual intervals.

– Major Migraine drug: was tested every month.

– Female Hormone Product: put every fifth lot on

stability due major dissolution problems, then

ultimately every lot pending reformulation. (Not

the only such example)

Stability Studies and Variability

• As number of tested samples increases...

– More tests lead to higher probability of failure

for unstable processes or products.

– Excessive variability in batches results in

higher probability of failure.

E11 2709

• One statistical approach for developing in-house specifications for USP Standards now gaining attention and acceptance is ASTM E11 E2709 adopted in 2009

• It is a statistical procedure that evaluates the variability in the data and calculates probability of passing the specification (assay, content uniformity, dissolution) with a specified confidence.

E11 2709: Probability of Passing

• So instead of a pass/fail response from using the USP

Standard as a specification, this statistical method gives

a probability.

• For example, we would be able to say:

– “we are 99% confident that the probability of the batch passing

the USP Standard in the future is 99% or better.”

• If a batch just barely passes the dissolution or content

uniformity criteria once (e.g., the USP Standard), what is

the probability of passing 1 to 9 more times?

– Depending on the overall inherent batch variability, it can range

from circa 1% to 100%!

For Example

(E2709 Analysis)

• A batch with a 90% probability of passing

(i.e. 10% fail) the test the first time, has

almost a 60% chance of failure if tested

eight times on a stability program.

• A batch with a 99% probability of passing

the test the first time, still has almost a 9%

chance of failure if tested nine times.

Summary / Recommendations

• Unwanted variability is the root cause!

– raw materials, product stability, and process

stability

• Passing the specifications once often

gives little assurance that it will pass again

– The batch has to be robust to be assured of

passing repeatedly on a stability program

Summary/Recommendations

1. Preformulation DOE and history• Learn and routinely use DOE in formulation

2. Process/product control • Learn and adjust under Quality System

3. Raw material change control

4. Follow GMPs to assure representative sampling

5. Minimize variability

6. Batch history

7. Process capability

Building Knowledge

Process Validation Lifecycle

Monitor

Confirm

Assess

Design

• Replication at full scale provides initial assurance of commercial process reliability.

• Validation includes lifecycle monitoring. Post-market information gathering, promotes maintenance of a stable process and identifies areas for continual improvement and adaptation.

• Our Compliance Policy Guide on Process Validation, and the draft Process Validation Guidance, recognize the value of advanced engineering principles and control technologies.

CGMP:

Every batch, Every day…

“We rely upon the manufacturing controls and standards to ensure that time and time again, lot after lot, year after year the same clinical profile will be delivered because the product will be the same in its quality… We have to think of the primary customers as people consuming that medicine and we have to think of the statute and what we are guaranteeing in there, that the drug will continue to be safe and effective and

perform as described in the label.”

- Janet Woodcock, M.D.

Reference

• “Six Sigma in the Pharmaceutical Industry:

Understanding, Reducing, and Controlling

Variation in Pharmaceuticals and

Biologics”

• By Brian Nunnally and John McConnell

• CRC Press, 2007

Acknowledgments:

Lynn Torbeck

For More Information:

www.fda.gov/aboutfda/centersoffices/cder/ucm096102.ht