# Presentation: 939474

## FDA Regulation of Drug Quality:  New Challenges

**Janet Woodcock, M.D.**
**Director, Center for Drug Evaluation and     Research, Food and Drug Administration****	**
**April 9, 2002**

## Regulation of Drug Quality: Current Status

**Pharmaceutical industry manufacturing sector highly regulated**
**FDA review and approval of process, documentation, and facility required prior to approval**
**Many process changes require FDA review and approval prior to institution**
**Ongoing manufacturing subject to FDA inspection and GMP standards conformance**

## Current Status of System for Ensuring Drug Quality

**US Drug products are of high quality, BUT**
**Increasing trend toward manufacturing-related problems**
**Recalls**
**Disruption of manufacturing operations**
**Loss of availability of essential drugs**
**Negative impact on new drug approvals**

## Current Status System for Ensuring Drug Quality, cont	

**US drug products are of high quality, BUT**
**Low manufacturing process efficiency--cost implications**
**Innovation, modernization and adoption of new technologies slowed**
**	****	****Introduction of new technologies in facilities not ****	****	****for US market**

## Current Status System for Ensuring Drug Quality, cont	

**US Drug Products are of high quality, BUT**
**High burden on FDA resources**
**About 4,000 manufacturing supplements submitted yearly**
**FDA inspectors unable to meet statutory biennial GMP inspection requirement**
**Lower scrutiny of non-domestic industry**
**Expensive & time-consuming litigation & legal actions**
**	****	**

## Regulation of Drug Quality:  Analysis of Industry Factors

**Reluctance to innovate/invest in manufacturing sector--poor stepchild compared to R&D?**
**Emphasis on getting product out discourages early work on process and changes after marketing**
**Possible role of regulatory oversight--unintended consequences**

## Regulation of Drug Quality:  Analysis of Regulatory Role

**Thirty years ago--FDA’s emphasis was on institution of basic procedures and recordkeeping--evolved to cGMP**
**Currently:  FDA attempting to drive innovation and investment in manufacturing sector via compliance/enforcement actions**** **

## Regulation of Drug Quality:  Opportunity

**Empirical methods are probably approaching their theoretical maximum effectiveness**
**New scientific understanding & new technologies can provide science-based approaches**
**Plan:  Use PAT as model**

## 11/2000 Science Board Presentation on PAT

**Presented inefficiencies & problems in current manufacturing processes**
**Presented examples of current industrial use of PAT (“Don’t tell”)**
**Potential benefits of adoption of PAT**

## Challenges for FDA

**How to encourage innovation while ensuring high quality**
**Successful adoption of new technologies will IMPROVE overall quality**
**How to successfully shift from empirical to science based standards for manufacturing process quality**

## Major Barrier to Adoption:

**Industry Concern About Regulatory Implications of Results **
**Closer  scrutiny will reveal variations in existing products missed by sampling**
**Delay in approval of new product**

## Example:  Content Uniformity

**Quantity of active ingredient in a tablet/stated quantity-expressed as a percent**
**USP has a standard algorithm**
**Analysis:****	****Stella Machado, Ph.D. **
**	****	****	****	****Meiyu Shen, Ph.D.**
**	****	****	****	****Charles Anello, Sc.D.**
**                   **

## USP testing procedure

**No**

**Accept**

**Yes**

-  **1 of 10 ********(85%,115%)**
**All 10 ******** (75%, 125%)**

**Yes**

**Reject**

**No**

**Step 3, additional 20 tablets**

**At most 1 of 30 ********(85%,115%)**
**All 30 ******** (75%, 125%)**
**RSD ******** 7.8%**

**Yes**

**Reject**

**Accept**

**All 10 ********(85%, 115%)**
**RSD ********  6%**

**No**

**USP testing procedure**

## Content Distribution for typical batch for USP testing

- Normal distribution: mean=100, sigma (standard deviation)=6

## EXAMPLE

**Assuming normal distribution, with mean 100% and sigma = 6%,**
**Probability (batch passes USP) = 0.957**
**Means about 4% of batches fail although they are no different than the passing batches**

## Consequences of 100% testing

**Use PAT to measure content uniformity of every tablet**
**Assume batch of 1x10****6**** tablets**
**Assume mean - 100% and sigma - 6%**
**Will find 30 tablets outside (75, 125)**
**Will find 12,419 tablets outside (85, 115)**

## LINKAGE BETWEEN 100% TESTING RESULT AND USP TEST

**Example:** Batch size = 1,000,000
**Number of****	****	****Probability Range of passing**
**tablets, out****	****	****USP test* with 30 tablets**
**of range {75,125}**
- 	  2000			0.39 – 0.45
- 	  1000			0.54 – 0.57
- 	  500			0.66 – 0.69
- 	  100			0.83 – 0.90
- 	  50				0.88 – 0.94
- 	  30				0.91 – 0.96
- 	* corresponding to a range of (mean,sigma) pairs that give desired N, for means between 95% and 105%.

##  Numbers of tablets found outside  range 75-125% among a batch of 1,000,000 tablets for different means, sigma’s

- 			_*Mean*_*	*
_*Sigma*__*	*__95%__	__	__100%__	__105%_
- 6%		430		30		430
- 7%		2150		360		2150
- 7.8%	5232		1350		5232

## 			Mean			

- 85-115% among a batch of 1,000,000 tablets for different means, sigma’s

- 			_*Mean*_*	*
_*Sigma*__*	*__95%__	__	__100%__	__105%_
- 6%		48219      12419      48219
- 7%		78701      32124      78701
- 7.8%	105084     54470    105084

## What about Normality Assumption?

**Likely incorrect for some processes**

## An Example:  Content Uniformity Test

**Increasing test frequency may identify problems in currently “validated” process**** Sample Analysis **
**(Thief)**
**%RSD = <1 PASS**

**USP Content Uniformity**
**Stage 1: PASS **

**An Example:  Content Uniformity Test**

**PQRI Proposed **
**Stratified Sampling**

## PHARMACEUTICAL MANUFACTURING CASE STUDY:

**Approved Product on The Market Today**
**Product Provides Excellent Benefit to Patient**
**Commercial Lots Meet All Final Product Specs**
**In-Process Testing During Validation Showed Content Uniformity To Be Within Range (95-105%) **
**The Company Would Like to Now Use PAT to Enhance Process Understanding & Efficiency..**

_**BACKGROUND**_

## In-Process Content Uniformity 

- In-Process Content Uniformity
***(During The Course Of A Batch)***

**% Of Batch **

- Lot 1

- Lot

- 2

**0**

** **

**20**

** **

**40**

** **

**60**

** **

**80**

** **

**100**

** **

**74**

** **

**84**

** **

**94**

** **

**104**

** **

**114**

** **

**Content**
**Uniformity**
**[Assay]**
**(%)**

**Early Results from Additional Uniformity Testing **
**In Developmental Mode**

**105%**

**95%**

## PHARMACEUTICAL MANUFACTURING CASE STUDY: CONTEXT

**      ****FORMULN**

**FILL**

**PACK**

** ****ACTIVE**

**      ****FORMULN**

**FILL**

**PACK**

** ****ACTIVE**

**      ****FORMULN**

**FILL**

**PACK**

_**RESEARCH**_

_**DEVELOPMENT**_

_**MANUFACTURING**_

**TIME**

**SPACE**

***All Release Product******Is Within Final Product Testing Specification******(i.e. Product is Safe & Effective)***

***Additional Content Uniformity Testing ***
***In Development Mode ***
***Revealed Some Potential ***
***Non-Random Patterns***

**PHARMACEUTICAL MANUFACTURING ****CASE STUDY**: CONTEXT

***How Do We Plan For***
***What This Pharmaceutical Company***
***Might See When They Attempt To***
***Use PAT At Commercial Scale?***

## PHARMACEUTICAL MANUFACTURING CASE STUDY:

**Pharmaceutical Company Wants to Do the Right Thing**
**Wants To Better Understand Its Process & Enhance Efficiency**
***BUT,**** ***Are They Ready To Put PAT On The Actual Commercial Line for This Product? **
***BUT,**** ***What If They See the Same (or Different) Kind of Content Uniformity Pattern on Commercial Batches That They Just Saw In Developmental Mode?**

_**CONCERNS**_

## PHARMACEUTICAL MANUFACTURING CASE STUDY:

**The**** ****Increased Ability to Measure**** ****Brings With It** **An Increased Responsibility To Understand/Explain**
**What Happens In The*** ***Interim Period**** ****When The Companies Can**** ****Measure More**** ****But Are Still Working On Being Able to**** ****Explain More****?**
**How Can The FDA Work With The Pharmaceutical Companies To Help Address This Concern?**
**Can The Pharmaceutical Industry Be Reassured In Some**** ****Way During This**** ****Interim Period****?**

_**GETTING TO **__**“**__***WIN-WIN”***__*** ***_

**Application of PAT may reveal facts about currently acceptable products that could jeopardize the cGMP compliance status of the firm.**

**PAT is likely to improve our understanding of current processes - identifying “critical” process variables that should be controlled and highlighting variability that was less visible with sampling techniques.**
**Need to develop risk based approach for addressing this new information without penalizing firms**

**Need to provide a “safe harbor” during R&D related to PAT application on existing lines**
**Scientific (statistical) approach to control tests needed****	**

## Summary

**Application of new technologies to pharmaceutical manufacturing can improve quality and increase efficiency**
**There are major (perceived) regulatory barriers to this happening**
**We seek Board input on our approach**
**Dr. Hussain:  Accomplishments and next steps**