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1 Pharmaceutical Technology and Education Areas: Industrialization Pharmaceutical Technology Manufacturing Science Pharmaceutical Engineering
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1

Overview of Pharmaceutical Technology and Education

Areas:Industrialization

Pharmaceutical TechnologyManufacturing Science

Pharmaceutical EngineeringEducation

2

The Pipeline Problem

Despite the most sophisticated drug discovery methods and the largest expenditures ever, fewer new drugs are reaching the market

Last year only 20 (not 50) New Molecular Entities reached the market

This is termed “the pipeline problem”

New technologies for bringing Molecules to Market are needed

Pharmaceutical Technology will achieve this goal

3

The Pipeline Problem

4

Critical Path Concepts

5

Critical Path Initiative

Tools for increasing the number of drugs reaching the market

Tools for speeding drugs to market Modernize tools for product development Create new tools

6

Critical Path

Critical Path Research and Translational Research are related

7

Three Areas on the Critical Path (FDA)

Scenario 1: The Pharma Industry will Fragment into these three areas and Discovery

8

Critical Path

D ru gS u b s ta n c e

(A P I)s y n th e s is

P r o c es s D ev elo p m en tM an u f ac tu r e

lau n c hs u p p lies

P r o c es s

T r an s f er

E a r ly so lidst a t e c h e m ist r y

a n dp r e f o r m ula t io n

P r o c es s D es ig n , P r o c es sD ev elo p m en t

M an u f ac tu r eP h as e 3S u p p lies

M an u f ac tu r elau n c h

s u p p lies

I n it ia lT o x ic o lo g ic a l

S tu d ies

P r o c es s

T r an s f er

C o m p le teT o x ic o lo g ic a l S tu d ies

P h as e 1( F I M )

P h as e 2 P h as e 3

I N D U S T R I A L I Z A T I O N

S A F E T Y

M E D I C A L U T I L I T Y

T I M E (Y E A R S )

0 1 2 3 4 5 6 +

9

The Amlodipine Story

HN

OCH3

O

H3CO

ONO2

H3C CH3 HN

ClOO

O CH3

ONH2H3C

H3CO

Nifedipine Amlodipine

10

Amlodipine Industrialization

Initially the maleate salt was made Maleate salt had a biologically active degradation

product Switched to besylate salt late in development Amlodipine besylate (Norvasc is the most

successful heart drug ever developed)

11

Status of Pharmaceutical Technology

HISTORICAL DATA DERIVED FROMTRIAL-N-ERROR EXPERIMENTATION

HEURISTIC RULES“Rules of Thumb”

EMPIRICAL MODELS

MECHANISTICMODELS

Rules

Current Level of Knowledge

Desired Level of Knowledge

12

Tools and Strategies

Approaches to dealing with problem compounds Product design concept and quality by design Predictive capabilities

• Solubility• Bioavailability• Stability

FDA – predictive capabilities could save $100 million per drug

13

Critical Path Dimensions

Physical design

• Screening and Simplified Formulations► Toxicology► Clinical trials► Example – salt, disintegrant, lubricant

Characterization

• XRPD Specifications

• GMP Analytical methods

14

Critical Path Dimensions

Lack of trained personnel Few educational programs Very little fundamental research on

pharmaceutical materials

15

Key Concepts

• Improve quality

1. Know what you have

2. Make the same thing every time (within the design space)

• Reduce costs• Cost of goods sold is up to $80 billion dollars• A 20% reduction leaves $16 billion to discover

new drugs or reduce costs

16

Educational Strategies

Pharmaceutical Engineering Molecules to Market educational strategy Allen Chao GMP Center Regulatory Programs

• National GMP Curriculum

17

Outcomes

More drugs on market Reduced time to market Improved quality Reduced costs of drugs

18

Extras

19

Dimensions of the Pipeline Problem

Patient deaths and unfavorable outcomes because of delays in marketing new drugs

At least $100,000,000 per drug under development ($2-4 billion per year)

20

Pipeline Problem - Related Issues

Higher risk manufacturing processes (variability is two sigma not six sigma)

Reduced flexibility in manufacturing Major manufacturing problems and

issues

• Disastrous CMC inspections by the FDA

21

Pipeline Problem - Related Issues

Significance /Insignificance of Validation

• Is validation just a well rehearsed demonstration lacking any significant value?

Difficulty in scaling up

• Numerous bridging bioequivalence studies

Insufficient size and personnel in existing centers and programs to address these issues

22

Status of Pharmaceutical Technology

HISTORICAL DATA DERIVED FROMTRIAL-N-ERROR EXPERIMENTATION

HEURISTIC RULES“Rules of Thumb”

EMPIRICAL MODELS

MECHANISTICMODELS

Rules

Current Level of Knowledge

Desired Level of Knowledge

23

Detector

Filter Whee

l

Optical filters

Sensors for Process Understanding and Control: Fixed-Wavelength (Filter) NIR Gauge

MM55

Beamspotsize

NDC-Infrared EngineeringIrwindale, CA

24

Heat and Mass Transfer Modeling of Drying: Two-Stage Drying In a UniGlatt

APAP Granulation at 60 °C

0 10 20 30Time (min)

25

50

75

100

125

150

175

NIR

KtoQQ

Linear Region (Evaporative Cooling)

)'exp('0 tkkQQQ

Exponential Region (Diffusion Limited)

P.L.D. Wildfong, A.-S. Samy, J. Corfa, G.E.Peck, and K.R. Morris J Pharm Sci 91 3 631–639 (2002).

25

Temperature vs Time for APAP Granulation: The Opportunity for Innovation

Critical moisture

Te

mp

era

ture

Mo

istu

re C

on

ten

t

40

60

80

100

120

140

160

180

Drying Time (min)

MM

55

Re

ad

ing

45

47

49

51

53

55

57

59

61

63

65

Te

mp

era

ture

(°C

)

T

MM55

0 30252015105

K.R. Morris, S.L. Nail, G.E. Peck, S.R. Byrn, U.J. Griesser, J.G. Stowell, S.-J. Hwang, K. Park Pharm Sci Tech Today 1 6 235–245 (1998).

26

Fast-Drying Trials of an Ibuprofen GranulationComparison of Average MM55 Values

Between Fast Drying and Traditional Drying

75

95

115

135

155

175

195

215

235

0 5 10 15 20 25

Time (min)

MM

55

Fast-DryingAverage MM55

Traditional-DryingAverage MM55

P.L.D. Wildfong, A.-S. Samy, J. Corfa, G.E.Peck, and K.R. Morris J Pharm Sci 91 3 631–639 (2002).

27

A National Center to Address these Issues

Materials science – fundamental understanding Pharmaceutical engineering Process understanding and control Design for six sigma Informatics Industrialization

• Physical design• Characterization• Scale-up & small scale production• Specifications

Build on success of current centers/consortia

28

National Center

Current Consortia & Programs

New Programs

29

Current Consortia

& Programs

CAMP NSFCPPR PTCC 21st

Century GMP RegulatoryEducation

30

New Programs

ERC Mater.Sci.

Infor-matics

Anal.Chem.

Six Sigma

Prediction Pharm.Engr.

31

Science and Engineering Expertise at Purdue

Leading basic and applied science programs in • Engineering• Chemistry• Pharmacy• Materials science

Top Pharmacy School and Industrial Pharmacy Department

Leading Chemical Engineering Department Leading manufacturing program Top analytical chemistry program Ability and willingness to collaborate

32

Regulatory Expertise Purdue faculty participation in Pharmaceutical

Sciences Advisory Committee of the FDA• Garnet Peck• Steve Byrn (former Chair)• Ken Morris

Training FDA “Patriot Team” in process analytical technology (PAT), receiving international kudos

Teaching courses to FDA and the only academics advising major CMC revisions (Ken Morris)

Purdue IPPH faculty are members of United States Pharmacopoeia Committee of Experts (Byrn and Peck)

Harvey Wiley a Purdue Professor was the first commissioner of the FDA

33

Multi-university Programs

Collaborator via CAMP – MIT Collaborator via PTCC – IIT Collaborators via NSF CPPR – Univ.

of Puerto Rico, U. Conn., Minnesota, Rutgers

Collaborators via ERC and National Center (Proposed) - Rutgers

34

Conclusion – StrategyNational Center for Pharmaceutical Technology

Establish a Center patterned after the National Center for Food Safety and Technology and/or Argonne Laboratory

Establish facilities and infrastructure Obtain programmatic support from FDA (for FDA

employees) and a consortium of companies Investigate scientific issues of mutual interest to

the FDA, companies and academia Establish educational programs

35

Administration of National Center

Not for profit Administered by Purdue MOU with several universities in process Run by full time professional project manager Board integrated by academics, industrialists,

government rep. Funding in the $20 M per year range

36

Extra

37

Hierarchy of Projects

1. Materials Science

2. PAT – Process understanding

3. Informatics

4. Prediction

5. Low Variability – 6 Sigma


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