sum11 pharma.pdf

8/14/2019 sum11 pharma.pdf

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&

G..

C E

65

NSF ERCFOR STRUCTURED ORGANICPARTICULATE SYSTEMS


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I

E

/

IE

EC


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3

39.80%

30.60%, , 12.70%

11.20%

5.70%

$800+ Billion/yGlobal Business!

Source: IMS Health Market Prognosis, March 2010


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D D C

Cost Component Distribution

Discover 20- 25%

C D $0.8 B $2 B

A &D $60 B

Safety & Toxicology 1520%

Product DevelopmentAPI process design

Product formulation & process designClinical supply

3035%

Clinical Trials ( Phase I-III) 35-40%

& , , , 151 (200)


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Disposition of salesrevenue of 8 largestresearch-basedpharmaceuticalmanufacturers

ManufacturingCOGS27%

After TaxAccounting Profit

18%

Taxes

U.S. pharmaceuticalexpenditures in 2009~ $320 B

(IMS Health and PMPRBAnnual Report, 2010)

COGS (U.S) = ~ $90 B .. , , 136, / 2001

7%

R&D13% Sales & General

Administration

35%


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D &

D A

L

()

NHHO

O

CH3

6

D , , ,

, ,

/

G


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ExcipientsAPI

Dosage Form

/


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C A : &

D &

FDA & ()

F &

C ,

: DD D

C D C A &


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E A

& DAI

& D

I B C

E D D

( CACE 2008; CACE 2008)

C C (496)

C C (L , CACE 2009,2010)


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D

Quantitative definitionFor selected set of equipment design

parameters

Probability distributions of feed

The established range of process parameters that has

been demonstrated to provide assurance of quality.

I A

Probability distributions ofinternal process variables

Required probability of meetingproduct critical quality attributes

Design space:Multidimensional region defined byranges of operating variablescontaining all variable adjustmentsnecessary to achieve desiredprobability of meeting product CQA

CA

D


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D C :

& E.., F ,

A , ,

)C ( ,

)

CA

C I:

&


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%

BloodL

evel

H

D & D

I

D

D

D

C

D

D

C

C

D

AI (, )

D

E


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Manuf.

Design

Space

Degradant

Unstable

form

Post-

Manufacturing

Degradation

Drug

Expiry

2.0

2.5

60 min

milled

30

40

50

5% H 30% H

I D

%

13

0 5 10 15 20 25 30

0.0

0.5

1.0

1.5

%l

actam

time(days)

milled

15 min

milled

API as

received 0

10

20

0 100 200 300 400 500 600

50% H

D

D

&

()

L


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D C : G

Excipients

Binder

Lubricants

O OH

NH2 NH

O

gabapentin lactam

AI

H (70%): HC,

CC, C,

2011

/

WetGranulation

Fluid BedDrying

Blending Tabletting

API

G: D A D

D

+

(

)


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I

E

/ IE


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NSF ERC for Structured Organic Particulate SystemsNSF ERC for Structured Organic Particulate Systems

30 Faculty

16

50+ PhDstudents &postdocsIndustrial

partners26

Launched

July 2006


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CC--SOPS ObjectivesSOPS Objectives

Develop scientific foundation foroptimal design of structured organiccomposite products for

pharmaceutical, nutraceutical &agrochemical industries

Develop science and engineeringmethods for desi nin scalin

NAE 2008

17

optimizing and controlling relevantmanufacturing processes.

Demonstrate developedfundamentals on novel test beds.

Establish effective educational andtechnology transfer vehicles. Engineer

better medicines !

Personalized medicine


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Thrust D: Integrated Systems Science

Model predictive design and operation ofintegrated particulate processes

Thrust Leader: Venkat Venkatasubramanian (PU)

Thrust B projec Thrust B proThrust D projects

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D-1 Sensing MethodologiesD-2 Hardware and Software Integration

D-3 Ontological Informatics Infrastructure

D-4 Real-time Process Management

D-5 Integrated Design and Optimization

Demonstration on Test Beds


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Data, Information, ModelsData, Information, Models

1. Feeder Screw Speed (rpm) Vibration if resent

7. Pneumatic Transfer

6. Transfer Receptacle Monitor mass over time

8. Tablet Press Fill weight

Pressure RPM Feed Frame RPM Feed Frame Blade

Speed Punch Distance

12

3

4

4. Roll Compactor Roll Speed Hydraulic Pressure Feed rate Roll Gap

Ribbon Content

Uniformity Ribbon Density (NIR)

5. Mill Milling Speed Particle Size

Continuous Granulation Line

19

Powder Flow

Powder Level in Hopper

2. Continuous Blender Tilt Speed (rpm) Load (mass/level) Inlet Powder Flow

Content Uniformity (NIR) Density (X-ray/Microwave

/NIR)

Outlet Powder Flow

9. Tablets Weight

Tensile strength

Density

n e ow er ow

Content Uniformity Density (NIR)

Tablet Weight

Tablet Density

Feed Frame Outlet

Flow

Powder Density

Powder Segregation85

6

7

9

3. Feed Hopper / Screw Screw Speed (rpm) Vacuum Pressure

Powder Level in Hopper Density at RC Entrance


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Information Ontology ArchitectureInformation Ontology Architecture

GUI

Decisions Knowledge Models

20

Information

Computationaltools

Unstructured information

Venkatasubramanian AICHE J 2009


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Real Time Process Management

21


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Process FaultsProcess Faults & Disturbances& Disturbances

2. Continuous Blender (DEM,Compartment)

No Content Uniformity

5. Mill (PBM) No Flow (screens clog/foul) Undesired Particle Size (over-milling)

RPM

6. Transfer Receptacle

8. Tablet Press (FEM) Flow Variability Incorrect Density Powder Segregation

7. Pneumatic Transfer

All Unit Operations Max/Min Limits of

Manipulated VariablesReached2

3

4

7

1Unit Operation

DEM

Neural Nets

22

. Insufficient Shear Force Generating Electrostatics

No Flow RPM/Motor Malfunction Tilt Angle Cohesiveness

4. Roll Compactor (FEM)

Undesired Density Pressure RPM/Motor Malfunction Feed Screw / Roll Speed

Ratio No Content Uniformity No Flow No Compaction

PSD Variation

Mass Accumulation Bridging Whiskering Dissolution Weight Variation Picking High Friability Sticking Capping Lamination Weak (Tensile Strength)

85

6

9

Statistical

DAE

Solvers


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Roller Compaction Model Management in POPE

Johansons rolling model with timevariation of roll gap included

10/11/2005

23

ENGINEERING RESEARCH CENTER FOR

STRUCTURED ORGANIC PARTICULATE SYSTEMS

RUTGERS UNIVERSITYPURDUE UNIVERSITY

NEW JERSEY INSTITUTE OF TECHNOLOGYUNIVERSITY OF PUERTO RICO AT MAYAGEZ

Model and OperationOntology JAVA Engine and

GUI


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EEM: Alexanderwerk Roller Compactor

Roll GapFeed Screw Speed

Hydraulic Pressure

RollSpeed

25

Feedback Control

Event: No powder entering roll region

Causes: No powder in hopperBlockage in hopper

Jam in nip region

Event: No powder entering roll region

Causes: No powder in hopperBlockage in hopper

Jam in nip region


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Exceptional Events Management

HydraulicPressure

Delta-V FaultDetection

Mitigation strategy isautomated wheneverpossible; otherwise, a

strategy is suggestedto the operator

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RollGap

Feed ScrewSpeed

FeedbackControl

RollSpeed

FaultDiagnosis

FaultMitigation


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Feeders

Blender

Multi-pointNIR

10/11/2005

27

ENGINEERING RESEARCH CENTER FOR

STRUCTURED ORGANIC PARTICULATE SYSTEMS

RUTGERS UNIVERSITYPURDUE UNIVERSITY

NEW JERSEY INSTITUTE OF TECHNOLOGYUNIVERSITY OF PUERTO RICO AT MAYAGEZ

TabletPress

Delta VControl System

Optical

Tablet thicknessMeasurement


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AICE 2010

383,G , F C I I

444, H , E E C

: F, B, & C

456, L , A CI C K D: HB

456, J , : I

596, G , C : I

697,L , I C I FBAED

D F 444,K , D C

()


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SummarySummary

Changes in business environment have openedexiting opportunities for development and

application of PSE methodology. Product /process design challenges: linking input

material properties & manufacturing conditions to

29

o pro uc s e e erapeu c per ormance

Key process operations challenges: predicting &optimizing performance of particulate and/orheterogeneous multicomponent systems

Risk management is critical: opportunity forexploitation of quantitative Bayesian basedestimation and analysis methods

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