recipe driven, data visualization

© Copyr i gh t 2014 OSIso f t , LLC.

Presented by

Recipe driven,

data visualization

from lab to

commercial

Barry Higgins and Koen Paeshuyse


Agenda

• Introduction

• Goal and Challenges

• S88 recipe strategy

• Recipe integration into systems

• OSIsoft PI AF/EF setup

• Data visualization

• Conclusions

2


Introduction

3

Cardiovascular & Metabolism

Immunology Infectious Diseases & Vaccines

Neuroscience Oncology

20%

80% Internal

External

API SM* Development

* API: Active Pharmaceutical Ingredient

SM: Small Molecules


Goal and Challenges

4

Building a Knowledge Based Organization

Common Data Warehouse

Enables leveraging of information

across systems to help drive data

driven decisions

Common Recipe Approach

Ensures that we all “speak the

same language” promoting

consistency

DPD

AD

API

Electronic

Lab Notebook

Data Infrastructure

Data Visualization


S88 – What is it?

5

Short for ANSI/ISA-88

• ANSI is American National Standards Institute

• ISA is Instrumentation, Systems, and Automation Society

An industry standard addressing batch process control

S88 provides a consistent set of standards and terminology for batch control


S88 – Process Model

6

Process A Process is made up of an ordered set of one or more

Process Stages

Process

Stage

A Process Stage is made up of an ordered

set of one or more Process Operations

Process

Operation

A Process Operation is made up of

an ordered set of one or more Process

Actions

Process

Actions\

Parameters ANSI/ISA-88.00.03-2003

Part 3 Figure 6


S88 – Process Model

7

Process A Process is made up of an ordered set of one or more

Process Stages

Process

Stage

A Process Stage is made up of an ordered

set of one or more Process Operations

Process

Operation

A Process Operation is made up of

an ordered set of one or more Process

Actions

Process

Actions\

Parameters ANSI/ISA-88.00.03-2003

Part 3 Figure 6

P S

O A

Process

Process

Stage

Process

Operation

Process

Actions\

Parameters


S88 recipe model for API SM Dev

8

ACTION

PARAMETERS

PROCESS

OPERATION

PROCESS

ACTION

Charge

Parameter

Name Target Unit Actual

Material

Quantity

Duration

pH

PROCESS

Project

PROCESS

STAGE

Product

Product

Temperature Control

Wait

Reaction (#)

Preparation (#)

Work up (#)

Agitate


S88 recipe model for API SM Dev

9

ACTION

PARAMETERS

PROCESS

OPERATION

PROCESS

ACTION

Charge

Parameter

Name Target Unit Actual

Material

Quantity

Duration

pH

PROCESS

Project

PROCESS

STAGE

Product

Product

Temperature Control

Wait

Reaction (#)

Preparation (#)

Work up (#)

Agitate


S88 Recipe KM* Strategy

10

Operation

Operation Operation

Operation

Operation Operation

Site Executable Recipe

Regulatory Filing = General Recipe

CONTENT Critical Parameters and Steps Structured in S88 Format

EXECUTION Data generated in S88 Format Contains additional site details

Process

Process

Stage

Process

Operation

Process

Action

VISUALIZATION Critical Parameters and Steps Context rich data

* KM: Knowledge Management


Dataflow in the Process Chemistry lab

11

Execute experiment

Samples during experiment incorporated in same ELN experiment

LAB

LAN

SERVER

Experiment done

iC Data Center by Mettler

Output files

SN – ID Username

Start experiment on Automate Lab Reactor

View/Reprocess on Client Automatic update on server

csv file contains ALR recipe and data (to be XML format)

IDM

ALR and PAT data

iControl

OFFICE

S88 Executed Recipe Based on Approved Operatios and Actions

Analytical results

LC

KF

NMR

Initiates ELN experiment in Symyx Notebook

Scientist Chemistry Table

Experiment master data


S88 integration in ELN

12


S88 integration in ELN

13

S88 Process Model


S88 integration in OSIsoft PI System

14

ELN

Process Analytical Technology

tools

Automated Lab

Reactor


OSIsoft PI System Architecture

• Existing infrastructure utilized.

• Development and Production environments.

• 74 Automated Lab Reactors (ALRs) across 20 of labs.

15

J&J Business LAN

Beerse J&J Automation VLAN

Pilot Plant

DeltaV 7.x

PI Base

1K

Automation Firewall

(VLANs) Failover

(Phase II)

Primary PI Interface

Node (Beerse)

Enterprise PI Server

(Primary)

Ø Windows Server 2003

Ø Terminal Services

Ø PI Enterprise 2010

Ø Interface Monitoring (PI ACE).

Janssen Beerse

PI System Architecture

TQS Integration Ltd

Rev 0.4

Sandbox PI Server


Ø Sharepoint Server (MOSS)

Ø PI WebParts

Ø RtReports

Enterprise PI Server

(Secondary)


Ø Terminal Services

Ø PI Enterprise 2010

Ø Interface Monitoring (ACE)

PI Web Parts Server


Ø Sharepoint Server (MOSS)

Ø PI tWebParts

Ø RtReports

Secondary PI Interface

Node (Beerse)

Sandbox PI Interface

Node (Beerse)

Higi Automation Isolation Network

Failover

(Phase II)

Secondary PI

Interface Node

(Higi)

Primary PI

Interface Node

(Higi)

Outside Clean Area

Coating Machine (PP-015)

Fixed Wire Devices

A

Coating Machine (PP-016)

Top Granulator (PP-002)

Livepoint Server


Ø Livepoint

PD Plant – DCS PD Plant - CRS

S7 PLC’s (16 No)

Win CC / PI

Reporting Nodes

PI ENT

5KReporting Nodes

PCS7

SIPCIP

10 Devices

PD - Standalone

WB0

1

RH0

2

Miniplant

PCS7

PST Plant

S7 PLC’s

Win CC / PI

PI ENT

5K

Development

Labs

ALR

Mettler ALR


PI Event Frames Addition

16

PI Interfaces


PI Event Frames 1 – ALR Data

• CSV generated from ALR, containing both continuous and event data.

• PI UFL Interface developed to write data to tags.

• PI System configured to generate PI Event Frames

17

UFL EF GEN


PI Event Frames 2 – ELN Data

• XML output from ELN exported every night.

• Stored Procedures run via PI RDBMS.

18

RDBMS

EF GEN


PI Event Frames 3 – ELN and ALR Data

• Challenge – ELN and ALR data are not time

linked.

• Goal – Create a single event frame that contains

and combines the ELN and ALR actions and all

its data for analysis

19


PI Event Frames 3 – Bringing it all together

• Data and action

timestamps.

• ELN Timestamps adjusted.

• Stored procedure call

writes to PI System.

• Entire experiment is

captured in one event.

20


Visualizing the data

• Ability to view, analyze and share experiment data away from the lab.

• Web based tools preferred.

• PI Coresight live point.

21


PI System lab data integration overview future

22

Pilot and

Commercial

Data

iControl,

touch panel

PAT

ELN

PI Interfaces

Analytical

Data

© Copyr i gh t 2014 OSIso f t , LLC. 23

Internal External External External External

Source Independent Cloud-based Data Presentation Layer

? ? ? ? ?

• Very disparate systems landscape – now

including MES, ELN, Manual Data Entry…

• Ability to share contextualized process data with

external partners is critical.

• Require capability to capture and aggregate data

for visualisation, reporting & analysis

Value of the OSIsoft PI System: Future


• Visualizing the data outside of

the lab.

• By applying the S88 structure,

lab to commercial comparisons

are possible

Solution Results and Benefits

Recipe driven, data visualization

from lab to commercial

Business Challenge

• Streamline and implement

the S88 recipe strategy in the

different variety on lab

systems we have in place

• Combining the data from

multiple data sources

• OSIsoft PI System as our

global Data Infrastructure is

the key enabler towards this

recipe concept.

• PI Asset Framework and

PI Event Frames components

to bring the data together

• Enabling scientists to generate and capture

consistent process data in a standard recipe context

to generate information and knowledge from

experiments.

• Enabling efficient transfer from the lab through our

pilot plants, commercial operations and ultimately to

our patients, capturing and building knowledge

throughout.

24

OSI PI


Acknowledgments

Ryan Bass, Nick Dani, Adam Fermier, Alison

Harkins, Jim Kenyon, Mike McGorry, Luc Moens,

Terry Murphy, Chris Nichols, Gaby Wevers

…and many others

25


Thanks

• Barry Higgins – [email protected]

• Koen Paeshuyse – [email protected]

• Janssen PDMS

26

mailto:[email protected]

mailto:[email protected]

© Copyr i gh t 2014 OSIso f t , LLC. 27

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