Rutgers CM Seminar - QbD Process Tech 051716-R1

Advanced Process Automation and Data Management Solutions for Continuous Manufacturing

Paul BrodbeckChief TechnologistQbD Process Technologies, Inc.ContinuousPlant™ Software Suite

2 QbD Process TechnologiesContinuousPlant™ Software Suite

AgendaAgenda

• QbD Process Technologies Overview• Process Automation System Supervisory Controller – DeltaV

– Unit Operations Integration for Continuous Manufacturing (CM) – Process Analytical Technology (PAT) – synTQ

• Process Automation Architecture– S88 Batch Model for Continuous Manufacturing (CM)– CM Architecture of the Future (Rutgers)

• Materials Characterization / Database• Enterprise Master / Network & Recipe Management

– PAT Enterprise Master / Network – synTQ – Enterprise Master / Network – DeltaV Process Automation System– Recipe Management – DeltaV

• Data Management for Continuous Manufacturing (CM)– Statistics Portal – Statistica– Big Data Platform - Sinequa – Continuous Data Historians / Dashboards – OSI PI– QbD Materials Traceability/Batch Reporting



QbD Process Technologies Continuous Manufacturing (CM)QbD Process Technologies Continuous Manufacturing (CM)

• Develop and apply innovative real-time software, applications and integrated solutions that enable manufacturers to integrally design quality into the control of their continuous drug product manufacturing processes

• Integrate advanced process automation solutions with real-time Process Analytical Technology (PAT) orchestrations, advanced process control (APC), and data management of Critical Process Parameter (CPP) variables that affect predefined and measured Critical Quality Attributes (CQA)

• Enable manufacturers to make drug products more efficiently, reliably and of better quality than traditional batch manufacturing methods

• Enable the implementation of emerging technologies in the fields of PAT and Continuous Manufacturing

Mission Key Objective & Goal


What is ContinuousPlantTM Software Suite?

• Suite of real-time (RT) software that enables pharmaceutical and biotech manufacturers to deploy advanced real-time continuous manufacturing processes

– Integrates production equipment with advanced real-time advanced process control (APC) applications, in-process Process Analytical Technology (PAT) orchestrations, continuous process data historian and material traceability data management system

QbD Process Technologies ContinuousPlant™ Software SuiteQbD Process Technologies ContinuousPlant™ Software Suite


Rutgers Continuous Manufacturing PlantRutgers Continuous Manufacturing Plant


DeltaV Process Automation SystemSupervisory ControllerDeltaV Process Automation SystemSupervisory Controller


Unit Operations IntegrationK-Tron FeederUnit Operations IntegrationK-Tron Feeder• PROFIBUS

– International standard for digital data transfer in process automation

• DeltaV reads / writes SPs / PVs with K-Tron Feeders

• Recipe loads formula, SPs and process parameters and Sequence of Operations to K-Tron Unit Operations

• DeltaV executes Feeder Sequence of Operations

• DeltaV Ratio & Mass Balance Control• QbD ContinuousPlant™ Real-Time (RT)

Throughput Optimization– Process flow optimizer to control and

maximize plant production flow/feed rate or throughput and product quality within a user defined design space

K-Tron Control Parameters in DeltaV• Hopper Weight (WT)• Feed Rate (PV)• Feed Setpoint (SP)• Controller Output (PV)


Unit Operations IntegrationGlatt Blender and GranulatorsUnit Operations IntegrationGlatt Blender and Granulators

• Interface to Glatt equipment using DeltaV classic IO or Ethernet/IP

• DeltaV starts/stops Blender directly• DeltaV sets Blender speed directly• DeltaV recipe loads formula, SPs and

process parameters and Sequence of Operations to Glatt Unit Operations

• QbD ContinuousPlant™ Real-Time (RT) Process Optimizer

– Advanced process control (APC) algorithm used for optimizing blend uniformity of a continuous blender

– Varies the rotational speed to minimize Relative Standard Deviation (RSD)

• DeltaV can read and write process parameters from Glatt Wet and Dry Granulators


Unit Operations IntegrationFette Tablet PressUnit Operations IntegrationFette Tablet Press

• OPC Server• DeltaV reads / writes / all OPC Tags• Fette HMI tags displayed on DeltaV• Press can be operated from DeltaV• Recipe loads formula, SPs and process

parameters and Sequence of Operations to Fette Unit Operation

• Rutgers C-SOPS working on feedforward and feedback control loops to Press through DeltaV

• Press speed varied to maintain level


synTQ Process Analytical Technology (PAT)synTQ Process Analytical Technology (PAT)


synTQ Process Analytical Technology (PAT)synTQ Process Analytical Technology (PAT)


Process Automation ArchitectureS88 – Process ModelProcess Automation ArchitectureS88 – Process Model

• Common Philosophy/Architecture fromDevelopment Thru Commercialization

• Improved Tech Transfer

• Contextualize Data


Process Automation ArchitectureS88 Batch Model − Physical & SoftwareProcess Automation ArchitectureS88 Batch Model − Physical & Software


Process Automation Architecture S88 Batch Adapted for Continuous Manufacturing (CM)Process Automation Architecture S88 Batch Adapted for Continuous Manufacturing (CM)

EQM

FEEDERS(PROFiBUS)

EQM EQM

BLENDER(VSD)

TABLETPRESS(PLC)

EQM

RAW MATERIAL

CoA

EQM

TABLETTESTER(OPC)

EQM

DRUMMINGSTATION(OPC)

UNIT UNIT

PLANTPROCEDURE(RECIPE)

UNIT

ENTERPRISERECIPE/FORMULA

PROCESSCELL(s)

COMMUNICATIONSETHERNET/IP – MODBUS/TCP – OPC – PROFIBUS

PHASE PHASE PHASE

OPERATION OPERATION OPERATION

PHASE

OPERATION

CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM

DATABASES


Process Automation ArchitectureS88 Batch Adapted for Continuous Manufacturing (CM)Process Automation ArchitectureS88 Batch Adapted for Continuous Manufacturing (CM)


Process Automation ArchitectureCM Architecture of the Future (Rutgers C-SOPS 2-3 Years)Process Automation ArchitectureCM Architecture of the Future (Rutgers C-SOPS 2-3 Years)


Materials Characterization / DatabaseMaterials Characterization / Database• Method automation with synTQ• Materials database (SQL)• synTQ reads / writes data to

materials database and LIMS• Raw material testing results in real-

time with bar coding• Materials data integrated in real-

time Models for feedforward control• synTQ can control off-line

analyzers / calibrate / read diagnostics

• Print Certificate of Analysis (CoA)


Materials DatabaseMaterials Database

• Stores material properties for products used in Continuous Manufacturing (CM)

• Materials properties used to optimize formulas for CM• Materials properties used to develop Models• Models used to design the optimal CM Plant• Manufacturing

– Raw Material Data captured in real-time is compared to properties in materials database and used for control models running in DeltaV


synTQ Enterprise Master / NetworksynTQ Enterprise Master / Network


DeltaV Enterprise Master / NetworkDeltaV Enterprise Master / Network

DeltaV Development

DeltaV Manufacturing

Plant1

DeltaV Manufacturing

Plant2

DeltaV EnterpriseMaster

SQL dB ReplicationContinuous Data

SQL dB Replication

ManufacturingNetwork

Enterprise/BusinessNetworkOr Cloud

OSI PI Data

Historian

Continuous Data

RecipeControl Logic

RecipeControl Logic


DeltaV Recipe ManagerDeltaV Recipe Manager


Data ManagementStatistica – Data Analytics Enterprise ServerData ManagementStatistica – Data Analytics Enterprise Server


Big Data ManagementSinequa – Real-time Big Data Search & AnalyticsBig Data ManagementSinequa – Real-time Big Data Search & Analytics


Data ManagementContinuous Data Historian / Dashboards – OSI PIData ManagementContinuous Data Historian / Dashboards – OSI PI

OSI PI Buffer Subsystem Architecture

Business Intelligence Dashboards

Quickly create web dashboards using existing PI

Elements


Data ManagementContextualize – OSI PI Asset FrameworkData ManagementContextualize – OSI PI Asset Framework


• Process Prediction– Analytical measurements for real-time quality information– “Soft Sensors” to back-up analyzers and predict other hard to

measure process parameters– Provide real-time predicted values to help Operator improve

process control

• Process Fault Detection– Fault detection indicates a “statistically abnormal” operating

condition– Provide operators with information on which inputs are root cause

of problems

• On-line Operations Interface– On-line quality predictions and fault detection help operator prevent

quality incidents and downtime

DeltaV Embedded AnalyticsDeltaV Embedded Analytics


Data ManagementAdvanced Data Management & ControlData ManagementAdvanced Data Management & Control

PAT Orchestrations at Runtime

Spectral Data


Data Management – Material Tracing for CMContinuousPlant™ RT Materials Traceability ModelData Management – Material Tracing for CMContinuousPlant™ RT Materials Traceability Model

Recalculated Every Second


SummarySummary

• Objective - Apply real-time software, applications and advanced process control solutions that enable pharmaceutical and biotech manufacturers to integrally design quality into the control of continuous manufacturing processes

• Deploy a process automation integration model that enables manufacturers to deploy advanced real-time continuous manufacturing processes

– Integrates production equipment with advanced real-time advanced process control (APC) applications, in-process Process Analytical Technology (PAT) orchestrations, continuous process data historian and material traceability data management system

• Goal - Enable production of drug products more efficiently, reliably and of better quality than traditional batch manufacturing methods

Paul BrodbeckChief TechnologistQbD Process Technologies, [email protected]

ContinuousPlant™ Software Suitehttp://www.qbdprocess.com/


Documents

Rutgers CM Seminar - QbD Process Tech 051716-R1