The manufacturing of pharmaceutical products is preceded by complex development phases where process design, planning, and scheduling problems must be considered as deeply linked, fact that has not yet been adequately handled by the existing literature. In this perspective, this work discusses the role of the production planning and scheduling decisions in the pharmaceutical industry. It starts by analysing the main aspects that influence planning and scheduling, and defines an extended scope of the related problems, as a way to account for higher levels of integration between process design and operational decisions. We propose a novel conceptual representation, the Delivery Trade-offs Matrix (DTM) to help managing the trade-offs occurring in the drug development process and to expose the factors that affect the performance of these manufacturing systems.
Production Planning and Control
Objective of PPC
There are three stages in PPC
Classification/Functions of PPC
Benefits of PPC
Limitations of PPC
Production Planning / Operations Planning
Factors determining Production Planning Procedures
Production Planning System
Production Control
Factors Determining PC procedures
Main Functions of Production Planning
& Control Department
Plant Planning & Facility Planning
Production Planning and Control
Objective of PPC
Classification/Functions of PPC
Levels of PPC
Factors determining Production Planning Procedures
Production Planning System
Factors Determining PC procedures
You can buy this here: http://imojo.in/330t3x
This presentation is aimed at helping small and medium businesses in their production planning processes.
Production Planning is explained in a detailed manner with step-by-step examples for better understanding.
Production Planning and Control
Objective of PPC
There are three stages in PPC
Classification/Functions of PPC
Benefits of PPC
Limitations of PPC
Production Planning / Operations Planning
Factors determining Production Planning Procedures
Production Planning System
Production Control
Factors Determining PC procedures
Main Functions of Production Planning
& Control Department
Plant Planning & Facility Planning
Production Planning and Control
Objective of PPC
Classification/Functions of PPC
Levels of PPC
Factors determining Production Planning Procedures
Production Planning System
Factors Determining PC procedures
You can buy this here: http://imojo.in/330t3x
This presentation is aimed at helping small and medium businesses in their production planning processes.
Production Planning is explained in a detailed manner with step-by-step examples for better understanding.
UNIT – I
Production System & Advanced Forecasting Method
Generalized Model of production system, design, optimization & control of production system. PPC – Production Planning, integrated part of corporate planning process, Integrative nature of production plans, centralized and decentralized production planning.
Advanced Forecasting – Principles, SWOT analysis, and 7S approach, Advanced Techniques – multi item forecasting, slow item forecasting.
UNIT - II
Capacity Planning
Measurement measures, estimating future capacity needs, factors influencing, factors favouring over capacity and under capacity, MPS.
Production Control Functions
Loading, sequencing, assignment models
High Volume Production System
Detroit type automation, automated flow lines, transfer mechanism, buffer storage, control function, automation for machining operation, Design and fabrication considerations.
UNIT – III
Inventory Management
Inventory models and safety stocks – Relevant costs, behaviour of costs in relation to level of inventory, optimal order quantity, EOQ, EBQ, Joint cycle for multiple products, model with purchase discounts, approaches to determine buffer stock, fixed order period models.
ABC and other classification of Materials selective management control, VED analysis, combination of ABC and VED analysis, purpose classification.
Material requirement planning (MRP – I) – Concepts, structure, working output reports, classes of users.
UNIT – IV
Material Management
Spare parts Management – Characteristics, codification concept, stocking, policy analysis, Maintenance or breakdown capital, insurance, rotable spares.
Other aspects of Material Management
Codification, characteristics, standardization, material handling, stores management.
UNIT – V
Physical Distribution Management
Transportation problem, Route scheduling problem, logistics management.
Material Management
An integrated view, Adaptability considerations, inventory – a part of production strategy, organization, effectiveness, a multi level interactive process.
Production management about in pharmaceutics as well as pharmaceutical jurisprudence.
How to deside the best ppt to deliver a seminar and the knowledge as well as the all details descriptions about productions and managements in it
Just i want to say one think PPT mens as simple considerations the power of the light to show the point only you want to present , not A FULL THEORY in it just that point those you want to present
Introduction of Production Planing, Levels and Procedure of Production Planning , Introduction of Production Control and its techniques , Relationship or difference between production planning and control
UNIT – I
Production System & Advanced Forecasting Method
Generalized Model of production system, design, optimization & control of production system. PPC – Production Planning, integrated part of corporate planning process, Integrative nature of production plans, centralized and decentralized production planning.
Advanced Forecasting – Principles, SWOT analysis, and 7S approach, Advanced Techniques – multi item forecasting, slow item forecasting.
UNIT - II
Capacity Planning
Measurement measures, estimating future capacity needs, factors influencing, factors favouring over capacity and under capacity, MPS.
Production Control Functions
Loading, sequencing, assignment models
High Volume Production System
Detroit type automation, automated flow lines, transfer mechanism, buffer storage, control function, automation for machining operation, Design and fabrication considerations.
UNIT – III
Inventory Management
Inventory models and safety stocks – Relevant costs, behaviour of costs in relation to level of inventory, optimal order quantity, EOQ, EBQ, Joint cycle for multiple products, model with purchase discounts, approaches to determine buffer stock, fixed order period models.
ABC and other classification of Materials selective management control, VED analysis, combination of ABC and VED analysis, purpose classification.
Material requirement planning (MRP – I) – Concepts, structure, working output reports, classes of users.
UNIT – IV
Material Management
Spare parts Management – Characteristics, codification concept, stocking, policy analysis, Maintenance or breakdown capital, insurance, rotable spares.
Other aspects of Material Management
Codification, characteristics, standardization, material handling, stores management.
UNIT – V
Physical Distribution Management
Transportation problem, Route scheduling problem, logistics management.
Material Management
An integrated view, Adaptability considerations, inventory – a part of production strategy, organization, effectiveness, a multi level interactive process.
Production management about in pharmaceutics as well as pharmaceutical jurisprudence.
How to deside the best ppt to deliver a seminar and the knowledge as well as the all details descriptions about productions and managements in it
Just i want to say one think PPT mens as simple considerations the power of the light to show the point only you want to present , not A FULL THEORY in it just that point those you want to present
Introduction of Production Planing, Levels and Procedure of Production Planning , Introduction of Production Control and its techniques , Relationship or difference between production planning and control
Production Planning Control, Demand Forecasting, Aggregate Production Planning, Strategies of Aggregate Planning . Scheduling
Workforce Planning
Materials Requirement Planning
Capacity Planning
Production Control using JIT
Shop-Floor Control
How SAP HANA can provide value for Pharma R&DMarc Maurer
This presentation describes how the in-memory data platform SAP HANA can provide value for different use cases found in research & deveopment of big pharma companies.
SCM-APO-PP/DS-Production Planning and Detailed SchedulingAJAY
APO Production Planning and Detailed Scheduling is a set of functionalities around Inhouse Production Planning, External Procurement Planning, Resource Scheduling and Sequence Optimization.
PPDS is primarily divided in two areas - Production Planning and Detailed Scheduling. This component has the highest amount of integration between APO and the OLTP (R/3 or ERP) system for real-time transaction data transfer back and forth. This is made possible by a standard interface from SAP named Core Interface Function.
PP/DS is more used for finite optimization at a plant level by optimizing the resources, materials and manpower. It considers all the finite constraints in more detail and allows the planners to generate a day-to-day finite schedule, resource loading charts etc.
Pharmaceutical, Bulk Drugs and Medicine Manufacturing Industry (Production, F...Ajjay Kumar Gupta
Quality control and quality assurance are vital in this industry. Many production workers are assigned full time to quality control and quality assurance functions, whereas other employees may devote part of their time to these functions. For example, although pharmaceutical company sales representatives, often called detailers, work primarily in marketing, they engage in quality control when they assist pharmacists in checking for outdated products.
Advances in manufacturing processes are also impacting the industry. While pharmaceutical manufacturers have long devoted resources to new drug development as a source for future profits, firms are increasingly realizing that improvements throughout the drug pipeline are needed to stay competitive.
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In Process Quality Control System (IPQC) for Solid Dosages Form (Tablets)Gaurav kumar
This presentation pertains to the in-process tests performed during the manufacturing process of the solid dosages form (tablets).
The presentation covers the methods and the permissible limits for the tests performed.
These tests are of great importance as these not only ensure quality product but also upholds the cGMP.
Participate in the full, interactive on-demand webinar here: https://bit.ly/ProcessValWebinar
Process validation is a complex step in the transition to commercial scale manufacturing. While Quality By Design (QBD) is the standard option for a risk-mitigating process validation strategy, there are other options for more flexibility and speed. Join our webinar to learn how outsourcing to a CDMO, able to take an adaptive, risk-based validation approach, will accelerate your time to market.
In this webinar, you will discover more about:
• How outsourcing to a CDMO partner in late-stage will increase flexibility and speed
• How a risk-based approach can help you optimize your process validation strategy
• How we have implemented a risk-based approach for our clients via case studies
Pharmaceutical Technology Transfer Best PracticesAnthony Grenier
Key Takeaways from the Technology Transfer Guidelines
• Standardize checklist for transferring product development, process development, and analytical method development knowledge
• Requirements are summarized in key deliverables and reports
Regulatory Due Diligence, Using Regulatory Affairs to Maximize the Value of a...SGS
Developing a new drug is a costly undertaking, which can cost several hundreds of millions. Except for the largest Pharma companies, any other company will need external funding at some stage in the development of a drug. A solid regulatory strategy in early phase clinical research is essential to convince your investors to further fund the clinical development of your compound. Depending on your compound (chemical, biotech product, advanced therapy) and the type of investors (private investors, government funding bodies or a larger pharmaceutical company), different aspects of the regulatory strategy need to be more developed.
The main aspects of such an early phase regulatory strategy will be discussed and illustrated with a number of case studies such as the development of a regulatory strategy for a bacteriophage and discussions with Health Authorities.
Contact Us: clinicalresearch@sgs.com
Visit our Website: http://www.sgs.com/cro
Follow Us on LinkedIn: http://bit.ly/SGSLifeSciences
Writing A Phase I Protocol: A Multidisciplinary Team ApproachSGS
A well-written and thought-out protocol is essential for achieving a high quality research study. To write this complete protocol, one must involve multiple key players from different disciplines, including: pharmacokinetics, toxicology, statisticians, modeling and simulation, and a biomarkers specialist. This approach will take additional time and resources, however the time spent on writing a detailed protocol will help to avoid problems and delays during the study conduct and will make publishing the results easier. A complete protocol is also essential for the study to be approved by the ethics committee. This presentation will explain the important roles of each team member in writing an early phase protocol.
Contact Us: clinicalresearch@sgs.com
Visit our Website: http://www.sgs.com/cro
Follow Us on LinkedIn: http://bit.ly/SGSLifeSciences
IC-SDV 2019: Competitive Intelligence: how to optimize the analysis of pipeli...Dr. Haxel Consult
BizInt for data compilation, selection and Chart Vizualisation and VantagePoint for specific graphic data representations can help for competitive intelligence analysis.
· Pipeline and clinical trials data
· Structure, reliability and updating of data
· Need to query and export data from different sources
· Added values of verification and visualization of information.
· Description of BizInt and VantagePoint
· Practical examples of the use of these 2 tools for the realization of competitive intelligence reports
Polyhydroxyalkanoate are linear polyesters that are produced from fermentation of lipid or sugar by bacteria. The rising demand for biodegradable materials, increase in oil prices and policies concerning green procurement are the driving factors for investment by companies in this market.
Manufacturing is a sophisticated function where people try to juggle between the tasks of increasing productivity, managing their inventory, and optimizing their resource utilization. All this has to be done without compromising on the quality of the product and this is why we are talking about - Production Planning and Control strategy. This strategy for manufacturing combines two essential components of manufacturing - #productionplanning and production control.
Read our e-book to know, what the crucial stages in production planning are, some best practices, and how it is important to get a granular understanding of which section needs to do what, along with where, when, and how.
Production Planning Manufacturing inventory E-book
Link: https://www.polestarllp.com/ebook/production-planning-in-manufacturing-industry-e-book
Follow Polestar Solutions for more such content.
IDMP Implementation - Impact on Data, Systems and Processes. How to cover gap...Torben Haagh
ISO IDMP will be mandatory from July 1st 2016 and it will make a fundamental impact on the way the pharmaceutical industry is required to collect, manage and submit relevant data. Now is the last call for all marketing authorisation holders to (re)think their data submission policies and processes to make sure you close your IDMP implementation gaps in the next 12 month and have a clear vision of the next challenges lying ahead!
Don’t miss out on the opportunity to get your questions answered, to benchmark the stage of your preparation, to initiate partnerships and to take an active part in designing the RIM’s community future agenda! Join us this summer in Berlin and gain valuable, practical information:
# Learn how to assess and analyse data requirements for the IDMP standards by discussing possible interpretations with our expert from regulatory bodies on-site!
# Benchmark your own IDPM Implementation process with peers from both big and mid-size pharma
# Share insights how the IDMP standards are changing the interactions between IT-Systems, company departments, contract manufacturers and regulatory agencies
# Discuss and compare with your peers experiences with vendors and solution providers offering help to achieve your IDMP implementation goals!
For more information visit our website: http://bit.ly/EventWebsite
If you would like to be part of the conference, you can register now here: http://bit.ly/Register-Event
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...
On the complexity of production planning and scheduling in the pharmaceutical industry: the Delivery Trade-offs Matrix
1. FromKnowledgeGenerationToScience-basedInnovation
On the complexity of production planning and scheduling
in the pharmaceutical industry: the Delivery Trade-offs
Matrix
Samuel Moniz,a,b
Ana Paula Barbosa-Póvoa,b
Jorge Pinho de
Sousa,a,c
a
INESC TEC, Rua Dr. Roberto Frias, Porto, Portugal
b
Centro de Estudos de Gestão, Instituto Superior Técnico, Lisboa, Portugal
c
Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, Porto,
Portugal
PSE2015/ESCAPE25| June, 2015
Research and Technological Development | Technology Transfer and Valorisation | Advanced Training | Consulting
Pre-incubation of Technology-based Companies
2. June 2015 PSE2015/ESCAPE25 2
Agenda
1. The pharmaceutical industry
2. Critical factors for planning and scheduling
3. Scope of planning and scheduling problems
4. Delivery Trade-offs Matrix
5. Challenges and opportunities
3. June 2015 PSE2015/ESCAPE25 3
1. The pharmaceutical industry
• The shortage in new drug approval applications
• The uncertainty associated to Research and Development
(R&D) and trials I-III phases
• The pressure of generic drugs
Markets tend to become more complex over time, forcing companies to increase
their responsiveness, both in terms of time and cost
4. June 2015 PSE2015/ESCAPE25 4
1.1. Some figures …
• Developing cost grew 481% to $802 million from 1970s to
1990s (DiMasi et al., 2003; Hynes III, 2009)
• The duration of the development cycle remained fairly
stable (roughly 15 years) (Kessel,2011)
• The production of the APIs is considered the rate-limiting
step of the supply chain (Shah, 2004)
The current worldwide
paradigm imposes a reduction
to less than 10 years (Federsel,
2009)
5. June 2015 PSE2015/ESCAPE25 5
1.2. Industry trends
• Adoption of continuous processes (Roberge et al., 2005)
• Process Analytical Technology (PAT) (McKenzie, 2006)
• Advanced optimization tools (Grossmann, 2005)
Production planning and scheduling are systematically considered very difficult
functions to perform
6. June 2015 PSE2015/ESCAPE25 6
1.2. Pharmaceutical Industry System
Main activities
Research and development activities
Development and manufacturing of Active Pharmaceutical
Ingredients (APIs)
Drugs manufacturing
Primary
manufacturing
Storage
Distributers StorageHospitals, clinics,
pharmacies
Raw Material
suppliers
Storage
Storage
Research and
Development
Secondary
manufacturing
(Shah, 2004)
7. June 2015 PSE2015/ESCAPE25 7
1.2. Pharmaceutical Industry System
Main activities
Research and development activities
Development and manufacturing of Active Pharmaceutical
Ingredients (APIs)
Drugs manufacturing
Primary
manufacturing
Storage
Distributers StorageHospitals, clinics,
pharmacies
Raw Material
suppliers
Storage
Storage
Research and
Development
Secondary
manufacturing
(Shah, 2004)
8. June 2015 PSE2015/ESCAPE25 8
Issues
1.Manufacturing in a high
regulated market
2.High variability on the
demand
4.Pressure created by generic
drugs
2. Critical factors for planning and scheduling: Market
3.Large production mixes
in the manufacturing sites
Main Decision Areas
1.Pipeline management
2.Capacity planning
3.Supply chain management
(Laínez, Schaefer, & Reklaitis, 2012)
Shah (2004) and Buchholz (2010) pointed out that time-to-market is a critical
driver of the pharmaceutical industry
9. June 2015 PSE2015/ESCAPE25 9
Issues
1.Process topology: sequential
and network processes
2.Regulatory and quality
procedures/lots traceability
4.Re-planning and rescheduling are
frequent
2.1. Critical factors for planning and scheduling:
Processes
Main Decision Areas
1.Product Development
2.Process design/scale-up
decisions
3.Processes under development- limited
knowledge of the first batches 3.Advanced Process Control
10. June 2015 PSE2015/ESCAPE25 10
Issues
1.Resources characteristics
2.Batch versus continuous
manufacturing
2.2. Critical factors for planning and scheduling: Plants
Main Decision Areas
1.Plant design: grassroot and retrofit
2.Operating mode: short-term
versus campaign mode
3.Inventory management and
associated policies
3.Reduction of inventory
11. June 2015 PSE2015/ESCAPE25 11
3. Scope of planning and scheduling problems
Process Synthesis
Quantitative
specification of
physicochemical
materials manipulations
Planning and scheduling extended scope
Process
Synthesis
Process
scale-up
Process design Planning Scheduling
Production
execution and
control
“Units
independent”
recipe
Processing
times,
quantities
Recipe
+
Units
R&D
Operations Management
12. June 2015 PSE2015/ESCAPE25 12
3.1. Scope of planning and scheduling problems
Process Synthesis
Quantitative
specification of
physicochemical
materials manipulations
Planning and scheduling extended scope
Process
Synthesis
Process
scale-up
Process design Planning Scheduling
Production
execution and
control
“Units
independent”
recipe
Processing
times,
quantities
Recipe
+
Units
R&D
Operations Management
Process Scale-up and
Process Design
Develop the process
from the laboratory
scale to the industrial
scale
13. June 2015 PSE2015/ESCAPE25 13
3.2. Scope of planning and scheduling problems
Process Synthesis
Quantitative
specification of
physicochemical
materials manipulations
Planning and scheduling extended scope
Process
Synthesis
Process
scale-up
Process design Planning Scheduling
Production
execution and
control
“Units
independent”
recipe
Processing
times,
quantities
Recipe
+
Units
R&D
Operations Management
Process Scale-UP and
Process Design
Develop the process
from the laboratory
scale to the industrial
scale
Planning and
Scheduling
Resources allocation so
as to minimize costs and
increase the plant
output
14. June 2015 PSE2015/ESCAPE25 14
3.3. Scope of planning and scheduling problems
Process Synthesis
Quantitative
specification of
physicochemical
materials manipulations
Planning and scheduling extended scope
Process
Synthesis
Process
scale-up
Process design Planning Scheduling
Production
execution and
control
“Units
independent”
recipe
Processing
times,
quantities
Recipe
+
Units
R&D
Operations Management
Process Scale-UP and
Process Design
Develop the process
from the laboratory
scale to the industrial
scale
Planning and
Scheduling
Resources allocation so
as to minimize costs and
increase the plant
output
Production Control
Production dispatching,
control actions and
quality assessment
15. June 2015 PSE2015/ESCAPE25 15
3.4. Scope of planning and scheduling problems
The scope of the planning and scheduling functions must be extended to account for design
decisions, especially for manufacturing products that are under development
Planning and scheduling extended scope
Process
Synthesis
Process
scale-up
Process design Planning Scheduling
Production
execution and
control
“Units
independent”
recipe
Processing
times, quantities
Recipe
+
Units
R&D
Operations Management
Available alternative units
+ -
16. June 2015 PSE2015/ESCAPE25 16
3.5. Extended scope of planning and scheduling: How?
Flexible graphical representations of
process design and integration with
scheduling
(Moniz, Barbosa-Póvoa, Pinho de Sousa, &
Duarte, 2014)
17. June 2015 PSE2015/ESCAPE25 17
3.5. Extended scope of planning and scheduling: How?
Flexible graphical representations of
process design and integration with
scheduling
(Moniz, Barbosa-Póvoa, Pinho de Sousa, &
Duarte, 2014)
Frameworks for supporting the overall
decision-making process: product
portfolio, capacity planning, planning and
scheduling, process control and safety
and supply chain management
(Venkatasubramanian et al., 2006)
18. June 2015 PSE2015/ESCAPE25 18
Trials I-III
R&D
Drug
F
Drug
F
Drug ADrug A
Drug CDrug C
Drug BDrug B
Commercialization
Drug DDrug D
Drug
E
Drug
E
Understanding and modelling the
conditions for achieving the global
optimization of these
manufacturing systems is by itself a
hard task
The pharmaceutical industry
should focus on the manufacturing
and delivery issues knowing that
each phase of the development
cycle has different challenges
4. Delivery Trade-offs Matrix
Lot size
Few kilograms
Hundreds of kilograms
19. June 2015 PSE2015/ESCAPE25 19
Uncertainty
Low
High
CostHigh
Low
Short-term
planning
Campaign
planning
Time-to-market Amount delivered
Trials I-III
R&D
II
III IV
Drug
F
Drug
F
Critical leap
Drug ADrug A
Drug CDrug C
Drug BDrug B
Commercialization
I
Drug DDrug D
Drug
E
Drug
E
Exposes the issues that affect the
performance of the manufacturing
systems
Graphical representation of the
portfolio
Helps managing the trade-offs
occurring in the drug development
process
4.1. Delivery Trade-offs Matrix
Lot size
20. June 2015 PSE2015/ESCAPE25 20
Uncertainty
Low
High
CostHigh
Low
Trials I-III
R&D
II
III IV
Drug
F
Drug
F
Critical leap
Drug ADrug A
Drug CDrug C
Drug BDrug B
Commercialization
I
Drug DDrug D
Drug
E
Drug
E
Uncertainty and Costs
1.High uncertainty associated to the
drug structure and to the process design
2.Difficulties in estimating the required
time and resources
3.In the development and
manufacturing of APIs it is common to
allocate production resources 6 to 12
months in advance
4. Critical leap: the first scaled up batch
5. Challenges and opportunities
Opportunity: Simulation-optimization can provide interesting solution methods to combine
the stochastic and deterministic parameters of the planning and scheduling problem
Chen, Mockus et al. (2012), Eberle, Sugiyama et al. (2014), Sahay and Ierapetritou (2014)
Lot size
21. June 2015 PSE2015/ESCAPE25 21
Uncertainty
Low
High
CostHigh
Low
Time-to-market Amount delivered
Trials I-III
R&D
II
III IV
Drug
F
Drug
F
Critical leap
Drug ADrug A
Drug CDrug C
Drug BDrug B
Commercialization
I
Drug DDrug D
Drug
E
Drug
E
Time-to-Market and Amount
Delivered
1. The delivery of products to Trials I-III
phases is of extreme importance
2. Fast and robust scalability of the
production processes
3. The inventory in the supply chain
provides flexibility om what concerns to
delivery dates
5.1. Challenges and opportunities
Opportunity: development of comprehensive methods capable of addressing the long–term
dimension of the design and scale-up decisions
Varma, Pekny et al. (2008)
22. June 2015 PSE2015/ESCAPE25 22
Uncertainty
Low
High
CostHigh
Low
Short-term
planning
Campaign
planning
Time-to-market Amount delivered
Trials I-III
R&D
II
III IV
Drug
F
Drug
F
Critical leap
Drug ADrug A
Drug CDrug C
Drug BDrug B
Commercialization
I
Drug DDrug D
Drug
E
Drug
E
Operating Mode
1.Heterogeneous demand
2.Mixed planning strategies: short
term mode versus campaign mode
5.2. Challenges and opportunities
Opportunity: solution methods capable of addressing mixed planning strategies
23. June 2015 PSE2015/ESCAPE25 23
Final remarks
1. We group the critical factors for planning-scheduling decision-making in 3
categories: market, processes, and plants
2. We propose a representation of R&D and manufacturing trade-offs
3. The integration of process scale-up/design decisions with planning and
scheduling decisions is fundamental to do in the early stages of the drug
development cycle
4. Research addressing integrated decision-making, uncertainty, and knowledge
management is essential to solve extended planning and scheduling
problems
Industrial companies are continuously assessing their operations, as a way to increase the overall effectiveness of the production systems.
Markets where these organizations operate tend to become more complex over time, forcing companies to increase their responsiveness, both in terms of time and cost.
The case of the pharmaceutical industry is a good example on how market is driving the change of drug development cycle and manufacturing activities. Some of the most relevant driving factors are related to:
The current worldwide paradigm imposes a reduction to less than 10 years from pre-clinical development to commercialization (Federsel, 2009).
The critical factors that drive the planning and scheduling functions, in the particular context of the pharmaceutical industry, can be grouped in three categories: market, processes, and plants.
Market factors are related to the specific contextual factors of this industry.
Process factors have to do with the structure of the chemical processes.
Plant factors relate to the operating strategies and resources characteristics of the manufacturing systems
Regulatory agencies such as the US Food and Drug Administration (FDA) or the European Medicines Agency (EMA) impose strict regulations that go from the development to the manufacturing of drugs.
Manufacturing in a high regulated market has to deal with additional complexities that do not exist in less regulated markets.
Chemical processes are executed under a close supervision of the regulatory agencies that define procedures to monitor process changes.
Pipeline and development management—this involves the selection of potential drugs to develop further, and the planning of the development activity.
The production process topology strongly determines the scheduling models that can be applied.
In the manufacturing of APIs, for example, processes require numerous production steps with tasks having short and long processing times, usually spanning across several working shifts
Regulatory and quality procedures define the lot size and the changeover requirements that must be rigorously followed in the manufacturing sites, thus introducing additional time to the effective production time.
Stable intermediaries and final products are produced in lots, and therefore lots traceability must be ensured
The first batches after a scale-up are usually more difficult to produce, since this may involve the use of different processing units or even performing changes in the process. For that reason, these processes impose frequent revisions of the production schedule.
The plant structure has also implications on how planning and scheduling are performed.
The characteristics of the plants (such as resources, plant structure, operating mode, and batch/continuous manufacturing) lead as well to specific planning and scheduling problems.
Continuous manufacturing of pharmaceuticals is an emergent process mode that relies on flow reactors and is currently being evaluated for the production of drugs.
A consequence of using flow reactors, instead of batch reactors, is that the production process moves from a batch mode to continuous operating conditions (Buchholz, 2010).
Benefits of continuous manufacturing when compared to batch manufacturing include lower plant and production costs, lower carbon footprint; better quality, higher safety; less costs to scale-up, and higher levels of automation (Roberge et al., 2008; Calabrese & Pissavini, 2011) Nevertheless, existing technological challenges of flow reactors and adaptation of batch processes to continuous processes have made their evaluation and deployment difficult.
Process Synthesis, refers to the quantitative specification of physicochemical materials manipulations that take place, having as output a recipe that is independent of particular processing units
In other words, the recipe describes the chemistry steps required to manufacture the product.
This step complies with the development of the chemical process so as to pass from a laboratory scale to an industrial production dimension, resulting in the determination of the final product quantities (lot sizes) and an initial assessment of the processing times.
Planning and scheduling encompass then the coordination of development and production manufacturing activities so as to pass from the laboratory scale to the industrial scale, resulting in the determination of the final product quantities (lot sizes)
The goal is to find optimal schedules that maximize expected economic value of the investment by considering the resources availability, the probability of success of the clinical trials, and the associated costs.
Production Execution and Control involve the following activities production dispatching, control actions and quality assessment, among others.
The first steps are mainly associated to the R&D functions, while the OM deals essentially with planning and manufacturing.
Nevertheless, decisions should be performed collaboratively in order to ensure that decisions made at each department are properly considered.
Although the figure suggests a sequential and directional decision flow, the different steps are often overlapped and revisited whenever necessary.
We argue that planning and scheduling functions are extended in order to integrate some decisions made in the process scale-up and design steps.
The planning problem, either of long-term or short-term, benefit from considering decisions taken at the scale-up and process design levels, since these decisions have a direct impact on the
determination of the processing units suitable for the process, resulting into different production routes (alternative processes).
On the contrary, after schedule release to the shop-floor, changes on planning and scheduling decisions are very limited, although rescheduling is a common practice.
The same happens with changes in process design decisions that may not be possible or are not desirable to perform.
Despite the significant academic and industrial achievements in this area, there are relevant challenges that make the planning and scheduling decision-making particularly difficult to address.
To address that, in a previous work, we proposed a representation of R&D and manufacturing trade-offs, called Delivery Trade-offs Matrix (DTM)
At the start of a research program, products and processes have not yet been developed, and therefore there is a high uncertainty associated to the drug structure and to the production process. Uncertainty makes planning decisions more complex, since it is more difficult to estimate the required times and resources.
For example, in the development and manufacturing of APIs it is common to allocate production resources 6 to 12 months in advance.
With drug development the uncertainty tends to decrease as product and process characteristics are better understood.
The delivery of the first scaled up batch (usually between 1 to 5 kg), used to support toxicological and formulation studies, along with phase I trials, is on the critical path of the development process
This scale-up is particular difficult to perform since the knowledge obtained at the laboratory scale is seldom sufficient to guarantee a successful process at a plant scale (Federsel, 2009).
Moreover, the drug development process requires a series of scale-ups so as to develop an efficient production process.
At the commercialization stage, the need for API or drug products is normally in the order of hundreds of kilograms. The processes are well defined, thus the uncertainty is mainly associated to market parameters such as demand, and to the processing time of the complex production tasks.
The current practice demonstrates that there are large costs and high uncertainty at the R&D and trials I-III phases (see Figure 2 a), with the total estimated cost of bringing a new drug to market being larger than 1 billion dollars (Kessel, 2011).
The total cost of bringing a new drug to market is estimated to exceed 1 billion dollars (Kessel, 2011). In terms of the total cost structure, pharmaceutical R&D costs are around 30% to 35% and clinical trials (typically representing the most significant cost) can be between 35% to 40% of the total (Suresh & Basu, 2008).
Capturing all relevant sources of uncertainty in comprehensive frameworks for the supporting the planning and scheduling decision-making process is still a not solved problem. Simulation-optimization can provide interesting solution methods to combine the stochastic and deterministic parameters of the planning and scheduling problems.
Chen et al. [15] developed a simulation-optimization model for managing the entire trial supply chain, including the planning and scheduling of the Active Pharmaceutical Ingredient (API) manufacturing
Sahay, Ierapetritou [16] have applied an agent-based model hybridized with a linear programing model so as to study different supply chain decision-making policies
Eberle et al. [17] have applied a Monte-Carlo simulation so as to better estimate the production lead time of pharmaceutical processes.
Modeling the uncertainty of real world problems with optimization often results into models with a large number of variables and computationally intractable.
On the other hand, simulation can easily deal with the stochastic nature of the problems and with complicating constraints of the production systems.
Recent methods combine simulation and optimization to propose efficient solution methods.
Simulation can be used to assess solutions provided by deterministic optimization models, by considering the uncertain of the parameters, and to provide additional information to optimization models
It should be noted that from the planning and scheduling perspective, the delivery of products to Trials I-III phases is of extreme importance On the other hand, at the commercialization phase there is more flexibility concerning delivery dates, if there is inventory on the supply chain. According to Shah (2004), the whole pharmaceutical chain stock can represent 30% to 90% of the annual demand in quantity.
Therefore, at this phase, we can say that delivering the right product amounts is relatively more important than respecting delivery dates.
Remember that the production lot sizes at the Trials I-III phases are in the order of few kilograms, while after several scale-up and validation steps, the lot sizes are around hundreds of kilograms. After drug development, the manufacturing costs are lower and tend to decrease with the reduction of the root causes of variability in the production process.
Varma et al. [6] have developed a comprehensive decision-making framework called Sim-Opt for resource management that includes components for stochastic simulation, schedules generation based on a mixed integer linear programming (MILP) formulation, and evaluation of various resource strategies.
Concerning the operating mode, manufacturing sites run in short-term mode to fulfil a small product demand, or run preferably in campaign mode to respond to a regular demand.
Sometimes the short-term mode is also used for manufacturing products that are in commercialization, this naturally resulting in the production of a smaller number of lots.
However, in all cases the process must run with the same lot size as approved by the regulatory agencies.
All the above issues led the pharmaceutical industry to recognize the need for reducing time-to-market, the costs of new drug development, and the manufacturing costs.
The path to efficient R&D and manufacturing activities requires new ways to address uncertainty and reduce costs
Such path must focus on improving the reliability of the drugs delivery by dealing with the uncertainty and the associated costs and account with a heterogeneous demand
This will involve the introduction of new production technologies (Suresh & Basu, 2008), as well as the adoption of innovative process design, planning, and scheduling decision-making tools.
For example, according to Roberge et al. (2005), 50% of the reaction tasks in the chemical-pharmaceutical industry could benefit from the adoption of continuous processes based on the micro-reactor technology.
In what concerns decision-making, the relevance of applying optimization tools and deploying more integrated decision-making processes is being recognized by the industry, despite the challenges that still exist (Grossmann, 2012).
A reduced number of works propose solution methods capable of addressing mixed planning strategies