Design Of Experiments For Formulation Chemists

2y ago
24 Views
2 Downloads
1.76 MB
47 Pages
Last View : 22d ago
Last Download : 2m ago
Upload by : Lilly Andre
Transcription

Introduces Design of Experiments for FormulatorsiFormulate Webinar12th July 2018

This webinar is beingrecorded and will bemade availableThe audience is mutedand you may askquestions using thequestion function inGoToWebinarThis webinar will lastaround 45 minutesPROGRAMME Introductions Design of Experiments forFormulation Benefits of using DoE Case study supporting QbD– Blending for formulation Training Course in Design ofExperiments Q&A

INTRODUCTIONS

Your SpeakersDr David CalvertiFormulate LtdDavid@iformulate.bizDr Paul MurrayPMCC Ltdpaul.murray@catalysisconsulting.co.uk

A Little About iFormulate A company founded in 2012 by two experienced industryprofessionals Combining diverse experiences, knowledge and wide range ofcontacts: polymers, materials science, chemistry, imaging, dyes,pigments, emulsion polymerisation, biocides, anticounterfeiting, environmental, formulation, consultancy,marketing, business development, strategy, regulatory,training, events, R&D, innovation Complementary network of Associateswww.iformulate.bizinfo@iformulate.bizDr Jim BullockE: jim@iformulate.bizM: 44 (0)7450 436515Dr David CalvertE: david@iformulate.bizM: 44 (0)7860 519582

Our Services

Design of Experiments forFormulation ChemistsDr Paul MurrayDesign of Experiments forFormulatorsWebinar, July 2018

Introduction Design of Experiments for formulation Benefits of using DoE Case study supporting QbD Blending for formulation

Traditional Approach Starts from a route Finds a process Perhaps struggles to understand itProcessRoute

DoE for Process Understanding Starts from a Route Understands the factors that affect the chemistry Designs a process on the basis of knowledgeProcess within designspaceRouteProcess Understanding

Design of Experiments (DoE) DoE, Statistical Experimental Design or FED (Factorial) DoE is an efficient, structured way to investigatepotentially significant factors and their cause-and-effectrelationships on an experimental outcome Careful factor selection increases the chances ofextracting useful information which factors to change the range of the variation DoE provides information about the way the totalsystem works Utilises statistical methods to extract and interpret therelationships between the factors Paul Murray Catalysis Consulting Ltd11

So development of a formulation Formulation Tablet, capsule, liquid, Bulking agent Caking agent Slipping agent For tableting Speed, pressure For liquids Solvents, additives Paul Murray Catalysis Consulting Ltd12

So Formulation processesFactorsResponsesActive ingredientBinderSlip agentBulking agentDisintegrantSurfactantFormulation equipmentFormulation typeDiscreteFormulant RatiosParticle sizeActive concentrationCompression forceTemperatureSpray pattern/rateMixingContinuous13 Paul Murray Catalysis Consulting LtdDissolution timeDissolution profileTablet strengthHumidity stabilityActive IngredientStability

Formulation processes Options for dosage forms: tablets, ointments,capsules, suspensions, gels Generally a separate design required for each type Granulation Particle size, amount of binder, mixing, drying Tableting Compression force, tableting speed, tablet size Tablet coating Paul Murray Catalysis Consulting Ltd14

OVATOne Variable at a Time Paul Murray Catalysis Consulting Ltd15

ConcentrationOne Variable at a Time (OVAT)Temp Consider the performance of areaction in relation to twofactors – concentration and temp16

ConcentrationOne Variable at a Time (OVAT)Temp From an arbitrary chosen starting point onefactor is varied17

ConcentrationOne Variable at a Time (OVAT)Temp18

ConcentrationOne Variable at a Time (OVAT)Temp An artificial ‘local’ optimum is identified19

ConcentrationOne Variable at a Time (OVAT)40%30%20%10% conversionTemp An artificial ‘local’ optimum is identified Paul Murray Catalysis Consulting Ltd20

ConcentrationOne Variable at a Time (OVAT)10% conversion20%30%40%Temp An artificial ‘local’ optimum is identified21

One Variable at a Time (OVAT) The genuine optimum may be missed the experimental approach may make it impossible to find! Inefficient use of resources better conditions are available 11 experiments carried out Limited coverage of chemical space (design space) No information of dependency of one parameter onanother interactions No measure of inherent variability experimental error Paul Murray Catalysis Consulting Ltd22

ConcentrationDoE: Screening Design10% conversion20%30%40%Temp Paul Murray Catalysis Consulting Ltd23

ConcentrationDoE: Optimisation60%50%40%30%20% conversionTemp Paul Murray Catalysis Consulting Ltd24

What will DoE do for you? A well-performed experiment will provide answers toquestions such as: What are the key variables/factors in a process? At what settings would the process deliver acceptableperformance? What are the key main and interaction effects in the process? What settings would bring about less variation in the output? Does the supplier or quality of a material effect the process? Paul Murray Catalysis Consulting Ltd25

What will DoE do for you? A good experimental design will: Avoid systematic error Be precise Allow estimation of error To provide confidence interval and significance of the results Have broad validity Paul Murray Catalysis Consulting Ltd26

DoEDesigning Experiments – Improving Answers Paul Murray Catalysis Consulting Ltd27

The Experimental Design Process The validity of an experiment is directly affected byits construction and execution Attention to the design of the experimental isextremely important Paul Murray Catalysis Consulting Ltd28

The DoE Process1. Aim &Objective8. Validatepredictions2. Factors &Ranges7. Modeldata3. Response6. Checkresults4. Selectdesign5. Carry out& analyse Paul Murray Catalysis Consulting Ltd29

The DoE Process1. Aim & 2.Objective9. Validatepredictions3. Factors& Ranges8. Modeldata4. Response7. Checkresults5. Selectdesign6. Carryout &analyse30

Identify Factors Consider all steps in the process Order of additionEquipmentReagents, additivesRates of heating, cooling, mixing Grades of material Paul Murray Catalysis Consulting Ltd31

Selecting Responses Maximise information from experimental data enough of the right type of data is available Responses should give accurate and consistent resultsclosely replicate actual experimental outcomeminimise variability between repeatsmeasure change as close to the event as possible even minimal work-up as can lead to additional error vary more than the ‘noise’ of the measurement area as aresult of the changes Paul Murray Catalysis Consulting Ltd32

Design SelectionFractional designto investigate allpotential factorsFurther experimentaldesign(s) focusing onchemical space ofinterestQuadratic design fordetailed reaction orprocess modellingConfirmation ofunderstandingacross entireoperating range Paul Murray Catalysis Consulting Ltd33

Mixture Designs Ideal for formulation Look at factors as a fraction of whole Analyse response against both mixture and processfactors simultaneously Uses D-optimal design Paul Murray Catalysis Consulting Ltd34

Benefits of mixture design A key deliverable is amount of active in a fixedweight/volume Mixture design allows everything to be varied whilefixing the final weight/volume This would be very hard to achieve with all otherdesign types as factors are completely separatefrom each other and therefore dose weight/volumewould vary considerably All at low would give very low weight/volume and viceversa Paul Murray Catalysis Consulting Ltd35

Mixture vs Factorial designs36 Paul Murray Catalysis Consulting Ltd

Case Study: blending parameters Quality Risk Assessment (QRA) on a tabletingprocess shows Active Pharmaceutical Ingredient(API) particle size, moisture control, blending andlubrication steps have the potential to affect theassay and content uniformity critical qualityattributes (CQAs) A study of the parameters likely to affect blendingwas conducted to develop a design space Paul Murray Catalysis Consulting Ltd37

DoE for blending: factors &ranges Factors investigated Blender typeRotation speedBlending timeAPI particle size Purpose: to assure that the blend is uniform Analysed by NIR, target uniformity of 0.01 Perform DoE to develop the design space Paul Murray Catalysis Consulting Ltd38

DoE: Select and perform designExp 01030301010303020202020v typev typev typev typedrumdrumdrumdrumv typedrumv 0150.0040.0050.0040.00450.0050.00550.0051 Paul Murray Catalysis Consulting Ltd39

Overview plot Paul Murray Catalysis Consulting Ltd40

Interaction, Ble*rpm Paul Murray Catalysis Consulting Ltd41

Contour plotOptimum conditions: 30 rpm, 11 min blending time foruniformity of 0.0025 Paul Murray Catalysis Consulting Ltd42

DoE Summary Particle size and blender type are insignificant Model explains 99% and predicts 98% of the data Squared term required, additional experimentsrecommended to define squared term Uniformity of 0.01 required levels as low as 0.0025 are predicted to be possible If you wanted to achieve 0.0025 uniformity, anotherexperiment can be carried out to confirm theconditions Paul Murray Catalysis Consulting Ltd43

DoE Summary Model identifies the important factors Model identifies setting for important factors Model requires quadratic and interaction terms DoE does this efficiently (12 experiments, additionalexperiments required to validate model) Paul Murray Catalysis Consulting Ltd44

Summary DoE is a powerful tool You need to avoid the pitfalls Incorrect factor selectionInvestigation of appropriate rangesInappropriate or inaccurate responsesValidate the model by carrying out the prediction A good DoE will give you much more information fora fraction of the work Paul Murray Catalysis Consulting Ltd45

Design of Experiments for Formulators New two day training course December 4th and 5th 2018 East Midlands UK Early Bird 995 plus VAT before 1st October 1149 plus VAT after More details and registration rmulators/ Paul Murray Catalysis Consulting Ltd46

Thanks for listening Any questions Paul Murray 44 7833 384027 paul.murray@catalysisconsulting.co.uk www.catalysisconsulting.co.uk David Calvert 44 7860 519582 David@iformulate.biz www.iformulate.biz Paul Murray Catalysis Consulting Ltd47

Design of Experiments (DoE) DoE, Statistical Experimental Design or FED (Factorial) DoE is an efficient, structured way to investigate potentially significant factors and their cause-and-effect relationships on an experimental outcome Careful factor selection increases the chances

Related Documents:

Bruksanvisning för bilstereo . Bruksanvisning for bilstereo . Instrukcja obsługi samochodowego odtwarzacza stereo . Operating Instructions for Car Stereo . 610-104 . SV . Bruksanvisning i original

10 tips och tricks för att lyckas med ert sap-projekt 20 SAPSANYTT 2/2015 De flesta projektledare känner säkert till Cobb’s paradox. Martin Cobb verkade som CIO för sekretariatet för Treasury Board of Canada 1995 då han ställde frågan

service i Norge och Finland drivs inom ramen för ett enskilt företag (NRK. 1 och Yleisradio), fin ns det i Sverige tre: Ett för tv (Sveriges Television , SVT ), ett för radio (Sveriges Radio , SR ) och ett för utbildnings program (Sveriges Utbildningsradio, UR, vilket till följd av sin begränsade storlek inte återfinns bland de 25 största

Hotell För hotell anges de tre klasserna A/B, C och D. Det betyder att den "normala" standarden C är acceptabel men att motiven för en högre standard är starka. Ljudklass C motsvarar de tidigare normkraven för hotell, ljudklass A/B motsvarar kraven för moderna hotell med hög standard och ljudklass D kan användas vid

LÄS NOGGRANT FÖLJANDE VILLKOR FÖR APPLE DEVELOPER PROGRAM LICENCE . Apple Developer Program License Agreement Syfte Du vill använda Apple-mjukvara (enligt definitionen nedan) för att utveckla en eller flera Applikationer (enligt definitionen nedan) för Apple-märkta produkter. . Applikationer som utvecklas för iOS-produkter, Apple .

och krav. Maskinerna skriver ut upp till fyra tum breda etiketter med direkt termoteknik och termotransferteknik och är lämpliga för en lång rad användningsområden på vertikala marknader. TD-seriens professionella etikettskrivare för . skrivbordet. Brothers nya avancerade 4-tums etikettskrivare för skrivbordet är effektiva och enkla att

Den kanadensiska språkvetaren Jim Cummins har visat i sin forskning från år 1979 att det kan ta 1 till 3 år för att lära sig ett vardagsspråk och mellan 5 till 7 år för att behärska ett akademiskt språk.4 Han införde två begrepp för att beskriva elevernas språkliga kompetens: BI

**Godkänd av MAN för upp till 120 000 km och Mercedes Benz, Volvo och Renault för upp till 100 000 km i enlighet med deras specifikationer. Faktiskt oljebyte beror på motortyp, körförhållanden, servicehistorik, OBD och bränslekvalitet. Se alltid tillverkarens instruktionsbok. Art.Nr. 159CAC Art.Nr. 159CAA Art.Nr. 159CAB Art.Nr. 217B1B