proposal for a manufacturing classification system (mcs) · pdf fileproposal for a...

Proposal for a Manufacturing

Classification System (MCS)

Michael Leane, BMS

Gavin Reynolds, AZ

APS Manufacturing Classification System Working Group

1

Kendal Pitt, GSK

IFPAC January 2015

Biopharmaceutics Classification System (BCS)

I

High Permeability

High Solubility

II

High Permeability

Low Solubility

III

Low Permeability

High Solubility

IV

Low Permeability

Low Solubility

High

Lo

w

Pe

rme

ability

• BCS is a scientific framework for classifying drugs based on their solubility

and permeability. When combined with the in vitro dissolution

characteristics of the drug product, the BCS takes into account: solubility,

intestinal permeability, (and dissolution rate), all of which govern the rate and

extent of oral drug absorption from IR solid oral-dosage forms.

Amidon GL, Pharm. Res., 12 (3), 1995. - Guidance for industry, Waiver of In Vivo Bioavailability and Bioequivalence Studies for Immediate Release Solid Oral Dosage Forms Based on a Biopharmaceutics Classification System. August 2000, CDER/FDA.

MCS: Why have one?

• Borrowing from BCS, use properties of particles to form a new

classification to aid drug product manufacturing.

• Defines the “right particles” and “best process”.

• Assist in particle engineering to provide targets for API

properties.

• Aid development and subsequent transfer to manufacturing.

• Provide a common understanding of risk.

• Fits with QbD principles. Potential of obtaining regulatory relief

by demonstrating that the properties of the ingoing API and

excipients are within established ranges for the process.

‘Difficult’ API

“Good” API

APS Joint Focus Group Meeting

BCS to MCS: From the particle to drug product: Predictions

from Material Science through to manufacturing

May 13th and 14th 2013, East Midlands Conference Centre, University of Nottingham, UK.

• Mat Sci and PEFDM focus groups

MCS: Initial discussions

. .

MCS Based on Processing Route

• Class I Direct compression.

• Class II: Dry Granulation,

• Class III: Wet Granulation,

• Class IV: Other Technologies.

• Assumes there is a preference for simpler manufacturing routes.

• Builds on prior knowledge e.g. Hancock’s direct compression criteria could form the foundation of MCS Class I.

• Ultimate aim of prediction from previous experience.

MCS Based on Processing Route

Direct compression

Dry Granulation

Wet granulation

Procedure

• Working group assembled comprising members from industry and academia.

• Subteams established to determine current best practice for DC, RC and WG.

• Short-term aim: Publish a peer-reviewed white paper to:

– Summarise current knowledge and provide a frame of reference of level of risk vs process type.

– Publicise this initiative to gain feedback from the wider pharmaceutical community

Logic Flow used

• Define general API properties for progression as a DC, RC or WG formulation “Developability”

• API considerations specific to:

– DC

– RC

– WG

• API considerations for specialised manufacturing processes:

– reserved for materials which cannot be processed using the first three conventional routes.

• Concept of “Percolation Threshold”

• Link to Risk Analysis for a compound.

White Paper

• Industry and academic collaboration • International contributions • Feedback questionnaire rolled out

Best guess at ideal DC properties 2004

Still relevant 10 years on?

SEDEM Expert System

Uses 12 tests to determine if a powder is suitable for direct compression.

• Broad guidelines based on current knowledge using

material properties to classify manufacturing risk

• As progression is made through the first three categories,

the dependence on initial API properties is reduced

• A key challenge is to avoid complexity caused by

considering the full range of properties and potential

interactions.

Which properties are best?

Ideal properties of an API for consideration as a DC, RC or WG solid dosage form

Property Value Source

Melting point >90 0C Merck Indx Ibuprofen mp 760C

Contact angle Water <900 Usual accepted deg of wetting

Hygroscopicity <1% over amb temp Idealised

Stability > 2years at room temp Idealised

Shape Aspect ratio 1:1:1 Idealised

Particle size 10 to 500 microns Idealised

Bulk density > 0.3g/cc Efficiency of equipment fill

Dose number <250ml BCS classification system

Projected Dose <50 ngt 100mg Stepnan AF et al (2011)

The probability of success greater the more of the above DEVELOPABILITY criteria that are met.

Class 4: Other Technologies

Active film coating2 LDT system for low dose API1

Resource Planning: If portfolio contains a lot of Class 4s will need increased effort, external manufacture etc.

1http://www.ddfevent.com/pdf/MartinRichardson&MarkWilson.pdf 2http://www.slideshare.net/elfoxy99/design-space-presentation. RA Lipper PAT QBD Workshop Sep-11-2006

API drug loading

• No absolute limit on what drug loading is suitable.

• Both high or low Drug loading will impact formulation performance.

• Rationalise likely impact in terms of percolation level.

• Assume that API will only impact dosage form bulk properties above percolation level.

• In practice, a risk zones approach might be best.

• Green Zone: < 20% drug loading.

• Amber: Between 20% and 50-60%.

• Red: Greater than 50-60%.

Visualisation: Radar Charts

Example representation; Best is nearest the bulls eye!

Capping and in-filling No issues

Powder flow, variable density and dissolution Capping in film coater

• Risk analysis score based on relevant API

properties and drug product target attributes (link to

TPP) . Overall score used to identify appropriate manufacturing methods

Risk Analysis

Parallel Co-ordinates Charts

UK Pharm Sci 2014 (Hatfield UK): EU input

AAPS 2014 + Webinar (San Diego) Global input

IFPAC 2015 (Washington DC) 25-28 Jan 2015: Regulatory Input

FIP 2015 (Dusseldorf) 28 Sept -3rd Oct 2015 Concluding Summary

Pre-competitive data sharing? Precedents in other areas.

Events for Input

Electronic Inputs

• Comments please plus volunteers for data gathering!

• At forthcoming meetings.

• By use of E-mail Address : MCS@apsgb.org

• Via Survey Monkey

• https://www.surveymonkey.com/s/57GGL8K

Abstract: next steps

“ This paper is intended to stimulate contribution from a broad range of stakeholders to develop the MCS concept further and apply it to practice. In particular, opinions are sought on what API properties are important when selecting or modifying materials to enable an efficient and robust pharmaceutical manufacturing process.”

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Key phrases

1. More data on input API .

centralized database?

2. Additional data subdivision of the developability space

3. Target material profiles would inform API optimization

4. Surrogate materials.

5. Modeling tools for predicting formulation

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Survey

“Others”

• Dose Number

• Chemical Stability

• Tap Bulk density

• Flow

• Particle Strength

• Yield stress

29

Selected comments from survey

• Will be useful as a first indicator/guide to material and process selection

• To work out boundaries for formulation properties may choose DC, if they knew how far away they were from an 'edge of failure'.

• Can help in evaluating dossiers for registration • Increase level of confidence in selected process • Develop common language for risk assessment • Why a route would not work!

Selected comments from survey

• Who should be involved: Generic companies, excipient manufacturers, regulators, equipment manufacturers.

• Further work on the boundaries for DC, RC, WG, including on the suggested 20% percolation threshold

• Prepare fishbone diagram.

Acknowledgements

• Michael Leane (BMS) • Gavin Reynolds (AZ) • Jamshed Anwar (Lancaster

Uni) • Stuart Charlton (BMS) • Abina Crean (SSPSC, Cork) • Richard Creekmore (AZ) • Conrad Davies (Pfizer) • Tomas DeBeer (Ghent Uni) • Marcel De-Matas (AZ) • Abdenour Djemai (GSK) • Dionysius Douroumis (Uni of

Greenwich) • Simon Gaisford (UCL)

• John Gamble (BMS)

• Linda Hakes (UCB)

• Bruno Hancock (Pfizer)

• Elaine Harrop Stone (Merlin)

• Anne Kavanagh (AZ)

• Yarolsav Khimyak (Uni of East Anglia)

• Peter Kleinebudde (Heinrich-Heine Uni)

• Chris Moreton (FinnBrit Consulting)

• Amrit Paudel (RCPE)

• Richard Storey (AZ)

• Mike Tobyn (BMS)

• Gregor Toschkoff (RCPE)

• Kiren Vyas (GSK)

• Morten Allesø (Lundbeck)

Comments / Questions

Survey Questions

• What API properties are important when selecting or modifying materials to enable an efficient and robust pharmaceutical manufacturing process?

• Do you think an MCS would assist you and why?

Survey Questions • What next steps do you think the MCS

working group should take: – Pre-competitive sharing of API properties

– Setting up boundaries for DC, RC, WG, OT

– Identifying surrogate materials to represent the different zones

– Using modelling tools to link API properties to manufacturing performance

– Others?

Recent comments After IFPAC: take into account regulatory feedback. Outline of the next paper. Submit by end of 2015? It will contain the parameters we currently have: size, shape, surface area,

wettability, compactibility, drug loading. We need to discuss why each of these parameters is in there. Size, shape

and surface are linked and could be merged. Think about sharing data: how could this be accomplished. Honest broker to house data: any candidates? Data analysis? What should the output be? Similar to BCS? A decision tree? Some

other tool?

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Drug loading and percolation concept

• As drug-loading of a formulation increases, the physical properties of

the API become more important for the manufacturability.

• The level at which an API can impact is referred to as the percolation

threshold

• Unfavourable API properties may still be accommodated by a simpler

process by using a low-drug loading formulation

Leuenberger, Adv. Pow. Tech., 1999