ICH Q3D: Practical implementation and the role of ... Q3D - Practical... · ICH Q3D: Practical implementation and the role of excipient data in a risk based approach Dr Andrew Teasdale

ICH Q3D: Practical implementation and the role of excipient data in a risk based

approach

Dr Andrew Teasdale [email protected]

Overview – areas covered

• Why share data?

• What data already exists? How can

this be augmented?

• What’s the strategic intent of the

database?• Contributing data to the database /

current status • Vision for how the database could be

used to facilitate risk assessments

Why Share Data? • ICH Q3D is predicated on the evaluation of risk,

this is made of 3 factors

• RISK = PROBABILITY x Severity x Detectability

• We know the severity – Defined PDEs.

• We have detectability – ICP / XRF

• DATA – either newly generated or Historical data

informs us as to the probability.

• Sharing data thus allows us to make informed

judgement during the IDENTIFY and EVALUATE

PHASES

Why Share Data?

• Q3D itself comments specifically on this:

• SECTION 5 - Information for this risk assessment includes but is not limited to:

data generated by the applicant, information supplied by drug substance and/or

excipient manufacturers and/or data available in published literature.

• SECTION 5.5. The data that support this risk assessment can come from a

number of sources that include, but are not limited to:• Prior knowledge;

• Published literature;

• Data generated from similar processes;

• Supplier information or data;

• Testing of the components of the drug product;

• Testing of the drug product.

What data already exists? How can this be augmented?

• Container Closure Systems

THEORETICAL RISK • Especially in the case of liquid formulations there is risk of metals leaching

out of CCS into the formulation

• WHAT DOES THE DATA SAY?

Materials in Manufacturing and Packaging Systems as Sources of Elemental Impurities in Packaged Drug Products: A Literature Review PDA J Pharm Sci TechnolJanuary/February 2015 69:1-48;

Section 5.3 – Probability of elemental leaching into solid dosage forms is minimal and does not require further consideration in the risk assessment

http://www.google.co.uk/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRw&url=http://www.toxikon.be/services/EandL_Parenteral_injectables.cfm&ei=CKD9VJ-FNMuBPabSgLAE&bvm=bv.87611401,d.d2s&psig=AFQjCNGQvyFG1USDfp7zu6cgy28dg5B1_A&ust=1425994112173701



Why Share Data?

• Q3D Case Studies –

use of ‘first principles’

approach based on

existing data

exemplified.

What data already exists ? How can this be augmented?

EXCIPIENT STUDIES • Study involved:

– Some 200+ samples– Examined 24 elements

SUMMARY OF RESULTS

• Little evidence of substantial levels of even the ‘big 4/Class 1’ (ubiquitous?) in mined excipients

– Pb seen in TiO2 but levels <10ppm, variability not significant.– Pb also seen in Zn Stearate.– Cd levels in Magnesium hydroxide / Calcium carbonate exceed

Option 1 limits – levels need to fail to an option 2 limit before serious concern

• THIS IS 200 SAMPLES – WHAT IF WE COULD COLLATE DATA FROM 2000+ SAMPLES ?

What data already exists? How can this be augmented?

• The data to be shared is the analytical

data generated to establish the levels

of trace metals within batches of

excipients used in the manufacture of

pharmaceuticals.

• Potential to facilitate more scientifically

driven elemental impurities risk

assessments and reduce

unnecessary testing as part of the

elemental impurities risk assessment

efforts.

Data = Knowledge

More data = More Knowledge

What’s the strategic intent of the database?

• Become the primary source of EI data for excipients

that drives initial risk assessment (c.f. the Jenke paper

for packaging components & EIs)

• Publish key findings with the intention of de-risking

commonly used excipients

• Compare / contrast with data published generated by FDA.

Building the database

• How has the database been built?

How much data is in it?

• Lhasa designed and developed

the Elemental Impurities database

based on Vitic NexusTM platform

• Approved by the consortium in

December 2015

• Initial round of donations was received beginning of 2016

• The database was first released at the end of March 2016

• The Elementals database

v2016.1.0 contains the following

number of records:

• 52 records in the Excipient table.

• 123 records in the Elementals

table.

• V2016.2.0 just released now

contains

• 157 excipients• 757 result records


• Procedure/process for organizations to share their in-house data

• Template defined to allow error free parsing of data.

• Data anonymised and checked by Lhasa Limited.


• Data quality requirements

• Extensive discussions

relating to data requirements

• Validation protocol generated

• Extent of Validation recorded + Digestion Conditions

• No difference between data

donated and data published

in peer review journal in

terms of vindication of data

Sub Class A Sub class BCompare a matrix matched blank to your lowest standard, making sure there is no significant contribution compared to your lowest standard

Compare a matrix matched blank to your lowest standard, making sure there is no significant contribution compared to your lowest standard

Minimum 5 point calibration R = >0.995 ~ >R2 = 0.990

Minimum 3 point calibration R = >0.990 ~ >R2 = 0.980

Minimum of 2 spikes one at the top and one at the bottom of the quantitative liner range spike recoveries are between 70-150%

Minimum of 1 spike within the quantitative liner range spike recoveries are between 50-150%

Governed by Accuracy and Range data. Governed by Accuracy and Range data.6 replicate aspirations of a standard or spiked sample either together or taken throughout the analysis giving %RSD ≤ 20% or spike sample or standard tested at the start and end of the run give the same measurement ± 20% or a 5 point calibration gives an R value of ≥0.995

6 replicate aspirations of a standard or spiked sample either together or taken throughout the analysis giving %RSD ≤ 20% or sample tested at the start and end of the run give the same measurement ±30% or a 5 point calibration gives an R value of ≥0.990

Minimum N=3 replicate spikes within the “Range” of the method, The spikes can be at the same level or different levels where the response factors give ≤20% RSD

Minimum of 2 spikes one at the top and one at the bottom of the quantitative liner range spike recoveries are between 50-150%

As long as test solutions and spikes are prepared within 24 hours of each other solution stability is assumed as long as all other parameters are met.

As long as test solutions and linearity standards are prepared within 48 hours of each other solution stability is assumed as long as all other parameters are met.

Equivalent concentration in ug/g in sample of your lowest spike

Equivalent concentration in ug/g in sample of your lowest standard

Equivalent concentration in ug/g in sample of your lowest and highest spike

Equivalent concentration in ug/g in sample of your lowest and highest standard

Estimate LOD by taking the Std Dev of 6 blank measurements, multiplying by 3.3 and dividing this by the slope of your calibration line.

Estimate LOD by taking the Std Dev of 6 blank measurements, multiplying by 3.3 and dividing this by the slope of your calibration line.

Building a Database

• Is all of the data for lactose and how will sufficient

diversity of materials and suppliers be managed?

• The content of the database will be actively managed

• Clear commitment from members to generate data if gaps are identified

ListNo CarlMrozListName Total1 Magnesium stearate 232 Microcrystalline cellulose 413 Lactose 324 Starch 145 Cellulose derivatives 186 Sucrose 97 Povidone 158 Stearic acid 39 Dibasic calcium phosphate 18

10 Polyethylene glycol 6

0

5

10

15

20

25

30

35

40

45

1 2 3 4 5 6 7 8 9 10

Num

ber o

f res

ults

How is use of the database envisioned?

• At EMA meeting in April – EFPIA presented a series of

Case Studies

Oral Solid DoseSeveral Excipients used in the formulated product. What data are available?

Number of materialsFDA External DB Internal

Lactose 6 3

Hypromellose 2910 6 (not defined as

2910)

8

MCC 14 6

Crospovidone 17 (povidone)

3

Magnesium Stearate 1 7 9

Titanium Dioxide 7

Blue Aluminium Lake #1 1

Blue Aluminium Lake #2

Note – Lactose is the main excipient – others <10%

Dat

abas

e sh

ould

con

tain

sub

stan

tivel

y m

ore

data

for c

omm

on e

xcip

ient

s

Component Functionality Amount per 400 mg tablet (mg)

% in coated tablet

Type (Excipient)

Core

API Drug substance 400.00 62.64

Hypromellose 2910 Binder 21.70 3.40 PlantMicrocrystalline Cellulose

Diluent 37.20 5.83 Plant

Lactose Monohydrate

Diluent 111.50 17.46 Animal

Crospovidone Disintegrant 43.40 6.79 SyntheticMagnesium stearate

Lubricant 6.20 0.97 Mineral

Coating Hypromellose 2910 Film-former 11.16 1.75 PlantTitanium dioxide Pigment 5.55 0.87 MineralTriacetin Plasticiser 1.49 0.23 SyntheticBlue Aluminium Lake #2

Colorant 0.37 0.06 Mineral


Colorant 0.03 0.005 Mineral

Excipient dataMaximum level seen (ppm)

Number of materials As Cd Hg Pb V Ni Co

FDA Extern DB

Intern FDA Extern DB







Intern

Lactose 6 3 <0.23 <0.03 <0.08 ND <0.5 ND <0.08 ND <2 ND <3 ND <0.8 ND

Hypromellose 2910

6 8 0 <0.03 0 <0.1 0 <0.3 0.01 <0.1 0.02 ND 0.64 2.09 0.01 <1

MCC 14 6 <1.0 ND <0.2 ND <0.5 ND <0.2 <0.1 <2 ND <3 <1 <0.8 ND0.2 (actual

number above LOQ)

Crospovidone 17 3 0.02 ND 0 ND 0 ND 0.06 ND 0.02 ND 0.1 ND 0.1 ND

Magnesium Stearate

1 7 9 0.02 <0.23 0.09 0 <0.2 <0.1 0 <0.5 <0.3 0.01 <0.2 <0.1 0 <2 1.7 0.16 <5 1.5 0 <0.8 <1

0.5 (actual number

above LOQ)

Titanium Dioxide 7 0.36 0.07 0.04 5.74 5.95 0.48 0.04


1 0 0.01 0.03 0.03 0.26 1.58 0.01

Excipient data – Reflection on significance

• No appreciable traces of Class 1 or

Class 2a elements in low risk

excipients

• Lactose• Povidone• MCC

• Mg Stearate – Ni seen at 1.5ppm

• NB less than 1% of the formulation

• Titanium dioxide

• 6ppm Pb / 6ppm V

Is this significant?

Component Functionality Amount per 400 mg tablet (mg)

% in coated tablet

Type (Excipient)

Core

API Drug substance

400.00 62.64 Hypromellose 2910 Binder 21.70 3.40 Plant

Microcrystalline Cellulose

Diluent

37.20 5.83 Plant

Lactose Monohydrate Diluent

111.50 17.46 Animal Crospovidone Disintegrant 43.40 6.79 Synthetic

Magnesium stearate Lubricant

6.20 0.97 MineralCoating Hypromellose 2910 Film-former 11.16 1.75 PlantTitanium dioxide Pigment 5.55 0.87 MineralTriacetin Plasticiser 1.49 0.23 Synthetic


Colorant

0.37 0.06 Mineral


Colorant

0.03 0.005 Mineral

Excipient data – Reflection on significance

Component CategoryQuantity (mg/form)

Dose "x" form(mg/day)

Arsenic in component ug/g

As ug in daily dose of formulation

Lead in component ug/g

Pb ug in daily dose of formulation

Mercury in component ug/g

Hg ug in daily dose of formulation

Cadmium in component ug/g

Cd ug in daily dose of formulation

Vanadium in component ug/g

V ug in daily dose of formulation

Cobalt in component ug/g

Co ug in daily dose of formulation

Nickel in component ug/g

Ni ug in daily dose of formulation

x = 1 TotalBio Acc Total Bio Acc Total

Bio Acc Total Bio Acc Total

Bio Acc Total Bio AccTotal


Bio Acc Total

Bio Acc Total


Bio Acc Total Bio Acc

Dosage Form :

Active Synthetic 400 400 0.00 0.00 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Hypomellose Synthetic 32.9 32.9 0.03 0.00 0.00 0.1 0.00 0.00 0.30 0.01 0.00 0.10 0.00 0.00 0.03 0.00 0.00 1.00 0.03 0.00 2.09 0.07 0.00

MCC Plant derived 37.2 37.2 1.00 0.04 0.00 0.2 0.01 0.00 0.50 0.02 0.00 0.20 0.01 0.00 2.00 0.07 0.00 0.80 0.03 0.00 3.00 0.11 0.00

Lactose Animal 112 112 0.23 0.03 0.00 0.1 0.01 0.00 0.50 0.06 0.00 0.08 0.01 0.00 2.00 0.22 0.00 0.80 0.09 0.00 3.00 0.34 0.00

Crospovidone Synthetic 43.4 43.4 0.02 0.00 0.00 0.1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.10 0.00 0.00 0.10 0.00 0.00

TiO2 Mineral 5.5 5.5 0.36 0.00 0.00 5.9 0.03 0.00 0.04 0.00 0.00 0.07 0.00 0.00 5.95 0.03 0.00 0.04 0.00 0.00 0.48 0.00 0.00

Mg Stearate Mineral 6.2 6.2 0.23 0.00 0.00 0.2 0.00 0.00 0.50 0.00 0.00 0.20 0.00 0.00 1.70 0.01 0.00 1.00 0.01 0.00 1.50 0.01 0.00

Al Lake 1 Mineral 3 3 0.00 0.00 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00

Triacetin Synthetic 1.5 1.5 0.00 0.00 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Al Lake 2 Mineral 0.3 0.3 0.00 0.00 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Total Dosage Formweight 642 642

Total element As 0.07 0.00 Pb 0.06 0.00 Hg 0.09 0.00 Cd 0.02 0.00 V 0.34 0.00 Co 0.16 0.00 Ni 0.53 0.00

Permissible Limits As Pb Hg Cd V Co Ni

Formulation Q3D Q3D Q3D Q3D Q3D Q3D Q3D

Oral PDE 15 5.0 30 5 100 50 200

Parenteral PDE 15 5.0 3 2 10 5 20

inhaled PDE 2 5.0 1 2 1 3 5

Based on data from database all predicted to be ~1% or less of PDE

Challenges to using first principles

The data set is limited! - True but plan to develop a critical mass.

• Mined excipients will always show variability - Potentially true.

Component CategoryQuantity

(mg/form)

Dose "x" form

(mg/day)

Arsenic in component

ug/g

As ug in daily dose of

formulationLead in

component ug/g

Pb ug in daily dose of

formulation

x = 1 Total Bio Acc Total Bio Acc Total Bio Acc Total Bio Acc

Dosage Form :

Active Synthetic 400 400 0.00 0.00 0.00 0.0 0.00 0.00

Hypomellose Synthetic 32.9 32.9 0.03 0.00 0.00 0.1 0.00 0.00

MCC Plant derived 37.2 37.2 1.00 0.04 0.00 0.2 0.01 0.00

Lactose Animal 112 112 0.23 0.03 0.00 0.1 0.01 0.00

Crospovidone Synthetic 43.4 43.4 0.02 0.00 0.00 0.1 0.00 0.00

TiO2 Mineral 5.5 5.5 0.36 0.00 0.00 1000.0 5.50 0.00

Mg Stearate Mineral 6.2 6.2 0.23 0.00 0.00 0.2 0.00 0.00

Al Lake 1 Mineral 3 3 0.00 0.00 0.00 0.0 0.00 0.00

Triacetin Synthetic 1.5 1.5 0.00 0.00 0.00 0.0 0.00 0.00

Al Lake 2 Mineral 0.3 0.3 0.00 0.00 0.00 0.0 0.00 0.00

Total Dosage Formweight 642 642

Total element As 0.07 0.00 Pb 5.52 0.00

How much impact would this have in the case of an excipient such as TiO2?

1000ppm Pb / Hg?• Pb overall just

exceeded

RISK = PROBABILITY x Severity x Detectability

So what can we learn from the database? 1 1 1 1 2A 2A 2A

Cd Pb As Hg Co V NiMAGNESIUM STEARATE

Max 0.20 0.20 1.00 0.50 0.80 2.00 5.00Min 0.02 0.05 0.02 0.01 0.03 0.01 0.14

Mean 0.08 0.10 0.25 0.13 0.19 0.57 1.32MICROCRYSTALLINE

CELLULOSEMax 0.20 0.20 1.00 0.50 0.80 2.00 3.00Min 0.003 0.01 0.02 0.01 0.02 0.01 0.03

Mean 0.04 0.07 0.19 0.11 0.18 0.43 0.68LACTOSE

Max 0.20 0.21 0.23 0.50 0.80 2.00 3.00Min 0.003 0.04 0.01 0.01 0.03 0.01 0.03

Mean 0.07 0.08 0.11 0.12 0.15 0.33 0.47STARCH

Max 0.10 0.10 0.20 0.10 0.10 0.15 0.30Min 0.02 0.05 0.02 0.01 0.03 0.01 0.03

Mean 0.03 0.07 0.14 0.04 0.06 0.11 0.21CELLULOSE DERIVATIVES

Max 0.20 0.20 0.20 0.20 0.20 0.56 1.04Min 0.02 0.02 0.02 0.01 0.01 0.01 0.09

Mean 0.05 0.08 0.11 0.05 0.07 0.16 0.34

Option1 Oral 0.5 0.5 1.5 3 5 10 20Option1 Oral 30% 0.15 0.15 0.45 0.9 1.5 3 6

v2016.2.0 just released

now contains

• 157 excipients

• 757 result records

• Examination of Top

5 excipients

Levels uniformly low sensible to apply 30% limit on top of Option 1?

So what can we learn from the database?

• What about

common mined

excipients?

• E.g. calcium phosphate

1 1 1 1 2A 2A 2ACd Pb As Hg Co V Ni

ANHYDROUS DIBASIC CALCIUM PHOSPHATEMax 0.20 0.20 1.00 0.20 0.60 10.00 21.84Min 0.05 0.10 0.10 0.01 0.07 0.04 0.27

Mean 0.11 0.16 0.38 0.08 0.31 2.06 7.72DIBASIC SODIUM PHOSPHATE

Max 0.20 0.20 0.41 10.00 0.20 0.20 3.06Min 0.004 0.01 0.10 0.003 0.03 0.01 0.05

Mean 0.04 0.07 0.17 1.46 0.08 0.08 0.72DIBASIC CALCIUM PHOSPHATE DIHYDRATE

Max 0.04 0.27 0.37 0.02 0.51 0.02 15.97Min 0.04 0.10 0.20 0.01 0.34 0.01 13.47

Mean 0.04 0.21 0.28 0.01 0.41 0.01 14.52SODIUM CHLORIDE

Max 0.20 0.20 0.20 0.20 1.00 0.20 1.00Min 0.01 0.01 0.05 0.05 0.01 0.05 0.04

Mean 0.05 0.10 0.08 0.13 0.15 0.09 0.17

Option1Oral 0.5 0.5 1.5 3 5 10 20Option1Oral30% 0.15 0.15 0.45 0.9 1.5 3 6

• Couple of examples where level exceeds Option 1 limit.

• Ni in anhydrous calcium phosphate• Mercury in Sodium phosphate • UNLIKELY TO ULTIMATELY TO POSE A RISK

Pharmacopoeial notifications – element specific testing

KEEP

• Current tests provide valuable data

that can be used as part of the risk

assessment.

• Removing such tests may mean no

data.

• Replacing tests with ICP could drive

new limits.

• The limits are quality as well as

safety limits.

• DELETE

• Specific testing to specific limits is

inconsistent with Q3D

• These tests are ineffective and

inefficient.

Pharmacopoeial notifications – element specific testing

Calcium Phosphate

• Common Filler

• Monograph recently revised

• Tests for 3 elements

1. Arsenic (2.4.2, Method A): maximum 10 ppm, determined on 2 mL of solution S. i.e. a wet chemistry limit test.

2. Barium. To 0.5 g, add 10 mL of water R and heat to boiling. While stirring, add 1 mL ofhydrochloric acid R dropwise. Allow to cool and filter if necessary. Add 2 mL of a 10 g/L solution ofdipotassium sulfate R and allow to stand for 10 min. No turbidity is produced. i.e. a Turbidity test

3. Iron (2.4.9): maximum 400 ppm. Dilute 0.5 mL of solution S to 10 mL with water R. i.e. another we chemistry limit test

Three separate tests for 3 metals – not really very efficient. Are these tests informative? Do they add value?

Pharmacopoeial element specific testing

SUBST_ID SUPPLIER Co Os V Rh Ru Pd Pb Ni Fe Mn Sb Li Cu Cr Ba Mo Tl Hg Cd As

Anhydrous dibasic calcium phosphate XA0081 0.60 LLOQ 0.07 0.06 LLOQ 0.29 0.18 21.8 1145 81.2 0.68 LLOQ 0.45 1.54 5.39 2.26 LLOQ 0.01 0.08 0.42Anhydrous dibasic calcium phosphate XA0010 0.4 Not tested 1.5 Not tested Not tested LLOQ LLOQ 1 Not

testedNot tested

Not tested Not tested Not tested Not tested Not tested

Not tested Not tested LLOQ LLOQ LLOQ

Anhydrous dibasic calcium phosphate XA0011 0.4 Not tested LLOQ Not tested Not tested LLOQ 0.2 1 Not tested

Not tested



Anhydrous dibasic calcium phosphate XA0478 0.36 LLOQ 0.06 0.04 LLOQ 0.22 0.14 13.5 604.0 75.0 0.68 LLOQ LLOQ 1.49 3.6 2.23 LLOQ LLOQ 0.07 0.25Anhydrous dibasic calcium phosphate XA0476 0.60 LLOQ 0.04 0.06 LLOQ 0.29 0.10 20.6 860.2 79.5 LLOQ LLOQ LLOQ 1.40 4.8 1.68 LLOQ LLOQ 0.08 0.35Anhydrous dibasic calcium phosphate XA0477 0.59 LLOQ 0.06 0.05 LLOQ 0.28 0.17 21.8 1145.2 76.9 0.237 LLOQ 0.448 1.54 5.4 1.83 LLOQ LLOQ 0.08 0.30Anhydrous dibasic calcium phosphate SW0172 Not

detectedNot tested 1.7 Not

detectedNot detected

Not detected

0.18 1.00 Not tested

Not tested

Not detected

Not detected

Not detected

Not detected

7.7 Not detected

Not detected

Not detected

0.07 Not detected

Anhydrous dibasic calcium phosphate XA0010 Not detected

Not tested 1.8 Not detected

Not detected

Not detected

0.17 0.9 Not tested

Not tested

Not detected

Not detected

Not detected

Not detected

8 Not detected

Not detected

Not detected

0.08 Not detected

Anhydrous dibasic calcium phosphate SW0174 Not detected

Not tested 0.8 Not detected

Not detected

Not detected

0.18 0.9 Not tested

Not tested

Not detected

Not detected

Not detected

Not detected

Not detected

Not detected

Not detected

Not detected

0.05 Not detected

Anhydrous dibasic calcium phosphate QW0356 LLOQ Not tested 5.7 Not tested Not tested Not tested LLOQ 2.03 Not tested

Not tested


Not tested Not tested LLOQ LLOQ 0.18

Anhydrous dibasic calcium phosphate BX0760 LLOQ Not tested LLOQ Not tested Not tested Not tested 0.1 0.27 Not tested

Not tested



Dibasic calcium phosphate dihydrate XA0079 0.51 LLOQ 0.02 0.04 LLOQ 0.18 0.27 16.0 1665 37 0.35 LLOQ LLOQ 0.99 LLOQ 0.19 LLOQ 0.018 0.04 0.37Dibasic calcium phosphate dihydrate XA0481 0.40 LLOQ 0.01 0.02 LLOQ 0.17 0.23 15.5 891 31 LLOQ LLOQ LLOQ 0.81 LLOQ 0.19 LLOQ LLOQ 0.04 0.37Dibasic calcium phosphate dihydrate XA0482 0.43 LLOQ LLOQ LLOQ LLOQ 0.14 0.10 13.9 1338 26 0.29 LLOQ LLOQ 0.95 LLOQ LLOQ LLOQ LLOQ 0.04 0.20Dibasic calcium phosphate dihydrate XA0484 0.43 LLOQ LLOQ LLOQ LLOQ 0.14 0.10 13.9 1338 26 0.29 LLOQ LLOQ 0.95 LLOQ LLOQ LLOQ LLOQ 0.04 0.20Dibasic calcium phosphate dihydrate XA0479 0.34 LLOQ 0.02 0.04 LLOQ 0.18 0.26 13.5 719 37 0.35 LLOQ LLOQ 0.65 LLOQ 0.16 LLOQ 0.018 0.04 0.24Dibasic calcium phosphate dihydrate XA0483 0.34 LLOQ 0.02 0.04 LLOQ 0.18 0.26 13.5 719 37 0.35 LLOQ LLOQ 0.65 LLOQ 0.16 LLOQ 0.018 0.04 0.24Dibasic calcium phosphate dihydrate XA0480 0.40 LLOQ 0.01 0.022 LLOQ 0.17 0.23 15.5 891 31 LLOQ LLOQ LLOQ 0.81 LLOQ 0.19 LLOQ LLOQ 0.04 0.37

Pharmacopoeial element specific testing

• As limit test – data from database shows although detected in some batches levels <1ppm

• Barium – levels <10ppm (Limits shown below). Set against these limits what value does this test provide?

• Perhaps the most interesting of all!

• Iron – limit 400ppm yet data derived from ICP shows that levels > 400ppm limit. Is this test therefore meaningful?

Conclusions• The feasibility of sharing excipient elemental impurity data has been

successfully demonstrated

• Pooling and publishing data can surely help to improve the ease with which risk assessments can be completed

• Ultimately it will give a much better picture of which materials represent a more significant risk than others

• Indicate where the risk is real & where it is negligible

• Reduce the amount of testing that is needed to be done moving forward to support implementation

• We typically expect that the EI database to be seen as key supportiveinformation that is used routinely in conjunction with some product specific test data in the risk assessment.

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ICH Q3D: Practical implementation and the role of ... Q3D - Practical... · ICH Q3D: Practical implementation and the role of excipient data in a risk based approach Dr Andrew Teasdale