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The British Pharmacopoeia & AQbD Stephen Maddocks Principal Pharmacopoeial Scientist: Operations Manager

The British Pharmacopoeia & AQbD

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The British Pharmacopoeia & AQbDStephen Maddocks – Principal Pharmacopoeial Scientist: Operations Manager

2

Initiation &

engagement

2016201420132012 2015

MHRA Project Approved Working Party Established

Product/method

selection

Risk assesment

+ FMEA

DoE

development

DoE execution &

assessment

2017 2018

ATP/method qualification &

data analysis

2

2019 2020

MHRA Consultation on the

Application of Analytical Quality by

Design principles to public quality

standards (Pharmacopoeia).

MHRA Project timelineMHRA Project timeline

3

2020 2021+

MHRA

consultation

response

and

ongoing

Strategy

Supporting and

Enabling

Innovation

Application to

public quality

standards

Collaboration,

Engagement &

Knowledge

Transfer

The Analytical Target Profile (ATP)

Industry project collaborations

Impurity methods/related substances

Publication of AQbD Supplementary Information - BP

Publication of Atorvastatin Tablets + Pharmacopoeial Robustness

Ongoing and evolving efforts

MHRA Project timeline

4

BP Supplementary Chapter

• Title: Use of Analytical Quality by Design Concepts for analytical

procedures

• Contents:

– Introduction, Background, Application to the BP

– Quality Risk Management

– Establishment of Method Understanding

– Analytical Control Strategy

5

QRM – Risk Identification

Sample retrievedfrom store andready to weigh

Select qualified andcalibrated balance

Tare weighing boatWeigh 100mg +/-

5mgTransfer to 100 mlvolumetric flask

Wash sample intoflask with dissolving

solvent

Add approx 70mldissolving solvent

Place flask in sonicbath and sonicate

for 15 mins

Make up to the markwith dissolving

solvent

Transfer 1ml intoand HPLC vial

Stir to mixAdd 250ml of water

to containerAdd 750ml of

Acetonitrile todissolving solvent

container

Dissolving solvent

Sample solutionready for

measurment

HPLC GradeAcetonitrile

HPLC GradeWater

6

QRM – Risk Analysis/Evaluation

VariableSeverity

(1 low, 5 high)Probability of variation (1 low, 5 high)

Risk

score

% Acetonitrile in dissolving

solvent

34 12

Sonication Time (mins) 4 3 12

% Acetonitrile in the mobile

phase3 4 12

Wavelength 4 2 8

Humidity % 1 5 5

Equilibration time 1 2 2

7

Method understanding - Development

Citric AcidL H

pHL

HTetr

ah

yd

rofu

ran

L

H

Citric AcidL H

pHL

HTetr

ah

yd

rofu

ran

L

H

Acetonitrile=Low Acetonitrile=High

8

Variation in Method operating conditions

9

Method control

10

Future Publications

• The Analytical Target Profile

• User Case stories

• Introduction into compendial finished product monographs.

• Further tests, wider scope

Feedback welcome!

11

Current project - Impurities

• Analytical methods – compendial perspective

– Queries, known issues, old products

• How can AQbD Concepts help?

– Prior knowledge!

– Focussed Experimental Design

– Translation to the user?

12

The Issue

• Impurity Elution order changes

• 4 product monographs for same Active ingredient

– Nuances in each procedure

• Actual pH Vs Apparent pH – Mobile phase

• Old column technology – differences in manufacturing

process?

13

The approach – Prior Knowledge

14

The approach – Prior Knowledge

EXPERIENCE

15

The Approach - Findings

Approx pKa 5-7 (depending on model). Approx pKa 1.2, pKb 4.5

• Mobile phase pH (validated range pH 6-8).

• Stationary Phase – ODS1

16

The Approach: In -Silico

0

0.2

0.4

0.6

0.8

1

1.2

6.5 7 7.3 7.5 7.7

Rela

tive

re

ten

tio

n tim

e

Buffer pH

Effect of buffer pH on impurity D RRT

17

The Approach: In-silico

18

The Approach - Experimental

• Flexible laboratory protocol

• Silico-modelling performed alongside

• Initial review will inform experimental design.

-------------------------------------------------------------------------

• Experimental design built taking into account prior

knowledge, silico models and initial review.

19

Experimental Design

Monitoring key method attributes

• Retention time impurities and API

• Resolution of all peaks

• Theoretical plates (API)

Power of replication

• Treat columns independent of design

• Repeat entire design

• Potential modifications based on results

20

Desired outcomes

• To publish 4 high-quality, robust and easy to use monographs

• To provide additional, helpful information on method

performance to users

• To utilise good practices within our monograph investigations

• To evaluate the benefits/drawbacks of paper/laboratory based

exercises