Managing Mutagenic Impurity Risks in Pharmaceutical Products … · – Impurities can be formed...

Managing Mutagenic Impurity Risks in Pharmaceutical Products

GSK Case studies

Mike Urquhart

May 2019

Today’s presentation

– Retrospective evaluation of pre-ICH M7 GSK projects can be valuable as case studies to inform control for

potential mutagenic impurities (P)MIs

– Analytical data generally aligns to dose aligned TTC – can’t show magnitude of the “actual” purge

– Two case studies involve a low dose clinical asset and a higher dose second generation process to a marketed asset

– Scientifically based purge rationales (ICH M7 Option 4 control strategy) can be used in lieu of analytical

data:

– Can apply to (P)MIs included close to drug substance if science allows

– Demonstrates conservativism of the Teasdale purge approach

– Discussion how “available” lab data can be easily used to validate purge rationales

– Inclusion of what a regulatory submission articulating an ICH M7 mutagenic impurity control could look like

Presentation title 2

Note on Impurities

Pharma develop small molecule products to deliver benefit to the patient. It is known that the reactive

chemistry used to manufacture medicines will also produce impurities

– Impurities do not add any benefit to the patient and in some cases could cause harm i.e. mutagenic

impurities

– Impurities can be formed from degradation of drug products, both in and ex vivo, and from the manufacture

of drug product

– Metabolites can’t be considered impurities as they are intrinsic to the medicinal products performance in vivo.

– There are two basic ways of managing impurities within pharmaceutical products and these are:

1. Avoidance – change process to obviate their formation

2. Instigate appropriate controls – to ensure impurities are maintained below acceptable levels

– This presentation will discuss formation of impurities within the synthetic processes to GW641597X and

Atovaquone and how these were either avoided or controlled


Evaluation of a low dose compound – GW641597


Background

Activation of the Peroxisome Proliferator-Activated Receptor alpha (PPAR-) in animal models had been shown to

raise HDL, lower LDL and TG

PPAR- agonists were being developed for treatment of dyslipidemia and one such GSK product was GW641597X

– Anticipated maximum daily dose 600 mcg (chronic treatment)

– Dose aligned TTC as per ICH M7 is 2500 mcg per g (0.25%)

17.9 Million people die each year from cardiovascular disease (CVD)

Dyslipidemia increases risk of CVD (stroke and peripheral artery disease):• Occurs when blood lipid levels are abnormally low, or high

• Can be an increase in low density lipoprotein (LDL), plasma cholesterol and

triglycerides (TG) or decrease in high density lipoprotein (HDL)

• LDL and TG are both recognised risk factors for CVDHDL believed to play role with

reverse cholesterol transport and benefit stabilisation and regression of

atherosclerosis plaques

• Statins (Fluvastatin or Pitavastatin) are treatments but aren’t universally effective

• Cardiovascular and coronary heart disease statistics are available from the WHO and Health knowledge UK respectively

• Heart and CVD image taken from health.harvard.edu

https://www.who.int/cardiovascular_diseases/en/

https://www.healthknowledge.org.uk/public-health-textbook/disease-causation-diagnostic/2b-epidemiology-diseases-phs/chronic-diseases/coronary-heart-disease#CHD

https://www.health.harvard.edu/heart-health/a-closer-look-at-heart-disease-risk

Synthetic Flow for Phase 2 supply (route A3) and implications from GSK

Computational Toxicology Assessment for Process

Ester (P)MI-1

alerts in-silico;

(P)MI-1 Ames

positive but reactive

and soluble in

downstream process

(P)MI-4 alerts in-silico tested

negative in HTFT assay but

was not tested in Ames.

Assume Class 1 for mono-

functional alkyl chloride and

close to final product

Hydroxylamine Ames –ve

but carcinogenic in rats.

Volatile as free base and

soluble – expected to

purge in downstream

process

Mutagenic Impurity discussion

There are three materials of concern from route A3 for GW641597X which are:

– Ethyl bromoisobutyrate (P)MI-1

– Hydroxylamine hydrochloride (ADI = 23 mcg* per day)

– Alkyl chloride (P)MI-4 (10 x staged TTC for mono-functional alkyl chloride)

* J.P. Bercu et al. Reg. Tox. and Pharmacol.; 2018, 94, 172 to 182 7

From an ICH M7 perspective…

4 control strategies appropriate for mutagenic and potentially mutagenic impurities (P)MIs …

Option 1: Include a test within the API for the (P)MI with acceptance criteria at, or below, the

acceptable daily intake (ADI)

Option 2: Include a test within a SM / intermediate for the (P)MI with acceptance criteria at, or below,

the ADI

Option 3: Include a test within a SM / intermediate for the (P)MI with acceptance criteria above the ADI

which is justified with appropriate purge spiking data

Option 4: A control strategy that relies on process controls in lieu of analytical testing can be

appropriate if the process chemistry and process parameters that impact levels of

mutagenic impurities are understood

A scientific risk assessment can be used to justify (P)MI purging i.e. Purge tool *

Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk

* Teasdale A et al. (2013). Risk Assessment of Genotoxic Impurities (GTIs) in New Chemical Entities: Strategies to Demonstrate Control. Org Process Res Dev 17:221-

230.

Purge numbers and agreed Consortium Regulatory Framework†

Required purge

– Accurate number based on how much (P)MI is

present either at point of introduction, or point of last

measurement, and how much this needs to reduce in

order to achieve the required API threshold of

toxicological concern (TTC)

Predicted purge

– Hypothetical number based on knowledge / intuition

of the (P)MIs solubility, reactivity, volatility, ionisability

and physical parameter properties

– Conservative relative to “actual” purge

Purge number ratio = predicted vs required purge

– The larger the number the more confidence the

(P)MI has been purged

Measured purge

– Analytical data to show the (P)MI has purged below

a certain threshold at a given processing stage

9† Chris Barber et al.; Regulatory Toxicology and Pharmacology; 2017, 90, 22 to 28.

Select ICH M7

Option 1,2 or 3

commercial

strategy, as

appropriate

Impurity requires management as (P)MI

Determine Purge Ratio (PR) in current API route for (P)MI

Predicted purge factor for (P)MI

Purge Ratio = ------------------------------------------------

Required purge factor @TTC or PDE for (P)MI

Select ICH

M7 Option 4

commercial

strategy Yes No

Select initial ICH M7 control strategy for (P)MI during

development based on Purge Ratio. Implement recommended

supporting experimental data collection and regulatory reporting

strategies based upon guidance in Table 1

Does final data

package support

commercial ICH

M7 Option 4

strategy ?

Agreed Consortium Decision Tree / Table (Cont.)

10

If PR > 1000x If PR > 100x and <1000x If PR < 100x

Data Collection Recommendations

Collection of additional experimental data not

recommended for non-commercial or

commercial API routes to support scientific

rationale

Collection of additional non-trace experimental

data (solubility, reactivity, and volatility)

recommended for both non-commercial and

commercial . API routes to support scientific

rationale. Collection of additional trace (P)MI

analysis not necessary for non-commercial or

commercial API routes to support scientific

rationale

For non-commercial API routes,

experimentally measure (P)MI purging, including

trace (P)MI analyses as appropriate, to support

scientific rationale. Note: additional data are

expected to support an Option 4 control strategy

when (P)MI Purge Ratio <<100x. For

commercial API routes, detailed experimental

fate & purge studies are expected for all (P)MI

to support a commercial Option 4 control

strategy

Regulatory Reporting Recommendations

Report “unlikely to persist” or cumulative

predicted purge factor and Purge Ratio for non-

commercial API routes in regulatory

submissions. Replace with summary of key

elements of predicted purge factor calculations

and Purge Ratio for commercial API routes in

regulatory submissions

Report the cumulative predicted purge factor

and Purge Ratio for non-commercial API

routes in regulatory submissions. Replace with

summary of key elements of predicted purge

factor calculations, Purge Ratio, and supporting

non-trace data on purge properties for


submissions

Report summary of key elements of predicted

purge factor calculations, Purge Ratio, and

supporting non-trace & trace data for non-


submissions. Replace with complete summary

of predicted purge factor calculations, Purge

Ratio, supporting trace and non-trace fate &

purge data for commercial API routes in

regulatory submissions

† Chris Barber et al.; Regulatory Toxicology and Pharmacology; 2017, 90, 22 to 28.

A note on input levels – assessment for “Commercial” product

– (P)MI-1 is input into Stage 1a at 2.9 equivalents (1.9 eq. excess):

– Significant polymerisation of this reagent occurs and the polymeric by-product is removed via filtration

– (P)MI-1 needs to be controlled within GW641597X to 2,500 mcg per gram (based on 1.5 mcg per day with a 600 mcg daily dose):

– Required purge = excess reagent used in mcg / control of mutagen per gram = 1.9 x 106 / 0.0025 x 106 = 760

– 2.5 equivalents of hydroxylamine hydrochloride is input into the Stage 2 process (1.5 eq. excess):

– Excess required to achieve an appropriate rate of reaction and to drive the reaction to completion

– Boiling point for hydroxylamine (NH2OH) is quite low (58ºC) and solubility high therefore significant purge anticipated

– Needs to be controlled within GW641597X to 38333 mcg per g (based on 23 mcg per day with a 600 mcg daily dose)

– Required purge = 1.5 x 106 / 0.0383 x 106 = 39.1

– 1.15 equivalents of (P)MI-4 are used within the Stage 4 process (0.15 eq. excess):

– Excess required to drive the reaction to completion

– Needs to be controlled within GW641597X to 25,000 mcg per gram (15 mcg per day – as per ICH M7 Note 5 for mono-functional alkyl

chlorides):

– Required purge = 0.15 x 106 / 0.025 x 106 = 6


Purge Factor Calculation – (P)MI-1 (Required Purge = 760)

Stage Reactivity Solubility Volatility Total Rationale

1a 1 1 1 1 2.9 Equivalents used where 1 equivalent used to prepare ester 3. No isolation

and assume no additional reactivity therefore 1.9 eq. remains at the end of this

stage (conservative).

1b 1 1 1 1 No reactivity or solubility calculated from Stage 1b.

4a 10 1 1 10 Expected to react with the phenolate from 4 during Stage 4a, potential

etherification with solvent (EtOH) and polymerisation.

4b 100 10 1 1000 Will react with the aqueous base through hydrolysis, polymerisation and

potential etherification during stage 4b. (P)MI-1 is an oil and highly soluble in

the isolation solvent

5 1 10 1 10 (P)MI-1 is an oil and highly soluble in the isolation solvent.

Predicted Purge Factor 1x105

Predicted / Required Purge Ratio = 132

Collection of non-trace data required to justify an ICH M7 option 4 control

When Purge Ratios <100x

13


For non-commercial API routes, experimentally measure (P)MI purging, including trace (P)MI

analyses as appropriate, to support scientific rationale.

Note: Additional data are expected to support an Option 4 control strategy when (P)MI Purge

Ratio <<100x. For commercial API routes, detailed experimental fate & purge studies are

expected to support a commercial Option 4 control strategy.


Report summary of key elements of predicted purge factor calculations, Purge Ratio, and

supporting non-trace or trace data for non-commercial API routes in regulatory submissions.

Replace with complete summary of predicted purge factor calculations, Purge Ratio, supporting

trace and non-trace fate and purge data for commercial API routes in regulatory submissions

Option 4 possible with strong data package,

otherwise Options 1, 2, or 3 are recommended

1.01.52.02.53.03.54.04.55.05.56.06.57.07.58.08.5 ppm

14

Free data – closer inspection of “isolated” Stage 1a product

4.7 % m/m

1.01.52.02.53.03.54.04.55.05.56.06.57.07.58.08.5 ppm

Free data – closer inspection of “isolated” Stage 1b product

15

4.5 % m/m

Typical levels of (P)MI-1 observed in the Stage 1b

product are < 5.0%



4a 10 1 1 10 Expected to react with the phenolate from 4 during Stage 4a, potential

etherification with solvent (EtOH) and polymerisation.

4b 100 10 1 1000 Expected to react with the aqueous base through hydrolysis, polymerisation

and potential etherification during stage 4b. (P)MI-1 is an oil and highly soluble

in the processing solvent anticipated

5 1 10 1 10 (P)MI-1 is an oil and likely to be highly soluble in the processing solvent.


Predicted / Required Purge Ratio = 5000 (Option 4)

(P)MI-1 “unlikely to persist”?

– (P)MI-1 was determined as typically being present within the Stage 1b product 4 at approx. 5% (50,000 mcg)

– Required purge (from stage 1b product) = 50,000 / 2500 = 20

Purge Factor Calculation – Hydroxylamine (Required Purge = 39)


2 1 10 1 10 2.5 Equivalents used in Stage 2 – anticipate 1 equivalent would react.

Hydroxylamine anticipated to be highly soluble in the isolation solvent (aq.

EtOH). Volatility during isolation and drying expected but not included within

the prediction

3 100 10 1 1000 Expected to react with chloroacetyl chloride. Anticipated solubility in the

extraction process (aqueous acid). Volatility during “put and take” drying

process expected but not included within the prediction

4 100 10 1 1000 Would react with (P)MI-4 and be soluble within isolation solvents (aq. EtOH)

Volatility during isolation and drying expected but not included within the

prediction

5 1 10 1 10 Anticipated solubility within the crystallisation / isolation solvent (EtOH and

MeOH).

Volatility during isolation and drying expected but not included within the

prediction


Predicted / Required Purge Ratio = 2.56 x 106 (Option 4)

NH2OH “unlikely to persist”

NH2OH

Observations on reactivity of (P)MI-4

Impurities from use of NaOEt and NaOH hydrolysis of the alkyl chloride – neither a mutagenic concern but

affects yield with a potential to affect purity. Levels of 6 and 2% for ether 8 and alcohol 9 typically observed

from the Stage 5 process:

18



4a 1 1 1 1 1 eq reacts with phenolate from 4 which has been reflected in starting

equivalents. Anticipated reactivity to form ether 8 and hydrolysis product 9 –

not included in the prediction

4b 10 10 1 100 Excess (P)MI-4 anticipated to react to form ether 8, hydrolysis product 9 and

symmetrical ether 15. Anticipated to be soluble within isolation solvents ( aq.

EtOH)

5 1 10 1 10 Solubility expected within the crystallisation / isolation solvent (EtOH and

MeOH).

Predicted Purge Factor 1000

Predicted / Required Purge Ratio = 167

Collection of non-trace data required to justify an ICH M7 Option 4 control

1.01.52.02.53.03.54.04.55.05.56.06.57.07.58.08.5 ppm

Free data – NMR of GW641597 (DMSO-d6, Stage 4b product)

20

Not observed0.2 % m/m

1.01.52.02.53.03.54.04.55.05.56.06.57.07.58.08.5 ppm

Free data – NMR of GW641597 (CDCl3, Stage 5 product) to confirm absence of

(P)MI-1 and (P)MI-4

21

Not observedNot observed

Synthetic Route A3 to GW641597X

What to submit within a late phase regulatory submission?

23

Impurity Point of Potential Formation / Introduction and Summary of Rationale for Impurity PurgingRequired Purge &

Predicted PurgeControl

Starting material in Stage 1a (2.9 eq.), 4 steps from DS

Consumed to low level (<5%) in stage 1b; reactive during processing (Stage 4); soluble in isolation

solvents (Stages 4 and 5)

Required Purge = 20

Predicted Purge = 1.0 x 105

Purge ratio = 5000

Option 4 - Controlled through chemical

reactivity and physical processing.

NH2OHReagent in Stage 2 (2.5 eq.), 4 steps from DS

Reactive during processing (Stages 2, 3 and 4), highly soluble in isolation solvents (Stages 2, 3, 4

and 5)

Required Purge = 39


Purge ratio = 2.56 x 106



Starting material in stage 4, 2 steps from DS

Confirmed at low level (c. 0.2%) within Stage 4b product following additional reactivity with aqueous

base used within the process and solubility within the isolation solvent. Additional solubility

anticipated in Stage 5 isolation solvent

Required Purge = 6

Predicted Purge =1000

Purge ratio = 167

Measured purge = 75 (Stage 4b)

Measured purge ≥ 150 (Stage 4b

and 5)



Route also assessed using Mirabilis in silico software

Evaluation of a high dose compound – GR151218X


Background

– Atovaquone (GR151218X) used to treat malaria (Malarone – tablets, since 1992) and

PCP infections in HIV / AIDS patients (Mepron – suspension since 1999):

– Mepron has treated approximately 2.5 million patients

– Maximum daily dose 1.5 g (Mepron) up to one month

– Dose aligned TTC as per ICH M7 is 80 mcg per g (0.008%)

– Second generation route** developed by GSK (2009-2012):

– Retrospective assessment versus requirements of ICH M7 conducted

About 214 million people suffer from malaria each year

90% malaria cases occur in Sub-Saharan Africa

Over 480,000 people die from malaria each year, mostly

children under 5 years old*

* Malaria statistics from Unicef

** M. Urquhart et al. “Discovery and Development of an Efficient Process to Atovaquone”; Organic Process Research and Development; 2012, 16 (10), pp 1607–1617.

https://data.unicef.org/wp-content/uploads/2015/09/Achieving_the_Malaria_MDG_Target.pdf

From an ICH M7 perspective…

– Retrospective assessment of marketed assets not required

– Post approval changes warrant a re-assessment of safety relative to mutagenic impurities

– Changes need to be assessed as per ICH M7…

“Post-approval submissions involving the drug substance chemistry, manufacturing, and controls should

include an evaluation of the potential risk impact associated with mutagenic impurities from changes to the

route of synthesis, reagents, solvents, or process conditions after the starting material. Specifically, changes

should be evaluated to determine if the changes result in any new mutagenic impurities or higher acceptance

criteria for existing mutagenic impurities”

Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk

Synthetic Flow (route C1) and implications from GSK Computational

Toxicology Assessment for Process

(P)MI-2 and (P)MI-3 alert in

silico - highly susceptible to

hydrolysis

Q Strategy – do they need

to be Ames tested if there is

a strong purge rationale ?

Bromoalkanes

alerted in-

silico; (P)MI-1

Ames

negative

Non-isolated aldehyde

alerted in-silico (non-

mutagenic toxicity)

confirmed Ames negative

Product alerted in-silico

(non-mutagenic toxicity)

confirmed Ames negative

EHS Worker Safety

Positive in MLA

Product did not

alert (Derek /

Leadscope)

EHS Worker

Safety

Ames positive†

Negative in

MLA and rat

micronucleus

† S. Araya, E. Lovsin-Barle and S. Glowienke; Regul. Toxicol. Pharmacol.; 2015 Nov., 73, 215 to 220

Purge Factor Calculation – (P)MI-2 (Required Purge = 1.25x104)


2b 100 10 1 1000 Not detected in isolated Int-2 (<0.05%) and expected to be soluble in the

predominantly organic isolation solvents

3c 100 10 1 1000 Expected to react with water during work up isolation and soluble in isolation

solvents (ethyl acetate / AcOH and IPA cake wash)

4 100 10 1 1000 Expected to react with water during work-up and soluble in the predominantly

organic isolation solvents

5 100 10 1 1000 Expected to react with potassium hydroxide / water during processing and

soluble in the predominantly organic isolation solvents.


Predicted / Required Purge Ratio = 8 x 107 (Option 4)

(P)MI-2 “unlikely to persist”



3b 100 1 1 100 Consumed to low level (<1%) in Rosenmund chemistry (Stage 3b)

3c 100 10 1 1000 Would react with isobutylamine (Stage 3c) and during cake washing (Stage 3c

– IPA)

Anticipated to be soluble in work-up solvent (AcOH and IPA)

4 100 10 1 1000 Reacts with sodium methoxide and methanol as well as with water during

work-up. Anticipated to be soluble in work-up solvent (Methanol and AcOH).

5 100 10 1 1000 Reacts with potassium hydroxide and methanol as well as with water during

processing. Anticipated to be soluble in work-up solvent (Methanol and AcOH).


Predicted / Required Purge Ratio = 8 x 106 (Option 4)


Purge Factor Calculation – Int-2 (Required Purge = 1.25x104)


3c 10 10 1 100 Consumed to low level in aldol condensation (Stage 3c) and soluble in isolation

solvent.

4 100 10 1 1000 Int-2 demonstrates base instability so anticipated to react with the sodium

methoxide in stage 4 and soluble in isolation solvent.

5 100 10 1 1000 Int-2 demonstrates base instability therefore anticipated to react with potassium

hydroxide and anticipated to be soluble within isolation solvents.


Predicted / Required Purge Ratio = 8000 (Option 4)

Int-2 “unlikely to persist”

(Development work conducted pre-ICH M7 – (P)MI control to 1.5 mcg per day required in 2012)



4 100 1 1 100 Consumed to low levels in methoxide mediated rearrangement to prepare

crude atovaquone (Stage 4)

5 100 1 1 100 (P)MI-5 unstable to base therefore anticipated to react with potassium

hydroxide and methanol as well as with water during processing.


Predicted / Required Purge Ratio = 0.8 (Informs Option 1)

When Purge Ratios <100x

32


For non-commercial API routes, experimentally measure (P)MI purging, including trace (P)MI

analyses as appropriate, to support scientific rationale.

Note: Additional data are expected to support an Option 4 control strategy when (P)MI Purge

Ratio <<100x. For commercial API routes, detailed experimental fate & purge studies are

expected to support a commercial Option 4 control strategy.


Report summary of key elements of predicted purge factor calculations, Purge Ratio, and

supporting non-trace or trace data for non-commercial API routes in regulatory submissions.

Replace with complete summary of predicted purge factor calculations, Purge Ratio, supporting

trace and non-trace fate and purge data for commercial API routes in regulatory submissions

Option 4 possible with strong data package,

otherwise Options 1, 2, or 3 are recommended

Experimental observations

1,4-Isochromandione (Int-2)

– Starting material in Stage 3c

– Consumed to low levels in the Stage 4 preparation of (P)MI-5 (typical levels are 0.2% area)

– Decomposition during Stages 4 and 5 (Base instability)

– Int-2 not observed in stage 4 product (method LOQ < 0.05% area by HPLC UV)

Vinyl ketone (P)MI-5

– Starting material in Stage 4

– Consumed during Stage 4 (LOQ < 0.03% w/w by NMR)

– Complete degradation to non-alerting acid / acetal (Int-3) when exposed to stage 5 conditions

Use of Selective excitation NMR to analyse Int-2 in DS to 1 mcg per g

– Trace NMR technique (selective excitation) developed:

– Method to determine 1 mcg per g level of Int-2 within DS validated

– Batches of Stage 4 IG GR151218X were analysed:

– Lab prepared Stage 4 product (IG GR151218X)

– Lab prepared Stage 4 product where 10 mol % (4.7% by weight) Int-2 spiked into the Stage 4 process

– Predicted purge for Int-2 within the stage 4 process was 1000 therefore:

– 2 mcg per g should be present in standard lab batch (based on < 0.2% in (P)MI-5 reducing to <0.0002% in IG GR151218X)

– 47 mcg per g should be present in spiked batch (based on 4.7% in (P)MI-5 reducing to <0.0047% in IG GR151218X)

– Both batches of stage 4 GR151218X were confirmed to have < 1 mcg per g Int-2:

– Measured purge for standard batch for stage 4 alone is > 2000

– Measured purge for spiked batch for stage 4 alone is > 47000

– Predicted purge is more conservative than measured and no risk for residual Int-2 being present within DS:

– Levels of Int-2 are controlled to << 30% of the dose aligned TTC by stage 4 (80 mcg per g)

– Additional purge predicted within stage 5 (1000)

Visualisation of the results

– 700 MHz selective-excitation 1H NMR spectra of two

batches of atovaquone, “standard” and “spiked” and

corresponding 1 mcg / g recovery samples

– The Signal to Noise (S/N) ratio for the Int-2 signal in the

recovery samples was 25:1, well above the S/N criterion

for the limit of detection (LOD) (4:1)

– ‘x’ indicates trace-level impurities other than Int-2

a

b

X

X

X

X

Int-2

c

d

X

X

X

X

X

X

X

X

X

XX

Int-2

Spiked batch of atovaquone

Spiked batch of atovaquone

1 ppm Int-2 recovery sample

Standard lab batch of atovaquone

Standard lab batch of atovaquone

1 ppm Int-2 recovery sample

Int-2

X X

Purge Factor Calculation – Int-2 (Required Purge = 1.25x104)

Stage Reactivity Solubility Volatility Total Measured Rationale

3c 10 10 1 100 500 Consumed to low level in aldol condensation (10 to 15%) and

further removed during isolation (Stage 3c – 0.2%)

4 100 10 1 1000 47000 Int-2 demonstrates base instability so anticipated to react with the

sodium methoxide in stage 4. Spiking and trace 1H NMR

experiment confirms measured purge

5 100 10 1 1000 Int-2 demonstrates base instability therefore anticipated to react

with potassium hydroxide and anticipated to be soluble within

isolation solvents.

Predicted Purge Factor (Stages 3c to 5)

Measured Purge Factor (Stages 3c and 4)

1 x 108

2.3x107

Predicted / Required Purge Ratio = 8000 (Informs Option 4)

Measured / Required Purge Ratio = 1880 (Confirms Option 4)

Int-2 “unlikely to persist”

Confirmatory NMR data for (P)MI-5 purging

– A less sensitive NMR method was also developed for (P)MI-5 in GR151218X drug substance

– A spike of 10 mol % (P)MI-5 was input into the stage 5 recrystallization:

– (P)MI-5 was confirmed as < 300 ppm by NMR (not detected and LOD is 0.03 w/w%) therefore measured purge for Stage 5 = 333

compared to 100 for predicted

– Given that (P)MI-5 has been shown to be routinely observed at <0.03% (w/w) in stage 4 product (IG GR151218X) then the

above spiking information informs control to 0.9 mcg per g which is << 30% of the dose aligned TTC (80 mcg per g)

– Measured / Required purge ratio > 88.9 therefore ICH M7 Option 4 control strategy is appropriate

1H NMR – (P)MI-5 Spiked into GR151218X IG at 0.03%w/w

Presentation title38

6.06.57.07.58.0 ppm

8.5 8.0 7.5 7.0 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 ppm

(P)MI-5 spiked into GR151218X at 0.03% w/w

(P)MI-5 in GR151218X after being spiked into stage 5 at 10% w/w


Stag

eReactivity Solubility Volatility Total Measured Rationale

4 100 1 1 100 3333 Consumed to low levels (routinely <0.03%) in methoxide

mediated rearrangement to prepare crude atovaquone (Stage 4)

5 100 1 1 100 333 (P)MI-5 unstable to base therefore anticipated to react with

potassium hydroxide and methanol as well as with water during

processing. Spiking and trace 1H NMR experiment confirms

measured purge

Predicted Purge Factor

Measured Purge Factor

1x104

1.1x106

Predicted / Required Purge Ratio = 0.8 (Informs Option 1)

Measured / Required Purge Ratio = 88.9 (Informs Option 4)


Synthetic Flow sheet, Route C1

What to disclose within a regulatory submission?

41

Impurity Point of Potential Formation / Introduction and Summary of Rationale for Impurity PurgingRequired Purge &

Predicted PurgeControl

Non isolated intermediate in Stage 2a, 4 steps from DS

Consumed to low level in stage 2b; reactive during processing (Stages 3c, 4 and 5); soluble in

isolation solvents (Stages 3c, 4 and 5)

Required Purge = 1.25 x 104


Purge ratio = 8 x 107



Non isolated intermediate in Stage 3b, 4 steps from DS

Consumed to low level in stage 3b; reactive during processing (Stages 3c, 4 and 5); soluble in

isolation solvents (Stages 3c, 4 and 5)



Purge ratio = 8 x 106



Starting material in Stage 3c, 3 steps from DS

Reactive during processing (Stage 3c, 4 and 5); soluble in isolation solvents (Stage 3c, 4 and 5)



Purge ratio = 8,000



Starting material in stage 4, 2 steps from DS

Consumed to low level within Stage 4; reactive during processing (Stage 5); soluble in isolation

solvents (Stages 4 and 5)

Measured Purge justification

Routinely observed at <0.03% in isolated stage 4 product providing a purge of > 3,333 (from

1,000,000 / 300)

Spiking confirms that 10% in stage 4 starting material would reduce to <0.03% within the stage 5

product providing a purge for that stage of >333 (from 100,000 / 300)

Total measured purge = 3,333 x 333 = 1.1 x 106


Predicted Purge = 1 x 104

Purge ratio = 0.8

Measured Purge = 1.1 x106

Measured / Required purge ratio =

88.9



Conclusions

✓ Process understanding and optimisation is the key to

impurity avoidance / control

✓ An ICH M7 Option 4 approach can be appropriate

even where purging predictions are less strong if

accompanying scientific rationale to confirm purging is

robust

✓ Non trace analytical data very useful to justify ICH M7

purge rationales

✓ The Teasdale approach for predicting (P)MI purging is

conservative

Acknowledgements

Chemistry Bernie Choudary, Steve Etridge,

Steve Moore, Mike Sasse, Steve Smith, Neil

Stevenson, Nick Wooster

Analytical Fiona King, Claire Lesurf, Clare

McKinley, Robert Reid

Spectroscopy Ben Bardsley, Andy Edwards,

Tran Pham, Andy Roberts, Alec Simpson

Computational Toxicology Amanda Giddings,

Jim Harvey, Angela White

Occupational Toxicology William Hawkins

Lhasa for opportunity to present today

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Insights from Managing Mutagenicity Risks in Pharmaceutical Products – GSK Case studies

GSK Case studies

Back-up slides


Use of Mirabilis for Purge Assessments

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Benefits of Mirabilis over existing paper approaches

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Standardisation

– Mirabilis helps avoid errors by providing standardised approach

– Harmonises industry best practices

Clarity

– Mirabilis provides a detailed report with full explanation – easily connects to regulatory submission

– Enhanced transparency to build trust with regulators

– Mirabilis uses same scoring approach as paper-based approach, ensuring conservatism is retained

Science-based

– All users access the same peer-reviewed knowledge

– Combined knowledge across Pharma will provide a greater understanding

Innovative

– Mirabilis developed and being refined through collaborative efforts within the consortium

– Aligns with expert systems used across a range of applications

Mirabilis – Headline from using the in silico tool

GSK is part of the Lhasa Mirabilis Pharmaceutical consortium and we used the Mirabilis in silico tool to

evaluate the purging for this synthetic route.

Mirabilis is very simple to use (route assessed within 1 to 1.5 h). Some observations:

– System recognises some reaction types, impurity classes and assigns reactivity:

– Allows for predictions to be made based on supporting data within knowledge base

– Automatically works out the required purge

– Predicted reactivity for (P)MI-4 within stages 4 and 5

– Under predicts compared to observed experimental purge which confirms conservative nature of the system

– Can revert to manual input where recognition is unsuccessful

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Managing Mutagenic Impurity Risks in Pharmaceutical Products … · – Impurities can be formed...

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