physical stability of an amorphous spray dried dispersion · amorphous solid dispersions (asd) 3...
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Physical Stability of an Amorphous Spray Dried Dispersion
Graeme Horne
SOS 2019 Amsterdam
14 & 15 October 2019
Marketed 30%, Development 60-70%
Marketed 35%, Development 5-10%
Solubilising the Insoluble
14 & 15 October 2019
SOS 2019 Amsterdam
2
Enabling The Drug Development Process
BCS
II
BCS
IV
BCS
III
BCS
I
solubility
pe
rme
ab
ility
BCS I
BCS II
BCS III
BCS IV
Marketed 25%, Development 5-10%
Marketed 10%, Development 10-20%
cost
co
mp
lexity
• Rate and extent of oral absorption governed
by solubility, dissolution rate, permeability
• Enabling technologies can be utilised to
overcome barriers to bioavailability
• Approaches include: crystal modifications,
lipidic delivery, particle size reduction,
amorphization
• Shifting trend to develop drugs that have low solubility and/or low permeability
Pharmaceutics 2017, 9, 50
Amorphous Solid Dispersions (ASD)
3
Stabilising the Unstable
Time
Dru
g C
on
ce
ntr
ati
on
Crystalline Drug
Amorphous Drug
Amorphous
Dispersion
• Most Active Pharmaceutical Ingredients (APIs) are crystalline materials possessing long-range
order and well-defined structures with stability, solubility and bioavailability (BA) related to the
crystalline form
• Amorphous materials do not have long-range order but exhibit short-range order
Crystalline
Ordered
Stable
Low solubility
Amorphous
Disordered
Unstable
High solubility
Amorphous Dispersion
Disordered, Stabilised
High & Sustained
Solubilitypolymer
API
ASDs in Drug Discovery
• Offer greater physical/chemical stability relative to
the amorphous form
• Improve dissolution and extend lumenal
supersaturation
• Enhance extent of oral absorption compared with
crystalline materials
• Can reduce the effects of pH and food on absorption
14 & 15 October 2019
SOS 2019 AmsterdamJ.Pharm.Sci. 2009, 98, 2549–2572
Commercialised Amorphous Dispersions
4
A growing trend
• Growing interest in the technology: ca. 4000 scientific articles since 1974; 2000 since 2014
• Amorphous dispersions have successfully been applied at late stage and in marketed products
to increase solubilisation and oral bioavailability of BCS class II/IV compounds
Routes to commercial manufacture:
• Spray Drying, HME, Microprecipitation, Spray Coating, Solvent Impregnation
Product API Company BCS Polymer
Cesamet Nabilone Valeant 2 / 4 PVP
Incivek Telaprevir Vertex 2 / 4 HPMCAS
Intelence Etravirine Janssen 4 HPMC
Kalydeco Ivacaftor Vertex 2 / 4 HMPCAS
Kaletra Lopinavir & Ritonavir AbbVie 2 & 4 PVP VA
Norvir Ritanovir AbbVie 4 PVP VA
Prograf Tacrolimus Astellas 2 HPMC
Sporanox Itraconazole Janssen 2 HPMC
Onmel Itraconazole Stiefel 2 HPMC
Xtandi Enzalutamide Astellas 2 HPMCAS
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Amorphous Solid Dispersions
5
The Physical Stability Challenge
• Physical stability of ASDs is often raised as a significant obstacle to development and
commercialization
• Physical degradation often controlled by molecular mobility in the solid state and is
restricted at temperature and humidity conditions below the Tg
• Crystallization can occur throughout process, supply and shelf-life and can have an
adverse impact on product quality, performance, and safety
Crystalline
API
Crystallization
Homogenous Dispersion Crystallized Dispersion
• Predicting the physical stability of amorphous dispersions is key when assessing
developability and viability for clinical candidates
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Manufacturing Amorphous Spray Dried Dispersions (SDD)Assessing the Physical Stability Risk
API, Polymer
Solvent
Solution
Tank
Atomiser
Drying
Chamber
Product
CollectionSecondary
Drying
Storage /
Supply
Finished
Product
Downstream
Processing
Supersaturation
Process time
and condition
Wet SDD
(%RS)
Drying temperature
and duration
Dosage form &
process train
Packaging, duration, condition
Packaging,
condition,
In-use
• Manufacture of SDDs involves mixing the drug and polymer in a suitable solvent
• Polymer stabilises the amorphous form and can inhibit crystallization
• Process, storage, supply can all impact physical stability
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Case Study:Physical Stability Modelling of a Spray Dried Amorphous Solid Dispersion
Clinical and Pharmaceutical Background
Indication
• Variation in GI motility and malabsorption
• Fed patients equivalent to fasted NHVs
8
Drug Profile
Property Result
BCS II
MW < 250
LogP > 4
MP < 175 °C
Solubility
(Biorelevant)Practically insoluble
Polymorphism 4 + amorphous
Tg < 30 °C
• Paediatric chronic condition
• Aqueous suspension of crystalline SMT-API progressed into Phase 1 studies (NHV & patient)
• Low MW, low Tg result in high mobility and propensity to crystallize
• Reformulation necessary to maximise exposure and enable full exploration of
therapeutic effect
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Reformulation
• 25% w/w SMT-API SDD progressed into
Phase 1 studies in NHVs and patients to
assess safety and PK:
• Safe and well tolerated
• > Six-fold increase in patient plasma
levels of SMT-API relative to
suspension formulation @ 40% of
dose
• Higher exposure with the SDD
allowed for further exploration of
therapeutic effect
• SDD entered Phase 2 study in parallel
to optimising the formulation ahead of
potential commercial use
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Maximising the Exposure Profile Through Amorphization
0
50
100
150
200
250
300
350
400
Ave
rag
e C
max
(ng
/mL
)Crystalline Amorphous
Patient Exposure
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Optimising the SDD
• Processing challenges to scaled manufacture necessitated refinement of the 25%
SDD formulation to one that is scalable yet meets the needs of the Target Product
Profile (TPP)
• Impact of process, polymer and drug loading on SDD stability (physical/chemical)
and performance assessed
• Output would identify the SDD with the profile aligned with the TPP
• 15% loaded HPMCAS SDD identified as preferred dispersion
• low miscibility of SMT-API in polymer & low MW, low Tg of SMT-API necessitate low
loading
• Manufacturing and processing viability
• Equivalent in vitro and in vivo profile to the clinical 25% SDD
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Addressing Manufacturability and Stability
Can we model the physical stability of the nominated SDD to de-risk the program?
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Accelerated Stability Programs
• Science and risk-based prediction with many stability applications to clinical development:
• API salt / polymorphic forms, ranking prototype formulations, process development (API /
DP), packaging and excursion evaluation, retest / shelf-life prediction, etc…
• Multiple storage conditions with varying temperature and humidity (open dish typically
used)
• Conditions tailored to the drug based on physical and chemical stability
• Model ideally verified using real time data
However:
• Primary use: modelling and prediction of small molecule chemical degradation
• Limited reports on application to physical degradation (e.g. amorphous to crystalline)
Two approaches considered:
• Model rate of crystallisation as a function of Tg/T (accounts for humidity)
• Model rate of crystallisation using humidity modified Arrhenius equation (accounts for
moisture uptake with packaging)
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General Principles and Applications
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Selecting the Stability Conditions
• %RH needs to be taken into consideration when selecting accelerated conditions for
amorphous products
• Moisture can depress Tg: increases molecular mobility and crystallization potential
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Tg vs. %RH
Conditions Timepoints (hr)
40°C/75%RH 5, 24, 72, 168, 208, 504
50°C/75%RH 3,5, 20, 44, 72
60°C/29%RH 5, 24, 72, 168, 208, 504
70°C/9%RH 5, 24, 72, 168, 208, 504
70°C/0%RH 8, 24, 75, 168, 336
80°C/0%RH 1, 3, 8, 24, 75
90°C/0%RH 1, 3, 8
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Modelling the Physical Stability of the SDD
SDD: SDDs manufactured at 15% w/w loading of SMT-API with HPMCAS-M as the
polymer carrier. Manufacture was undertaken at development scale using a PSD-2 spray
dryer with acetone as process solvent.
Crystallinity Challenge: Dried SDDs were exposed to varying temperature and humidity
conditions with rate of crystallisation, up to a limit of 10%, determined. In addition, dried
SDD (2g) was packaged into HDPE containers with HIS and placed on a 12-month
stability study (25°C/60%RH, 30°C/65%RH, 40°C/75%RH)
Crystallinity Determination: All samples were analysed for crystallinity using DSC via
relative heat of fusion to nominal 100% crystalline SMT-API (scan rate of 10°C/min and
no modulation). For each SDD sample at each condition heat of fusion was plotted
against time and linear fits up to 10J/g API were used to calculate the initial rate of
crystallisation (J/g API.min). Rates of crystallisation were modelled as a function of T,
%RH and/or Tg using modified Arrhenius equations with predicted stability compared to
real time data.
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Methodology
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Modelling the Physical Stability of the SDD - 1
Crystallinity was measured for each sample
using a fast DSC method that allowed for
the detection of Tm and corresponding heat
of fusion (representative data for
40°C/75%RH hold condition)
14
Quantifying API Crystallinity within the SDD
Temperature (°C)
He
at F
low
(W
/g)
50 100 150
y = 0.0144x - 0.0417R² = 0.9979
0
1
2
3
4
5
6
7
8
9
10
0 200 400 600
Heat of fusion was plotted versus time for
each condition and linear fits of the data up
to 10J/gAPI were plotted (representative
data for 40°C/75%RH hold condition)
14 & 15 October 2019
SOS 2019 Amsterdam
% C
rys
tall
init
y
Temperature (°C)
Signal of
interest
Modelling the Physical Stability of the SDD - 2
• Assessed relationship between the rate of
crystallisation and Tg/T
• Initial crystallisation rates modelled as a
function of Tg/T assuming open conditions
• Equivalent rate of crystallisation was
observed at three different temperatures
with different %RH suggesting a strong
correlation with Tg (40°C/75%RH,
60°C/29%RH, 70°C/9%RH)
15
Results: Ln(k) versus Tg/T
Below the Tg
• Although linear fit of the data shows poor correlation (R2=0.6366) model predicts 0.09%
crystallinity at 21 days at 25°C/60%RH (0.11% observed)
• Despite poor correlation this model accounts for the impact of humidity on the Tg and
demonstrates SDD recrystallisation rate is controlled by moisture-induced plasticization
of the polymer and consequent increased amorphous SMT-API molecular mobility
14 & 15 October 2019
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Modelling the Physical Stability of the SDD - 3
• ASAPprime® uses modified Arrhenius equation to predict rates of degradation
• Humidity modified Arrhenius equation accounts for moisture uptake within packaging
Lnk = −Ea/RT + lnA + B(%RH)
• Primary application of ASAPprime® is prediction chemical degradation rates
• Limited reports on the application of ASAPprime ® to model physical changes during
stability studies (e.g. amorphous to crystalline)
• In general physical properties show non-Arrhenius behaviour
• However, there is no reason this approach can’t be applied to physical instability
16
ASAPprime®
14 & 15 October 2019
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Modelling the Physical Stability of the SDD - 4
17
Results: ASAPprime®
Including 0% RH Excluding 0% RH
• Initial crystallisation rates were modelled using the humidity modified Arrhenius equation
Including 0% RH Excluding 0% RH
ln(A) 61.1 ± 1.4 38.8 ± 0.2
Ea (kcal/mol) 44.5 ± 1.3 29.8 ± 2.3
B 0.078 ± 0.003 0.064 ± 0.004
R2 0.904 1.0
Lnk = −Ea/RT + lnA + B(%RH)]
14 & 15 October 2019
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Modelling the Physical Stability of the SDD
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Accuracy of the Fit
Including 0% RH Excluding 0% RH
• Accuracy of fit was determined through comparison of ASAPprime® output with real time
data at three conditions
• 25°C/60%RH, 30°C/65%RH, 40°C/75%RH
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Modelling the Physical Stability of the SDD
• Modelled data was used to predict shelf life (10% crystalline API) for open and/or
closed conditions and compared to real-time data
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Shelf Life Prediction
Time to 10% crystallinity (years)
Model Conditions Used Open Packaged
ASAPprime® 7 (0% + > 0% RH) 15.3 15.9
ASAPprime® 4 (> 0% RH) 2.4 3.6
• ASAPprime® accurately models the rate of crystallisation for the SDD up to 12 months
and predicts a shelf life of 3.6 years in clinically relevant packaging
Hypotheses for why the 0% RH samples have different rates:
• Samples contain residual moisture and/or unaccounted water. May be
thermodynamically distinct from “bulk” adsorbed water
• This water may be decreasing the rate of crystallisation due to API-water interaction,
different miscibility in the polymer
14 & 15 October 2019
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Physical Stability Modelling of Amorphous SDD
• Predictive physical stability modelling de-risked the late-stage development
of a chemically stable BCS class II SDD
• ASAPprime® successfully predicted rate of crystallisation over 12 months in
clinically relevant packaging
• Predictive stability modelling can be applied to understanding the physical
stability profile of chemically stable SDDs that have similar mechanisms of
recrystallisation
• Prone to initial phase separation, low miscibility, low MW, low Tg
• Application of predictive stability approaches to physical stability broadens
the opportunity to progress NCE’s with otherwise unfavourable
pharmaceutical profiles
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Conclusions
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Acknowledgements
Summit Therapeutics
Preclinical
Clinical
Peter Timmins
Bend Research
Corey Bloom
Tyler Clikeman
Tim Elwell
Clinical Studies
Patients, Carers/Parents
Investigators
Sites
21
14 & 15 October 2019
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