Designing amorphous dispersion formulations for poorly ...

Designing amorphous dispersion formulations for poorly soluble drugsIan Yates – Product Development Lead, Lonza Bend

Tyler Clikeman – Senior Scientist, Product Development, Lonza Bend

WEBINAR | May 23rd, 2019

• Lonza Dosage Forms and Delivery Systems (DFDS) Intro

• Problem statement definition and formulation selection

• Amorphous spray-dried dispersion formulation design

• Case studies

• Physical stability

• Chemical stability

• Correlating in vitro performance testing to in vivo data

Presentation Outline

Yates Clikeman | Pharmaceutical Technology Webcast | May 23rd, 2019

3

Lonza DFDS Business Model

Feasibility Studies

Commercial Manufacture

Drug Substance Intermediates

Drug substances Drug Product Intermediates

Drug Products

DesignSmall / Lab-Scale (non-GMP)

DevelopClinical Scale

ManufactureCommercial Scale


4

Specialized Focus Areas

Design Develop Manufacture

Drug Substance and Intermediates

Drug Product Concepts

Early –stage Clinical Trial Materials

Clinical Trial Materials

CommercialSupply

• Customized API Development

• Highly Potent API & Drug Products

• Addressing Bioavailability Challenges

• Particle Engineering

• Modifying Pharmacokinetics

• Multi-particulate Formulations

Product Options

API / HAPI Drug Product Intermediate

Soft Gelatin Capsules

Tablets – IR, Osmotic, Matrix, Orally Dissolving

Powder Multi-particulate Filled Capsules

Liquid-filled Hard Capsules


Problem Statement Definition and Formulation Selection


6

70-80% of drugs in pharmaceutical pipeline are low solubilityBiopharmaceutical classification system

Our BA enhancement toolkit is geared towards addressing BCS II and IV compound challengesDepth in all enabling technologies used in addressing either BCS IIA, IIB, and IV compounds• phase-appropriate equipment

• extensive track record

• predictive modeling & tools for tech selection

2008;7:255–270

IIA Dissolution Rate Limited

IIB Solubility Limited

Butler, J., Dressman, J. J. Pharm. Sci., 2010


7

Goal is to efficiently arrive at product development with enabling approachProblem statement definition guides technology choice

SDD

LIPIDIC

NXSTAL

Product Concept

Molecular Properties

Predictions

Technology & Formulation

In vitro, in silico, & in vivo testing

Problem Statement

HME


8

Many Enabling Technologies Are Available for Bioavailability Enhancement

• Polymorphs• Cocrystals• Salts

• Cosolvents• Surfactants• Cyclodextrins• Lipids:

• Oils• SEDDS/SMEDDS• Solid lipid pellets• Solid lipid

nanoparticles

AmorphousCrystal Form SolvationSize Reduction

• Micronization• Sub-micron crystals (100 to

800 nm)• Nanocrystals (<100 nm)

• Solid dispersions• SDD• HME• Lyophiles• Drug/polymer

nanoparticles• Layered beads,

nanoadsorbates• Pure amorphous drug

• Molecular modification

• Pro-drugs

API Selection

• Oral• Parenteral• Pulmonary

Route of Admin

Lonza Bend Technologies in BA Enhancement


9

Important Considerations for Pre-formulation Assessment

Solubility1. Crystalline Aqueous

2. Amorphous Aqueous3. Crystalline Organic

Aqueous Solubility Challenge1. Lipophilicity/Micelle partitioning

2. Melting point/Crystal lattice energy (i.e. “brick dust”)

Permeability1. Molecular Descriptors

(e.g. MW, rotatable bonds, charge state)

2. Caco-23. Perfusion

Metabolism/Efflux

Pharmacokinetics 1. Absolute BA

2. BA dose dependence3. Food effect

4. Gastric pH effect

Target Product Profile1. Clinical Phase

2. Dose3. Dosing Frequency

4. In vivo model (e.g. rat, dog, monkey, human, etc.)

Chemical Stability1. Labile functional groups

2. Forced degradation

Physical Stability1. Thermal Properties

(e.g. Tm, Tc, Tg)2. Water Uptake


10

Technology Mapping

Bioavailability Enhancement Map

Friesen et. al. Mol. Pharmaceutics, 5:6 (2008)1003-1019

Fraction Absorbed Classification System (FACS)

Amorphous Dispersion Guidance Map

Williams et. al. Pharmacol. Rev.,65(2013), 315-499

Sugano and Terada, Pharm. Sci. 104:2777-2788, 2015.


11

Three Areas of Focus for Development of an Amorphous Dispersion

Performance

ManufactureStability

Performance:• Problem statement identification• Initial characterization through complementary

in vitro tests• Biomodels to test hypotheses

• Inputs for in vivo results• Refinement of in vitro tests• Phase appropriate

Stability• Prediction using thermal

properties• Phase diagrams• Accelerated stability

Manufacturability• Define solvent system• Define key process parameters• Scale-up considerations• Enabling technologies for compounds

with poor organic solubility

Early Development Goals: 1. Learn as much as we can to deliver

the best formulation possible in a time and cost effective manner

2. Position program well for late stage development


Amorphous Spray Dried Dispersion Formulation Design


13

Spray-Dried Dispersion – What Is It?

DRYI

NG

CH

AMBE

R

30 microns

Nozzle

THE PROCESS

FEED SOLUTIONDrug is dissolved with polymer in a common organic

solvent.

DRYING GAS

RESULTING SDDThe resulting powder is a homogenous, stable, amorphous dispersion suitable for incorporation into oral dosage forms.

Pressure Nozzle

Initial Solution Droplet

Hot Drying Gas Contacts Droplet

Dried SDD Particle

Skinned Droplet

10-6 sec

10-2 sec

~1 sec

Inten

sity (

coun

ts)

0

100

200

300

400

500

600

700

800

900

2-Theta - Scale4 10 20 30

Amorphous SDD

Bulk Drug

Inten

sity (

coun

ts)

0

100

200

300

400

500

600

700

800

900


Inten

sity (

coun

ts)

0

100

200

300

400

500

600

700

800

900


Amorphous SDD

Bulk Drug

PXRD ANALYSES

SDD

Bulk drug

SEM TEM

THE PRODUCT

RESULTING FORMULATIONHomogeneous, stable, amorphous dispersion

BIOAVAILABILITY ENHANCED• Dissolves rapidly • Solubility increased• Maintains super- saturation

in intestine

MULTIPLE ORAL DOSAGE FORMS • Tablets • Capsules• Powder in bottle• CR dosage forms


14

SDD Dissolution Model

Several mechanisms


33

Problem Statement-specific Bioperformance in vitro Tools

Dissolution FluxAmorphous Solubility Controlled Transfer

• Amorphous “solubility”• Precipitation risk • Polymer selection• Drug/polymer interaction

• Dissolution rate• Precipitation rate• Maximum apparent

concentration• Speciation

• Clean measurement of “effective” concentration

• Able to properly account for micelle, colloid, and particle contribution to boundary layer diffusion and dissolution rate

• Dissolution rate• Precipitation rate vs.

emptying rate• Gastric precipitation • “Book-end” for

formulation performance


16

Physical Stability of Spray Dried Dispersions

Thermodynamics Kinetics Experience


Case Study #1: Modeling Physical Stability with a Chemically Stable SDD


18

• Low drug loading SDD: 15/85 API/HPMCAS-M

• Balance of manufacturability, performance, and

stability required accepting a small amount of

crystallization over time

• Modeling showed that we could minimize

physical instability with packaging and storage

SDD characteristics

Performance

ManufactureStability


19

Modeling Physical Stability

Method:1. Store SDD at accelerated T/%RH stability conditions Crystallize SDD at high

temperature/humidity conditions below Tg in ovens.2. Measure resulting crystallinity from heat of fusion using fast DSC method.3. Calculate initial rates of crystal growth (up to 10% crystalline drug).4. Model rate of crystallization as a function of T, %RH, and/or Tg.

Model Rates of Crystallization

Lnk vs. Tg/T

Lnk = −Ea/RT + lnA + B(%RH)

1 2, 3 4


20

Modeling Physical StabilityMethod:1. Store SDD at accelerated T/%RH stability conditions Crystallize SDD at high



21

Quantifying low levels of crystallinity in a low drug loading SDD

15/85 API/HPMCAS-M SDDVery low levels of surface crystals are qualitatively detected by SEM, but quantitation is difficult.

<LOD by DSC and PXRD >LOQ by DSC, <LOQ by PXRD >LOQ by DSC, >LOQ by PXRD

Crystalline growth on stability

DSC was able to detect intermediate levels of crystallinity with fast scan rateA significant amount of crystals were needed to quantitate by PXRD and long scan times were required


22

Measure rate of crystallization with DSC

Up to 10% crystalline API was used for initial rates

3 weeks

1 week



melt

Tm 162 °C

Tg 33 °C

Tm/Tg 1.42

Heat of Fusion 99.7 J/g


23

Model crystallization at storage conditions



Lnk vs. Tg/T



24

Model using Lnk vs. Tg/T

• Accounts for humidity with Tg.• Predicts 6.7 years of stability at 25 °C/60% RH open.• Water can initiate a different reaction mechanism and cause a

different driving force for crystallization.

Below the Tg

• Same rate at 3 different temps with 3 different %RH suggests strong correlation with Tg.


25

Model using Lnk = −Ea/RT + lnA + B(%RH)

• Uses humidity modified Arrhenius equation that was developed for chemical stability.• ASAPprime modeling software accounts for moisture uptake with packaging.• Model accurately predicts 12 month stability data when 0% RH conditions are excluded.

2 g SDD in a 40 cc HDPE bottle with HIS


Parameter Results

ln(A) 38.8 ± 0.2

Activation Energy, Ea

(kcal/mol)29.8 ± 2.3

Humidity Sensitivity

Factor, B0.064 ± 0.004

Case Study #2:Modeling Chemical Stability with a Physically Stable SDD


27

Modeling Chemical Stability with a Physically Stable SDD

N

O NH2

R

NH

R

API Impurity

hydrolysis

• 50/50 API/PVP-K30 SDD• Low degradation specification (up to 0.6%)• Humidity both increased molecular mobility by plasticizing

the SDD and introduced more water for the hydrolysis reaction.

• Physical changes occur above Tg and change mechanism• Conditions near the Tg were required to measure

degradation within a reasonable timeframe (3 weeks)• Degradation measured by HPLC


28

• Linear rates at each condition were fit to

the modified Arrhenius equation

Accelerated Stability Study

Parameter Results

ln(A) 28.6 ± 2.2

Activation Energy, Ea (kcal/mol) 22.5 ± 1.5

Humidity Sensitivity Factor, B 0.063 ± 0.005

R2 0.924



29

• Modeled 8 kg SDD in 10 liter LDPE double bag with 8-unit sieve desipaks

• Model showed that SDD could be stored in bags with > 10% desiccant, but double bags

in foil was more appropriate

Bulk SDD Storage

desipaks Wt% desiccant

Probabilityof passing at 2 years (%)

0 0 2

1 3 13

2 5 41

3 8 73

4 10 91


desiccant estimation

30

comparison with long-term dataCapsule Stability

30 capsules in 30 cc HDPE HIS bottle, closed, no desiccant

add desiccant

• Model accurately predicts 12 month stability data. • 2 g desiccant can increase stability by 20 months• Model was used to choose desiccant level for

future clinical packaging.


31

Using model to understand stability outliers

• Prediction helped show that 9 month water value was an outlier.• Additional processing steps and desiccant were added in order to

reduce starting water content and slow impurity formation.


Case Study #3:Mechanistic Understanding of Belinostat Oral Absorption in Beagle DogsYates Clikeman | Pharmaceutical Technology Webcast | May 23rd, 2019

33

Case study - SDDs of belinostat dosed to dogs

+Belinostat

BCS II/IV

pKa = ≥8 (acidic)

LogP < 2

HPMCAS (weakly acidic)25% activeHPMCAS-M SDD

Polyvinylpyrrolidone (neutral)

Polyvinylpyrrolidone Vinyl Acetate (neutral)

SDDs dosed to beagle dogs(n=4), fastedDose: 50 mgDosing vehicle: 0.5% MethocelA4M in H2O, 15 ml water rinse

25% activePVP K30 SDD

25% activePVP VA64 SDD

Key belinostat attributes:

• High amorphous solubility in biorelevant media (>500 µg/mL).

• Amorphous solubility is impacted by the presence of polymer.

• Dissolution rate is a key driver for absorption and differs depending on SDD formulation and testing method.

Stewart A, Yates I, et al. Mechanistic Study of Belinostat Oral Absorption from Spray Dried Dispersions. J. Pharm. Sci. (2018).


34

Belinostat apparent amorphous solubility depends upon dispersion polymer type

Belinostat

BCS II/IV

pKa = ≥8 (acidic)

LogP < 2

Ilevbare, G. A. & Taylor, L. S. Cryst. Growth Des. 13, 1497–1509 (2013).

Blank Buffer (pH 2)6.7 mM SIF

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Amor

phou

s Sol

ubili

ty (m

g/m

l)

Belinostat + HPMCAS-M

Belinostat+ PVP K30

Belinostat+ PVP VA64

Amorphous solubility is defined as the onset of amorphous liquid-liquid phase separation. Presence of polymer influences the LLPS concentration.

6.7mM SIF pH 6.5


35

Evaluate belinostat dissolution performance using pH transfer test versus single medium test

In vitro Gastric In vitro Intestinal In vitro Intestinal In vivo Gastric In vivo Intestinal

HPMCAS-M SDD 1.3 0.4 1.5 1.3 0.8

PVP K30 SDD 1.4 0.4 1.7 1.4 0.8

PVP VA64 SDD 3.3 1.0 4.0 3.3 2.0

Assumes:• Fasted state• 50 mL gastric volume• 50 mL intestinal volume

In vivo

pH 6.56.7 mM SIF

20 ml

Intestinal pH test(pH 6.5, 6.7 mM

SIF)

Gastric transfer test(pH 2 SGF 6.5, 6.7 mM SIF)

pH 2 SGF pH 6.56.7 mM SIF

AddConcentratedSIF solution att = 30 min

10 ml

20 ml

Dose/Volume/Solubility:

source: daviddarling.info

Non-sink Dose: 1000 µg/mL in SGF Non-sink Dose: 2000 µg/mL in SIF

In situ fiber optic detection


36

Relative extents of dissolution between SDDs depends upon dissolution medium composition

0.0

0.5

1.0

1.5

0 30 60 90

Conc

entr

atio

n (m

g/m

L)Time (min)

0.0

0.5

1.0

1.5

0 30 60 90 120

Conc

entr

atio

n (m

g/m

l)

Time (min)

HPMCAS-M SDD

PVP K30 SDD

PVP VA64 SDD

HPMCAS-M SDD

PVP K30 SDD

PVP VA64 SDD

Intestinal pH test (pH 6.5, 7 mM SIF)M SDD > K30 SDD > VA64 SDD

Gastric transfer (pH 2 SGF 6.5, 7 mM SIF)K30 SDD > M SDD ≈ VA64 SDD

Dashed lines represent the apparent amorphous solubility measured in SGF and SIF from the amorphous solubility assay (slide 30)

Dose: 1000 µg/mL (SGF), 500 µg/mL (SIF) Dose: 2000 µg/mL


37

Using amorphous solubility and dissolution data as key inputs to absorption model supports hypothesis of dissolution rate limited absorption Amorphous solubility Dissolution rate/extent

In vitro inputs to model

In silico predictions


38

Gastric → intestinal transfer test better rank orders SDDs with respect to in vivo performance in dogs

Gastric transfer (pH 2 pH 6.5, 7 mM SIF) Intestinal pH test (pH 6.5, 7 mM SIF)

Sequential exposure to SGF and SIF at a more relevant dose/volume/solubility (dose number) is a better indicator for rank-ordering in vivo exposure from each SDD.


39

ConclusionsBelinostat Case Study

• Amorphous solubility of belinostat depends on polymer type.

• SGF/SIF transfer test a better indicator of in vivo performance.

• Used in vitro inputs to describe blood plasma profiles via absorption modeling.

• Rate-determining step to absorption: dissolution rate and extent achieved in the stomach prior to transit down the GI tract.


40

Thank youContact us: [email protected]


Designing amorphous dispersion formulations for poorly ...

Documents

Transcript of Designing amorphous dispersion formulations for poorly ...