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A Molecular Dynamics Simulation Approach
towards Designing of Drug Formulations:
Case study of Anti-cancer Drug (Taxol)
Apoorva Purohit, Ravi C Dutta, Beena Rai
Tata Consultancy Services, Pune, India
Email: [email protected]
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Anti-cancer Agent : Paclitaxel (Taxol)
Natural product from the Western yew tree (Taxus brevifolia)
Activity against a broad band of tumor types, including breast, ovarian,
lung, head and neck cancers
Also used for previously-treated lymphoma, small cell lung cancers,
oesophageal, gastric endometrial, bladder and germ cell tumors
Active against AIDS-associated Kaposi's sarcoma and restenosis
Difficulty in its oral absorption
• Low water solubility & membrane permeability
Yew treeTAXOL
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Commercial Formulations: Challenges
1:1 Cremophor EL (polyoxyethylated castor oil) and
ethanol
Serious side effects (immune system, kidneys and nervous
system)
– Premedication with corticosteroids and antihistamine
5 to 20-fold dilution of the product
– Stability of diluted Taxol is limited to 12-24
Need for a new formulation of Taxol
– More efficient
– Less toxic
Six 100-year old trees to provide enough Taxol to treat just
one patient
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Alternative Formulations
Ref.: A.K. Singla et al. / International Journal of Pharmaceutics
235 (2002) 179–192
in-silico approach
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in-silico Formulation Development
Design issues • Rheological parameters
– viscosity, yield stress
• Stability
– Thermal & Chemical
• Additional Functional Requirements
– Low friction
– Anti-stick
– Scratch resistance
– Seal compatibility
Solvent
(Water/Organic)
Drug/Pigment/Filler
Excipients/Binder/Resin
Typical
Formulation
Dispersant
Existing Methods: Trial & error
Largely experimental
Solution:
Atomistic Simulations to
delineate interactions amongst
different components and
design/optimize formulations
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Drug Formulations
Established means to improve the solubility, toxicity and/or
efficacy of a drug
The physico-chemical properties of drug-excipient blend
effect the performance of formulation
Drug loading and retention is largely influenced by the
specific interactions between drug and excipient
Molecular modeling provide an attractive alternative for
prediction of– Drug solubility
– Viscosity
– Water absorption
Benefits– Savings in cost and time
– Identification of early stage failures
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Rational Design Paradigm
•Techniques – Force field (Atomistic)
– Quantum Mechanics • Density Functional Theory (DFT)
– Molecular Dynamics
– Quantitative Structure Activity Relationship (QSAR)
•Tools – Cerius2, Material Studio (Accelrys Inc.)
– PWScf (http://www.quantum-espresso.org/
– LAMMPS (http://lammps.sandia.gov/
• Platform- Linux cluster
- EKA Super computer
Correlation of E with experimental
properties: screen/design for better
efficiency
O OH
R
r
Surface
Surfactant
Interaction energy (E) = TEcomplex - (TEsurface + TEsurfactant)
Ref.: Molecular Modeling for the Design of Novel Performance
Chemicals and Materials, (Ed.) Beena Rai, Ch. 2, 2012,CRC Press
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Earlier Simulation Studies*
Molecular Dynamics (MD) simulations
Solubility of docetaxel in five different excipients
Computation of solubility using semi-empirical and MD methods
MD with single solvent/excipient systems
Good agreement with the experimental data
MD method was found to be more accurate
* Allen et al., Pharm. Research, 25, 147 (2008)
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Present Study
Taxol in binary (1:1) and ternary solvent (1:1:1) mixtures
Solvent
– Ethanol, Water, PEG 400, Glycerol, Tween 80
Molecular dynamics simulations to compute solubility and
relative diffusivity of Taxol in the solvent combinations
Comparison of simulated solubility with the experimental
data
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System Details
Construction of molecules (solvent and drug) using Material Studio 4.1
3D periodic boxes of solvent system (all of fixed volume - approx.
42875 Å ³) was done using the Amorphous Cell Builder Module
(Material Studio) at 300K.
The constructed solvent boxes were then minimized
Water-water interactions:
– SPC/E model – hydrogen atoms are located at 1A0 from the
oxygen with an H-O-H angle of 109.47 deg.
In every optimized solvent box, Taxol molecules were added and the
system was again geometrically optimized and exported to LAMMPS
Cohesive energy density and Solubility parameter were computed
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Computation Details
Tools: Material Studio 4.1 (Accelrys Inc.) & Large-scale
Atomic/Molecular Massively Parallel Simulator (LAMMPS)
(Sandia National Lab)
Ensemble : NVT/NVE
Time : 20- 200 ns
Force field : CVFF
SPC/E model for water
Bond distances and bond angles were fixed throughout the
simulation with SHAKE algorithm
LJ 12-6 potential for short range interactions
Long range electrostatic interactions: Particle-Particle Mesh
Ewald method
EKA @ Computation Research Laboratory, Pune, India
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Solubility Parameter
Cohesive energy density is intermolecular non-bond energy per
unit volume
Solubility parameter is defined as the square root of cohesive
energy density
Energy of mixing
Flory-Huggins interaction parameter
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Approach
Calculation of CED for given volume fraction (φ)
Calculation of ΔE mix
Calculation of χ FH for given φ
Volume fraction of Taxol at χ FH = 0.5 is considered as maximum solubility
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Model Validation : Water
SPC/E model
5000 water molecules
Diffusion coefficient
Thermal Conductivity
Viscosity
RDF Analysis
Hydrogen bond analysis
0
1000
2000
3000
0 1 2
MS
D (
Ų
)
time (ns)
MSD vs time
Simulation Expt.*
D (X 10-5 cm2/sec) 2.75 2.49
K (W/m.K) 0.62 0.58
*Ref. D. R. Lide, CRC Handbook of Chemistry and Physics,
Boca Raton (FL), CRC Press, 1990
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Model Validation: Taxol Solubility
Excipients Experimental Solubility
(mg/ml)*
Simulated solubility
(mg/ml)
Tributyrin 108+1.8 112+0.6
Tricaporion 85.7+2.0 84+0.9
Vitamin E 75.0+1.8 76+0.5
Tricapryylin 55.6+2.2 63+0.8
*Ref. Huynh et al. Pharm. Research, 25(1), 2008, 147-157
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Taxol in Solvent Combinations
1440 Water + 1 Taxol 764 Water + 236 Ethanol + 1 Taxol
722 Water + 11 Tween 80 + 1 Taxol 481 Water + 148 Ethanol
+ 7 Tween 80 + 1 Taxol
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Contd.
668 Water + 165 Glycerol + 1 Taxol471 Water + 145 Ethanol +
23 PEG 400 + 1 Taxol
470 Water + 23 PEG 400
+ 7 Tween 80 + 1 Taxol 146 Ethanol + 116 Glycerol +
7 Tween 80 + 1 Taxol
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System CED
(Kcal/mole ų)
δ
(Kcal/mole ų)1/2
Diffusivity
(x10-9 m²/s)
Water + (T) 543.51 23.31 6.9
Water + ethanol + (T) 543.70 23.32 5.3
Water + tween80 + (T) 514.69 22.69 0.9
Water + glycol + (T) 544.42 23.33 2.73
Water + ethanol + tween80 + (T) 544.31 23.33 4.28
Water + PEG + tween80 + (T) 522.53 22.86 0.451
Ethanol + water + PEG + (T) 546.19 23.37 1.81
Ethanol + tween80 + glycol + (T) 530.52 23.03 0.52
Computed Properties of Taxol
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Experimental Validation
Difference in turbidity of the solvent system before and after
addition of the Taxol*
*Ref. SRI International, USA, Copyright © 2010
Frederick Furness Publishing www.ondrugdelivery.com
Solvent System
3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5T
urb
idity D
iffe
rence
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
Solu
bili
ty P
ara
mete
r
23.30
23.32
23.34
23.36
23.38
23.40
Turbidity Difference
Solubility Parameter
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Concluding Remarks
A molecular modleing protocol for predicting drug solubility in
the solvent mixtures
The roder of predicted solubility
eth+W+PEG ≈ W+gly ≈ eth+W+twe ≈ eth+W ≈ W>eth+tween+gly>
W+PEG+twe > W+tween
MD simulation results compare well with the experimental
results
MD simulations a complimentary tool for the design and
optimization of drug formulations
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Way Forward
Remaining 28 solvent combinations
Force field for propylene glycol
Bigger solvent box
DOE for new combinations
Experimental validation
Extend to other drugs