Gibbs free-energy differences between polymorphs via a diabat approach

Kamat, Kartik; Peters, Baron

doi:10.1063/1.5051448

Cited by 3 publications

(4 citation statements)

References 81 publications

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“…[135][136][137] A diabat free energy variant of LSMC makes further use of the exact Zwanzig-Bennet relationship 138,139 between free energy diabats. 140 This new method shows promising precision and efficiency for polymorphs of atomic systems, 141 as well as molecular systems 142 (requiring only two unbiased MD simulations in some cases). Our application to carbamazepine demonstrated precision at a level ±0.01 kcal mol -1 (±0.04 kJ mol -1 ) in computed free energy differences with just 5 ns of computing time per polymorph pair.…”

Section: Free Energies By Einstein Crystalmentioning

confidence: 99%

Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process

Burcham,

Doherty,

Peters

et al. 2024

Preprint

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A workflow for the digital design of crystallization processes starting from the chemical structure of the active pharmaceutical ingredient (API) is a multi-step, multi-disciplinary process. A simple version would be to first predict the API crystal structure and from it the corresponding properties of solubility, morphology, and growth rates, assume that the nucleation would be controlled by seeding, and then use these parameters to design the crystallization process. This is usually an over-simplification as most APIs are polymorphic, and the most stable crystal of the API alone may not have the required properties for development into a drug product. This perspective, from the experience of a Lilly Digital Design project, considers the fundamental theoretical basis of crystal structure prediction (CSP), free energy, solubility, morphology and growth rate prediction, and the current state of nucleation simulation. This is illustrated by applying the modeling techniques to real examples, olanzapine and succinic acid. We demonstrate the promise of using ab initio computer modeling for solid form selection and process design in pharmaceutical development. We also identify open problems in the application of current computational modeling and achieving the accuracy required for immediate implementation that are currently limiting the applicability of the approach.

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Section: Free Energies By Einstein Crystalmentioning

confidence: 99%

Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process

Burcham,

Doherty,

Peters

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…The use of a reference model system, namely the Einstein crystal, − coupled with free energy perturbation (FEP) or thermodynamic integration (TI), provides an alternative method. These methods and some of their modifications have been implemented in MD packages. − Some inherent errors in calculating relative free energies are removed by using the Lattice Switch Monte Carlo (LSMC) method, which has mainly been used in atomic solids. − A further enhancement using the exact Zwanzig-Bennett relationship shows promise. − Application to carbamazepine demonstrated precision at a level of ±0.01 kcal mol –1 (±0.04 kJ mol –1 ) in computed free energy differences with just 5 ns of computing time per polymorph pair . All of these methods are described in greater detail in Sections S2 and S3.…”

Section: Crystal Polymorph Selectionmentioning

confidence: 99%

Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process

Burcham,

Doherty,

Peters

et al. 2024

Crystal Growth & Design

View full text Add to dashboard Cite

A workflow for the digital design of crystallization processes starting from the chemical structure of the active pharmaceutical ingredient (API) is a multistep, multidisciplinary process. A simple version would be to first predict the API crystal structure and, from it, the corresponding properties of solubility, morphology, and growth rates, assuming that the nucleation would be controlled by seeding, and then use these parameters to design the crystallization process. This is usually an oversimplification as most APIs are polymorphic, and the most stable crystal of the API alone may not have the required properties for development into a drug product. This perspective, from the experience of a Lilly Digital Design project, considers the fundamental theoretical basis of crystal structure prediction (CSP), free energy, solubility, morphology, and growth rate prediction, and the current state of nucleation simulation. This is illustrated by applying the modeling techniques to real examples, olanzapine and succinic acid. We demonstrate the promise of using ab initio computer modeling for solid form selection and process design in pharmaceutical development. We also identify open problems in the application of current computational modeling and achieving the accuracy required for immediate implementation that currently limit the applicability of the approach.

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“…Kamat and Peters demonstrated moderate efficiency advantages compared to the standard LSMC framework for the body-centered cubic and hexagonal close-packed phases of zirconium. 55 In this work, we extend the diabat method to non-orthorhombic crystals of flexible molecules. The mapping procedure we propose is system independent and easy to implement.…”

Section: The Journal Of Chemical Physicsmentioning

confidence: 99%

“…In previous work, we showed that the LSMC free energy profiles are superpositions of free energy diabats-one for the starting polymorph and one for the final polymorph with the two diabats crossing where the energy gap is zero. 54 We used (and generalized 55 ) the Zwanzig-Bennett relation 56,57 to calculate Helmholtz and Gibbs free energy differences (ΔF and ΔG, respectively) between the two polymorphs.…”

Section: Introductionmentioning

confidence: 99%

Diabat method for polymorph free energies: Extension to molecular crystals

Kamat

Guo

Reutzel‐Edens

et al. 2020

The Journal of Chemical Physics

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Lattice-switch Monte Carlo and the related diabat methods have emerged as efficient and accurate ways to compute free energy differences between polymorphs. In this work, we introduce a one-to-one mapping from the reference positions and displacements in one molecular crystal to the positions and displacements in another. Two features of the mapping facilitate lattice-switch Monte Carlo and related diabat methods for computing polymorph free energy differences. First, the mapping is unitary so that its Jacobian does not complicate the free energy calculations. Second, the mapping is easily implemented for molecular crystals of arbitrary complexity. We demonstrate the mapping by computing free energy differences between polymorphs of benzene and carbamazepine. Free energy calculations for thermodynamic cycles, each involving three independently computed polymorph free energy differences, all return to the starting free energy with a high degree of precision. The calculations thus provide a force field independent validation of the method and allow us to estimate the precision of the individual free energy differences.

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Gibbs free-energy differences between polymorphs via a diabat approach

Cited by 3 publications

References 81 publications

Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process

Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process

Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process

Diabat method for polymorph free energies: Extension to molecular crystals

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