Predicting crystal form stability under real-world conditions

Nature, Journal Year: 2023, Volume and Issue: 623(7986), P. 324 - 328

Published: Nov. 8, 2023

The physicochemical properties of molecular crystals, such as solubility, stability, compactability, melting behaviour and bioavailability, depend on their crystal form1. In silico form selection has recently come much closer to realization because the development accurate affordable free-energy calculations2-4. Here we redefine state art, primarily by improving accuracy calculations, constructing a reliable experimental benchmark for solid-solid differences, quantifying statistical errors computed free energies placing both hydrate structures different stoichiometries anhydrate same energy landscape, with defined error bars, function temperature relative humidity. calculated have standard 1-2 kJ mol-1 industrially relevant compounds, method place landscape can be extended other multi-component systems, including solvates. These contributions reduce gap between needs experimentalist capabilities modern computational tools, transforming structure prediction into more actionable procedure that used in combination evidence direct establish control5.

Language: Английский

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Solubilization techniques used for poorly water-soluble drugs

Acta Pharmaceutica Sinica B, Journal Year: 2024, Volume and Issue: 14(11), P. 4683 - 4716

Published: Sept. 2, 2024

About 40% of approved drugs and nearly 90% drug candidates are poorly water-soluble drugs. Low solubility reduces the drugability. Effectively improving bioavailability is a critical issue that needs to be urgently addressed in development application. This review briefly introduces conventional solubilization techniques such as solubilizers, hydrotropes, cosolvents, prodrugs, salt modification, micronization, cyclodextrin inclusion, solid dispersions, details crystallization strategies, ionic liquids, polymer-based, lipid-based, inorganic-based carriers bioavailability. Some most commonly used carrier materials for presented. Several using summarized. Furthermore, this summarizes mechanism each technique, reviews latest research advances challenges, evaluates potential clinical translation. could guide selection approach, dosage form, administration route Moreover, we discuss several promising attracting increasing attention worldwide.

Language: Английский

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The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods

Journal of Chemical Information and Modeling, Journal Year: 2022, Volume and Issue: 62(22), P. 5317 - 5320

Published: Nov. 28, 2022

ADVERTISEMENT RETURN TO ISSUEEditorialNEXTThe (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge Machine Learning MethodsThereza A. Soares*Thereza SoaresDepartment Chemistry, University São Paulo, Ribeirão Preto 055508−090, BrazilHylleraas Centre for Quantum Molecular Sciences, Oslo, Oslo 0315, NorwayMore Thereza Soareshttps://orcid.org/0000-0002-5891-6906, Ariane Nunes-AlvesAriane Nunes-AlvesInstitute Technische Universität Berlin, Berlin 10623, GermanyMore Nunes-Alves, Angelica MazzolariAngelica MazzolariDepartment Pharmaceutical Milan, Via Mangiagalli 25, Milan I-20133, ItalyMore Mazzolarihttps://orcid.org/0000-0003-1352-1094, Fiorella RuggiuFiorella RuggiuInsitro Inc., 279 East Grand Avenue, South San Francisco 94080, California, United StatesMore Ruggiuhttps://orcid.org/0000-0001-7260-3255, Guo-Wei WeiGuo-Wei WeiDepartment Mathematics, Michigan State University, Lansing 48824, Michigan, Weihttps://orcid.org/0000-0002-5781-2937, and Kenneth MerzKenneth MerzDepartment Merzhttps://orcid.org/0000-0001-9139-5893Cite this: J. Chem. Inf. Model. 2022, 62, 22, 5317–5320Publication Date (Web):November 28, 2022Publication History Received9 November 2022Published online28 inissue 28 2022https://pubs.acs.org/doi/10.1021/acs.jcim.2c01422https://doi.org/10.1021/acs.jcim.2c01422editorialACS PublicationsCopyright © Published 2022 American Chemical Society. This publication is available under these Terms Use. Request reuse permissions free to access through this site. Learn MoreArticle Views6307Altmetric-Citations5LEARN ABOUT THESE METRICSArticle Views are COUNTER-compliant sum full text article downloads since 2008 (both PDF HTML) across all institutions individuals. These metrics regularly updated reflect usage leading up last few days.Citations number other articles citing article, calculated Crossref daily. Find more information about citation counts.The Altmetric Attention Score a quantitative measure attention that research has received online. Clicking on donut icon will load page at altmetric.com with additional details score social media presence given article. how calculated. Share Add toView InAdd Full Text ReferenceAdd Description ExportRISCitationCitation abstractCitation referencesMore Options onFacebookTwitterWechatLinked InRedditEmail (1 MB) Get e-AlertscloseSUBJECTS:Algorithms,Bioinformatics computational biology,Drug discovery,Molecules,Structure activity relationship e-Alerts

Language: Английский

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Accelerating 3D printing of pharmaceutical products using machine learning

International Journal of Pharmaceutics X, Journal Year: 2022, Volume and Issue: 4, P. 100120 - 100120

Published: June 10, 2022

Language: Английский

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

Crystal Growth & Design, Journal Year: 2024, Volume and Issue: 24(13), P. 5417 - 5438

Published: June 24, 2024

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

Language: Английский

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A robust crystal structure prediction method to support small molecule drug development with large scale validation and blind study

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 5, 2025

Crystal polymorphism is an important and fascinating aspect of solid state chemistry with far reaching implications in the pharmaceuticals, agrisciences, nutraceuticals, battery aviation industries. Late appearing more stable polymorphs have caused numerous issues pharmaceutical industry. Experimental polymorph screening can be very expensive time consuming, sometimes may miss low energy due to inability exhaust all crystallization conditions. In this paper, we report a crystal structure prediction (CSP) method art accuracy efficiency, validated on large diverse dataset including 66 molecules 137 experimentally known polymorphic forms. The combines novel systematic packing search algorithm use machine learning force fields hierarchical ranking. Our not only reproduces polymorphs, but also suggests new yet discovered by experiment that might pose potential risks development currently forms these compounds. addition, results blinded study, for Target XXXI from seventh CSP blind test, demonstrate how used accelerate clinical formulation design derisk downstream processing.

Language: Английский

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Virtual Screening, Structural Analysis, and Formation Thermodynamics of Carbamazepine Cocrystals

Pharmaceutics, Journal Year: 2023, Volume and Issue: 15(3), P. 836 - 836

Published: March 3, 2023

In this study, the existing set of carbamazepine (CBZ) cocrystals was extended through successful combination drug with positional isomers acetamidobenzoic acid. The structural and energetic features CBZ 3- 4-acetamidobenzoic acids were elucidated via single-crystal X-ray diffraction followed by QTAIMC analysis. ability three fundamentally different virtual screening methods to predict correct cocrystallization outcome for assessed based on new experimental results obtained in study data available literature. It found that hydrogen bond propensity model performed worst distinguishing positive negative experiments 87 coformers, attaining an accuracy value lower than random guessing. method utilizes molecular electrostatic potential maps machine learning approach named CCGNet exhibited comparable terms prediction metrics, albeit latter resulted superior specificity overall while requiring no time-consuming DFT computations. addition, formation thermodynamic parameters newly evaluated using temperature dependences Gibbs energy. reactions between selected coformers be enthalpy-driven, entropy being statistically from zero. observed difference dissolution behavior aqueous media thought caused variations their stability.

Language: Английский

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Best Practices for the Collection of Robust Time Course Reaction Profiles for Kinetic Studies

ACS Catalysis, Journal Year: 2023, Volume and Issue: 13(2), P. 1418 - 1430

Published: Jan. 9, 2023

Kinetic investigations can provide critical mechanistic information for the optimization of reaction parameters and development. Modern kinetic analyses such as RPKA VTNA many advantages over traditional initial rate methods are especially powerful when coupled with monitoring technologies. While these robust analytical methods, lack careful observation lead to misinterpretation data. In this Perspective, we highlight some commonly overlooked considerations in studies based on our experiences present a general guide proper reactions analytics prior acquiring

Language: Английский

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Conformational Screening of Arbidol Solvates: Investigation via 2D NOESY

Pharmaceutics, Journal Year: 2023, Volume and Issue: 15(1), P. 226 - 226

Published: Jan. 9, 2023

Understanding of the nucleation process's fundamental principles in saturated solutions is an urgent task. To do this task, it necessary to control formation polymorphic forms biologically active compounds. In certain cases, a compound can exist single form, but have several solvates which appear different crystal forms, depending on medium and conditions formation, show pharmaceutical activity. present paper, we report analysis Arbidol conformational preferences two solvents polarities-deuterated chloroform dimethyl sulfoxide-at 25 °C, using 2D NOESY method. The molecule has various solvate molecular conformation. method based nuclear Overhauser effect spectroscopy was shown be efficient complex heterocyclic compounds possessing conformation-dependent pseudo-polymorphism. It one types polymorphism observed forming solvates. Combined use NMR methods X-ray data allowed determining conformer populations CDCl3 DMSO-d6 were found 8/92% 37/63%, respectively. preferred conformation solution same that appears stable Arbidol.

Language: Английский

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DEM-DDM investigation of the intra-tablet coating uniformity for tablets with different shapes

Powder Technology, Journal Year: 2024, Volume and Issue: 438, P. 119666 - 119666

Published: March 15, 2024

Language: Английский

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