Discovery of Cilnidipine Cocrystals with Enhanced Dissolution by the Use of Computational Tools and Semiautomatic High-Throughput Screening DOI Creative Commons
Matteo Guidetti,

Rolf Hilfiker,

Susan M. De Paul

et al.

Crystal Growth & Design, Journal Year: 2025, Volume and Issue: 25(10), P. 3374 - 3385

Published: April 29, 2025

Cocrystals are an attractive option for overcoming drug limitations, such as a low dissolution rate and absorption of poorly water-soluble compounds. Nevertheless, the discovery new cocrystals remains trial-and-error approach in which hundreds coformers several experimental methods often tested. To streamline cocrystal screening, computational can be used to select most likely form cocrystal, while high-throughput screening (HTS) approaches rapidly screen them experimentally. In this manuscript, extremely soluble cilnidipine (solubility ≈30 ng/mL, 0.06 μM) was successfully discovered by applying HTS approaches. Only one resulted from with total 52 coformers, whereby molecular complementarity ranked coformer (p-toluenesulfonamide) at third position list. Dissolution studies conducted on blank FaSSIF (fasted-state simulated intestinal fluid) pH 6.5 revealed enhanced maximum achieved supersaturation equal seven times solubility crystalline drug. rates were compared better mechanistic understanding dissolution-supersaturation-precipitation behavior. The case rare occurrence emphasized importance using joint enable successful identification pharmaceutical development.

Language: Английский

Pharmaceutical cocrystals: A review of preparations, physicochemical properties and applications DOI Creative Commons

Minshan Guo,

Xiaojie Sun, Jiahui Chen

et al.

Acta Pharmaceutica Sinica B, Journal Year: 2021, Volume and Issue: 11(8), P. 2537 - 2564

Published: March 23, 2021

Pharmaceutical cocrystals are multicomponent systems in which at least one component is an active pharmaceutical ingredient and the others pharmaceutically acceptable ingredients. Cocrystallization of a drug substance with coformer promising emerging approach to improve performance pharmaceuticals, such as solubility, dissolution profile, pharmacokinetics stability. This review article presents comprehensive overview cocrystals, including preparation methods, physicochemical properties, applications. Furthermore, some examples highlighted illustrate effect crystal structures on various aspects ingredients, physical stability, chemical mechanical optical bioavailability, sustained release therapeutic effect. will provide guidance for more efficient design manufacture desired properties

Language: Английский

Citations

231
Cocrystal engineering of pharmaceutical solids: therapeutic potential and challenges DOI

Si Nga Wong,

Yu Chee Sonia Chen,

Bianfei Xuan

et al.

CrystEngComm, Journal Year: 2021, Volume and Issue: 23(40), P. 7005 - 7038

Published: Jan. 1, 2021

This highlight presents an overview of pharmaceutical cocrystal production and its potential in reviving problematic properties drugs different dosage forms. The challenges future outlook translational development are discussed.

Language: Английский

Citations

79
Coupling complementary strategy to flexible graph neural network for quick discovery of coformer in diverse co-crystal materials DOI Creative Commons
Yuanyuan Jiang, Zongwei Yang, Jiali Guo

et al.

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: Oct. 12, 2021

Abstract Cocrystal engineering have been widely applied in pharmaceutical, chemistry and material fields. However, how to effectively choose coformer has a challenging task on experiments. Here we develop graph neural network (GNN) based deep learning framework quickly predict formation of the cocrystal. In order capture main driving force crystallization from 6819 positive 1052 negative samples reported by experiments, feasible GNN is explored integrate important prior knowledge into end-to-end molecular graph. The model strongly validated against seven competitive models three independent test sets involving pharmaceutical cocrystals, π–π cocrystals energetic exhibiting superior performance with accuracy higher than 96%, confirming its robustness generalization. Furthermore, one new cocrystal predicted successfully synthesized, showcasing high potential practice. All data source codes are available at https://github.com/Saoge123/ccgnet for aiding community.

Language: Английский

Citations

64
Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials DOI Creative Commons
Gregory J. O. Beran

Chemical Science, Journal Year: 2023, Volume and Issue: 14(46), P. 13290 - 13312

Published: Jan. 1, 2023

Molecular crystal structure prediction has matured to the point where it can routinely facilitate discovery and design of new organic materials.

Language: Английский

Citations

41
Computational screening for prediction of co-crystals: method comparison and experimental validation DOI
Fateme Molajafari, Tianrui Li, Mehrnaz Abbasichaleshtori

et al.

CrystEngComm, Journal Year: 2024, Volume and Issue: 26(11), P. 1620 - 1636

Published: Jan. 1, 2024

COSMO-RS and machine learning-based models can reduce the cost of screening identifying crystal coformers, facilitating discovery new cocrystals.

Language: Английский

Citations

13
Discovery of new cocrystals beyond serendipity: lessons learned from successes and failures DOI

Si Nga Wong,

Minqi Fu,

Si Li

et al.

CrystEngComm, Journal Year: 2024, Volume and Issue: 26(11), P. 1505 - 1526

Published: Jan. 1, 2024

A holistic understanding of reaction kinetics, the presence catalysts, and annealing conditions can advance accelerate screening elusive cocrystals, expediting development novel drug cocrystals for future clinical use.

Language: Английский

Citations

11
Virtual Cocrystal Screening Methods as Tools to Understand the Formation of Pharmaceutical Cocrystals—A Case Study of Linezolid, a Wide-Range Antibacterial Drug DOI Creative Commons
Mehrnaz Khalaji, Marek J. Potrzebowski, Marta K. Dudek

et al.

Crystal Growth & Design, Journal Year: 2021, Volume and Issue: 21(4), P. 2301 - 2314

Published: Feb. 26, 2021

Experimental mechanochemical screening of cocrystals with linezolid (LIN) resulted in the formation six new crystal phases, including three neat and cocrystal hydrates, addition to seven previously described cocrystals. In an attempt understand factors governing these different experimental conditions reactions (polymorphic forms LIN presence solvents create liquid-assisted grinding conditions) were tested results compared predictions from commonly used virtual tools: molecular complementarity, hydrogen bond propensity, electrostatic potential maps. It is shown that methods can be help a molecule's preferences form particular coformers. The influence conformation on outcome also evaluated. A comparison between prediction indicates while considering set similar coformers, approach based maps seems more consistent than complementarity propensity tools. Instead, two latter approaches are recommended at early stages coformer selection. addition, intermolecular energy contribution (lattice energy) total coformers was found indicative feasibility case capable forming supramolecular synthons.

Language: Английский

Citations

51
Emerging Landscape of Computational Modeling in Pharmaceutical Development DOI
Yuriy A. Abramov, Guangxu Sun, Qun Zeng

et al.

Journal of Chemical Information and Modeling, Journal Year: 2022, Volume and Issue: 62(5), P. 1160 - 1171

Published: Feb. 28, 2022

Computational chemistry applications have become an integral part of the drug discovery workflow over past 35 years. However, computational modeling in support development has remained a relatively uncharted territory for significant both academic and industrial communities. This review considers workflows three key components preclinical clinical development, namely, process chemistry, analytical research as well product formulation development. An overview each step respective is presented. Additionally, context solid form design, special consideration given to modern physics-based virtual screening methods. covers rational approaches polymorph, coformer, counterion, solvent selection design.

Language: Английский

Citations

37
Efficient Screening of Coformers for Active Pharmaceutical Ingredient Cocrystallization DOI Creative Commons
Isaac J. Sugden, Doris E. Braun, David Bowskill

et al.

Crystal Growth & Design, Journal Year: 2022, Volume and Issue: 22(7), P. 4513 - 4527

Published: June 15, 2022

Controlling the physical properties of solid forms for active pharmaceutical ingredients (APIs) through cocrystallization is an important part drug product development. However, it difficult to know a priori which coformers will form cocrystals with given API, and current state-of-the-art cocrystal discovery involves expensive, time-consuming, and, at early stages development, API material-limited experimental screen. We propose systematic, high-throughput computational approach primarily aimed identifying API/coformer pairs that are unlikely lead experimentally observable can therefore be eliminated only brief check, from any investigation. On basis well-established crystal structure prediction (CSP) methodology, proposed derives its efficiency by not requiring expensive quantum mechanical calculations beyond those already performed CSP investigation neat itself. The assumptions tested on 30 potential 1:1 multicomponent systems (cocrystals solvate) involving 3 9 one solvent. This complemented detailed all pairs, led five new (three API-coformer combinations, polymorphic example, different stoichiometries) cis-aconitic acid polymorph. indicates that, some APIs, significant proportion could investigated thereby saving considerable effort.

Language: Английский

Citations

33
Virtual Screening, Structural Analysis, and Formation Thermodynamics of Carbamazepine Cocrystals DOI Creative Commons
Artem O. Surov, Anna G. Ramazanova, Alexander P. Voronin

et al.

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

Citations

22