Computational screening of crystal co-formers

晶体共形成剂的计算筛选

• 批准号: 532625-2018
• 负责人: Johnson, Erin
• 金额: $ 1.82万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=654728
• 关键词: Computational; screening; crystal; co; formers

Solid State Pharma Inc. (SSPI) has identified that engineering stable co-crystals of active ingredients is a rising**topic in the pharmaceutical industry, with significant medical implications. Presently, their researchers rely on**experience and intuition to select promising crystal co-formers for use with a given pharmaceutical molecule.**However, a method for co-former selection based on computational predictions would provide a considerable**edge over their competition, allowing them to take an international leadership role in the development of**pharmaceutical co-crystals. Due to the computational complexity and specialized nature of the problem of**screening and scoring, neither SSPI or their competitors have the technical expertise to develop a such a**method. SSPI has consequently approached the Johnson group to address this challenge, as the PI is a world**leader in the development computational methods for the study of intermolecular interactions and has extensive**experience with applications to molecular crystals. Through consultation with SSPI, we propose to develop an**efficient computational protocol, using dispersion-corrected density-functional theory, to screen and score**potential crystal co-formers. SSPI will then use this protocol to guide their experiments in every co-crystal**screening project, providing them with a significant competitive advantage in the field of pharmaceutical**co-crystal engineering.

Solid State Pharma Inc. (SSPI) has identified that engineering stable co-crystals of active ingredients is a rising**topic in the pharmaceutical industry, with significant medical implications. Presently, their researchers rely on**experience and intuition to select promising crystal co-formers for use with a given pharmaceutical molecule.**However, a method for co-former selection based on computational predictions would provide a considerable**edge over their competition, allowing them to take an international leadership role in the development of**pharmaceutical co-crystals. Due to the computational complexity and specialized nature of the problem of**screening and scoring, neither SSPI or their competitors have the technical expertise to develop a such a**method.因此，SSPI 联系了 Johnson 小组来解决这一挑战，因为该 PI 是开发用于研究分子间相互作用的计算方法的世界**领导者，并且在分子晶体应用方面拥有丰富的**经验。 Through consultation with SSPI, we propose to develop an**efficient computational protocol, using dispersion-corrected density-functional theory, to screen and score**potential crystal co-formers. SSPI will then use this protocol to guide their experiments in every co-crystal**screening project, providing them with a significant competitive advantage in the field of pharmaceutical**co-crystal engineering.