PFI:AIR - TT: Automated Software for Advanced Molecular Modeling of Biomolecules and Materials

这个PFI: AIR技术翻译项目的重点是将PI博士Slipchenko实验室开发的计算方法翻译到药物配方市场，以满足对多晶结构和性质快速可靠预测的需求。药物分子晶体结构的预测分子模型有助于更快地开发更便宜、更安全的药物。此外，由于多晶型可申请专利，多晶型的预测计算建模为开发药物配方的公司提供了直接的商业利益。该项目将产生一个名为Simplexity的分子建模软件的原型。简单性具有以下独特的特征：它提供了计算预测的准确性和消耗的计算时间之间的折衷，它简化了计算建模并通过采用自动化计算工作流节省了用户的时间，并且它基于专业编写的轻量级计算机代码。与领先的竞争软件产品（如GRACE、Materials Studio和CASTEP）相比，这些功能在性能、效率和成本节约方面具有优势。该项目解决了以下技术差距，因为它从研究发现转化为商业应用。首先，将实现不同晶体对称和构象最小搜索的周期性边界条件的计算机代码，使计算方法能够进行多晶筛选。然后通过晶体结构预测盲试验对所建立的计算方法进行验证。此外，将开发图形用户界面、自动计算工作流程和作业管理器，使软件产品在软件市场上具有竞争力。参与该项目的人员，包括一名研究生、一名博士后和一名本科生，将通过进行市场研究、与潜在客户互动、学习及时解决客户需求，以及参加普渡大学为研究人员和创新者组织的活动，获得创业和技术翻译经验。该项目聘请了商业伙伴Mark Cisneros博士（MBA）和Amanda Thompson博士（MBA），他们将在与该项目相关的业务形成、业务计划制定、财务模型开发以及初始运营和管理任务方面提供支持、指导和服务。

This PFI: AIR Technology Translation project focuses on translating computational methodologies developed in the PI Dr. Slipchenko lab to the pharmaceutical formulation market to fill the need for fast and reliable predictions of polymorph structures and properties. The predictive molecular modeling of crystalline structures of drug molecules facilitates faster development of cheaper and safer drugs. Additionally, as polymorph forms are patentable, predictive computational modeling of polymorphs provides direct commercial benefit to companies developing drug formulations. The project will result in a prototype of the molecular modeling software called Simplexity. Simplexity has the following unique features: it provides a compromise between accuracy of computational predictions and consumed computational time, it simplifies computational modeling and saves user's time by employing automated computational workflows, and it is based on professionally written lightweight computer codes. As compared to the leading competing software products such as GRACE, Materials Studio and CASTEP, these features provide advantages in performance, efficacy, and cost savings. This project addresses the following technology gaps as it translates from research discovery toward commercial application. First, computer codes for periodic boundary conditions for different crystal symmetries and conformational minima search will be implemented to make computational methodology capable for polymorph screening. Then the developed computational methodology will be validated on molecules from crystal structure prediction blind tests. Additionally, graphical user interface, automated computational workflows and a job manager will be developed to make the software product competitive on a software market. Personnel involved in this project, a graduate student, a postdoctoral fellow, and undergraduate students, will receive entrepreneurship and technology translation experiences through conducting market research, interacting with potential customers, and learning to address customers' needs in a timely manner, as well as participating in Purdue-organized activities for investigators and innovators. The project engages business partners Dr. Mark Cisneros, MBA and Dr. Amanda Thompson, MBA, who will provide support, guidance and services through business formation, business plan development, financial model development and initial operational and administrative tasks, related to this project.