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

该PFI：AIR技术翻译项目的重点是将PI Slipchenko博士实验室开发的计算方法转化为药物制剂市场，以满足对多晶型物结构和性质的快速可靠预测的需求。 药物分子晶体结构的预测性分子建模有助于更快地开发更便宜和更安全的药物。此外，由于多晶型物形式是可专利的，多晶型物的预测计算建模为开发药物制剂的公司提供了直接的商业利益。该项目将产生一个名为Simplexity的分子建模软件原型。Simplexity具有以下独特的功能：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，并通过采用自动计算工作流程节省用户的时间，它是基于专业编写的轻量级计算机代码。与GRACE、Materials Studio和CASTEP等领先的竞争软件产品相比，这些功能在性能、效率和成本节约方面具有优势。 该项目解决了从研究发现到商业应用的以下技术差距。首先，计算机代码的周期性边界条件，不同的晶体对称性和构象最小搜索将实施计算方法能够多晶型筛选。然后，所开发的计算方法将在来自晶体结构预测盲测的分子上进行验证。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，以使软件产品在软件市场上具有竞争力。参与该项目的人员，一名研究生，一名博士后研究员和本科生，将通过进行市场调查，与潜在客户互动，学习及时解决客户需求，以及参加普渡为调查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西斯内罗斯博士，MBA和阿曼达汤普森博士，MBA，他们将提供支持，指导和服务，通过业务形成，商业计划开发，财务模式开发和初始运营和行政任务，与此项目有关。

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.