Software Application For Use In Drug Discovery

Software Application For Use In Drug Discovery

If a potentially useful drug fails to satisfy key performance parameters such as those related to physicochemical/pharmacokinetic properties like solubility and stability, it may be delayed or abandoned. Repercussions may include loss of time, money and life. Co-crystallization offers one of the most promising approaches to improve physicochemical/ pharmacokinetic properties of active pharmaceutical ingredients (APIs), without loss of biological activity by combining them with a suitable co-former. This may create a more effective and marketable form of the drug. In the last decade, ‘co-crystals’ and ‘co-crystallization technologies’ have rapidly emerged as new avenues for the development of a wide range of high-value crystalline organic solids with applications in pharmaceutics, agrochemicals, explosives, energetics, food and the fragrance industry. Researchers at Kansas State University have developed “CoForm” a computational screening software to automatically predict the likelihood of successful co-crystallization of an API and an appropriate molecular partner, the co-former.

CoForm is a desktop application that offers inexpensive, fast, reliable, user-friendly co-crystal prediction. Cocrystals have been used to improve APIs in a number of ways. However, it has not been fully integrated into advanced technologies for materials applications due to the amount of experimental work, time, and money it takes to identify successful co-former candidates. Additionally, methods in the literature are costly, very complex, require in-depth knowledge of theoretical chemistry and quantum mechanical methods, and may be unsuitable for systematic screens. CoForm, which is based on a foundation of extensive experimental data, is a versatile tool offering a cheaper, faster, and more reliable method for predicting when a pair of molecules will form a co-crystal, and when they will not. Potential positive and negative partners are ranked based on the closeness of match. The technology is made available through a user-friendly software application where even a novice can interpret the results.


  • Automatic, inexpensive, rapid, and user-friendly software with easy to interpret results for predicting co-crystal formation
  • Helps facilitate reliable synthesis of new co-crystals of high-value solid materials
  • Based on extensive and unique experimental data
  • Find a suitable co-former candidate for any given small-molecule API
  • Potential partners are ranked based on the closeness of match
  • The software is platform independent and may work on Windows, Linux, and Mac OSX

Applications and Commercial Opportunities

  • Prediction of co-crystallization
  • Pharmaceutical development
  • Active pharmaceutical ingredient (API)
  • Agrochemical development

Additional Details

Owner: Kansas State University

IP Protection Status: Pending Patent