Advancements in Automated Drop Setting and Imaging

for High Throughput Crystallization


About Mayank Aggarwal, Ph.D.

Mayank Aggarwal earned his Ph.D. in Biochemistry from the University of Florida (Gainesville, FL) and then worked as a scientist at the Oak Ridge National Lab (Oak Ridge, TN) for 3.5 years. After having gained an experience of over 7 years in the field of protein crystallization, he joined FORMULATRIX® as the product manager and application scientist. At FORMULATRIX, his role defines collecting feedback from the market, prioritizing feature requests, and defining requirements, thereby managing the development of crystallization software. In addition to building a customer rapport, he also is involved in assisting sales, support, and marketing.


Over the past 10 years, automation for crystallization has been widely adopted and has become general practice in most industrial and academic labs. The use of automation has increased throughput and resulted in an explosion of structure determinations. As automation has become the norm, creativity from scientists has directed implementation of new hardware solutions and continual improvement. Recently, FORMULATRIX has optimized the use of their drop setter, the NT8®, to perform seeding experiments which has been long known to provide an initial nucleation point and thus increase the number and quality of crystals that grow in a particular condition. Reliable drop setting is the backbone of crystallization experiments and the NT8 simplifies this often tedious step while increasing reproducibility with tight humidity control. Imaging is also essential in finding positive crystallization hits with FORMULATRIX offering a suite of different options. Recently, visible fluorescence imaging options have been brought to market allowing scientists to accurately distinguish between single protein crystals and protein-protein complex co-crystals, as well as detect protein crystals with ultra-high sensitivity and shorter imaging times. Nonlinear imaging, SONICC®, has proven to be exceptional for detecting sub-micron crystals and identifying positive crystallization conditions never seen before. Recent advancements in imaging methods and detectors has led to a vast improvement in signal to noise allowing identification of even more crystals. Software solutions to aid in automatic scoring of drops has also recently been implemented. We have opened up our ROCK MAKER® software to allow the coupling of machine learning algorithms to work within ROCK MAKER and automatically score drops without human intervention. With each year comes new ideas and solutions to solve our biggest challenges in structure determination, with FORMULATRIX striving to meet the needs of the crystallographers.


About the Presentation

Dr. Aggarwal presented this talk at the 68th Annual Meeting of the American Crystallographic Association on July 22, 2018 in Toronto, Canada.  The abstract was selected to be part of a session on the Current state of instrumentation, automation, status and future.


If you have any questions about the talk or would like to learn more about our automation solutions, please email: