High Throughput Screening is a scientific experimentation method widely used in pharmaceutical research especially in the field of drug discovery. Because the large number of promising compounds for new drugs cannot be analyzed by manual labor, the screening process is automated using robotics. Robotic screening systems are used to handle microplates containing chemical compounds. These robotic screening systems perform a sequence of tasks and experiments on a given set of microplates – called the assay protocol – and generate experimentation data.
CyBio, merged into Analytik Jena AG in 2009, and the Max Planck Institute Magdeburg developed optimization methods involving GAMS to increase the throughput of robotic screening systems. The GAMS driven assay optimization has significantly boosted the production rate of high throughput screening systems and improved the quality of the experimentation data.
Before assay optimization involving GAMS was an integral part of CyBio Scheduler only experts were able to modify the timing to improve the throughput. This was feasible only for relatively small assays and was a task that involved hours of focused work. With growing complexity of assay protocols, this task is nowadays far beyond what human labor can handle.
Another common issue before an algebraic model described the screening systems with a focus on reducing idle time, were inefficiencies in the utilization of critical resources. Idle time of the compounds also leads to systematic errors in the experimentation data due to sedimentation, decay, or temperature drift.
A central part of the CyBio Scheduler is an algebraic model written in GAMS. It describes the screening systems in a way that allows the minimization of idle time for any component ensuring the most efficient utilization ratio for critical resources. Several resources may be used for different tasks, so it is possible for the screening system to simultaneously process a number of microplates using else idle devices. Short and direct microplate transfers facilitate an efficient resource usage and thereby a high production rate. The model avoids conflicts when coordinating resource access and ensures that the resulting schedule is deadlock free.
A number of constraints are inherent to the system, such as limited temporary storage or resources which cannot be used simultaneously and to which access must be coordinated. Some constraints are assay specific. Typically the user defines the target time for incubation periods including an upper and lower bound, or the maximum time between specific events. So, for example, the time between compound addition and measurement may be limited. Assay definition and these constraints build a system of disjunctive inequalities.
Due to the strict timing, micro plates follow an identical itinerary for each cycle. Fast and uniform microplate processing with the CyBio Scheduler reduces systematic errors introduced by sedimentation, decay, or temperature drift, which are difficult to quantify. An increased throughput therefore not only reduces the investment per experiment but also improves the data quality.
With the GAMS model running in the background, the CyBio Scheduler focuses on providing a simple and convenient user experience. It manages to hide the complexity of mapping an assay protocol to the current system design and finding the global optimal solution for the objective to minimize the cycle time.
The user is relieved from system layout decisions and can focus on the experiment. The CyBio Scheduler automatically inserts microplate transports where they are required, resolves conflicts in resource allocation and allows for incubations to be effortlessly specified. Depending on the number of independent tasks, involved components and constraints the resulting model may become considerably complex. However, the optimal solution is typically calculated fast enough to allow the user to verify if relaxing some constraints may lead to a better result.