Thursday, July 11, 2019

Part 5 of 6: Opportunities to accelerate projects

You may already know that the most commonly used noun in the English language is "time".  In today's world, many of us feel almost permanently under time pressure and we talk about not having enough time for all kinds of things we'd like to do.  Not having time takes on a whole new meaning for patients with life changing medical conditions, reminding us in chemical development and scale-up that opportunities to accelerate our work and commercialization of new medicines should be taken with both hands.

Achieving acceleration using modeling (e.g. Dynochem or Reaction Lab) is already well covered by extensive case studies from customers in Dynochem Resources.  Acceleration using automation of modeling and connection of modeling to other workflows is the subject of this post.  In our core software development team, we have thought a  lot about these future applications and taken steps to support their realization, providing a platform and the ‘hooks’ needed to link with other technologies.

A basic platform is the ability to automatically generate and run a large number of virtual experiments.  We use parallel processing to execute the simulations as illustrated in the short animation below.  The automation calls are exposed and may be 'scripted' and run by other programs (e.g. Python) as part of an integrated workflow.
Chemists and engineers can leverage automated generation and execution of a large set of virtual experiments with parallel processing and collation of results in convenient Excel tables and contour plots.
Tasks involved in model building may also be scripted/ automated in Dynochem 5 and Reaction Lab.  For example, area percent data may be entered in a model, a set of kinetic parameters fitted and many simulations carried out, all without human intervention.  To do this requires some scripting / code at several stages in the workflow.  Cloud computing resources (Azure or AWS) may be used for execution, leveraging our cloud licensing.

For example, the animation below shows scripted fitting of three UA (heat transfer characterization) values to three solvent tests using Dynochem 5.  This takes a short time to fit the parameters needed for each of three liquid levels in a reactor.  (The ‘fit’ button is just for demo purposes and normally the fit would be started from another scripted workflow process).
Scripted parameter fitting is possible using new function calls built into Dynochem 5 and Reaction Lab; this example illustrates automated heat transfer characterization (UA) and the techniques are equally applicable to e.g. chemical kinetics.
Additional opportunities exist in leveraging information from electronic lab notebooks (ELN) to create models for users that are already populated with features such as chemical structures and experimental data.  In a move beyond existing relatively crude self-optimizing reactor algorithms, customers are interested in closing the loop between modeling and experimentation, using model outputs to set up and execute the next experiment(s) in a fully automated loop.

Contact our support team if you'd like to discuss any of these applications further for use inside your organization.

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