Deep Machine Learning

Working on problems that don’t yield to physics-based models, or physics-based models take too long to run?

Simulation and modeling have evolved considerably in the past 40-50 years, since computers first began to be used for such purposes. Simulations today run thousands of times faster and with greater mechanistic detail than when we landed on the moon in 1969. Yet there remain certain kinds of problems that are not yet solvable via simulation, as well as some where simulation can work, but the run times are too long to be practical.

Machine learning models have also evolved:

We have applied our advanced machine learning (“artificial intelligence”) methods to highly complex problems, such as:

  • Drug Discovery and Toxicology
  • Magnetic resonance imaging
  • And other research areas

Want to optimize a design but modifications take too long to evaluate? Or there is no mechanistic solution available? Turn your data into very fast and accurate models:

Computerized design optimization starts with an initial guess, or baseline design, and then some number of design parameters are systematically adjusted to work toward an optimum solution. As each parameter is adjusted, the new design must be evaluated. If that new design requires an inordinate amount of computer time (e.g., CFD) or if there is no mechanistic solution in existence, then true optimization is prevented, or at best restricted, and less efficient designs result.

Simulations Plus has re-purposed it’s advanced machine learning technology, originally developed and proven best-in-class for molecule property prediction in pharmaceutical chemistry, to enable rapid development of custom applications for a wide variety of problems.