To explore what the future of multidimensional experiments might look like, we decided to look back.

In this episode, we explored how different multi-dimensional (aka Design of Experiments, or DOE) methods have come about to date. 

Then, we pondered how these different methods, together with tech and software innovations, have brought both opportunities to scale multidimensional experimentation, and exciting questions on the best way to go about it.

Conversation highlights

• 10:58 - Era 1: Factorial designs came about, and benefited agriculture

  
  



• 15:12 - Era 2: Response surface methods emerged in process industries

  
  



• 18:17 - Era 3: Software packages helped design the “optimal” experiment  

  
  



• 21:29 - “DOE 4.0”: Bayesian optimization, and the pros and cons for biology