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

00:00 - Introduction

01:04 - The question mark around automation: what to do with 1000+ runs  

10:15 - History of multidimensional (Design of Experiments / DOE) methods to date:

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

Episode ID: 1000678376044

GUID: d83428d0-f3a3-493a-9c63-270d95fc8cac

Release Date: 27/11/2024, 07:30:00