For successful rational indexing, you can’t just make a guess and refine. Each unit cell is defined by six parameters, meaning there could be billions of potential solutions. Your probability of being correct is abysmal.
Your best approach is to use advanced indexing tools. Machine learning can transform rational indexing from an intellectual challenge into the click of a button.
In this episode, Simon Bates , VP of Science and Technology at Rigaku, speaks with us about the problem that rational indexing solves, its uses in pharma since the 1940s, and near-future breakthroughs that will make it more efficient.
We discuss:
- Using diffraction data to identify crystal unit cells
- How rational indexing reduces the search space
- Why pharma should focus on identifying crystal unit cells
- The evolution of advanced indexing tools
For more insights into the pharmaceutical industry, subscribe to the show on Apple Podcasts, Spotify, or w herever podcasts are found.
Listening on a desktop & can’t see the links? Just search for The Pharma Lab Show in your favorite podcast player.
Your best approach is to use advanced indexing tools. Machine learning can transform rational indexing from an intellectual challenge into the click of a button.
In this episode, Simon Bates , VP of Science and Technology at Rigaku, speaks with us about the problem that rational indexing solves, its uses in pharma since the 1940s, and near-future breakthroughs that will make it more efficient.
We discuss:
- Using diffraction data to identify crystal unit cells
- How rational indexing reduces the search space
- Why pharma should focus on identifying crystal unit cells
- The evolution of advanced indexing tools
For more insights into the pharmaceutical industry, subscribe to the show on Apple Podcasts, Spotify, or w herever podcasts are found.
Listening on a desktop & can’t see the links? Just search for The Pharma Lab Show in your favorite podcast player.
10/15/21 • 25 min
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