Structuring the unstructured: Deterministic AI and white box data cleanliness
![pharmaphorum podcast Episode 149a, young lady listening to headphones on a train while looking out the window](/sites/default/files/styles/x_large/public/2024-08/pharmaphorum_podcast-Episode-149a.jpg?itok=8ClWIazy)
Speed and safety in drug development and discovery represent some of the biggest challenges and opportunities facing life sciences companies today. It costs around $1 billion to develop one successful drug, for instance, and only one out of 10 drug candidates successfully passes clinical trial testing and regulatory approval.
In a new pharmaphorum podcast, web editor Nicole Raleigh speaks with Jane Reed, director of life sciences at Linguamatics, an IQVIA company - which, since the conversation took place, has rebranded to IQVIA-NLP - to discuss some of the major barriers preventing researchers from accessing the data they need to advance drug discovery and development and address safety concerns – and just how AI technologies can assist.
Linguamatics (now IQVIA-NLP) provides natural language processing (NLP) tools and technologies to the pharmaceutical industry. Unstructured text is one of the challenges preventing access to information – 80% of all data needed in life sciences is held in unstructured format; a huge amount of information. And having deterministic white box rules means the sought information can be surfaced in a measurable and clean – as well as useful – way.
As to what will be around in even a year’s time? Now, that’s an exciting concept…
You can listen to episode 149a of the pharmaphorum podcast in the player below, download the episode to your computer, or find it - and subscribe to the rest of the series - in iTunes, Spotify, Amazon Music, Podbean, and pretty much wherever you get your other podcasts!