Artwork

Konten disediakan oleh Questex Podcasts and Fierce Life Sciences. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Questex Podcasts and Fierce Life Sciences atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.
Player FM - Aplikasi Podcast
Offline dengan aplikasi Player FM !

Discover Turbine’s way to build avatars true to patient biology [Sponsored]

18:15
 
Bagikan
 

Manage episode 447352317 series 3386301
Konten disediakan oleh Questex Podcasts and Fierce Life Sciences. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Questex Podcasts and Fierce Life Sciences atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

Discover how Turbine Simulated Cell Technologies is transforming drug development by addressing biases in training data. Guests Bence Szalai, MD, PhD, and Istvan Taisz, MD, PhD, share insights on the challenges of biased AI models in biology and introduce their groundbreaking framework, EFFECT (Evaluation Framework for Predicting Efficacy of Cancer Treatment).

Learn how Turbine's innovative bias detector ensures meaningful predictions, enhancing the accuracy of drug response models. Explore their tailored in silico biomarker discovery process, including a collaboration with Cancer Research Horizons to identify the right patient populations for new cancer drugs.

By integrating recent patient samples, Turbine achieves remarkable predictive capabilities, significantly improving model accuracy. This episode is essential for anyone interested in the future of biotechnology and precision medicine. Don’t miss this opportunity to understand how Turbine is shaping the landscape of drug development.

Listen now and be part of the conversation that’s paving the way for more effective cancer treatments.

See omnystudio.com/listener for privacy information.

  continue reading

100 episode

Artwork
iconBagikan
 
Manage episode 447352317 series 3386301
Konten disediakan oleh Questex Podcasts and Fierce Life Sciences. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Questex Podcasts and Fierce Life Sciences atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

Discover how Turbine Simulated Cell Technologies is transforming drug development by addressing biases in training data. Guests Bence Szalai, MD, PhD, and Istvan Taisz, MD, PhD, share insights on the challenges of biased AI models in biology and introduce their groundbreaking framework, EFFECT (Evaluation Framework for Predicting Efficacy of Cancer Treatment).

Learn how Turbine's innovative bias detector ensures meaningful predictions, enhancing the accuracy of drug response models. Explore their tailored in silico biomarker discovery process, including a collaboration with Cancer Research Horizons to identify the right patient populations for new cancer drugs.

By integrating recent patient samples, Turbine achieves remarkable predictive capabilities, significantly improving model accuracy. This episode is essential for anyone interested in the future of biotechnology and precision medicine. Don’t miss this opportunity to understand how Turbine is shaping the landscape of drug development.

Listen now and be part of the conversation that’s paving the way for more effective cancer treatments.

See omnystudio.com/listener for privacy information.

  continue reading

100 episode

Semua episode

×
 
Loading …

Selamat datang di Player FM!

Player FM memindai web untuk mencari podcast berkualitas tinggi untuk Anda nikmati saat ini. Ini adalah aplikasi podcast terbaik dan bekerja untuk Android, iPhone, dan web. Daftar untuk menyinkronkan langganan di seluruh perangkat.

 

Panduan Referensi Cepat