BioCentury

12:47 AM GMT, Feb 23, 2019
This article and the information contained in BioCentury's publications and services are solely for your own personal, non-transferable licensed use and cannot be shared with any other individuals. For information about adding subscribers to your account or obtaining article reprints, please contact support@biocentury.com.
Tools & Techniques

Modeling now for precision later

GNS Healthcare Inc. is building a platform that aims to make value-based payment models unnecessary by giving companies a way to know which patients will respond before they even launch the drug.

While drug companies and payers are entering conversations about how to structure reimbursement to ensure payers are compensated for treatments that don’t perform as promised, GNS is looking beyond, using machine learning to build models that can dial in the most responsive patient population from the start.

Part of the picture is the idea of virtual patients, designed via the integration of real world evidence and clinical data through GNS’s causal learning platform.

GNS’s reverse engineering and forward simulation (REFS) platform is a hypothesis-free, causal machine learning technology that uses Bayesian network inference to build disease models. As it brings in more data, it learns from the information and updates its parameters and models accordingly.

The platform leverages genomic, clinical and real world data from electronic medical records, wearable devices

Read the full 1619 word article

This article and the information contained in BioCentury's publications and services are solely for your own personal, non-transferable licensed use and cannot be shared with any other individuals. For information about adding subscribers to your account or obtaining article reprints, please contact support@biocentury.com.