DeepAI AI Chat
Log In Sign Up

ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine

by   Ilker Demirel, et al.

Finding an optimal individualized treatment regimen is considered one of the most challenging precision medicine problems. Various patient characteristics influence the response to the treatment, and hence, there is no one-size-fits-all regimen. Moreover, the administration of even a single unsafe dose during the treatment can have catastrophic consequences on patients' health. Therefore, an individualized treatment model must ensure patient safety while efficiently optimizing the course of therapy. In this work, we study a prevalent and essential medical problem setting where the treatment aims to keep a physiological variable in a range, preferably close to a target level. Such a task is relevant in numerous other domains as well. We propose ESCADA, a generic algorithm for this problem structure, to make individualized and context-aware optimal dose recommendations while assuring patient safety. We derive high probability upper bounds on the regret of ESCADA along with safety guarantees. Finally, we make extensive simulations on the bolus insulin dose allocation problem in type 1 diabetes mellitus disease and compare ESCADA's performance against Thompson sampling's, rule-based dose allocators', and clinicians'.


page 1

page 2

page 3

page 4


Kernel Assisted Learning for Personalized Dose Finding

An individualized dose rule recommends a dose level within a continuous ...

Precision Dose-finding Cancer Clinical Trials in the Setting of Broadened Eligibility

Broadening eligibility criteria in cancer trials has been advocated to r...

A simulation study of methods for handling disease progression in dose-finding clinical trials

In traditional dose-finding studies, dose-limiting toxicity (DLT) is det...

SUBIC: A Supervised Bi-Clustering Approach for Precision Medicine

Traditional medicine typically applies one-size-fits-all treatment for t...

Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints

Phase I dose-finding trials are increasingly challenging as the relation...

The Computational Patient has Diabetes and a COVID

Medicine is moving from a curative discipline to a preventative discipli...