# Optimizing Warfarin Dosing using Deep Reinforcement Learning

arXiv: https://arxiv.org/abs/2202.03486 · HTML: https://mlsanity.com/paper/2202.03486/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 41 references that are in the map.
- First posted on arXiv 7 Feb 2022.

## Builds on (most cited first, 1 of 1)

- [Reinforcement Learning in Healthcare: A Survey](https://mlsanity.com/paper/1908.08796/) (2019)

## Built on by (most cited first, 4 of 4)

- [On the Challenges of using Reinforcement Learning in Precision Drug Dosing: Delay and Prolongedness of Action Effects](https://mlsanity.com/paper/2301.00512/) (2023)
- [An Explainable Deep Reinforcement Learning Model for Warfarin Maintenance Dosing Using Policy Distillation and Action Forging](https://mlsanity.com/paper/2404.17187/) (2024)
- [Toward a Reinforcement-Learning-Based System for Adjusting Medication to Minimize Speech Disfluency](https://mlsanity.com/paper/2312.11509/) (2023)
- [To Start Up a Start-Up-Embedding Strategic Demand Development in Operational On-Demand Fulfillment via Reinforcement Learning with Information Shaping](https://mlsanity.com/paper/2504.05633/) (2025)

## Abstract (arXiv)

Warfarin is a widely used anticoagulant, and has a narrow therapeutic range. Dosing of warfarin should be individualized, since slight overdosing or underdosing can have catastrophic or even fatal consequences. Despite much research on warfarin dosing, current dosing protocols do not live up to expectations, especially for patients sensitive to warfarin. We propose a deep reinforcement learning-based dosing model for warfarin. To overcome the issue of relatively small sample sizes in dosing trials, we use a Pharmacokinetic/ Pharmacodynamic (PK/PD) model of warfarin to simulate dose-responses of virtual patients. Applying the proposed algorithm on virtual test patients shows that this model outperforms a set of clinically accepted dosing protocols by a wide margin. We tested the robustness of our dosing protocol on a second PK/PD model and showed that its performance is comparable to the set of baseline protocols.