Skip to content
#artificial intelligence Book Open access

Precision Dosing, Adaptive Algorithms and AI driven Prescribing

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education

Abstract

Personalized drug exposure The concept of precision dosing is the next generation of drug-based therapy, which stops at a stereotyped regimen and gets triggered by targeted biological, clinical, and digital data streams that are unique to each patient. The use of pharmacometrics, real-time therapeutic drug monitoring, artificial intelligence (AI), and adaptive algorithmic modeling has allowed more active and adjustable systems of prescribing. Adaptive dosing models involve the introduction of pharmacokinetic-pharmacodynamic (PK-PD) mechanistic modeling and an integration of pharmacogenomic data and organ functions, wearable biosensor, and real-world data are used to continuously optimize clinical treatments. Prescribing AI improves predictive accuracy, risk stratification, and clinical decision support, which reduces the adverse drug reactions and improves the efficacy outcome. Nonetheless, this has to be implemented under the strict governance, and the validation of algorithms, the protection of transparency, and the government by pharmacists. The scientific basis of precision dosing, adaptive clinical algorithms architecture, AI-based prescribing platforms, ethical and regulatory issues, as well as the widening role of pharmacists as intelligent therapeutic systems custodians are explored in this chapter. Through the combination of computational analytical tools and clinical knowledge, precision dosing and AI-based prescribing represent a future-capable structure of pharmacy care, which improves safety, customization and the sustainability of the healthcare system.

View source

Similar papers

#artificial intelligence Conference Open access Jun 2018

Gibson Env: Real-World Perception for Embodied Agents

This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.

F. Xia, Amir Zamir, Zhi-Yang He et al. · 1,069 citations · ⚡112
#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17

KTO: Model Alignment as Prospect Theoretic Optimization

This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al. · 195 citations · ⚡28
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#artificial intelligence Review Nov 2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...

Masoud Mohseni, Artur Scherer, K. Johnson et al. · 121 citations · ⚡9

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.