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Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
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Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
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Updated: Jun 9, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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Published on: February 6, 2019

Optimal radiotherapy dose scheduling with variable fraction sizes and breaks via sequential mixed-integer convex

Anqi Fu1, Zeno Gouw2, Jeho Jeong1

  • 1Department of Medical Physics, Memorial Sloan-Kettering, 321 East 61st Street, 10065, NY, USA.

Physics and Imaging in Radiation Oncology
|June 8, 2026
PubMed
Summary
This summary is machine-generated.

Optimized radiotherapy schedules with variable fraction sizes and breaks improve tumor control probability (TCP). This novel approach accounts for hypoxia and cellular competition, outperforming standard treatments.

Keywords:
Mixed-integer programmingNumerical optimizationOptimal controlRadiation oncologyTreatment planning

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Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources
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Published on: October 6, 2023

Area of Science:

  • Radiation Oncology
  • Mathematical Modeling
  • Cancer Biology

Background:

  • Standard radiotherapy uses equi-dose fractions, but non-uniform schedules may enhance tumor control.
  • Tumor response is influenced by cellular resource competition and hypoxia.

Purpose of the Study:

  • To develop an optimization method for constructing non-uniform radiotherapy dose schedules.
  • To improve tumor control probability (TCP) by optimizing fraction size and treatment breaks.

Main Methods:

  • Formulated dose scheduling as a finite-horizon optimal control problem.
  • Employed a convex-concave procedure to solve the nonconvex problem with constraints on normal tissue dose and daily limits.
  • Calibrated a tumor dose-response model to head-and-neck squamous cell carcinoma.

Main Results:

  • Optimal schedules featured an initial "primer shot", a 1-week break, followed by smaller fractions and a final large fraction.
  • The schedule leverages reoxygenation of hypoxic cells during the break for increased radiosensitivity.
  • Achieved a 12% higher TCP compared to standard equi-dose schedules in computational experiments.

Conclusions:

  • An optimization method for non-uniform radiotherapy schedules was successfully developed.
  • The method effectively models tumor response under hypoxia, leading to significant TCP improvements.
  • This approach offers a promising strategy for enhancing radiotherapy efficacy.