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Related Concept Videos

Dosage Regimen: Individualization01:24

Dosage Regimen: Individualization

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Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...
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Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

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It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
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Dosage Regimens: Designs and Approaches01:28

Dosage Regimens: Designs and Approaches

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Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
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Measurement of Bioavailability: Pharmacodynamic Methods01:20

Measurement of Bioavailability: Pharmacodynamic Methods

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Pharmacodynamic methods provide insights into a drug's effects on physiological processes over time and play a crucial role in understanding bioavailability and therapeutic efficacy. These methods can be broadly classified into acute pharmacological and therapeutic response approaches, each with distinct mechanisms and applications.The acute pharmacological response method directly correlates a drug's physiological effects, such as ECG or pupil diameter changes, to its time course in the body.
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Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

166
Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
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Dose Size and Dosing Frequency: Determination Methods01:21

Dose Size and Dosing Frequency: Determination Methods

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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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Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids
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A utility approach to individualized optimal dose selection using biomarkers.

Pin Li1, Jeremy M G Taylor1, Spring Kong2

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.

Biometrical Journal. Biometrische Zeitschrift
|November 7, 2019
PubMed
Summary

This study introduces a novel individualized dosing strategy to optimize cancer treatment efficacy while managing toxicity. By analyzing patient data, the method tailors radiation therapy doses for lung cancer patients, improving outcomes.

Keywords:
constrained LASSOefficacy toxicity trade-offoptimal treatment regimepersonalized medicineutility

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Area of Science:

  • Oncology
  • Biostatistics
  • Medical Informatics

Background:

  • Treatment dose escalation often increases both efficacy and toxicity.
  • Validated biomarkers and prediction models enable personalized medicine approaches.
  • Existing datasets with heterogeneous doses, outcomes, and patient factors can be leveraged for dose optimization.

Purpose of the Study:

  • To develop an optimal individualized dose-finding rule for patients based on their clinical features and biomarkers.
  • To maximize patient-specific utility, defined as a weighted combination of efficacy and toxicity probabilities.
  • To achieve maximum overall efficacy under a prespecified toxicity constraint.

Main Methods:

  • Modeling binary efficacy and toxicity using logistic regression, incorporating dose, biomarkers, and their interactions.
  • Employing the LASSO (Least Absolute Shrinkage and Selection Operator) method to handle a large number of potential parameters.
  • Constraining the dose effect to be non-negative for both efficacy and toxicity.

Main Results:

  • Simulation studies demonstrated that the proposed utility-based approach improves efficacy without increasing toxicity compared to fixed dosing.
  • The methods were successfully illustrated using a dataset of lung cancer patients treated with radiation therapy.
  • The individualized dosing strategy shows potential for enhancing treatment outcomes in clinical practice.

Conclusions:

  • The proposed optimal individualized dose-finding rule effectively balances treatment efficacy and toxicity.
  • This approach offers a data-driven method for personalizing cancer therapy doses.
  • The utility maximization framework provides a robust strategy for optimizing treatment in the presence of patient-specific factors.