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Related Concept Videos

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

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PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure...
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Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

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Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
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Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

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Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
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Drug Administration and Therapy Phases: Overview01:26

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Drugs, the chemical agents used in diagnosing, treating, or preventing diseases, undergo a four-phase process of development: pharmaceutic, pharmacokinetics, pharmacodynamics, and therapeutic.
The pharmaceutical phase focuses on leveraging the physicochemical properties of the drug to design and manufacture an effective product. Variants include orally administered tablets or capsules, topical creams or ointments, and parenteral-delivery solutions or emulsions.
The pharmacokinetic phase...
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Pharmacokinetic–Pharmacodynamic Relationship: Problems01:24

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The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
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Pharmacodynamic Models: Linear Concentration–Effect Model01:15

Pharmacodynamic Models: Linear Concentration–Effect Model

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The linear concentration–effect model, underpinned by the principle that pharmacological effect (E) is directly proportional to plasma drug concentration (C), emerges as a pivotal simplification of the Emax model for conditions where C is significantly less than EC50. This model portrays a linear trajectory of the concentration–effect relationship when drug levels are markedly below the EC50 threshold.Despite its inherent assumption of continuous effect augmentation with increasing...
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Related Experiment Video

Updated: Feb 17, 2026

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Developing a policy maturity model for prescription digital therapeutics based on expert consensus: protocol for an

João Rocha-Gomes1, Bernardo Sousa-Pinto2, Ana Luisa Neves2,3

  • 1Faculty of Medicine, Department of Community Medicine, Health Information and Decision, University of Porto, Porto, Portugal jngomes@med.up.pt.

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Summary

This study develops a policy maturity framework to assess readiness for prescription digital therapeutics (PDTx). The eDelphi study aims to guide consistent adoption of these software-based health solutions.

Keywords:
Delphi TechniqueDigital TechnologyHealth informaticsHealth policyOrganisation of health serviceseHealth

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Area of Science:

  • Digital Health
  • Health Policy
  • Healthcare Innovation

Background:

  • Prescription digital therapeutics (PDTx) offer novel treatment solutions but face fragmented policy landscapes.
  • Variations in regulation, reimbursement, and integration create adoption uncertainties for stakeholders.
  • A systematic approach is needed to assess national or regional preparedness for PDTx.

Purpose of the Study:

  • To develop and validate a comprehensive policy maturity framework for assessing PDTx adoption readiness.
  • To guide policymakers, developers, and providers in navigating the complexities of PDTx implementation.
  • To establish a consensus-driven tool for benchmarking and advancing PDTx integration into health systems.

Main Methods:

  • An e-Delphi study involving up to three rounds with diverse experts from six stakeholder groups.
  • Purposive sampling prioritizing European experts, with potential for broader international perspectives.
  • Utilizing a 5-point Likert scale for quantitative data and open-text prompts for qualitative insights, with consensus defined as ≥70% agreement.

Main Results:

  • The study protocol outlines the iterative refinement and validation of a PDTx policy maturity framework.
  • Consensus will be reached on framework domains, scoring criteria, and maturity thresholds.
  • The validated framework will capture essential elements for PDTx policy development and implementation.

Conclusions:

  • The developed framework will provide a reference for assessing and advancing PDTx adoption.
  • It aims to reduce uncertainties and foster consistent policy development across jurisdictions.
  • Dissemination through publications and policy briefs will support digital health governance.