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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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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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Dosage Regimen: Multiple Oral Dosage01:25

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Understanding how a drug's concentration fluctuates within the body over time is crucial in pharmacokinetics, particularly with multiple oral doses. A graphical representation of multiple oral dosages provides insight into these dynamics. Typical accumulation curves of a drug's concentration in the body reveal a sawtooth pattern, indicating periodic peaks and troughs correlating with each dose administration and the drug's subsequent elimination.The plasma concentration at any time during an...
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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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Calculating drug dosage and accumulation in multiple-dose regimens is crucial for achieving therapeutic efficacy while avoiding toxicity. This involves determining the plasma drug concentrations over time to optimize dosing schedules. The principle of superposition is fundamental in this process, allowing for the prediction of drug concentration in plasma following multiple doses based on single-dose data.The principle of superposition asserts that the plasma concentration-time curves from...
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Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
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Estimation of Maximum Recommended Therapeutic Dose Using Predicted Promiscuity and Potency.

T Liu1, T Oprea2, O Ursu2

  • 1Department of Genetics, Stanford University, Stanford, California, USA.

Clinical and Translational Science
|October 14, 2016
PubMed
Summary
This summary is machine-generated.

A new model predicts maximum recommended therapeutic doses (MRTD) for small molecule drugs by analyzing protein-drug interactions. This approach identifies high-risk off-targets (HROTs) to improve drug discovery and explain adverse reactions.

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Area of Science:

  • Pharmacology
  • Computational Chemistry
  • Drug Discovery

Background:

  • Accurate prediction of maximum recommended therapeutic dose (MRTD) is crucial for drug safety.
  • Understanding protein-drug interactions and drug promiscuity is key to predicting therapeutic outcomes.
  • Previous work established methods for computational estimation of drug promiscuity and potency.

Purpose of the Study:

  • To develop a simple model for predicting the MRTD of small molecule drugs.
  • To leverage computational estimations of drug promiscuity and potency for MRTD prediction.
  • To identify potential high-risk off-targets (HROTs) associated with low-dose drugs.

Main Methods:

  • A linear model was constructed using data from 238 small molecular drugs.
  • The model incorporates assessments of likely protein-drug interactions, drug promiscuity, and potency.
  • The model was validated by predicting MRTDs for nonsteroidal antiinflammatory drugs (NSAIDs) and antiretroviral drugs.

Main Results:

  • The developed model successfully predicted MRTDs for tested NSAIDs and antiretroviral drugs.
  • 83 proteins were identified as high-risk off-targets (HROTs) frequently associated with low drug doses.
  • The model provides insights into MRTD variations, particularly for drugs with severe adverse reactions linked to HROTs.

Conclusions:

  • A straightforward computational model can predict drug MRTD based on protein-drug interactions.
  • The identification of HROTs offers a valuable tool for early-stage drug discovery and safety assessment.
  • This model aids in understanding the mechanisms behind severe adverse drug reactions related to off-target interactions.