Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Fundamental Mathematical Principles in Pharmacokinetics: Mathematical Expressions and Units01:19

Fundamental Mathematical Principles in Pharmacokinetics: Mathematical Expressions and Units

1.4K
Mathematical principles play a crucial role in pharmacokinetics, providing a framework for understanding and quantifying drug distribution and elimination dynamics in the body. By utilizing mathematical expressions and units, pharmacologists can accurately characterize the behavior of drugs, optimize dosing regimens, and predict therapeutic outcomes.
One significant application of mathematics in pharmacokinetics is the characterization of drug distribution through the volume of distribution...
1.4K
Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs

2.9K
The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
On the other hand, integral calculus focuses on...
2.9K
Drug Accumulation During Multiple Dosing: Repetitive IV Injections01:21

Drug Accumulation During Multiple Dosing: Repetitive IV Injections

215
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...
215
Biopharmaceutical Factors Influencing Drug Product Design: Overview01:22

Biopharmaceutical Factors Influencing Drug Product Design: Overview

189
Rational drug product design integrates knowledge of the drug’s physicochemical properties, formulation components, manufacturing techniques, and intended route of administration. Each factor influences the drug’s performance, including how it is released, absorbed, and eliminated in the body.The physicochemical properties of a drug—such as solubility, stability, and particle size—affect its compatibility with excipients and the choice of dosage form. Excipients, though...
189
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

128
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...
128
Drug Dissolution: Requirements and Profile Comparison01:14

Drug Dissolution: Requirements and Profile Comparison

199
The acceptance criteria for dissolution profile data are anchored in Q values, representing the percentage of drug dissolved within a specified period. This assessment unfolds in three stages:First Stage: The test passes if all six drug dosage units are equal to or greater than Q plus 5%; otherwise, the sample proceeds to the second stage.Second Stage: The average of twelve units must be equal to or greater than Q, with no unit falling below Q - 15% to pass; if not, it progresses to the final...
199

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The Multistate Pharmacy Jurisprudence Exam (MPJE): To RIP or Not to RIP.

American journal of pharmaceutical education·2026
Same author

Battle of the (Chat)Bots: Comparative Evaluation of April 2025 AI Model Accuracy on Pharmacotherapeutic Cases.

American journal of pharmaceutical education·2025
Same author

Deficiencies in Mathematical Skills Identified in First-Year Students at Two Pharmacy Institutions.

American journal of pharmaceutical education·2025
Same author

TikTok's take on adverse effects for glucagon-like peptide-1 and gastric inhibitory polypeptide receptor agonists.

Journal of the American Pharmacists Association : JAPhA·2025
Same author

Effect of changing multiple choice questions from "all of the above" to "select all that apply".

Currents in pharmacy teaching & learning·2024
Same author

Falling NAPLEX pass rates are cause for concern.

Currents in pharmacy teaching & learning·2023

Related Experiment Video

Updated: Jan 4, 2026

An In Vitro Caseum Binding Assay that Predicts Drug Penetration in Tuberculosis Lesions
12:17

An In Vitro Caseum Binding Assay that Predicts Drug Penetration in Tuberculosis Lesions

Published on: May 8, 2017

12.3K

Predicting success in pharmaceutical calculations.

Kamila A Dell1, Gwendolyn A Wantuch2

  • 1University of South Florida, College of Pharmacy, 12901 Bruce B. Downs Blvd., MDC 30, Tampa, FL 33612, United States.

Currents in Pharmacy Teaching & Learning
|November 6, 2019
PubMed
Summary
This summary is machine-generated.

Preadmission grade point average (GPA) and Pharmacy College Admission Test (PCAT) scores are key predictors of success in pharmaceutical calculations courses. These factors explain a significant portion of student performance, aiding admissions and advising strategies.

Keywords:
Pharmaceutical calculationsPreadmission variablesPredictorsSuccess

More Related Videos

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.7K
Evaluation of Drug Sorption to PVC- and Non-PVC-based Tubes in Administration Sets Using a Pump
06:08

Evaluation of Drug Sorption to PVC- and Non-PVC-based Tubes in Administration Sets Using a Pump

Published on: March 11, 2017

11.0K

Related Experiment Videos

Last Updated: Jan 4, 2026

An In Vitro Caseum Binding Assay that Predicts Drug Penetration in Tuberculosis Lesions
12:17

An In Vitro Caseum Binding Assay that Predicts Drug Penetration in Tuberculosis Lesions

Published on: May 8, 2017

12.3K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.7K
Evaluation of Drug Sorption to PVC- and Non-PVC-based Tubes in Administration Sets Using a Pump
06:08

Evaluation of Drug Sorption to PVC- and Non-PVC-based Tubes in Administration Sets Using a Pump

Published on: March 11, 2017

11.0K

Area of Science:

  • Pharmacy Education
  • Academic Performance Analysis

Background:

  • Preadmission predictors are crucial for pharmacy admissions and student advising.
  • Success in pharmaceutical calculations is vital for pharmacy practice.

Purpose of the Study:

  • To identify student-specific preadmission variables that best predict success in a pharmaceutical calculations course.
  • To inform admissions selection and academic advising practices.

Main Methods:

  • Retrospective analysis of preadmission data from 388 students (2013-2016).
  • Evaluation of 15 preadmission variables including GPA, PCAT scores, demographics, prior degrees, and credit hours.
  • Relative importance analysis to determine correlations with course grades.

Main Results:

  • Eight of 15 preadmission variables significantly correlated with pharmaceutical calculations course grades.
  • Cumulative and science-specific GPA, and quantitative and verbal PCAT scores were the strongest predictors.
  • These variables explained 26.1% of the variance in course success.

Conclusions:

  • Preadmission GPA and PCAT scores are the most effective predictors of success in pharmaceutical calculations.
  • While significant, these predictors explain only about a quarter of performance variance.
  • Further research is needed to identify additional factors influencing success in pharmaceutical calculations.