I discuss clinical pharmacology and pharmacometrics topics from the perspective of drug development scientists. I share my expertise and knowledge about designing and conducting clinical pharmacology studies and discuss how to analyze the data using the most effective approaches. I draw from my experience of over 20 years working in drug development organizations and consultancies.
In this episode I discuss bioequivalence testing and how it was developed to support generic drug approvals, but is now a mainstream tool for all of drug development. I discuss the basics of what bioequivalence means, how the studies are designed, and then how to perform the statistical analysis. I end with some examples of how this can be used for both generic drug and innovator drugs to support labeling.
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In this episode we’re going to define Volume of Distribution, look at the different types of Volume of Distribution parameters, talk about how we actually calculate it, examine what drives its value, and—most importantly—discuss why it matters for the decisions we make every day in drug development.
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This episode is an interview with Michael Stackhouse, the Chief Innovation Officer at Atorus Research. We discussed a variety of topics such as modern data science tools, why regulatory agencies want to get rid of SAS transport files in favor of Dataset JSON file formats, and how AI is being used in data programming and data science.
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This episode is an interview with Dr. Wouter Vaes, the Chief Science Officer of Peregrion. We discuss how accelerator mass spectrometry is being used in early clinical development for drug metabolism and pharmacokinetics. We discuss using this technology to support development of oncology agents, determining absolute bioavailability without IV toxicology work, and more.
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This episode is an interview with Aruna Dhontabhaktuni, Founder and CEO of RegKey, a regulatory intelligence platform that uses AI. The discussion touches on how companies can leverage large language model AI tools to accelerate regulatory strategy work.
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This episode is a collection of my thoughts on model-informed drug development and where different modeling modalities fit into the development schedule. These are just my opinions and each development program is different.
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In this episode I chat with Ahmed Elmokadem about QSP modeling. Ahmed, from Metrum Research Group, is an expert consultant in QSP modeling and how it can be used to provide a framework to connect mechanistic understanding with clinical pharmacology and decision-making.
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In this episode I discuss dataset-JSON, a new proposed data standard for CDISC files and explain some of the CDISC files I use in my clinical pharmacology work. I end with some brief thoughts about the ACoP 2025 meeting in Denver in October 2025.
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Copyrig...
In this episode I discuss review statistics that are commonly used in pharmacokinetics and pharmacometrics work. I reviewed the basic theory of the normal distribution and then discussed various individual statistics that we use in PK work. I concluded with some examples of which statistics I use in my work.
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In this episode I discuss clinical trial simulations. I review concepts of trial simulation including different variability terms and when to use them. I also share my thoughts on 3 different applications used in clinical trial simulation.
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In this episode I discuss R Shiny and how it can be used for building clinical pharmacology tools. I provide an overview of the technology, suggest a few example use cases, and then walk through a specific practical example of predicting AUC and Cmax for future doses from observed data. I end with a discussion of the benefits and challenges of using R Shiny for clinical pharmacology tools.
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In this episode I discuss noncompartmental analysis. I categorize PK parameters calculated by NCA methods as either Important, Useful, or Questionable. I also share my thoughts on how to report PK parameters calculated using NCA methods in nonclinical and clinical reports. I want to hear your thoughts about this episode. Do you agree or disagree with my categorization of PK parameters? Why? Use the links below to let me know.
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In this episode I review the process I follow for fitting a base pharmacokinetic (PK) model. I talk from the perspective of an individual PK model, but include some differences associated with population PK models. I go over exploratory data analysis, getting initial estimates, and how to choose between different base models.
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In this episode I discuss different algorithms used for pharmacometrics modeling. I describe difference between maximum likelihood and expectation maximization methods. I review the FO and FOCEI maximum likelihood algorithms. I then review SAEM, IMP, and QRPEM expectation maximization algorithms that are available. I conclude with an brief explanation of the difference between parameter estimation and parameter uncertainty.
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In this episode I discuss my experience as an independent consultant in the clinical pharmacology and pharmacometrics space. I talk about how I got from high school to become a consultant. I touched on the many different activities I do as an independent consultant. I shared a bit about how I handle compensation with clients and how I pay myself. And I ended with some brief comments about getting customers.
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In this episode I discuss using nlmixr for population PK modeling in R. I give an overview of the software package, describe the installation process, and walk through a simple example. Overall, nlmixr is a nice package that can be used for most modeling activities you encounter. It eliminates the need for a license since it is open-source. There are some challenges associated with using R for modeling with large datasets and long-...
In this episode I discuss power calculations using the R package PowerTOST. I gave an introduction to power calculations and the statistical premise. I reviewed bioequivalence study designs that are commonly used for generic drug development, food effect evaluation, and drug-drug interaction studies.
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In this episode I share a couple short clips from my conversation with Chad Briscoe and Greg Austin from BioTalk Unzipped (www.biotalkunzipped.com). We chat about a variety of topics including artificial intelligence and challenges with cell therapy development. You can hear the entire conversation on the BioTalk Unizipped podcast or YouTube channel in January. For now, enjoy these clips from the upcoming show!
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In this episode I discuss toxicokinetic analysis. This is the analysis of exposure data to support animal toxicology studies. I review the purpose of toxicology studies and how exposure metrics are used. Then I discuss different blood sampling schemes, and how to calculate exposure parameters for both full profiles and mean profiles.
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This episode is a discussion of steady state pharmacokinetics. Steady state occurs when the amount of drug input is equivalent to the amount of drug elimination in a dosing interval. I discuss some key PK parameters at steady state and how to use them. I also discuss different methods of confirming that you have reached steady state.
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