Pharmacokinetic model of human exposure to ciprofloxacin through consumption of fish.

Fluoroquinolones are broad-spectrum antibiotics that accumulate in the environment. To assess human exposure through the food chain, we developed a pharmacokinetic model of fluoroquinolone accumulation in fish and a human pharmacokinetic model to predict gastrointestinal concentrations of ciprofloxacin, a common fluoroquinolone, following consumption of fish. At 70 ng/L ciprofloxacin, the average in North American surface waters, the fish steady-state concentration was calculated to be 7.5 × 10-6 µg/g. Upon human consumption of the FDA-recommended portion of 113 g of fish containing this ciprofloxacin level, the predicted human intestinal concentration was 2 × 10-6 µg/mL. At 4 × 106 ng/L (4 µg/mL) ciprofloxacin, the highest recorded environmental measurement, these numbers were 0.42 µg/g in fish and 0.1 µg/mL in the human intestine. Thus, based on the ciprofloxacin MIC for E. coli of 0.13 µg/mL, background environmental ciprofloxacin levels are unlikely to be problematic, but environmental pollution can result in high intestinal levels that may cause gut dysbiosis and antibiotic resistance.

Teaching of drug disposition using physiologically based pharmacokinetic modeling software: GastroPlus as an educational tool.

Physiologically based pharmacokinetic (PBPK) modeling requires an understanding of chemical, physiologic, and pharmacokinetic principles. Active learning with PBPK modeling software (GastroPlus) may be useful to teach these scientific principles while also teaching software operation. To examine this issue, a graduate-level course was designed using learning objectives in science, software use, and PBPK model application. These objectives were taught through hands-on PBPK modeling to answer clinically relevant questions. Students demonstrated proficient use of software, based on their responses to these questions, and showed an improved understanding of scientific principles on a pre- and post-course assessment. These outcomes support the effectiveness of simultaneous teaching of interdependent software and science.NEW & NOTEWORTHY Physiologically based pharmacokinetic (PBPK) modeling is a major growth area in drug development, regulatory submissions, and clinical applications. There is a demand for experts in this area with multidisciplinary backgrounds. In this article, we describe a course designed to teach PBPK modeling and the underlying scientific principles in parallel.

Prediction of Peptide and TCR CDR3 Loops in Formation of Class I MHC-Peptide-TCR Complexes Using Molecular Models with Solvation.

Formation of major histocompatibility (MHC)-peptide-T cell receptor (TCR) complexes is central to initiation of an adaptive immune response. These complexes form through initial stabilization of the MHC fold via binding of a short peptide, and subsequent interaction of the TCR to form a ternary complex, with contacts made predominantly through the complementarity-determining region (CDR) loops of the TCR. Stimulation of an immune response is central to cancer immunotherapy. This approach depends on identification of the appropriate combinations of MHC molecules, peptides, and TCRs to elicit an antitumor immune response. This prediction is a current challenge in computational biochemistry. In this chapter, we introduce a predictive method that involves generation of multiple peptides and TCR CDR 3 loop conformations, solvation of these conformers in the context of the MHC-peptide-TCR ternary complex, extraction of parameters from the generated complexes, and use of an AI model to evaluate the potential for the assembled ternary complex to support an immune response.

Prediction of Water Distributions and Displacement at Protein-Ligand Interfaces.

The retention and displacement of water molecules during formation of ligand-protein interfaces play a major role in determining ligand binding. Understanding these effects requires a method for positioning of water molecules in the bound and unbound proteins and for defining water displacement upon ligand binding. We describe an algorithm for water placement and a calculation of ligand-driven water displacement in >9000 protein-ligand complexes. The algorithm predicts approximately 38% of experimental water positions within 1.0 Å and about 83% within 1.5 Å. We further show that the predicted water molecules can complete water networks not detected in crystallographic structures of the protein-ligand complexes. The algorithm was also applied to solvation of the corresponding unbound proteins, and this allowed calculation of water displacement upon ligand binding based on differences in the water network between the bound and unbound structures. We illustrate use of this approach through comparison of water displacement by structurally related ligands at the same binding site. This method for evaluation of water displacement upon ligand binding may be of value for prediction of the effects of ligand modification in drug design.

Integration of Clinical and Scientific Principles in the Teaching of Drug-Drug Interactions.

Evaluation of drug-drug interactions (DDIs) is an integral part of pharmacy practice worldwide. An understanding of the scientific mechanisms behind and the clinical implications of DDIs is important for proper management of pharmacotherapy. Here, we describe an integrated approach to teaching both aspects of DDIs as a standalone module in diverse course settings. These include on-campus and online delivery to international and local audiences in small and large classes. We describe the scientific, clinical, and integrated learning objectives of the module, and we show how these can be achieved through group projects based on published DDI case reports.

Using Interactive Fiction to Teach Clinical Decision-Making in a PharmD Curriculum.

Teaching of clinical decision-making is an important component of health professions education. Patient case examples are widely used in didactic coursework to teach this material, but engaging all learners in large, lecture-based courses remains a challenge. Interactive fiction (IF), a digital choose-your-own-adventure media, provides an accessible way for students to individually explore the narrative of a patient-case in a safe environment. Here, we report the development of interactive, digital patient-cases (eCases) using Twine, a free IF development platform. Fourteen eCases were developed in collaboration with 11 faculty members and were used in seven different PharmD courses over three semesters. eCase content was developed by faculty members for their respective instructional topics and accessed via Web browsers on students' personal electronic devices. eCases were received positively by students, with > 90% of students reporting that eCases were easy to use, helped them learn the material at their own pace, and gave them an opportunity to learn from mistakes. Student self-perceived confidence also increased significantly after eCase use. Faculty reported that eCases took more time to develop than conventional cases, but were easier to deliver and provided better student engagement. IF is an accessible media for creating and delivering low-fidelity interactive patient cases that can engage all students in a large class. eCases allow students to apply their knowledge, practice clinical decision-making, and safely learn from their mistakes. eCases are versatile and well suited for both in-person and virtual teaching across a variety of health professions programs to teach clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40670-021-01245-7.

Ligand-specific pharmacogenetic effects of nonsynonymous mutations.

In pharmacogenomics, variable receptor phenotypes, resulting from genetic polymorphisms, are often described as a change in protein function or regulation observed upon exposure to a drug. However, in some instances, phenotypes are defined using a class of medications rather than individual drugs. This paradigm assumes that a variation associated with a drug response phenotype will retain the magnitude and direction of the effect for other drugs with the same mechanism of action. However, nonsynonymous polymorphisms may have ligand-specific effects. The purpose of this study was to investigate the potential for point mutations to asymmetrically affect the binding of different drugs to a common target. Ligand binding data from site-directed mutagenesis studies on five G-protein coupled receptors (beta-1 and -2 adrenergic, dopamine D2, angiotensin II and mu-opioid receptor) were collected and analyzed. Binding data from 81 studies for 253 ligands with 447 mutant proteins, including 10 naturally occurring human variants, were analyzed, yielding 1989 mutation-ligand pairs. Fold change in binding affinity for mutant proteins, relative to the wild-type, for different drugs was examined for ligand-specific effects, with a fold-change difference of one or more orders of magnitude between agents considered significant. Of the mutations examined, 49% were associated with ligand-specific effects. One human variant (T164I, beta-2 adrenergic receptor) showed ligand-specific effects for antiasthmatic agents. These results indicate that ligand-specific changes in binding are a possible consequence of missense mutations. This implies that caution needs to be exercised when grouping drugs together during design or interpretation of genotype-phenotype association studies.