Sources of pharmacokinetic and pharmacodynamic variability and clinical pharmacology studies of antiseizure medications in the pediatric population.

Multiple treatment options exist for children with epilepsy, including surgery, dietary therapies, neurostimulation, and antiseizure medications (ASMs). ASMs are the first line of therapy, and more than 30 ASMs have U.S. Food and Drug Administration (FDA) approval for the treatment of various epilepsy and seizure types in children. Given the extensive FDA approval of ASMs in children, it is crucial to consider how the physiological and developmental changes throughout childhood may impact drug disposition. Various sources of pharmacokinetic (PK) variability from different extrinsic and intrinsic factors such as patients' size, age, drug-drug interactions, and drug formulation could result in suboptimal dosing of ASMs. Barriers exist to conducting clinical pharmacological studies in neonates, infants, and children due to ethical and practical reasons, limiting available data to fully characterize these drugs' disposition and better elucidate sources of PK variability. Modeling and simulation offer ways to circumvent traditional and intensive clinical pharmacology methods to address gaps in epilepsy and seizure management in children. This review discusses various physiological and developmental changes that influence the PK and pharmacodynamic (PD) variability of ASMs in children, and several key ASMs will be discussed in detail. We will also review novel trial designs in younger pediatric populations, highlight the role of extrapolation of efficacy in epilepsy, and the use of physiologically based PK modeling as a tool to investigate sources of PK/PD variability in children. Finally, we will conclude with current challenges and future directions for optimizing the efficacy and safety of these drugs across the pediatric age spectrum.

Advancing the utilization of real-world data and real-world evidence in clinical pharmacology and translational research-Proceedings from the ASCPT 2023 preconference workshop.

Real-world data (RWD) and real-world evidence (RWE) are now being routinely used in epidemiology, clinical practice, and post-approval regulatory decisions. Despite the increasing utility of the methodology and new regulatory guidelines in recent years, there remains a lack of awareness of how this approach can be applied in clinical pharmacology and translational research settings. Therefore, the American Society of Clinical Pharmacology & Therapeutics (ASCPT) held a workshop on March 21st, 2023 entitled "Advancing the Utilization of Real-World Data (RWD) and Real-World Evidence (RWE) in Clinical Pharmacology and Translational Research." The work described herein is a summary of the workshop proceedings.

Beyond lectures and practical courses: Teaching pharmacology using imaginative pedagogical tools.

Pharmacology has broadened its scope considerably in recent decades. Initially, it was of interest to chemists, doctors and pharmacists. In recent years, however, it has been incorporated into the teaching of biologists, molecular biologists, biotechnologists, chemical engineers and many health professionals, among others. Traditional teaching methods, such as lectures or laboratory work, have been superseded by the use of new pedagogical approaches to enable a better conceptualization and understanding of the discipline. In this article, we present several new methods that have been used in Spanish universities. Firstly, we describe a teaching network that has allowed the sharing of pedagogical innovations in Spanish universities. A European experience to improve prescribing safety is described in detail. The use of popular films and medical TV series in biomedical students shows how these audiovisual resources can be helpful in teaching pharmacology. The use of virtual worlds is detailed to introduce this new approach to teaching. The increasingly important area of the social aspects of pharmacology is also considered in two sections, one devoted to social pharmacology and the other to the use of learning based on social services to improve understanding of this important area. Finally, the use of Objective Structured Clinical Evaluation in pharmacology allows to know how this approach can help to better evaluate clinical pharmacology students. In conclusion, this article allows to know new pedagogical methods resources used in some Spanish universities that may help to improve the teaching of pharmacology.

[Management of high-alert medications by clinical pharmacological approaches].

During the past decade, many high-alert medications have been developed and used in clinical practice. Particularly, in the pharmacotherapy of high-alert medications with large individual differences, more attention is needed. To achieve appropriate and individualized pharmacotherapy, there are many issues to be addressed from a clinical pharmacology perspective, such as enhanced monitoring and prior risk identification. This paper is focusing on the therapeutic drug monitoring of molecularly targeted anticancer drugs, and the provision of real-world evidence based on the clinical implementation of pharmacogenetic testing.

Integrating clinical pharmacology and artificial intelligence: potential benefits, challenges, and role of clinical pharmacologists.

INTRODUCTION: The integration of artificial intelligence (AI) into clinical pharmacology could be a potential approach for accelerating drug discovery and development, improving patient care, and streamlining medical research processes. AREAS COVERED: We reviewed the current state of AI applications in clinical pharmacology, focusing on drug discovery and development, precision medicine, pharmacovigilance, and other ventures. Key AI applications in clinical pharmacology are examined, including machine learning, natural language processing, deep learning, and reinforcement learning etc. Additionally, the evolving role of clinical pharmacologists, ethical considerations, and challenges in implementing AI in clinical pharmacology are discussed. EXPERT OPINION: The AI could be instrumental in accelerating drug discovery, predicting drug safety and efficacy, and optimizing clinical trial designs. It can play a vital role in precision medicine by helping in personalized drug dosing, treatment selection, and predicting drug response based on genetic, clinical, and environmental factors. The role of AI in pharmacovigilance, such as signal detection and adverse event prediction, is also promising. The collaboration between clinical pharmacologists and AI experts also poses certain ethical and practical challenges. Clinical pharmacologists can be instrumental in shaping the future of AI-driven clinical pharmacology and contribute to the improvement of healthcare systems.

Treatment resistance in pancreatic and biliary tract cancer: molecular and clinical pharmacology perspectives.

INTRODUCTION: Treatment resistance poses a significant obstacle in oncology, especially in biliary tract cancer (BTC) and pancreatic cancer (PC). Current therapeutic options include chemotherapy, targeted therapy, and immunotherapy. Resistance to these treatments may arise due to diverse molecular mechanisms, such as genetic and epigenetic modifications, altered drug metabolism and efflux, and changes in the tumor microenvironment. Identifying and overcoming these mechanisms is a major focus of research: strategies being explored include combination therapies, modulation of the tumor microenvironment, and personalized approaches. AREAS COVERED: We provide a current overview and discussion of the most relevant mechanisms of resistance to chemotherapy, target therapy, and immunotherapy in both BTC and PC. Furthermore, we compare the different strategies that are being implemented to overcome these obstacles. EXPERT OPINION: So far there is no unified theory on drug resistance and progress is limited. To overcome this issue, individualized patient approaches, possibly through liquid biopsies or single-cell transcriptome studies, are suggested, along with the potential use of artificial intelligence, to guide effective treatment strategies. Furthermore, we provide insights into what we consider the most promising areas of research, and we speculate on the future of managing treatment resistance to improve patient outcomes.

Clinical pharmacology strategies to accelerate the development of polatuzumab vedotin and summary of key findings.

The favorable benefit-risk profile of polatuzumab vedotin, as demonstrated in a pivotal Phase Ib/II randomized study (GO29365; NCT02257567), coupled with the need for effective therapies in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL), prompted the need to accelerate polatuzumab vedotin development. An integrated, fit-for-purpose clinical pharmacology package was designed to support regulatory approval. To address key clinical pharmacology questions without dedicated clinical pharmacology studies, we leveraged non-clinical and clinical data for polatuzumab vedotin, published clinical data for brentuximab vedotin, a similar antibody-drug conjugate, and physiologically based pharmacokinetic and population pharmacokinetic modeling approaches. We review strategies and model-informed outcomes that contributed to regulatory approval of polatuzumab vedotin plus bendamustine and rituximab in R/R DLBCL. These strategies made polatuzumab vedotin available to patients earlier than previously possible; depending on the strength of available data and the regulatory/competitive environment, they may also prove useful in accelerating the development of other agents.

A Modified Delphi Study to Establish Essential Clinical Pharmacology Competencies.

INTRODUCTION: Competency-based education has been commonly used to enhance the healthcare workforce for some time. A translational discipline that is integral to drug development and impactful on healthcare and public health is clinical pharmacology. With such contribution, it is essential that the clinical pharmacology workforce is adequately equipped to address the demands of emerging trends of drug development. OBJECTIVES: The primary objective of this study was to determine the most significant competencies needed for a clinical pharmacologist in the regulatory environment. METHODS: A two round modified Delphi technique was administered to 29 clinical pharmacologists within the Office of Clinical Pharmacology (OCP) between November 2021-January 2022. A questionnaire consisting of core and technical competencies was administered electronically using SurveyMonkey ® to gain consensus about essential clinical pharmacology competencies. Participants used a Likert scale to rank importance of competencies from strongly agree (1), agree (2), neutral (3), disagree (4), strongly disagree (5). Participants also suggested topics to be included in the next round. Consensus was set at 60%. The competencies receiving the most consensus at 60% in round one and the new topics proceeded to the second round. In the second and final round, participants ranked the suggested competencies. Descriptive statistics and a McNemar change test were utilized to analyze data. Only data from the participants who completed both rounds was used in the study. RESULTS: In round one participants ranked all fifty-six core and technical competencies as essential with consensus of at least 60%. In round two, participants ranked sixty-two competencies as essential with consensus of at least 60%. A McNemar change test demonstrated stability of ranking between rounds. CONCLUSION: Essential core and technical competencies can build education programs to sustain the emerging clinical pharmacology workforce in the Office of Clinical Pharmacology. The Delphi technique is a suitable approach to determine essential competencies because it cultivates consensus and gains insight from experts in the forefront of drug development.

An account on the history of pharmacology in Spain.

Here we present an account on the history of pharmacology in Spain. Pharmacology as an independent science in Europe began with the creation of university chairs. Of particular relevance was the appointment in 1872 of Osswald Shmiedeberg as chairman of an Institute of Pharmacology at the University of Strassbourg, Germany. Teófilo Hernando pioneered in Spain the new emerging pharmacology at the beginning of the XX Century. He made a posdoctoral stay in the laboratory of Schmiedeberg, working on digitalis. In 1912 he won the chair of "Materia Médica y Arte de Recetar" at "Universidad Central of Madrid" (today, "Universidad Complutense de Madrid", UCM). He soon decided to transform such subject to the emerging modern pharmacology, with the teaching of experimental pharmacology in the third course of medical studies and clinical therapeutics (today clinical pharmacology) in the sixth course. This was the status of pharmacology in 1920, supporting the view that Hernando was a pioneer of clinical pharmacology. However, the Spanish Civil War and the II Word War interropted this division of preclinical and clinical pharmacology; only in the 1980's was clinical pharmacolgy partially developed in Spain. From a scientific point of view, Hernando directly trained various young pharmacologists that extended the new science to various Spanish universities. Some of his direct disciples were Benigno Lorenzo Velázquez, Francisco García Valdecasas, Rafael Méndez, Tomás Alday, Gabriel Sánchez de la Cuesta, Dámaso Gutiérrez or Ramón P é rez-Cirera. One of the central research subject was the analysis of the effects of digitalis on the cat and frog heart. In the initiation of the 1970 s pharmacologists trained by those Hernando's students grew throughout various universities and the "Consejo Superior de Investigaciones Científicas" (CSIC). And hence, in 1972 the "Sociedad Española de Farmacología" (SEF) emerged. Later on, in the 1990's the "Sociedad Española de Farmacología Clínica (SEFC) also emerged. The relationship between the two societies is still weak. Out of the vast scope of the pharmacological sciences, Spanish pharmacologists have made relevant contributions in two areas namely, neuropsychopharmacology and cardiovacular pharmacology. Nonetheless, in other areas such as smooth muscle, gastroenterology, pharmacogenetics and hepatic toxicity, Spanish pharmacologists have also made relevant contributions. A succint description of such contributions is made. Finally, some hints on perspectives for the further development of preclinical and clinical pharmacology in Spain, are offered.

Clinical Pharmacology Approaches to Support Approval of New Routes of Administration for Therapeutic Proteins.

Intravenous or subcutaneous routes of administration (ROAs) are common dosing routes for therapeutic proteins. Eleven therapeutic proteins with approval for one ROA have subsequently received approval for a second ROA. The clinical programs supporting the second ROA consistently leveraged data from the first ROA and included studies that characterized the pharmacokinetics (PKs) of the drug administered by the new ROA to identify an appropriate dosage regimen. The selected dosing regimen was then further evaluated in clinical trials designed with various primary end points. All programs implemented model-informed drug development approaches to ensure that the selected regimens would achieve comparable systemic exposures (PK-based bridging) or pharmacodynamic (PD) responses (PD-based bridging) as the reference ROA. To support the approval of a second ROA, these programs either demonstrated noninferiority in PK, PD, and/or clinical end points for the second ROA, or established efficacy and safety through a comparison to a placebo treatment. The accumulative examples showed that clinical trials which provided the primary evidence to support approvals of the second ROA generally demonstrated noninferiority in the systemic exposures regardless of being specified as an end point or not in the study protocols. The experience to date supports the use of PK- and PD-based bridging approaches not only in the selection of dosing regimens for a second ROA to be tested in clinical studies, but also for providing evidence of effectiveness to support approval, when appropriate.

Artificial intelligence and machine learning in clinical pharmacological research.

BACKGROUND: Clinical pharmacology research has always involved computational analysis. With the abundance of drug-related data available, the integration of artificial intelligence (AI) and machine learning (ML) methods has emerged as a promising way to enhance clinical pharmacology research. METHODS: Based on an accepted definition of clinical pharmacology as a field of research dealing with all aspects of drug-human interactions, the analysis included publications from institutes specializing in clinical pharmacology. Research topics and the most used machine learning methods in clinical pharmacology were retrieved from the PubMed database and summarized. RESULTS: ML was identified in 674 publications attributed to clinical pharmacology research, with a significant increase in publication activity over the last decade. Notable research topics addressed by ML/AI included Covid-19-related clinical pharmacology research, clinical neuropharmacology, drug safety and risk assessment, clinical pharmacology related to cancer research, and antimicrobial and antiviral research unrelated to Covid-19. In terms of ML methods, neural networks, random forests, and support vector machines were frequently mentioned in the abstracts of the retrieved papers. CONCLUSIONS: ML, and AI in general, is increasingly being used in various research areas within clinical pharmacology. This report presents specific examples of applications and highlights the most used ML methods.

An update on the clinical pharmacology of kratom: uses, abuse potential, and future considerations.

INTRODUCTION: Kratom (Mitragyna speciosa) has generated substantial clinical and scientific interest as a complex natural product. Its predominant alkaloid mitragynine and several stereoisomers have been studied for activity in opioid, adrenergic, and serotonin receptors. While awaiting clinical trial results, the pre-clinical evidence suggests a range of potential therapeutic applications for kratom with careful consideration of potential adverse effects. AREAS COVERED: The focus of this review is on the pharmacology, pharmacokinetics, and potential drug-drug interactions of kratom and its individual alkaloids. A discussion on the clinical pharmacology and toxicology of kratom is followed by a summary of user surveys and the evolving concepts of tolerance, dependence, and withdrawal associated with kratom use disorder. EXPERT OPINION: With the increasing use of kratom in clinical practice, clinicians should be aware of the potential benefits and adverse effects associated with kratom. While many patients may benefit from kratom use with few or no reported adverse effects, escalating dose and increased use frequency raise the risk for toxic events in the setting of polysubstance use or development of a use disorder.

A Quantitative Clinical Pharmacology-Based Framework For Model-Informed Vaccine Development.

Historically, vaccine development and dose optimization have followed mostly empirical approaches without clinical pharmacology and model-informed approaches playing a major role, in contrast to conventional drug development. This is attributed to the complex cascade of immunobiological mechanisms associated with vaccines and a lack of quantitative frameworks for extracting dose-exposure-efficacy-toxicity relationships. However, the Covid-19 pandemic highlighted the lack of sufficient immunogenicity due to suboptimal vaccine dosing regimens and the need for well-designed, model-informed clinical trials which enhance the probability of selection of optimal vaccine dosing regimens. In this perspective, we attempt to develop a quantitative clinical pharmacology-based approach that integrates vaccine dose-efficacy-toxicity across various stages of vaccine development into a unified framework that we term as model-informed vaccine dose-optimization and development (MIVD). We highlight scenarios where the adoption of MIVD approaches may have a strategic advantage compared to conventional practices for vaccines.

Fifty Years of Unraveling the Clinical Pharmacology of Corticosteroids.

This review will highlight portions of Dr. William Jusko's and colleagues' work that affected the clinical use and study of corticosteroids in acute and chronic disease management. Selected publications related to corticosteroid pharmacokinetics and pharmacodynamics from the 1970s through today were included in this review, with a focus on the foundational human-based studies conducted in the 1970s-1990s. Dr. Jusko contributed significantly to early corticosteroid pharmacology across several domains including: 1) foundational corticosteroid pharmacokinetic methods and parameter development, 2) disease state-variation in corticosteroid pharmacokinetics, 3) drug interaction effects on corticosteroid pharmacokinetics, and 4) early corticosteroid pharmacodynamic studies. In an era where little was known about the pharmacokinetics and pharmacodynamics of corticosteroids, Dr. Jusko's work opened the eyes of researchers and clinicians to the potential for disease and drug interactions that could reduce or enhance the effects of corticosteroids. This significant body of work paved the way for alternative routes of administration that would be useful in concentrating the activity at the site of action and markedly reduced systemic drug exposure, minimizing the risk of adverse effects through application of the dose-sparing pharmacokinetic and pharmacodynamic principles.

Artificial intelligence and machine learning for clinical pharmacology.

Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug discovery and development, clinical trials, personalized medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in healthcare means clinical pharmacologists should have an understanding of AI and its implementation in clinical practice. As with any new therapy or health technology, it is imperative that AI tools are subject to robust and stringent evaluation to ensure that they enhance clinical practice in a safe and equitable manner. This review serves as an introduction to AI for the clinical pharmacologist, highlighting current applications, aspects of model development and issues surrounding evaluation and deployment. The aim of this article is to empower clinical pharmacologists to embrace and lead on the safe and effective use of AI within healthcare.