Mechanism-based organization of neural networks to emulate systems biology and pharmacology models.

Deep learning neural networks are often described as black boxes, as it is difficult to trace model outputs back to model inputs due to a lack of clarity over the internal mechanisms. This is even true for those neural networks designed to emulate mechanistic models, which simply learn a mapping between the inputs and outputs of mechanistic models, ignoring the underlying processes. Using a mechanistic model studying the pharmacological interaction between opioids and naloxone as a proof-of-concept example, we demonstrated that by reorganizing the neural networks' layers to mimic the structure of the mechanistic model, it is possible to achieve better training rates and prediction accuracy relative to the previously proposed black-box neural networks, while maintaining the interpretability of the mechanistic simulations. Our framework can be used to emulate mechanistic models in a large parameter space and offers an example on the utility of increasing the interpretability of deep learning networks.

Un mecanismo nefrogénico subyace a la poliuria inducida por dexmedetomidina: informe de un caso / Nephrogenic mechanism underlies dexmedetomidine-induced polyuria: A case report

La dexmedetomidina, agonista del adrenorreceptor α, se utiliza cada vez más como agente sedativo-hipnótico y analgésico, aunque su popularidad suscita preocupación acerca de los efectos secundarios de dicho fármaco.La bradicardia y la hipotensión son efectos adversos comunes, pero también existen diversos informes de gasto urinario excesivo, posiblemente debido a la secreción de vasopresina y a la permeabilidad de los conductos colectores.La poliuria se resuelve normalmente con la discontinuación del fármaco, no habiéndose reportado morbilidad significativa. La identificación temprana, la eliminación del agente y el tratamiento son imperativos para minimizar las complicaciones, principalmente natremia y síntomas neurológicos.Este informe de caso describe la poliuria relacionada con dexmedetomidina durante la anestesia general libre de opioides para cirugía mayor de cabeza y cuello. Nuestra hipótesis de etiología nefrogénica se ve reforzada por los datos analíticos obtenidos. También describimos cómo abordar la poliuria intraoperatoria. (AU)

Dexmedetomidine's α-adrenoreceptor agonism has been gaining popularity in the anesthetic room as a sedative-hypnotic and analgesic agent, and with extensive perioperative use rising concern about side effects is necessary.Bradycardia and hypotension are common but excessive urine output is increasingly reported, suggested mechanisms being vasopressin secretion and increasing permeability of the collecting ducts.Polyuria usually resolves with discontinuation of the drug and significant morbidity has not been reported. Early identification, removal of agent and treatment are imperative to minimize complications, mainly associated with natremia levels and neurological symptoms.This case report describes a dexmedetomidine-related polyuric syndrome during opioid-free general anesthesia for major head and neck surgery. A nephrogenic mechanism for the clinical effect is proposed and reinforced by analytical data obtained. An intra-operative polyuria approach is also delineated. (AU)

Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology.

Understanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME dynamics and predict the efficacy of immunotherapy in virtual patient populations/digital twins but require vast amounts of multimodal data for parameterization. Large-scale datasets characterizing the TME are available due to recent advances in bioinformatics for multi-omics data. Here, we discuss the perspectives of leveraging omics-derived bioinformatics estimates to inform QSP models and circumvent the challenges of model calibration and validation in immuno-oncology.

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.

PharmaMemory: an interactive, animated web application for learning autonomic physiology and pharmacology.

Medical students face challenging but important topics they must learn in short periods of time, such as autonomic pharmacology. Autonomic pharmacology is difficult in that it requires students to synthesize detailed anatomy, physiology, clinical reasoning, and pharmacology. The subject poses a challenge to learn as it is often introduced early in medical school curricula. To ease the difficulty of learning autonomic pharmacology, we created a free web application, PharmaMemory (www.pharmamemory.com), that interactively depicts the effects of high-yield autonomic drugs on the human body. PharmaMemory provides users with the opportunity to read and quiz themselves on the mechanisms, side effects, indications, and contraindications of these drugs while interacting with the application. We provided PharmaMemory to first-year medical students for three consecutive years of quality improvement and assessed the application's perceived effects on learning via user surveys. Survey feedback showed that users viewed PharmaMemory favorably and self-reported increased knowledge and confidence in the subject of autonomic pharmacology. Comments revealed that users liked the website's visuals, opportunity for challenged recall, and conciseness. PharmaMemory utilizes challenged recall, visual stimulation, and interactive learning to provide users with a multifaceted learning tool. Preliminary data suggest that students find this method of learning beneficial. Further studies are needed to assess PharmaMemory compared with more traditional learning methods such as PowerPoint or text-based learning. Additionally, further research is needed to quantitatively assess reduction in cognitive load.NEW & NOTEWORTHY PharmaMemory (www.pharmamemory.com) is a free web application that interactively depicts the effects of high-yield autonomic drugs on the human body.

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.

Finding new analgesics: Computational pharmacology faces drug discovery challenges.

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

Defining and unpacking the core concepts of pharmacology: A global initiative.

BACKGROUND AND PURPOSE: Development of core concepts in disciplines such as biochemistry, microbiology and physiology have transformed teaching. They provide the foundation for the development of teaching resources for global educators, as well as valid and reliable approaches to assessment. An international research consensus recently identified 25 core concepts of pharmacology. The current study aimed to define and unpack these concepts. EXPERIMENTAL APPROACH: A two-phase, iterative approach, involving 60 international pharmacology education experts, was used. The first phase involved drafting definitions for core concepts and identifying key sub-concepts via a series of online meetings and asynchronous work. These were refined in the second phase, through a 2-day hybrid workshop followed by a further series of online meetings and asynchronous work. KEY RESULTS: The project produced consensus definitions for a final list of 24 core concepts and 103 sub-concepts of pharmacology. The iterative, discursive methodology resulted in modification of concepts from the original study, including change of 'drug-receptor interaction' to 'drug-target interaction' and the change of the core concept 'agonists and antagonists' to sub-concepts of drug-target interaction. CONCLUSIONS AND IMPLICATIONS: Definitions and sub-concepts of 24 core concepts provide an evidence-based foundation for pharmacology curricula development and evaluation. The next steps for this project include the development of a concept inventory to assess acquisition of concepts, as well as the development of case studies and educational resources to support teaching by the global pharmacology community, and student learning of the most critical and fundamental concepts of the discipline.

Training the next generation of pharmacometric modelers: a multisector perspective.

The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.

Physiological Indirect Response Model to Omics-Powered Quantitative Systems Pharmacology Model.

Over the past several decades, mathematical modeling has been applied to increasingly wider scopes of questions in drug development. Accordingly, the range of modeling tools has also been evolving, as showcased by contributions of Jusko and colleagues: from basic pharmacokinetics/pharmacodynamics (PK/PD) modeling to today's platform-based approach of quantitative systems pharmacology (QSP) modeling. Aimed at understanding the mechanism of action of investigational drugs, QSP models characterize systemic effects by incorporating information about cellular signaling networks, which is often represented by omics data. In this perspective, we share a few examples illustrating approaches for the integration of omics into mechanistic QSP modeling. We briefly overview how the evolution of PK/PD modeling into QSP has been accompanied by an increase in available data and the complexity of mathematical methods that integrate it. We discuss current gaps and challenges of integrating omics data into QSP models and propose several potential areas where integrated QSP and omics modeling may benefit drug development.

Oral Medicine and Pharmacology Teleconsulting Sessions of the Telehealth Program in one Southeastern State of Brazil

ABSTRACT Objective: To evaluate questions concerning oral medicineand pharmacology-related specialties of asynchronous dental teleconsulting sessions of the Telehealth Brazil Networks Program. Material and Methods: Data were collected from secondary databases of asynchronous dental teleconsulting sessions of the telehealth centers of Minas Gerais from July 2015 to July 2017. The variables for dental underlying fields and the types of questions were evaluated. Descriptive analysis was performed with the SPSS v.22.0 program. Results: 3,920 teleconsulting sessions were referred to the telehealth centers of Minas Gerais during the study period. Regarding oral medicine-related questions (n=745), most (n=469; 62.95%) addressed diagnosis, whereas the underlying field questions mostly regarded fungal, viral, and bacterial infections (17.3%), biopsies (16.4%), developmental defects and dental abnormalities (9.9%), and soft tissue tumors (9.4%). Pharmacology-related questions (n=738) mostly addressed general approaches (n=672; 91.06%), and the most common questions were about underlying fields' prescriptions (44.7%), anesthetics (17.6%), adverse effects of medications and anesthetics (10.2%), and selection of anesthetics for patients with systemic conditions (9.8%). Conclusion: Most teleconsulting sessions regarded conditions or procedures common in primary health care and essential for diagnosis and treatment planning at all care levels, which suggests a need for more academic learning processes for healthcare professionals, especially in dentistry primary fields.

Presentation of the obsolete drug reserpine in three German-language pharmacology textbooks.

For several decades, reserpine was used to treat hypertension and, to a limited extent, psychoses. Over time, however, the indication became more and more restricted to the point of obsolescence. This study examines the extent to which textbooks are up to date in their content and oriented towards therapeutic guidelines, using the obsolete drug reserpine as a paradigm. Three German pharmacology textbook series were examined for the coverage of reserpine from 1964-2023: Allgemeine und Spezielle Pharmakologie und Toxikologie (Aktories), Allgemeine und Spezielle Pharmakologie und Toxikologie (Karow) and Pharmakologie und Toxikologie (Lüllmann). We compared the textbook content with data on reserpine prescriptions and hypertension guidelines and analysed the relevance of reserpine in examinations using German federal exam questions by the Institute for medical and pharmaceutical exam questions (IMPP). The textbooks differ conceptually from each other. The indication of reserpine for hypertension has become more restricted over time in all three textbooks, yet they partially show discrepancies with hypertension guidelines. The reserpine prescription figures show a strong decline , and reserpine has not been queried by the IMPP, which underlines the obsolescence of the drug. Overall, our study shows that the presentation of a representative obsolete drug in pharmacology textbooks lags current medical practice. We also unmasked more differences in the presentation of an obsolete drug in standard textbooks than anticipated. In conclusion, the analysis of obsolete drugs in pharmacology textbooks is an informative way of assessing how up-to-date they are.