A Search for Biologically Active Compounds for Potential Pharmaceutic and Agronomic Applications.

Summarized here are some aspects of my research activities in Ciba-Geigy Central Research Laboratories (1985-1996), in Novartis and Syngenta Crop Protection Research (1997-2020). I have followed the chronological order of these research activities covering only published data.

Evaluating the quality of multiple-choice question pilot database: A global educator-created tool for concept-based pharmacology learning.

The Core Concepts of Pharmacology (CCP) initiative is developing educational resources to transform pharmacology education into a concept-based approach. This study evaluated the quality of global educator-created MCQs in generating items for the pharmacology concept inventory (PCI) instrument and developed as a resource for learning pharmacology fundamental concepts. A panel of 22 global pharmacology experts recruited from the CCP initiative research team participated in the MCQ pilot database design and evaluation. The quality analysis framework of the MCQs in the pilot database included four assessment tools: item writing guidelines (IWGs), Bloom's taxonomy, the CCP, and the MCQ design format. A two-phase evaluation process was involved, including inter-rater agreement on item quality, followed by resolving conflicts that occurred in quality assessment. The chi-square (χ2) test of independence and Cramer's V correlation tests were utilized to measure the relationship among quality assessment attributes. About 200 MCQs were gathered and 98% underwent expert evaluation. Nearly 80% addressed one or more CCP, with 52% designed using a context-dependent format. However, only 40% addressed higher levels of Bloom's cognitive domain and 10% adhered to all IWGs. A strong positive correlation was observed between the context-based item format and its effectiveness in assessing the higher cognitive domain, the main CCP and improved IWGs adherence. Context-based item construction can assess the higher cognitive skills and fundamental pharmacology concepts, showing potential for rigorous PCI development. The pilot database will store items to create the PCI, aiding the development of a concept-based pharmacology curriculum.

--------Comparison of Hybrid-Simulation-Based Teaching with Traditional Teaching of Pharmacology.

OBJECTIVE: To compare the outcome of traditional teaching with hybrid simulation-based teaching for undergraduate medical students. Place and Duration of the Study: Department of Pharmacology, Jinnah Medical and Dental College, Karachi, Pakistan, from June to August 2023. STUDY DESIGN: Quasi-experimental study. METHODOLOGY: One hundred students from MBBS 3rd year were included in the study after taking the informed consent. Participants were divided into two cross-over groups and sampling was done randomly. Group A: (even roll numbers, n = 50) was the control group, taught by traditional lecture on positive inotropic medicines. Group B: (with odd roll numbers, n = 50) was the intervention group, taught the same topic by simulation-based teaching through 5 case scenarios. The teaching of this group was reinforced by role plays. Scores of post-test and retention test were compared by applying the Student's t-test. RESULTS: Students taught by traditional lectures i.e., Group A, their post-test mean scores were 30.7 ± 5.6, whereas Group B scored 45.7 ± 3.3, taught by hybrid stimulation (p <0.001). Retention test (MCQs based) was conducted after one month in which Group A obtained a mean score of 18.8 ± 9 with a passing percentage of approximately 30, whereas Group B obtained a score of 41.3 ± 5.6 (p <0.001). CONCLUSION: Hybrid-simulation-based teaching improved the immediate test scores as well as retention. KEY WORDS: Traditional teaching, Hybrid-simulation, MCQs, Retention test, Intervention group.

The evaluation of digital educational game use in pharmacology teaching process.

The aim of the study was to determine the usefulness of educational video games as a variety applied to the traditional teaching of pharmacology in topics of antifungal and hypolipidemic drugs. Sixty-six volunteers were divided into control group (n = 33) and experimental group (n = 33). The first group received traditional seminar only, and the second played video game designed with the use of Kahoot! platform after the seminar. The assessment of knowledge was conducted with the use of three tests: pre-test was presented before seminar, post-test after seminar (for control group) or after playing the video game (for experimental group), and test no. 3 took place 4 weeks later. Analysis of tests' scores with respect to both topics resulted in the observation that the control and experimental groups show statistically significant improvement in knowledge, whether it was measured after the seminar or 4 weeks later. However, the results of experimental group were statistically better in comparison to the control group. It proves that electronic GBL (game-based learning) applied to standard educational processes increases short- and long-term knowledge retention compared to traditional seminars.

High-fidelity simulation versus case-based tutorial sessions for teaching pharmacology: Convergent mixed methods research investigating undergraduate medical students' performance and perception.

INTRODUCTION: Medical educators strive to improve their curricula to enhance the student learning experience. The use of high-fidelity simulation within basic and clinical medical science subjects has been one of these initiatives. However, there is paucity of evidence on using simulation for teaching pharmacology, especially in the Middle East and North Africa region, and the effectiveness of this teaching modality, relative to more traditional ones, have not been sufficiently investigated. Accordingly, this study compares the effects of high-fidelity simulation, which is designed in alignment with adult and experiential learning theories, and traditional case-based tutorial sessions on the performance and perception of undergraduate Year 2 medical students in pharmacology in Dubai, United Arab Emirates. METHODS: This study employed a convergent mixed methods approach. Forty-nine medical students were randomly assigned to one of two groups during the 16-week pharmacology course. Each group underwent one session delivered via high-fidelity simulation and another via a case-based tutorial. A short multiple-choice question quiz was administered twice (immediately upon completion of the respective sessions and 5 weeks afterwards) to assess knowledge retention. Furthermore, to explore the students' perceptions regarding the two modes of learning delivery (independently and in relation to each other), an evaluation survey was administered following the delivery of each session. Thereafter, the iterative joint display analysis was used to develop a holistic understanding of the effect of high-fidelity simulation in comparison to traditional case-based tutorial sessions on pharmacology learning in the context of the study. RESULTS: There was no statistically significant difference in students' knowledge retention between high-fidelity simulation and case-based tutorial sessions. Yet, students expressed a greater preference for high-fidelity simulation, describing the corresponding sessions as more varied, better at reinforcing learning, and closer to reality. As such, the meta-inferences led to expansion of the overall understanding around students' satisfaction, to both confirmation and expansion of the systemic viewpoint around students' preferences, and lastly to refinement in relation to the perspective around retained knowledge. CONCLUSION: High-fidelity simulation was found to be as effective as case-based tutorial sessions in terms of students' retention of knowledge. Nonetheless, students demonstrated a greater preference for high-fidelity simulation. The study advocates caution in adapting high-fidelity simulation, where careful appraisal can lend itself to identifying contexts where it is most effective.

Natural product pharmacology: the British Journal of Pharmacology perspective.

Natural products (NPs) have long been used as a rich source of bioactive compounds for drug development. Recent technological advancements have revitalised natural products research as evidenced by increased publications in this field. In this editorial review, we highlight key points from the 2020 British Journal of Pharmacology (BJP) practical guide, which outlines standards for natural products research reports, and provide papers published in BJP between years 2020 to 2023 that demonstrate adherence to these guidelines. Looking ahead, we discuss the potential of chemical proteomics approaches to elucidate natural products mechanisms of action and identify therapeutic targets for future research. By fostering innovation, we aim to advance natural products research and contribute to the development of novel therapeutics that will have a significant impact on healthcare.

Quality and impact of pharmacology digital simulation education on pre-registration healthcare students: A systematic literature review.

OBJECTIVE: This review aimed to assess the quality and nature of the literature related to digital simulation-based pharmacology education. Specifically, we sought to understand the influence of simulations on the knowledge, satisfaction, and confidence of pre-registration nurses and other healthcare students participating in such educational programs. DESIGN: Systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement. This study was registered in the Prospective Register of Systematic Reviews (PROSPERO, reg no: CRD42023437570). DATA SOURCES: PubMed, MEDLINE, APA PsycInfo, ProQuest, Web of Science, ScienceDirect, and CINHAL databases were searched. REVIEW METHODS: The review focused on the quantitative findings from the studies published from 2016 to 2023. Only the studies that assessed the impact of digital simulation-based pharmacology education on pre-registration healthcare students' knowledge, satisfaction, and confidence were selected for review. Data were synthesized using a narrative approach. The Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of the included articles. This was followed by a narrative synthesis to consolidate the themes. RESULT: Out of 1587 articles,16 met the inclusion criteria. A wide variety of digital technologies have been utilised, such as virtual simulation, computer simulation (2D/3D), mixed reality, and augmented reality, with the majority using virtual simulation. All studies implemented single-user simulations. The themes emerging from the narrative synthesis suggest that a digital simulation-based pharmacology course is an effective tool for enhancing students' knowledge, confidence, and satisfaction in learning pharmacological concepts. Furthermore, simulation-based teaching with a blended approach was found to be beneficial. However, the integration of the polypharmacy concept and the intra and interprofessional approach to teaching and learning was not evident in these studies. CONCLUSION: This systematic literature review provides evidence of the potential of digital simulation-based education in pharmacology teaching among healthcare pre-registration students. In future studies, the integration of polypharmacy content with an intra and interprofessional teaching-learning approach is recommended.

[Modular pharmacology: research progress and development of analysis platform].

Based on the systematic deconstruction of multi-dimensional and multi-target biological networks, modular pharmacology explains the complex mechanism of diseases and the interactions of multi-target drugs. It has made progress in the fields of pathogenesis of disease, biological basis of disease and traditional Chinese medicine(TCM) syndrome, pharmacological mechanism of multi-target herbs, compatibility of formulas, and discovery of new drug of TCM compound. However, the complexity of multi-omics data and biological networks brings challenges to the modular deconstruction and analysis of the drug networks. Here, we constructed the "Computing Platform for Modular Pharmacology" online analysis system, which can implement the function of network construction, module identification, module discriminant analysis, hub-module analysis, intra-module and inter-module relationship analysis, and topological visualization of network based on quantitative expression profiles and protein-protein interaction(PPI) data. This tool provides a powerful tool for the research on complex diseases and multi-target drug mechanisms by means of modular pharmacology. The platform may have broad range of application in disease modular identification and correlation mechanism, interpretation of scientific principles of TCM, analysis of complex mechanisms of TCM and formulas, and discovery of multi-target drugs.

Of rodents, research and relationships: a pharmacological odyssey.

This article is an autobiographical account of a research career in inflammatory diseases, mechanisms and pharmacotherapy, drug research and development, in academia and industry in various European countries spanning the last 55 years. The author describes how tenacity and independent thought, learned in formative years, and tempered later by the development of good relationships with colleagues have guided his career. This has spanned research, among other fields, on prostaglandins as pro-and anti-inflammatory mediators, oxidative stress and antioxidants, phospholipid mediators, cytokines, innate and adaptive immune responses and the establishment of various inflammatory and immunological models. The author has helped discover and develop novel therapeutic approaches to pain, arthritic, dermatological, respiratory, and autoimmune disorders and contributed to bringing eight drug candidates to clinical trials. He has helped establish new research labs in four different centres and been involved in teaching undergraduate and mature students in three different universities. With extensive experience in scientific publishing and several international awards, he emphasises that without good teamwork, little can be achieved in scientific research.

[Fluorescence microscopy for brain activity imaging: one-photon microscopy and its application to pharmacological research].

The development of genetically-encoded fluorescent probes for the detection of intracellular calcium ions and various neurotransmitters has progressed significantly in recent years, and there is a growing need for techniques that rapidly and efficiently image these signals in the living brain for pharmacological studies of the central nervous system. In this article, we discuss one-photon fluorescence microscopy techniques used for brain activity imaging, particularly wide-field imaging and head-mounted miniaturized microscopy, and introduce their basic principles, recent advances, and applications in pharmacological research. Wide-field calcium imaging is suitable for mesoscopic observation of cortical activity during behavioral tasks in head-fixed awake mice, while head-mounted miniaturized microscopes can be attached to the animal's head to image brain activity associated with naturalistic behaviors such as social behavior and sleep. One-photon microscopy allows for the development of a simple and cost-effective imaging system using an affordable excitation light source such as a light-emitting diode. Its excitation light illuminates the entire field of view simultaneously, making it easy to perform high-speed imaging using a high-sensitivity camera. In contrast, the short wavelength of the excitation light limits the field of observation to areas on or near the brain surface due to its strong light scattering. Moreover, the out-of-focus fluorescence makes it difficult to obtain images with a high signal-to-noise ratio and spatial resolution. The use of one-photon microscopy in brain activity imaging has been limited compared to two-photon microscopy, but its advantages have recently been revisited. Therefore, this technique is expected to become a useful method for pharmacologists to visualize the activity of the living brain.

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.