Dr. Saree Alnaghy is an Honorary Associate Professor at the University of Wollongong's Faculty of Engineering and Information Sciences, affiliated with the Centre for Medical Radiation Physics. She holds a Bachelor of Medical and Radiation Physics (Honours) and a PhD in Physics from the University of Wollongong (2009–2017). Her research focuses on advanced medical imaging and radiation therapy technologies, including photon counting detectors, dosimetry systems, and robotic motion phantoms for quality assurance. Key research areas include: Development of novel X-ray detectors for radiotherapy guidance High-resolution dosimetry techniques using silicon and polymer-based systems Integration of real-time imaging in radiation therapy Robotic systems for motion management in oncology Her work has been supported by grants such as 'Sharper Targeting, Brighter Future' (2024) and 'Bringing Colour to Radiotherapy' (2021–2025). She currently supervises PhD and MRes students on projects involving photon counting CT scanners and radiotherapy imaging. Alnaghy also serves as a Radiation Oncology Medical Physics Registrar at the Nelune Comprehensive Cancer Centre.
Pasquale Bottalico serves as Associate Professor in the Department of Speech and Hearing Science at the University of Illinois, with dual appointments as Associate Professor at the Center for Latin American and Caribbean Studies and Affiliate Faculty in the School of Music. His unique interdisciplinary profile bridges engineering, music performance, and speech science, reflecting his dual academic training and professional artistry. His educational foundation includes: Bachelor's in Telecommunications Engineering from Univeristà Mediterranea di Reggio Calabria, Italy Concurrent Opera Singing degree from F. Cilea Music Academy, Reggio Calabria Master's in Telecommunications Engineering from Politecnico di Torino, Italy Ph.D. in Metrology specializing in acoustics measurement uncertainty and classroom acoustics Dr. Bottalico's research centers on vocal load quantification and professional voice techniques , with significant contributions to understanding vocal fatigue in teachers and singers. His work spans Speech Intelligibility in educational environments, Room Acoustics for performance and learning spaces, and Musical Acoustics of historical vocal styles. A distinctive thread throughout his research examines how acoustic conditions modulate voice production and perception, increasingly incorporating virtual reality and bone conduction technologies for innovative assessment and intervention approaches. His Colombian vocal health study demonstrates cross-cultural applications of his work. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) The impact of noise and dysphonia on children's speech processing in educational settings, using multimodal assessment including EEG; (2) Virtual reality applications for voice production research and therapeutic intervention; (3) Cross-cultural validation of vocal fatigue metrics and development of biofeedback systems. His work consistently bridges engineering precision with clinical applicability, particularly for professional voice users in challenging acoustic environments. No scientific awards were documented in the available information. While specific advising relationships aren't detailed, his research collaborations span international institutions including Colombian and Italian universities, suggesting graduate mentorship in interdisciplinary projects. No grant information was provided, though his systematic reviews and cross-cultural studies imply externally funded research activities. Though no dedicated laboratory is specified, his virtual reality voice studies and acoustic parameter assessments suggest affiliations with audio engineering facilities and voice clinics, likely through the Speech and Hearing Science department's research infrastructure.
Dr. Ahmet Acar is an Associate Professor at the Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey. He leads the Cancer Precision Medicine and Drug Resistance Laboratory, focusing on understanding mechanisms of drug resistance in cancer. His research integrates experimental models, next-generation sequencing, and deep learning to address clinical challenges in cancer therapy. Dr. Acar holds a B.Sc. from METU's Biological Sciences department and a Ph.D. from the Cancer Research UK Manchester Institute. He completed postdoctoral training at the Institute of Cancer Research, London, and the University of Manchester. Research Interests: Drug resistance mechanisms, precision oncology, tumor microenvironment modeling, patient-derived organoids, computational pathology, and evolutionary cancer biology. His lab develops 2D/3D co-culture systems, PDO biobanks, and AI-driven histopathology tools to improve treatment strategies. Recent Work Trends: Recent publications emphasize tumor evolution modeling, matrix mechanics in drug resistance, and AI applications in histopathology. Collaborations with hospitals in Turkey and Europe support PDO biobank initiatives. His team explores evolutionary steering strategies to exploit collateral drug sensitivities. Labs/Teams: Precision Medicine and Drug Resistance Lab at METU focuses on interdisciplinary approaches combining wet-lab experiments with computational methods. Current projects include ex vivo tumor modeling and AI-driven diagnostic tools for oncology.
Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.
Christopher E. Nelson is an Assistant Professor in the Department of Biomedical Engineering at the University of Arkansas, College of Engineering. His lab focuses on developing biologically inspired strategies for controlled drug and gene delivery, particularly in the context of gene therapy and regenerative medicine. He is actively supported by the NIH, DoD, and Arkansas Bioscience Institute. Education: Postdoctoral Fellow – Duke University Ph.D. – Vanderbilt University B.S. – University of Arkansas Research Focus: Dr. Nelson’s lab integrates genome editing technologies with targeted delivery systems to address challenges in treating genetic diseases and promoting tissue regeneration. Major themes include CRISPR/Cas9 delivery , gene regulation in wound healing , and safe-harbor genome integration in skeletal muscle. His work spans viral and non-viral delivery vehicles , including lipid nanoparticles and AAV vectors, with a strong emphasis on preclinical validation in models of Duchenne muscular dystrophy and inflammatory disease. Scientific Awards: Controlled Release Society Postdoctoral Fellowship The Hartwell Foundation Postdoctoral Fellowship NIH Pathway to Independence Award (K99/R00) Funding & Support: The Nelson Lab is currently funded by: NIH NIGMS R35 DoD CDMRP DMD IDEA Award Arkansas Bioscience Institute University of Arkansas Engineering & Honors Colleges Lab & Team: The Nelson Lab is a dynamic, interdisciplinary team working at the intersection of gene editing, biomaterials, and regenerative medicine. They regularly present at national conferences such as ASGCT and NCUR, and mentor undergraduate researchers through SURF and Honors College grants.
Brian W. Pogue, Ph.D., is the Robert A. Pritzker Chair in Biomedical Engineering at Dartmouth College's Thayer School of Engineering, with a joint appointment as an Honorary Fellow in Medical Physics at the University of Wisconsin-Madison. His academic background includes a Ph.D. in Medical/Nuclear Physics from McMaster University and a Research Fellowship at Harvard Medical School's Wellman Center for Photomedicine. He has led significant administrative roles, including Dean of Graduate Studies at Dartmouth (2008–2012) and Chair of Medical Physics at Wisconsin (2022–2025). Research Focus : Dr. Pogue pioneers Optics in Medicine , specializing in cancer imaging, photodynamic therapy, and surgical guidance. His work integrates fluorescence imaging, radiation therapy monitoring, and molecular diagnostics to improve cancer treatment precision. Key innovations include Cherenkov imaging for radiotherapy dosimetry and hypoxia-sensitive probes for tumor resection. Publication Trends : Recent articles (2023–2025) emphasize real-time surgical guidance, hypoxia quantification, and multimodal imaging systems. Dominant themes include fluorescence tomography, radiation dosimetry, and low-cost diagnostic devices, reflecting a translational focus from preclinical validation to clinical applications. Awards & Honors : Fellow, Optica (formerly OSA) Fellow, American Institute for Medical and Biological Engineering (AIMBE) Fellow, American Association of Physicists in Medicine (AAPM) Fellow, SPIE (International Society for Optics and Photonics) Funding & Innovation : Continuously funded by the NIH since 2001 ($52M+ total), Dr. Pogue founded three startups: DoseOptics LLC (radiotherapy dose imaging) and Hypoxia Surgical LLC (tissue hypoxia cameras), bridging academic research to clinical tools.
Christian Lindh is an active Associate Professor and Senior Lecturer at Lund University's Division of Occupational and Environmental Medicine. He serves as Research Team Manager for Applied Mass Spectrometry in Environmental Medicine and is affiliated with EpiHealth: Epidemiology for Health. His research focuses on environmental and occupational exposures and their health impacts, with particular expertise in biomonitoring and analytical chemistry. His research interests span Occupational Health , Environmental Health , Analytical Chemistry , Exposure Assessment , and Epidemiology . Lindh specializes in studying human exposure to environmental pollutants including PFAS, heavy metals, phthalates, and polycyclic aromatic hydrocarbons, with particular focus on vulnerable populations such as pregnant women and children. His work contributes to UN Sustainable Development Goals related to health and environmental protection. Analysis of his recent publications reveals a strong focus on environmental epidemiology, particularly examining PFAS exposure patterns, heavy metal toxicity, and the health impacts of environmental contaminants across different life stages. His research employs advanced analytical techniques, particularly mass spectrometry, to precisely measure exposure levels and investigate dose-response relationships. Lindh has secured significant research funding, currently leading projects including 'Temporal Trends in Lead, Mercury, and Cadmium Levels in Children' (Swedish Environmental Protection Agency, 2025-2026) and 'Trade-offs between food safety and food security' (FORMAS, 2024-2027). He serves as Principal Investigator on multiple active research projects totaling 15, with 7 currently active and 7 completed. As Manager of the 'Targeted Exposomics at Lund University' infrastructure, Lindh leads the Applied Mass Spectrometry in Environmental Medicine research team. His work bridges analytical chemistry with public health research, developing methodologies to assess human exposure to environmental chemicals and evaluating their health consequences through epidemiological studies.
Pamela Ronald is a Distinguished Professor of Plant Pathology at the University of California, Davis, affiliated with the Department of Plant Pathology within the College of Agricultural and Environmental Sciences. Her research focuses on understanding and enhancing crop resilience, particularly in rice, through genetic and molecular mechanisms. Key areas include plant immunity against pathogens, climate adaptation, and sustainable agricultural practices. Education and Background: Details on her academic qualifications are not explicitly mentioned in the provided text, but her career trajectory suggests advanced training in plant genetics and pathology. Research Interests: Ronald’s work centers on engineering disease-resistant crops, studying plant-microbe interactions, and developing climate-resilient varieties. Notably, she has contributed to identifying genes like XA21 that confer resistance to bacterial infections and pioneered methods to reduce methane emissions in rice. Her studies also explore the role of sulfated peptides in pathogen virulence and host defense mechanisms. Publications Trends: Her recent articles emphasize molecular mechanisms of plant immunity, genetic engineering applications, and sustainability challenges. Themes include directed evolution of immune receptors, machine learning in genotype-phenotype prediction, and mitigation of agricultural greenhouse gases. Awards and Recognition: While specific awards are not listed here, her leadership in plant genetics and advocacy for evidence-based biotechnology policies reflect significant recognition in her field. Grants and Advising: Ronald has led projects funded by agencies like the U.S. Department of Energy, focusing on bioenergy crops like switchgrass. She collaborates globally on initiatives such as the Rice Protein Tagging Project and the AI Institute for Next Generation Food Systems. Labs and Teams: She directs the Crop Genetics Innovation Lab at UC Davis, fostering interdisciplinary research in crop improvement and sustainable agriculture.
Marjo Yliperttula is a Professor at the Department of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki. She serves as a supervisor in the Doctoral Programmes in Biomedicine, Drug Research, and Materials Research and Nanosciences, with expertise in biomaterials and pharmaceutical technology. Her research focuses on nanofibrillated cellulose (NFC) hydrogels for wound healing and drug delivery, extracellular vesicle (EV) engineering for therapeutic applications, and freeze-drying technologies for biomaterial preservation. Key contributions include NFC-based wound dressings that enhance platelet-rich plasma release (2024), Raman spectroscopy methods for monitoring freeze-drying-induced mutarotation (2024), and tandem chromatography techniques for high-purity EV isolation (2023). Her work bridges pharmaceutical sciences with regenerative medicine, emphasizing translational applications in chronic wound treatment and targeted drug delivery. Recent publications (2022-2025) reveal three dominant trends: (1) Optimization of NFC hydrogels for controlled drug release and tissue regeneration, (2) Advanced characterization of EV phenotypes under hypoxic conditions for improved therapeutic efficacy, and (3) Development of analytical methods (Raman spectroscopy, chromatography) to address manufacturing challenges in biopharmaceuticals. These themes reflect her group's commitment to solving critical problems in biomaterial stability, EV-based delivery, and precision wound care. Professor Yliperttula has supervised 10 doctoral theses, including recent work on NFC for skin substitutes (Elle Koivunotko), freeze-drying of hydrogels (Arto Merivaara), and mesenchymal stromal cells for wound healing (Jasmi Snirvi). She currently leads the Academy of Finland-funded GeneCellNa project (2024-2026) on gene/cell/nanotherapy for chronic diseases and a Finnish Red Cross project (2023-2024) on NFC for blood products, with cumulative project funding spanning 18 initiatives since 2005. She heads the Biopharmaceuticals Group within the Drug Research Program, fostering collaborations across pharmaceutical biosciences, materials science, and clinical medicine to advance next-generation therapeutic platforms.
Carl Henrik Ek is a Professor of Statistical Learning at the Department of Computer Science and Technology (Computer Laboratory) at the University of Cambridge. He is also a fellow and Director of Studies at Pembroke College, and holds visiting positions at Karolinska Institute in Stockholm and the Royal Institute of Technology. He serves as co-Director for the UKRI AI Centre for Doctoral Training in Decision Making for Complex Systems, a collaboration between Cambridge and Manchester universities, and is involved with the Accelerate Program in the Computer Laboratory. Dr. Ek's educational background includes a MEng degree in Vehicle Engineering from the Royal Institute of Technology in Stockholm, followed by a PhD from Oxford Brookes University. During his PhD, he spent time at the University of Manchester and the University of Sheffield. His PhD supervisors were Professor Neil Lawrence and Professor Phil Torr, and his postdoctoral research was conducted at UC Berkeley with Professor Trevor Darrell and Professor Raquel Urtasun. Professor Ek's research focuses on statistical learning, particularly on developing data-efficient and interpretable machine learning methods. His work spans modeling and inference in machine learning, with special emphasis on Bayesian non-parametric methods and Gaussian processes. He explores how to specify assumptions that allow learning from small amounts of data, bridging theoretical foundations with practical applications in various domains. His recent publications demonstrate a strong trend toward applying machine learning to healthcare, drug discovery, and engineering design. There's significant work on Gaussian processes, reinforcement learning, and generative models, with applications ranging from medical diagnostics to structural engineering. His research shows an increasing interdisciplinary focus, connecting machine learning with fields like cardiology, pharmacology, and computational geometry. Professor Ek has received numerous teaching awards throughout his career: Pilkington Price for Teaching Excellence (2024) Teacher of the year in Computer Science at University of Bristol (2016) Docent in Machine Learning at Royal Institute of Technology (2016) Teacher of the year at Royal Institute of Technology, Sweden (2015) Teacher of the year from Student chapter in Industrial Economics at Royal Institute of Technology (2015) Teacher of the year in Computer Science at Royal Institute of Technology (2012) Professor Ek teaches Advanced Data Science, Advanced topics in machine learning, and Machine Learning and the Physical World. He has supervised PhD students throughout his career but is not currently accepting new PhD students for 2025/26 or 2026/27. His research is supported by various grants, including his role as co-Director of the UKRI AI Centre for Doctoral Training. He is an active member of the ml@cl research group at Cambridge and has previously been involved with research groups at University of Bristol and Royal Institute of Technology. His work connects with several interdisciplinary initiatives, particularly in healthcare AI and engineering applications of machine learning.
Professor Ananya Choudhury serves as Chair and Honorary Consultant in Clinical Oncology at the University of Manchester, where she is also Co-Group Leader of the Translational Radiobiology Group within the Division of Cancer Sciences. She joined The Christie NHS Foundation Trust in 2008, specializing in urology and sarcoma, and has since focused on radiotherapy-related research in prostate and bladder cancers. Professor Choudhury is clinical lead for advanced radiotherapy, including the groundbreaking MRLinac project, and plays a key role in national radiotherapy research initiatives. Professor Choudhury earned her BA (Hons) in 1993, MB. BChir (Cantab) in 1995, and MA (Cantab) in 1997 from Trinity College, Cambridge. She completed her Clinical Oncology training at the Yorkshire Deanery from 2000-2008, during which she earned her MRCP in 2000 and F.R.C.R in 2004. She completed her PhD in 2008 through the University of Leeds and Princess Margaret Hospital in Toronto, Canada, where she studied the molecular epidemiology of DNA double strand break repair in bladder cancer. Professor Choudhury's research program focuses on optimizing and personalizing radiotherapy using advanced imaging technology to deliver high doses while minimizing side effects. Her work centers on prostate and bladder cancers, with particular interest in predictive biomarkers, hypoxia, and the integration of magnetic resonance imaging to improve treatment precision. She has pioneered research in radiotherapy dose optimization, biomarker development, and the identification of patients who would benefit most from different treatment approaches. Her extensive publication record demonstrates a strong focus on radiation therapy, particularly in genitourinary cancers. Recent work explores MRI-guided radiotherapy, hypoxia biomarkers, and personalized treatment approaches across multiple cancer types. She has made significant contributions to understanding how imaging technology can improve radiotherapy precision and effectiveness while reducing side effects, with several publications appearing in top journals through 2025. Professor Choudhury has received multiple prestigious awards recognizing her contributions to the field: Cancer Research-UK/Royal College of Radiologists Clinical Training Fellowship (2005) Fellowship for the 10th ECCO-AACR-ASCO Workshop on Methods in Clinical Cancer Research (2007) Outstanding Contribution, Greater Manchester Clinical Research Awards (2017) RCR Research Fellowship (2005) Research Fellowship, Princess Margaret Hospital, Toronto (2004) Professor Choudhury has supervised numerous doctoral and master's students across multiple cancer types, with current students expected to complete through 2024. She is Principal Investigator on multiple research grants, including 'Measuring tumour radioresistance to improve radiotherapy outcomes' and the 'MAESTRO Programme' as part of CRUK RadNet. Her research program is supported by significant funding from NIHR Manchester Biomedical Research Centre and other major funding bodies. As Co-Group Leader of the Translational Radiobiology Group, Professor Choudhury collaborates extensively with leading researchers including Peter Hoskin, Catharine West, Corinne Faivre-Finn, and Marcel van Herk. Her team is at the forefront of integrating advanced imaging with radiotherapy to improve cancer treatment outcomes, with active projects spanning from basic radiobiology to clinical implementation of novel radiotherapy techniques.
Yading Yuan, PhD is an Associate Professor of Radiation Oncology (Physics) at Columbia University Irving Medical Center and a member of the Data Science Institute. He holds a PhD in medical physics from the University of Chicago (2010) and completed clinical residency at Harvard Medical Physics Program (2013). His research focuses on AI-driven innovations in radiation oncology, including automated medical image analysis systems, federated learning frameworks for tumor segmentation, and data-driven approaches to personalized cancer treatment. He is certified by the American Board of Radiology and licensed in New York State. Education: PhD in Medical Physics (University of Chicago, 2010); Clinical Residency (Harvard Medical Physics Program, 2013). Research interests include: automated knowledge-based treatment planning, large-scale clinical AI systems, medical image reconstruction algorithms, and panomics integration for precision oncology. His work emphasizes translating data science advancements into clinical practice to improve patient outcomes. Key trends in his publications include federated learning for privacy-preserving medical AI, tumor segmentation in multi-modal imaging (PET/CT, MRI), and AI-driven prediction of treatment outcomes and recurrence risks. Recent work emphasizes decentralized learning architectures and cross-institutional collaboration systems. Scientific Awards: Distinguished Reviewers 2013 (selected by peer review committees) Advising/grants: No specific student names or grant details listed in provided text. His work is supported through institutional and collaborative research initiatives. Labs/teams: Active member of Columbia's Data Science Institute and Radiation Oncology department, contributing to interdisciplinary medical AI research groups.
Benedikt Günther is a research scientist at the Technical University of Munich (TUM) working within the Chair of Biomedical Physics led by Prof. Dr. Franz Pfeiffer. His research focuses on the Munich Compact Light Source (MuCLS), a laboratory-scale inverse Compton X-ray source that provides synchrotron-like radiation for biomedical applications. Günther plays a key role in developing, optimizing, and characterizing this innovative technology, contributing to both its fundamental physics and practical medical applications. His primary research interests center around X-ray physics and imaging techniques, particularly laser enhancement cavities for inverse Compton X-ray sources, X-ray microscopy, dynamic phase-contrast imaging, and X-ray spectroscopy. Günther's work bridges fundamental physics with practical medical applications, developing instrumentation that brings synchrotron-quality imaging to conventional laboratory settings. His research has significant implications for improving medical diagnostics while making advanced imaging techniques more accessible. Analysis of Günther's publication record reveals a consistent focus on advancing compact X-ray source technology and its applications. His work demonstrates expertise in both theoretical modeling and experimental implementation, with publications spanning instrument development, imaging techniques, and specific medical applications. The research shows progression from fundamental source characterization to increasingly sophisticated biomedical applications, particularly in breast imaging, dental diagnostics, and materials science. 2019 Best Poster Award at the combined meeting of the 68th Denver X-ray Conference (DXC) & 25th International Congress on X-ray Optics and Microanalysis (ICXOM) for 'Full-Field Structured Illumination Super-Resolution X-ray Transmission Microscopy' Günther regularly presents his work at major international conferences including the International Particle Accelerator Conference, High-Brightness Sources and Light-driven Interactions Congress, and specialized X-ray imaging meetings. His research is conducted within the Munich Compact Light Source facility, a collaborative project involving physicists, engineers, and medical researchers working to develop laboratory-scale synchrotron technology for widespread biomedical use.
Huixiao Chen is an Assistant Professor and Clinical Medical Physicist II in the Department of Therapeutic Radiology at Yale School of Medicine. She holds a primary appointment in Therapeutic Radiology and is actively engaged in clinical and research activities related to radiation oncology physics. Assistant Professor, Department of Therapeutic Radiology, Yale School of Medicine Clinical Medical Physicist II, Therapeutic Radiology Education: Resident, Yale University (2016) Postdoctoral Fellow, Harvard University (2013) Postdoctoral Fellow, Virginia Commonwealth University (2011) PhD, University of Heidelberg, Germany (2010) MS, Zhejiang University, China (1998) BS, Zhejiang University, China (1995) Huixiao Chen's research centers on medical physics in radiation oncology, with a focus on treatment planning optimization, dosimetry, and image-guided radiotherapy. Her work includes the development and evaluation of advanced radiotherapy techniques such as VMAT and SBRT, with applications in spine, lung, and prostate cancers. She has contributed to improving the accuracy of dose calculations using Monte Carlo methods and has explored the impact of patient motion on treatment delivery. Her research also extends to the design of clinical devices to support safe and effective radiotherapy for diverse patient populations. Her recent publications demonstrate a consistent focus on enhancing the precision and efficiency of radiotherapy. Key themes include multicriteria optimization in treatment planning, dosimetric validation of radiochromic films, and the development of supportive devices for image-guided radiotherapy. These works reflect a strong commitment to advancing clinical medical physics through both computational and engineering innovations. Scientific Contributions: Characterization of GafchromicTM EBT4 film for clinical dosimetry Design of a small-footprint couch-top support for heavy patients in IGRT Application of multicriteria optimization in VMAT planning for spine and prostate cancers Comparison of Monte Carlo vs. pencil beam algorithms in lung SBRT Analysis of diaphragm motion effects on spine SBRT Huixiao Chen has collaborated with researchers such as Emily Draeger and Zhe Jay Chen on various projects. While no formal students or grants are listed, her role as a clinical medical physicist and faculty member suggests active mentorship and potential involvement in funded research. She is a key contributor to the medical physics team at Yale, ensuring high standards in treatment planning and delivery.
Dr. Vera Deneer is an Associate Professor of Clinical Pharmacology at the Utrecht Institute for Pharmaceutical Research (UIPS) within the Faculty of Science at Utrecht University, specializing in the Division of Pharmacoepidemiology and Clinical Pharmacology since 2019. She also serves as a hospital pharmacist and clinical pharmacologist at the University Medical Center Utrecht (UMC Utrecht) at the Department of Clinical Pharmacy since 2017. Dr. Deneer holds significant leadership positions including Vice-Chair of the Medicines Evaluation Board (MEB-CBG) since 2019 and Chair of the Dutch Pharmacogenetics Working Group (DPWG). Dr. Deneer received her PharmD from Utrecht University in 1991 and her PhD from Groningen University in 2003, with research focused on clinical pharmacology and pharmacokinetics of antiarrhythmic drugs in atrial fibrillation. She completed clinical training in hospital pharmacy in 1994 and clinical pharmacology training in 1998. Prior to her current positions, she served as Head of the Pharmacogenetics, Pharmaceutical and Toxicological Laboratory at St. Antonius Hospital, Nieuwegein/Utrecht from 1998 to 2017. Her research focuses on personalized medicine through the study of biomarkers including genetic variants, patient characteristics, and clinical parameters to optimize drug treatment efficacy and safety. Her work primarily targets cardiovascular disease, lung cancer, and immune-mediated inflammatory diseases. She also investigates clinical reasoning and decision-making by pharmacists to improve medication management in clinical practice. Dr. Deneer serves as principal investigator for multiple research projects funded by The Netherlands Organisation for Health Research and Development. Dr. Deneer's recent publications demonstrate her leadership in pharmacogenetics guidelines development, with numerous Dutch Pharmacogenetics Working Group (DPWG) guidelines published in 2023-2025 covering gene-drug interactions for various medication classes including antidepressants, antipsychotics, anti-epileptics, and cardiovascular medications. Her work spans both clinical implementation research and educational aspects of pharmacy practice. Among her significant appointments, Dr. Deneer serves as Vice-Chair of the Medicines Evaluation Board (MEB-CBG) and Chair of the Dutch Pharmacogenetics Working Group (DPWG). She previously chaired a medical research ethics committee from 2012-2017 and serves on multiple national and hospital committees related to pharmacotherapy and drug safety. Dr. Deneer has been actively involved in mentoring pharmacy students and professionals, with recent publications focusing on clinical decision-making education for pharmacists. Her work bridges the gap between pharmacogenetic research and clinical implementation, with particular emphasis on optimizing drug treatment strategies for individual patients while minimizing adverse drug reactions.
