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84 Using Opportunistic Sampling and Remnant Blood Samples to Develop Pediatric Pharmacokinetic Models to Inform Antidepressant Dosing
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- Jeffrey R. Strawn, Ethan A. Poweleit, Zachary L. Taylor, Tomoyuki Mizuno, Samuel Vaughn, Zeruesenay Desta, Stephani Stancil, Laura B. Ramsey
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- Journal:
- Journal of Clinical and Translational Science / Volume 8 / Issue s1 / April 2024
- Published online by Cambridge University Press:
- 03 April 2024, pp. 22-23
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OBJECTIVES/GOALS: Developing pharmacokinetic (PK) models to guide selective serotonin reuptake inhibitor (SSRI) dosing in youth is costly, time-intensive, and requires large numbers of participants. We evaluated the use of remnant blood samples from SSRI-treated youth and developed precision PK dosing strategies. METHODS/STUDY POPULATION: Following IRB approval, we used a clinical surveillance platform to identify patients with routine phlebotomy within 24 hours of escitalopram or sertraline dosing. Remnant blood samples were obtained from youth aged 5–18 years, escitalopram and sertraline concentrations were determined, and clinical characteristics (e.g., age, sex, weight, concomitant medications that inhibit sertraline or escitalopram metabolism) and phenotypes for CYP2C19, the predominant enzyme that metabolizes these SSRIs, were extracted from the electronic medical record (EMR). A population PK analysis of escitalopram and sertraline was performed using NONMEM. The influence of clinical variables, CYP2C19, and dosing was evaluated from simulated concentration-time curves. RESULTS/ANTICIPATED RESULTS: Over 21 months, we collected315 samples from escitalopram-treated patients (N=288) and 265 samples from sertraline-treated patients (N=255). In youth, escitalopram and sertraline exposure (concentrations over time) and specific pharmacokinetic parameters (e.g., clearance) were influenced by CYP2C19 phenotype, concomitant CYP2C19 inhibitors, and patient-specific characteristics. Escitalopram and sertraline concentrations from remnant blood samples were 3.98-fold higher and 3.23-fold higher, respectively, in poor metabolizers compared to normal metabolizers (escitalopram, p<0.001) and compared to normal, rapid, and ultrarapid metabolizers combined (sertraline, p<0.001). DISCUSSION/SIGNIFICANCE: Combining remnant blood sampling with pharmacogenetic-integrated EMR data can facilitate large-scale population PK analyses of escitalopram and sertraline in youth. This real-world approach can be used to rapidly develop precision SSRI dosing strategies, including slower titration and reduced target doses in CYP2C19 poor metabolizers.
An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges
- Karamarie Fecho, Chris Bizon, Tursynay Issabekova, Sierra Moxon, Anne E. Thessen, Shervin Abdollahi, Sergio E. Baranzini, Basazin Belhu, William E. Byrd, Lawrence Chung, Andrew Crouse, Marc P. Duby, Stephen Ferguson, Aleksandra Foksinska, Laura Forero, Jennifer Friedman, Vicki Gardner, Gwênlyn Glusman, Jennifer Hadlock, Kristina Hanspers, Eugene Hinderer, Charlotte Hobbs, Gregory Hyde, Sui Huang, David Koslicki, Philip Mease, Sandrine Muller, Christopher J. Mungall, Stephen A. Ramsey, Jared Roach, Irit Rubin, Shepherd H. Schurman, Anath Shalev, Brett Smith, Karthik Soman, Sarah Stemann, Andrew I. Su, Casey Ta, Paul B. Watkins, Mark D. Williams, Chunlei Wu, Colleen H. Xu, The Biomedical Data Translator Consortium
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- Journal:
- Journal of Clinical and Translational Science / Volume 7 / Issue 1 / 2023
- Published online by Cambridge University Press:
- 14 September 2023, e214
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Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.
Contributors
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- By Adele Abrahamsen, H. Clark Barrett, William Bechtel, Nick Chater, Andy Clark, Keith Frankish, Aaron B. Hoffman, Ray Jackendoff, Laura A. Libby, William G. Lycan, Gregory L. Murphy, Mike Oaksford, Casey O’Callaghan, Elisabeth Pacherie, Jesse Prinz, William M. Ramsey, Charan Ranganath, Sara J. Shettleworth, Dominic Standage, Neil Stewart, Paul Thagard, Thomas Trappenberg, Barbara Von Eckardt, Ling Wong
- Edited by Keith Frankish, The Open University, Milton Keynes, William Ramsey, University of Nevada, Las Vegas
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- Book:
- The Cambridge Handbook of Cognitive Science
- Published online:
- 05 August 2012
- Print publication:
- 19 July 2012, pp -
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Contributors
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- By Jane E. Adcock, Yahya Aghakhani, A. Anand, Eva Andermann, Frederick Andermann, Alexis Arzimanoglou, Sandrine Aubert, Nadia Bahi-Buisson, Carman Barba, Agatino Battaglia, Geneviève Bernard, Nadir E. Bharucha, Laurence A. Bindoff, William Bingaman, Francesca Bisulli, Thomas P. Bleck, Stewart G. Boyd, Andreas Brunklaus, Harry Bulstrode, Jorge G. Burneo, Laura Canafoglia, Laura Cantonetti, Roberto H. Caraballo, Fernando Cendes, Kevin E. Chapman, Patrick Chauvel, Richard F. M. Chin, H. T. Chong, Fahmida A. Chowdhury, Catherine J. Chu-Shore, Rolando Cimaz, Andrew J. Cole, Bernard Dan, Geoffrey Dean, Alessio De Ciantis, Fernando De Paolis, Rolando F. Del Maestro, Irissa M. Devine, Carlo Di Bonaventura, Concezio Di Rocco, Henry B. Dinsdale, Maria Alice Donati, François Dubeau, Michael Duchowny, Olivier Dulac, Monika Eisermann, Brent Elliott, Bernt A. Engelsen, Kevin Farrell, Natalio Fejerman, Rosalie E. Ferner, Silvana Franceschetti, Robert Friedlander, Antonio Gambardella, Hector H. Garcia, Serena Gasperini, Lorenzo Genitori, Gioia Gioi, Flavio Giordano, Leif Gjerstad, Daniel G. Glaze, Howard P. Goodkin, Sidney M. Gospe, Andrea Grassi, William P. Gray, Renzo Guerrini, Marie-Christine Guiot, William Harkness, Andrew G. Herzog, Linda Huh, Margaret J. Jackson, Thomas S. Jacques, Anna C. Jansen, Sigmund Jenssen, Michael R. Johnson, Dorothy Jones-Davis, Reetta Kälviäinen, Peter W. Kaplan, John F. Kerrigan, Autumn Marie Klein, Matthias Koepp, Edwin H. Kolodny, Kandan Kulandaivel, Ruben I. Kuzniecky, Ahmed Lary, Yolanda Lau, Anna-Elina Lehesjoki, Maria K. Lehtinen, Holger Lerche, Michael P. T. Lunn, Snezana Maljevic, Mark R. Manford, Carla Marini, Bindu Menon, Giulia Milioli, Eli M. Mizrahi, Manish Modi, Márcia Elisabete Morita, Manuel Murie-Fernandez, Vivek Nambiar, Lina Nashef, Vincent Navarro, Aidan Neligan, Ruth E. Nemire, Charles R. J. C. Newton, John O'Donavan, Hirokazu Oguni, Teiichi Onuma, Andre Palmini, Eleni Panagiotakaki, Pasquale Parisi, Elena Parrini, Liborio Parrino, Ignacio Pascual-Castroviejo, M. Scott Perry, Perrine Plouin, Charles E. Polkey, Suresh S. Pujar, Karthik Rajasekaran, R. Eugene Ramsey, Rahul Rathakrishnan, Roberta H. Raven, Guy M. Rémillard, David Rosenblatt, M. Elizabeth Ross, Abdulrahman Sabbagh, P. Satishchandra, Swati Sathe, Ingrid E. Scheffer, Philip A. Schwartzkroin, Rod C. Scott, Frédéric Sedel, Michelle J. Shapiro, Elliott H. Sherr, Michael Shevell, Simon D. Shorvon, Adrian M. Siegel, Gagandeep Singh, S. Sinha, Barbara Spacca, Waney Squier, Carl E. Stafstrom, Bernhard J. Steinhoff, Andrea Taddio, Gianpiero Tamburrini, C. T. Tan, Raymond Y. L. Tan, Erik Taubøll, Robert W. Teasell, Mario Giovanni Terzano, Federica Teutonico, Suzanne A. Tharin, Elizabeth A. Thiele, Pierre Thomas, Paolo Tinuper, Dorothée Kasteleijn-Nolst Trenité, Sumeet Vadera, Pierangelo Veggiotti, Jean-Pierre Vignal, J. M. Walshe, Elizabeth J. Waterhouse, David Watkins, Ruth E. Williams, Yue-Hua Zhang, Benjamin Zifkin, Sameer M. Zuberi
- Edited by Simon D. Shorvon, Frederick Andermann, Renzo Guerrini
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- Book:
- The Causes of Epilepsy
- Published online:
- 05 March 2012
- Print publication:
- 14 April 2011, pp ix-xvi
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