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Journal articles on the topic 'Pharmacometrics'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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1

Gobburu, Jogarao V. S. "Pharmacometrics 2020." Journal of Clinical Pharmacology 50, S9 (September 2010): 151S—157S. http://dx.doi.org/10.1177/0091270010376977.

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2

Liu, Xiaoxi, and Robert M. Ward. "Pharmacometrics in Pediatrics." Therapeutic Innovation & Regulatory Science 53, no. 5 (September 2019): 579–83. http://dx.doi.org/10.1177/2168479019851793.

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3

Mager, Donald E. "Future of Pharmacometrics." Proceedings for Annual Meeting of The Japanese Pharmacological Society WCP2018 (2018): CL—15. http://dx.doi.org/10.1254/jpssuppl.wcp2018.0_cl-15.

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4

Fukuda, Tsuyoshi. "Pharmacometrics in children." Proceedings for Annual Meeting of The Japanese Pharmacological Society WCP2018 (2018): SY35–2. http://dx.doi.org/10.1254/jpssuppl.wcp2018.0_sy35-2.

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5

Pfister, Marc, Richard C. Brundage, Marc R. Gastonguay, Raymond Miller, Stacey J. Tannenbaum, and David Z. D'Argenio. "Defining the Future of Pharmacometrics: The American Society of Pharmacometrics." Journal of Clinical Pharmacology 50, S9 (September 2010): 158S. http://dx.doi.org/10.1177/0091270010377632.

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6

Usman, Muhammad, Sitaram Khadka, Mohammad Saleem, Huma Rasheed, Bimal Kunwar, and Moshin Ali. "Pharmacometrics: A New Era of Pharmacotherapy and Drug Development in Low- and Middle-Income Countries." Advances in Pharmacological and Pharmaceutical Sciences 2023 (March 7, 2023): 1–10. http://dx.doi.org/10.1155/2023/3081422.

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Pharmacotherapy, in many cases, is practiced at a suboptimal level of performance in low- and middle-income countries (LMICs) although stupendous amounts of data are available regularly. The process of drug development is time-consuming, costly, and is also associated with loads of hurdles related to the safety concerns of the compounds. This review was conducted with the objective to emphasize the role of pharmacometrics in pharmacotherapy and the drug development process in LMICs for rational drug therapy. Pharmacometrics is widely applied for the rational clinical pharmacokinetic (PK) practice through the population pharmacokinetic (popPK) modeling and physiologically based pharmacokinetic (PBPK) modeling approach. The scope of pharmacometrics practice is getting wider day by day with the untiring efforts of pharmacometricians. The basis for pharmacometrics analysis is the computer-based modeling and simulation of pharmacokinetics/pharmacodynamics (PK/PD) data supplemented by characterization of important aspects of drug safety and efficacy. Pharmacometrics can be considered an invaluable tool not only for new drug development with maximum safety and efficacy but also for dose optimization in clinical settings. Due to the convenience of using sparse and routine patient data, a significant advantage exists in this regard for LMICs which would otherwise lag behind in clinical trials.
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7

MORI, KAZUHIKO. "Medicament inspection and pharmacometrics." Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics 29, no. 3 (1998): 565–66. http://dx.doi.org/10.3999/jscpt.29.565.

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8

Manolis, Efthymios, and Ralf Herold. "Pharmacometrics for Regulatory Decision Making." Clinical Pharmacokinetics 50, no. 10 (October 2011): 625–26. http://dx.doi.org/10.2165/11594340-000000000-00000.

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9

van der Graaf, Piet H. "CPT: Pharmacometrics and Systems Pharmacology." CPT: Pharmacometrics & Systems Pharmacology 1, no. 9 (September 2012): 8. http://dx.doi.org/10.1038/psp.2012.8.

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10

Waldman, S. A., and A. Terzic. "Advancing Pharmacometrics and Systems Pharmacology." Clinical Pharmacology & Therapeutics 92, no. 5 (November 2012): 535–37. http://dx.doi.org/10.1038/clpt.2012.151.

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11

Pfister, Marc, Donald E. Mager, Nicholas H. G. Holford, Brian Corrigan, Stacey Tannenbaum, Rene Bruno, Liping Zhang, Yaning Wang, and David Z. D’Argenio. "The International Society of Pharmacometrics." Journal of Pharmacokinetics and Pharmacodynamics 40, S1 (April 30, 2013): 3–4. http://dx.doi.org/10.1007/s10928-013-9310-8.

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12

Mentré, France, Lena E. Friberg, Stephen Duffull, Jonathan French, Douglas A. Lauffenburger, Lang Li, Donald E. Mager, Vikram Sinha, Eric Sobie, and Ping Zhao. "Pharmacometrics and Systems Pharmacology 2030." Clinical Pharmacology & Therapeutics 107, no. 1 (November 23, 2019): 76–78. http://dx.doi.org/10.1002/cpt.1683.

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13

Garrido, MJ, P. Berraondo, and IF Trocóniz. "Commentary on Pharmacometrics for Immunotherapy." CPT: Pharmacometrics & Systems Pharmacology 6, no. 1 (January 2017): 8–10. http://dx.doi.org/10.1002/psp4.12162.

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14

Graaf, Piet H. "Pharmacometrics and/or Systems Pharmacology." CPT: Pharmacometrics & Systems Pharmacology 8, no. 6 (February 2, 2019): 331–32. http://dx.doi.org/10.1002/psp4.12376.

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15

Dumitrescu, T. Pene, MJ Fossler, and VD Schmith. "Pharmacometrics: Focus on the Patient." CPT: Pharmacometrics & Systems Pharmacology 4, no. 1 (December 30, 2014): 51–54. http://dx.doi.org/10.1002/psp4.5.

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16

van Hasselt, J. G. Coen, Marilee A. Andrew, Mary F. Hebert, Joel Tarning, Paolo Vicini, and Donald R. Mattison. "The status of pharmacometrics in pregnancy: highlights from the 3 rd American conference on pharmacometrics." British Journal of Clinical Pharmacology 74, no. 6 (November 13, 2012): 932–39. http://dx.doi.org/10.1111/j.1365-2125.2012.04280.x.

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17

Gayatri, Anggi, and Rianto Setiabudy. "Pharmacometrics: alternative approach of quantitative pharmacology." Pharmaceutical Sciences Asia 46, no. 2 (2019): 63–68. http://dx.doi.org/10.29090/psa.2019.02.018.0032.

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18

Ke, Alice Ban, Amin Rostami-Hodjegan, Ping Zhao, and Jashvant D. Unadkat. "Pharmacometrics in Pregnancy: An Unmet Need." Annual Review of Pharmacology and Toxicology 54, no. 1 (January 6, 2014): 53–69. http://dx.doi.org/10.1146/annurev-pharmtox-011613-140009.

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19

Davies, GR, W. Hope, and S. Khoo. "Opinion: The Pharmacometrics of Infectious Disease." CPT: Pharmacometrics & Systems Pharmacology 2, no. 8 (August 2013): 70. http://dx.doi.org/10.1038/psp.2013.46.

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20

Krause, Andreas. "Pharmacometrics: The Science of Quantitative Pharmacology." Journal of the American Statistical Association 103, no. 481 (March 1, 2008): 431–32. http://dx.doi.org/10.1198/jasa.2008.s224.

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21

Yano, Ikuko. "Clinical Pharmacometrics for Rational Drug Treatment." YAKUGAKU ZASSHI 139, no. 10 (October 1, 2019): 1227–34. http://dx.doi.org/10.1248/yakushi.19-00124.

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22

Pfister, Marc, and David Z. D'Argenio. "The Emerging Scientific Discipline of Pharmacometrics." Journal of Clinical Pharmacology 50, S9 (September 2010): 6S. http://dx.doi.org/10.1177/0091270010377789.

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23

Houk, BE. "Pharmacometrics: The Science of Quantitative Pharmacology." Clinical Pharmacology & Therapeutics 83, no. 5 (May 2008): 660–61. http://dx.doi.org/10.1038/clpt.2008.22.

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24

Pfister, Marc, and Don Mager. "The American Conference on Pharmacometrics 2013." Journal of Pharmacokinetics and Pharmacodynamics 40, S1 (April 30, 2013): 1. http://dx.doi.org/10.1007/s10928-013-9309-1.

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25

Barrett, Jeffrey S. "Time to Expect More From Pharmacometrics." Clinical Pharmacology & Therapeutics 108, no. 6 (June 19, 2020): 1129–31. http://dx.doi.org/10.1002/cpt.1914.

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26

Lavielle, Marc. "Pharmacometrics models with hidden Markovian dynamics." Journal of Pharmacokinetics and Pharmacodynamics 45, no. 1 (August 31, 2017): 91–105. http://dx.doi.org/10.1007/s10928-017-9541-1.

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27

Garrido, MJ, P. Berraondo, and IF Trocóniz. "CORRIGENDUM: Commentary on Pharmacometrics for Immunotherapy." CPT: Pharmacometrics & Systems Pharmacology 6, no. 4 (April 2017): 277. http://dx.doi.org/10.1002/psp4.12186.

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28

Mentré, France. "CPT: Pharmacometrics & Systems Pharmacology 2.0." CPT: Pharmacometrics & Systems Pharmacology 8, no. 4 (March 6, 2019): 195–96. http://dx.doi.org/10.1002/psp4.12396.

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29

Roganović, Maša, Ana Homšek, Marija Jovanović, Valentina Topić-Vučenović, Milica Ćulafić, Branislava Miljković, and Katarina Vučićević. "Concept and utility of population pharmacokinetic and pharmacokinetic/pharmacodynamic models in drug development and clinical practice." Arhiv za farmaciju 71, no. 4 (2021): 336–53. http://dx.doi.org/10.5937/arhfarm71-32901.

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Due to frequent clinical trial failures and consequently fewer new drug approvals, the need for improvement in drug development has, to a certain extent, been met using model-based drug development. Pharmacometrics is a part of pharmacology that quantifies drug behaviour, treatment response and disease progression based on different models (pharmacokinetic - PK, pharmacodynamic - PD, PK/PD models, etc.) and simulations. Regulatory bodies (European Medicines Agency, Food and Drug Administration) encourage the use of modelling and simulations to facilitate decision-making throughout all drug development phases. Moreover, the identification of factors that contribute to variability provides a basis for dose individualisation in routine clinical practice. This review summarises current knowledge regarding the application of pharmacometrics in drug development and clinical practice with emphasis on the population modelling approach.
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30

Roupe, Kathryn, Connie Remsberg, Jaime Yanez, and Neal Davies. "Pharmacometrics of Stilbenes: Seguing Towards the Clinic." Current Clinical Pharmacology 1, no. 1 (January 1, 2006): 81–101. http://dx.doi.org/10.2174/157488406775268246.

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31

Nekka, Fahima, Chantal Csajka, Mélanie Wilbaux, Sachin Sanduja, Jun Li, and Marc Pfister. "Pharmacometrics-based decision tools facilitate mHealth implementation." Expert Review of Clinical Pharmacology 10, no. 1 (November 24, 2016): 39–46. http://dx.doi.org/10.1080/17512433.2017.1251837.

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32

VÄLITALO, P., V. P. RANTA, A. C. HOOKER, M. KOKKI, and H. KOKKI. "Population pharmacometrics in support of analgesics studies." Acta Anaesthesiologica Scandinavica 58, no. 2 (January 2, 2014): 143–56. http://dx.doi.org/10.1111/aas.12253.

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33

Suzuki, Akiyuki. "Quantitative Decision Making in Drug Development: Pharmacometrics." YAKUGAKU ZASSHI 136, no. 4 (April 1, 2016): 537–42. http://dx.doi.org/10.1248/yakushi.15-00224-3.

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34

Vicini, P., and B. P. Smith. "Whither Pharmacometrics?: Present State and Future Choices." Clinical Pharmacology & Therapeutics 95, no. 6 (June 2014): 567–71. http://dx.doi.org/10.1038/clpt.2014.72.

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35

Zheng, Qing-shan, and Lu-jin Li. "Pharmacometrics: a quantitative tool of pharmacological research." Acta Pharmacologica Sinica 33, no. 11 (November 2012): 1337–38. http://dx.doi.org/10.1038/aps.2012.149.

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36

Kawai, Ryosei. "Pharmacometrics in pharmaceutical industry; Perspective in pharmacology." Proceedings for Annual Meeting of The Japanese Pharmacological Society WCP2018 (2018): SY31–3. http://dx.doi.org/10.1254/jpssuppl.wcp2018.0_sy31-3.

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37

Zhang, Liping, and Donald Mager. "The American conference on pharmacometrics 2014 (ACoP5)." Journal of Pharmacokinetics and Pharmacodynamics 41, S1 (September 24, 2014): 1. http://dx.doi.org/10.1007/s10928-014-9378-9.

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38

Jin, Jin Y., and Donald E. Mager. "The American Conference on Pharmacometrics 2015 (ACoP6)." Journal of Pharmacokinetics and Pharmacodynamics 42, S1 (September 14, 2015): 1–2. http://dx.doi.org/10.1007/s10928-015-9431-3.

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39

Ouellet, Daniele, Mirjam N. Trame, and Brian Corrigan. "The American Conference on Pharmacometrics 2016 (ACoP7)." Journal of Pharmacokinetics and Pharmacodynamics 43, S1 (September 19, 2016): 1–2. http://dx.doi.org/10.1007/s10928-016-9488-7.

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40

Cirincione, Brenda, Navin Goyal, and Rene Bruno. "The American Conference on Pharmacometrics 2017 (ACoP8)." Journal of Pharmacokinetics and Pharmacodynamics 44, S1 (September 20, 2017): 1–2. http://dx.doi.org/10.1007/s10928-017-9538-9.

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41

Li, L. "Precision Medicine in Pharmacometrics and Systems Pharmacology." CPT: Pharmacometrics & Systems Pharmacology 6, no. 3 (March 2017): 151–52. http://dx.doi.org/10.1002/psp4.12176.

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42

Mehrotra, Shailly, Virginia D. Schmith, Teodora Pene Dumitrescu, and Jogarao Gobburu. "Pharmacometrics-guided drug development of antihyperhidrosis agents." Journal of Clinical Pharmacology 55, no. 11 (June 18, 2015): 1256–67. http://dx.doi.org/10.1002/jcph.536.

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43

Kolbin, Alexey S., and Liudmila I. Yemelyanova. "The Use of Biotechnological Drugs in Pediatrics on the Example of Monoclonal Antibodies: Clinical Pharmacology View." Pediatric pharmacology 18, no. 4 (October 17, 2021): 304–13. http://dx.doi.org/10.15690/pf.v18i4.2293.

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The article reviews monoclonal antibodies, its structure, classifications, pharmacodynamics, pharmacokinetics, and adverse effects. There are examples for each section. Approaches to the research and criteria for drug selection in paediatrics are discussed in detail: the role of clinical trials, extrapolation and pharmacometrics. It has been shown that the differences in the pharmacokinetics of monoclonal antibodies between adults and children present due to the age-related characteristics of various physiological processes. The authors analyse such parameters as absorption, bioavailability, distribution, and elimination. The role of monoclonal antibodies immunogenicity in the structure of adverse effects in children is fully presented. Pharmacometrics is reviewed in the form of modelling and simulation in monoclonal antibodies dosing in paediatrics. It is important to consider the growth and development as “moving targets" in pediatrics regardless the principle of monoclonal antibodies dosage in children. The conclusions were made, and the guidelines were prepared based on the article results.
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44

Srinivasan, Meenakshi, Annesha White, Ayyappa Chaturvedula, Valvanera Vozmediano, Stephan Schmidt, Leo Plouffe, and La’Marcus T. Wingate. "Incorporating Pharmacometrics into Pharmacoeconomic Models: Applications from Drug Development." PharmacoEconomics 38, no. 10 (July 31, 2020): 1031–42. http://dx.doi.org/10.1007/s40273-020-00944-0.

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Abstract Pharmacometrics is the science of quantifying the relationship between the pharmacokinetics and pharmacodynamics of drugs in combination with disease models and trial information to aid in drug development and dosing optimization for clinical practice. Considering the variability in the dose–concentration–effect relationship of drugs, an opportunity exists in linking pharmacokinetic and pharmacodynamic model-based estimates with pharmacoeconomic models. This link may provide early estimates of the cost effectiveness of drug therapies, thus informing late-stage drug development, pricing, and reimbursement decisions. Published case studies have demonstrated how integrated pharmacokinetic–pharmacodynamic–pharmacoeconomic models can complement traditional pharmacoeconomic analyses by identifying the impact of specific patient sub-groups, dose, dosing schedules, and adherence on the cost effectiveness of drugs, thus providing a mechanistic basis to predict the economic value of new drugs. Greater collaboration between the pharmacoeconomics and pharmacometrics community can enable methodological improvements in pharmacokinetic–pharmacodynamic–pharmacoeconomic models to support drug development.
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45

Franck, Sebastian, Robin Michelet, Fiordiligie Casilag, Jean-Claude Sirard, Sebastian G. Wicha, and Charlotte Kloft. "A Model-Based Pharmacokinetic/Pharmacodynamic Analysis of the Combination of Amoxicillin and Monophosphoryl Lipid A Against S. pneumoniae in Mice." Pharmaceutics 13, no. 4 (March 30, 2021): 469. http://dx.doi.org/10.3390/pharmaceutics13040469.

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Combining amoxicillin with the immunostimulatory toll-like receptor 4 agonist monophosphoryl lipid A (MPLA) represents an innovative approach for enhancing antibacterial treatment success. Exploiting pharmacokinetic and pharmacodynamic data from an infection model of Streptococcus pneumoniae infected mice, we aimed to evaluate the preclinical exposure-response relationship of amoxicillin with MPLA coadministration and establish a link to survival. Antibiotic serum concentrations, bacterial numbers in lung and spleen and survival data of mice being untreated or treated with amoxicillin (four dose levels), MPLA, or their combination were analyzed by nonlinear mixed-effects modelling and time-to-event analysis using NONMEM® to characterize these treatment regimens. On top of a pharmacokinetic interaction, regarding the pharmacodynamic effects the combined treatment was superior to both monotherapies: The amoxicillin efficacy at highest dose was increased by a bacterial reduction of 1.74 log10 CFU/lung after 36 h and survival was increased 1.35-fold to 90.3% after 14 days both compared to amoxicillin alone. The developed pharmacometric pharmacokinetic/pharmacodynamic disease-treatment-survival models provided quantitative insights into a novel treatment option against pneumonia revealing a pharmacokinetic interaction and enhanced activity of amoxicillin and the immune system stimulator MPLA in combination. Further development of this drug combination flanked with pharmacometrics towards the clinical setting seems promising.
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46

Michelet, Robin, Moreno Ursino, Sandrine Boulet, Sebastian Franck, Fiordiligie Casilag, Mara Baldry, Jens Rolff, et al. "The Use of Translational Modelling and Simulation to Develop Immunomodulatory Therapy as an Adjunct to Antibiotic Treatment in the Context of Pneumonia." Pharmaceutics 13, no. 5 (April 22, 2021): 601. http://dx.doi.org/10.3390/pharmaceutics13050601.

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The treatment of respiratory tract infections is threatened by the emergence of bacterial resistance. Immunomodulatory drugs, which enhance airway innate immune defenses, may improve therapeutic outcome. In this concept paper, we aim to highlight the utility of pharmacometrics and Bayesian inference in the development of immunomodulatory therapeutic agents as an adjunct to antibiotics in the context of pneumonia. For this, two case studies of translational modelling and simulation frameworks are introduced for these types of drugs up to clinical use. First, we evaluate the pharmacokinetic/pharmacodynamic relationship of an experimental combination of amoxicillin and a TLR4 agonist, monophosphoryl lipid A, by developing a pharmacometric model accounting for interaction and potential translation to humans. Capitalizing on this knowledge and associating clinical trial extrapolation and statistical modelling approaches, we then investigate the TLR5 agonist flagellin. The resulting workflow combines expert and prior knowledge on the compound with the in vitro and in vivo data generated during exploratory studies in order to construct high-dimensional models considering the pharmacokinetics and pharmacodynamics of the compound. This workflow can be used to refine preclinical experiments, estimate the best doses for human studies, and create an adaptive knowledge-based design for the next phases of clinical development.
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47

Muller, Anouk E., Peter van Vliet, and Birgit C. P. Koch. "Clinical Experience with Off-Label Intrathecal Administration of Selected Antibiotics in Adults: An Overview with Pharmacometric Considerations." Antibiotics 12, no. 8 (August 5, 2023): 1291. http://dx.doi.org/10.3390/antibiotics12081291.

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Drain-associated intracerebral infections are life-threatening emergencies. Their treatment is challenging due to the limited penetration of antibiotics to the site of infection, resulting in potentially inadequate exposure. The emergence of multidrug-resistant pathogens might force the use of off-label intrathecal (IT) doses of antibiotics. We reviewed the literature on general aspects determining intrathecal dosing regimen, using pharmacometric knowledge. We summarised clinical experience with IT doses of antibiotics that are usually not used intrathecally, as well as the outcome of the cases and concentrations reached in the cerebrospinal fluid (CSF). Factors determining the IT regimen are the size of the ventricle system and the CSF drainage volume. With regard to pharmacometrics, pharmacokinetic/pharmacodynamic indices are likely similar to those in non-cerebral infections. The following number (N) of cases were described: benzylpenicillin (>50), ampicillin (1), ceftazidime (2), cephaloridine (56), ceftriaxone (1), cefotiam (1), meropenem (57), linezolid (1), tigecycline (15), rifampicin (3), levofloxacin (2), chloramphenicol (3) and daptomycin (8). Many side effects were reported for benzylpenicillin in the 1940–50s, but for the other antibiotics, when administered correctly, all side effects were minor and reversible. These data might help when choosing an IT dosing regimen in case there is no alternative option due to antimicrobial resistance.
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48

French, Jonathan, and France Mentré. "Welcome to the statistics and pharmacometrics themed issue." CPT: Pharmacometrics & Systems Pharmacology 10, no. 4 (April 2021): 273–74. http://dx.doi.org/10.1002/psp4.12625.

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49

Dong, Min, Tsuyoshi Fukuda, and Alexander A. Vinks. "Optimization of Mycophenolic Acid Therapy Using Clinical Pharmacometrics." Drug Metabolism and Pharmacokinetics 29, no. 1 (2014): 4–11. http://dx.doi.org/10.2133/dmpk.dmpk-13-rv-112.

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50

Perera, Vidya, Michael J. Dolton, Andrew J. McLachlan, Vaughan J. Carr, and Richard O. Day. "Pharmacometrics: an underused resource in Australian clinical research." Medical Journal of Australia 200, no. 2 (February 2014): 82–83. http://dx.doi.org/10.5694/mja13.10663.

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