Reproducible pharmacokinetics release hrsbug7wkzfhjprf7egzztskcy

by John P. A. Ioannidis

Published in Journal of Pharmacokinetics and Pharmacodynamics by Springer Nature
ISSN-L 1567-567X
Release Date 2019-04-19
Publisher Springer Nature
Primary Language en (lookup)
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crossref.alternative-id ['9621']
crossref.subject ['Pharmacology']
crossref.type journal-article

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  1. Sci Transl Med.2016.Goodman SN, Fanelli D, Ioannidis JP (2016) What does research reproducibility mean? Sci Transl Med 8:34. https://doi.org/10.1126/scitranslmed.aaf5027 (DOI: 10.1126/scitranslmed.aaf5027)
  2. Eur J Drug Metab Pharmacokinet.1996.Macheras P, Argyrakis P, Polymilis C (1996) Fractal geometry, fractal kinetics and chaos en route to biopharmaceutical sciences. Eur J Drug Metab Pharmacokinet 21:77–86 (DOI: 10.1007/bf03190255)
  3. Pharm Res.1997.Macheras P, Argyrakis P (1997) Gastrointestinal drug absorption: is it time to consider heterogeneity as well as homogeneity? Pharm Res 14:842–847 (DOI: 10.1023/a:1012183313218)
  4. AAPS J.2007.Pang KS, Weiss M, Macheras P (2007) Advanced pharmacokinetic models based on organ clearance, circulatory, and fractal concepts. AAPS J 9:E268–E283 (DOI: 10.1208/aapsj0902030)
  5. J Clin Pharmacol.2015.Dykstra K, Mehrotra N, Tornøe CW, Kastrissios H, Patel B, Al-Huniti N, Jadhav P, Wang Y, Byon W (2015) Reporting guidelines for population pharmacokinetic analyses. J Clin Pharmacol 55:875–887. https://doi.org/10.1002/jcph.532 (DOI: 10.1002/jcph.532)
  6. Clin Pharmacokinet.2015.Kanji S, Hayes M, Ling A, Shamseer L, Chant C, Edwards DJ, Edwards S, Ensom MH, Foster DR, Hardy B, Kiser TH, la Porte C, Roberts JA, Shulman R, Walker S, Zelenitsky S, Moher D (2015) Reporting guidelines for clinical pharmacokinetic studies: the ClinPK statement. Clin Pharmacokinet 54:783–795. https://doi.org/10.1007/s40262-015-0236-8 (DOI: 10.1007/s40262-015-0236-8)
  7. Guidance for Industry (2018) Population Pharmacokinetics.US Food and Drug Administration website. Available at http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/U CM072137.pdf. Accessed Aug 3 2018
  8. J Clin Pharmacol.2010.Romero K, Corrigan B, Tornùe CW et al (2010) Pharmacometrics as a discipline is entering the "industrialization" phase: standards, automation, knowledge sharing, and training are critical for future success. J Clin Pharmacol 50:9S–19S (DOI: 10.1177/0091270010377788)
  9. AAPS J.2005.Wade JR, Edholm M, Salmonson T (2005) A guide for reporting the results of population pharmacokinetic analyses: a Swedish perspective. AAPS J 7:E456 (DOI: 10.1208/aapsj070245)
  10. Guideline on Reporting the Results of Population Pharmacokinetic Analyses (2018). Committee for Medicinal Products for Human Use (CHMP) http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500003067.pdf . Accessed Aug 3 2018
  11. CPT.2013.Byon W, Smith MK, Chan P, Tortorici MA et al (2013) Establishing best practices and guidance in population modeling: an experience with an internal population pharmacokinetic analysis guidance. CPT 2(e51):1–8
  12. AAPS J.2012.Bonate PL, Strougo A, Desai A et al (2012) Guidelines for the quality control of population pharmacokinetic-pharmacodynamic analyses: an industry perspective. AAPS J 14:749–758 (DOI: 10.1208/s12248-012-9387-9)
  13. Clin Pharmacokinet.2014.Jamesen KM, McLeay SC, Barras A, Green B (2014) Reporting a population pharmacokinetic-pharmacodynamic study: a journal's perspective. Clin Pharmacokinet 53:111–122 (DOI: 10.1007/s40262-013-0114-1)
  14. Clin Pharmacokinet.2007.Brendel K, Dartois C, Comets E et al (2007) Are population pharmacokinetic and/or pharmacodynamic models adequately evaluated? A survey of the literature from 2002 to 2004. Clin Pharmacokinet 46:221–234 (DOI: 10.2165/00003088-200746030-00003)
  15. Br J Clin Pharmacol.2007.Dartois C, Brendel K, Comets E et al (2007) Overview of model building strategies in population PK/PD analyses: 2002–2004 literature survey. Br J Clin Pharmacol 64:603–612 (DOI: 10.1111/j.1365-2125.2007.02975.x)
  16. Br J Clin Pharmacol.2004.Mills E, Loke YK, Ping W, Victor MM, Daniel P, David M et al (2004) Determining the reporting quality of RCTs in clinical pharmacology. Br J Clin Pharmacol 58:61–65 (DOI: 10.1111/j.1365-2125.2004.2092.x)
  17. Trials.2009.Mills EJ, Chan AW, Ping W, Andy V, Gordon HG, Douglas GA (2009) Design, analysis, and presentation of crossover trials. Trials 10:27 (DOI: 10.1186/1745-6215-10-27)
  18. Int J Clin Pharmacol Ther.2017.Woodcock BG, Harder S (2017) The 10-D assessment and evidence-based medicine tool for authors and peer reviewers in clinical pharmacology. Int J Clin Pharmacol Ther 55:639–642 (DOI: 10.5414/cp203073)
  19. Pharm Dev Technol.2017.Jasińska-Stroschein M, Kurczewska U, Orszulak-Michalak D (2017) Errors in reporting on dissolution research: methodological and statistical implications. Pharm Dev Technol 22:103–110. https://doi.org/10.1080/10837450.2016.1194858 (DOI: 10.1080/10837450.2016.1194858)
  20. Bioanalysis.2011.Schaefer P (2011) Automated reporting of pharmacokinetic study results: gaining efficiency downstream from the laboratory. Bioanalysis 3:1471–1478. https://doi.org/10.4155/bio.11.133 (DOI: 10.4155/bio.11.133)
  21. Pharmazie.2010.Uesawa Y, Takeuchi T, Mohri K (2010) Publication bias on clinical studies of pharmacokinetic interactions between felodipine and grapefruit juice. Pharmazie 65:375–378
  22. Int J Cardiol.1993.Cowley AJ, Skene A, Stainer K, Hampton JR (1993) The effect of lorcainide on arrhythmias and survival in patients with acute myocardial infarction: an example of publication bias. Int J Cardiol 40:161–166 (DOI: 10.1016/0167-5273(93)90279-p)
  23. Milbank Q.2016.Ioannidis JP (2016) The mass production of redundant, misleading, and conflicted systematic reviews and meta-analyses. Milbank Q 94:485–514. https://doi.org/10.1111/1468-0009.12210 (DOI: 10.1111/1468-0009.12210)
  24. CMAJ.2007.Ioannidis JP, Trikalinos TA (2007) The appropriateness of asymmetry tests for publication bias in meta-analyses: a large survey. CMAJ 176:1091–1096 (DOI: 10.1503/cmaj.060410)
  25. JAMA.1997.Rennie D (1997) Thyroid storm. JAMA 277:1238–1243 (DOI: 10.1001/jama.1997.03540390068038)
  26. JAMA.1997.Dong BJ, Hauck WW, Gambertoglio JG, Gee L, White JR, Bubp JL, Greenspan FS (1997) Bioequivalence of generic and brand-name levothyroxine products in the treatment of hypothyroidism. JAMA 277:1205–1213 (DOI: 10.1001/jama.1997.03540390035032)
  27. Circ Res.2015.Begley CG, Ioannidis JP (2015) Reproducibility in science: improving the standard for basic and preclinical research. Circ Res 116:116–126. https://doi.org/10.1161/CIRCRESAHA.114.303819 (DOI: 10.1161/circresaha.114.303819)
  28. Nature.2012.Begley CG, Ellis LM (2012) Drug development: raise standards for preclinical cancer research. Nature 483:531–533. https://doi.org/10.1038/483531a (DOI: 10.1038/483531a)
  29. Cochrane Database Syst Rev.2017.Lundh A, Lexchin J, Mintzes B, Schroll JB, Bero L (2017) Industry sponsorship and research outcome. Cochrane Database Syst Rev 2:MD000033. https://doi.org/10.1002/14651858.MR000033.pub3 (DOI: 10.1002/14651858.mr000033.pub3)
  30. PLoS Biol.2016.Iqbal SA, Wallach JD, Khoury MJ, Schully SD, Ioannidis JP (2016) Reproducible research practices and transparency across the biomedical literature. PLoS Biol 14(1):e1002333. https://doi.org/10.1371/journal.pbio.1002333 (DOI: 10.1371/journal.pbio.1002333)
  31. JAMA.2014.Ebrahim S, Sohani ZN, Montoya L, Agarwal A, Thorlund K, Mills EJ, Ioannidis JP (2014) Reanalyses of randomized clinical trial data. JAMA 312:1024–1032. https://doi.org/10.1001/jama.2014.9646 (DOI: 10.1001/jama.2014.9646)
  32. Eur J Pharm Sci.2017.Völler S, Flint RB, Stolk LM, Degraeuwe PLJ, Simons SHP, Pokorna P, Burger DM, de Groot R, Tibboel D, Knibbe CAJ, DINO study group (2017) Model-based clinical dose optimization for phenobarbital in neonates: an illustration of the importance of data sharing and external validation. Eur J Pharm Sci 109S:S90–S97. https://doi.org/10.1016/j.ejps.2017.05.026 (DOI: 10.1016/j.ejps.2017.05.026)
  33. Trends Pharmacol Sci.2013.Doshi P, Goodman SN, Ioannidis JP (2013) Raw data from clinical trials: within reach? Trends Pharmacol Sci 34:645–647. https://doi.org/10.1016/j.tips.2013.10.006 (DOI: 10.1016/j.tips.2013.10.006)
  34. Paediatr Anaesth.2009.Anderson BJ, Merry AF (2009) Data sharing for pharmacokinetic studies. Paediatr Anaesth 19:1005–1010 (DOI: 10.1111/j.1460-9592.2009.03051.x)
  35. Comput Methods Progr Biomed.2017.Lacy-Jones K, Hayward P, Andrews S, Gledhill I, McAllister M, Abrahamsson B, Rostami-Hodjegan A, Pepin X (2017) Biopharmaceutics data management system for anonymised data sharing and curation: first application with orbito IMI project. Comput Methods Progr Biomed 140:29–44. https://doi.org/10.1016/j.cmpb.2016.11.006 (DOI: 10.1016/j.cmpb.2016.11.006)
  36. Science.2016.Stodden V, McNutt M, Bailey DH, Deelman E, Gil Y, Hanson B, Heroux MA, Ioannidis JP, Taufer M (2016) Enhancing reproducibility for computational methods. Science 354:1240–1241 (DOI: 10.1126/science.aah6168)
  37. NONMEM's user's guides.2009.Beal S, Sheiner LB, Boekmann A, Bauer RJ (2009) NONMEM's user's guides. ICON Development Solutions, Ellicott City
  38. Comput Methods Progr Biomed.2005.Lindbom L, Pihlgren P, Jonsson EN (2005) PsN-Toolkit–a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Progr Biomed 79:241–257 (DOI: 10.1016/j.cmpb.2005.04.005)
  39. CPT Pharmacometrics Syst Pharmacol.2015.Sanduja S, Jewell P, Aron E, Pharai N (2015) Cloud computing for pharmacometrics: using AWS, NONMEM, PsN, Grid Engine, and Sonic. CPT Pharmacometrics Syst Pharmacol 4:537–546. https://doi.org/10.1002/psp4.12016 (DOI: 10.1002/psp4.12016)
  40. Eur J Pharm Sci.2017.Conrado DJ, Karlsson MO, Romero K, Sarr C, Wilkins JJ (2017) Open innovation: towards sharing of data, models and workflows. Eur J Pharm Sci 109S:S65–S71. https://doi.org/10.1016/j.ejps.2017.06.035 (DOI: 10.1016/j.ejps.2017.06.035)
  41. CPT Pharmacometrics Syst Pharmacol.2015.Swat MJ, Moodie S, Wimalaratne SM, Kristensen NR, Lavielle M, Mari A, Magni P, Smith MK, Bizzotto R, Pasotti L, Mezzalana E, Comets E, Sarr C, Terranova N, Blaudez E, Chan P, Chard J, Chatel K, Chenel M, Edwards D, Franklin C, Giorgino T, Glont M, Girard P, Grenon P, Harling K, Hooker AC, Kaye R, Keizer R, Kloft C, Kok JN, Kokash N, Laibe C, Laveille C, Lestini G, Mentré F, Munafo A, Nordgren R, Nyberg HB, Parra-Guillen ZP, Plan E, Ribba B, Smith G, Trocóniz IF, Yvon F, Milligan PA, Harnisch L, Karlsson M, Hermjakob H, Le Novère N (2015) Pharmacometrics Markup Language (PharmML): opening new perspectives for model exchange in drug development. CPT Pharmacometrics Syst Pharmacol 4:316–319. https://doi.org/10.1002/psp4.57 (DOI: 10.1002/psp4.57)
  42. CPT Pharmacometrics Syst Pharmacol.2017.Smith MK, Moodie SL, Bizzotto R, Blaudez E, Borella E, Carrara L, Chan P, Chenel M, Comets E, Gieschke R, Harling K, Harnisch L, Hartung N, Hooker AC, Karlsson MO, Kaye R, Kloft C, Kokash N, Lavielle M, Lestini G, Magni P, Mari A, Mentré F, Muselle C, Nordgren R, Nyberg HB, Parra-Guillén ZP, Pasotti L, Rode-Kristensen N, Sardu ML, Smith GR, Swat MJ, Terranova N, Yngman G, Yvon F, Holford N, DDMoRe consortium (2017) Model description language (MDL): a standard for modeling and simulation. CPT Pharmacometrics Syst Pharmacol 6:647–650. https://doi.org/10.1002/psp4.12222 (DOI: 10.1002/psp4.12222)
  43. CPT Pharmacometrics Syst Pharmacol.2017.Wilkins JJ, Chan P, Chard J, Smith G, Smith MK, Beer M, Dunn A, Flandorfer C, Franklin C, Gomeni R, Harnisch L, Kaye R, Moodie S, Sardu ML, Wang E, Watson E, Wolstencroft K, Cheung S, DDMoRe Consortium (2017) Thoughtflow: standards and tools for provenance capture and workflow definition to support model-informed drug discovery and development. CPT Pharmacometrics Syst Pharmacol 6:285–292. https://doi.org/10.1002/psp4.12171 (DOI: 10.1002/psp4.12171)
  44. Nucleic Acids Res.2015.Chang A, Schomburg I, Placzek S, Jeske L, Ulbrich M, Xiao M, Sensen CW, Schomburg D (2015) BRENDA in 2015: exciting developments in its 25th year of existence. Nucleic Acids Res 43:D439–D446 (DOI: 10.1093/nar/gku1068)
  45. Nucleic Acids Res.2012.Wittig U, Kania R, Golebiewski M, Rey M, Shi L, Jong L, Algaa E, Weidemann A, Sauer-Danzwith H, Mir S et al (2012) SABIO-RK–database for biochemical reaction kinetics. Nucleic Acids Res 40:D790–D796 (DOI: 10.1093/nar/gkr1046)
  46. FEBS J.2014.Wittig U, Rey M, Kania R, Bittkowski M, Shi L, Golebiewski M, Weidemann A, Mueller W, Rojas I (2014) Challenges for an enzymatic reaction kinetics database. FEBS J 281:572–582 (DOI: 10.1111/febs.12562)
  47. Perspect Sci.2014.Wittig U, Kania R, Bittkowski M, Wetsch E, Shi L, Jong L, Golebiewski M, Rey M, Weidemann A, Rojas I et al (2014) Data extraction for the reaction kinetics database SABIO-RK. Perspect Sci 1:33–40 (DOI: 10.1016/j.pisc.2014.02.004)
  48. FEBS J.2018.Swainston N, Baici A, Bakker BM, Cornish-Bowden A, Fitzpatrick PF, Halling P, Leyh TS, O'Donovan C, Raushel FM, Reschel U, Rohwer JM, Schnell S, Schomburg D, Tipton KF, Tsai MD, Westerhoff HV, Wittig U, Wohlgemuth R, Kettner C (2018) STRENDA DB: enabling the validation and sharing of enzyme kinetics data. FEBS J 285:2193–2204. https://doi.org/10.1111/febs.14427 (DOI: 10.1111/febs.14427)
  49. Nature.2016.Baker M (2016) 1,500 scientists lift the lid on reproducibility. Nature 533:452–454 (DOI: 10.1038/533452a)
  50. PLoS Biol.2015.Ioannidis JP, Fanelli D, Dunne DD, Goodman SN (2015) Meta-research: evaluation and improvement of research methods and practices. PLoS Biol 13:e1002264. https://doi.org/10.1371/journal.pbio.1002264 (DOI: 10.1371/journal.pbio.1002264)
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