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Translational PK–PD modeling in pain

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Abstract

The current gap between animal research and clinical development of analgesic drugs presents a challenge for the application of translational PK–PD modeling and simulation. First, animal pain models lack predictive and construct validity to accurately reflect human pain etiologies and, secondly, clinical pain is a multidimensional sensory experience that can’t always be captured by objective and robust measures. These challenges complicate the use of translational PK–PD modeling to project PK–PD data generated in preclinical species to a plausible range of clinical doses. To date only a few drug targets identified in animal studies have shown to be successful in the clinic. PK–PD modeling of biomarkers collected during the early phase of clinical development can bridge animal and clinical pain research. For drugs with novel mechanism of actions understanding of the target pharmacology is essential in order to increase the success of clinical development. There is a specific interest in the application of human pain models that can mimic different aspects of acute/chronic pain symptoms and serves as link between animal and clinical pain research. In early clinical development the main objective of PK–PD modeling is to characterize the relationship between target site binding and downstream biomarkers that have a potential link to the clinical endpoint (e.g. readouts from the human pain models) so as to facilitate the selection of doses for proof of concept studies. In patient studies, the role of PK–PD modeling and simulation is to characterize and confirm patient populations in terms of responder profiles with the aim to find the right dose for the right patient.

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References

  1. Woodcock J, Witter J, Dionne RA (2007) Stimulating the development of mechanism-based, individualized pain therapies. Nat Rev Drug Discov 6:703–710

    Article  PubMed  CAS  Google Scholar 

  2. Kola I, Landis J (2004) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3:711–715

    Article  PubMed  CAS  Google Scholar 

  3. Taylor ML (2011) The impact of the “business” of pain medicine on patient care. Pain Med 12:763–772

    Article  PubMed  Google Scholar 

  4. Fish L, Nicholson BD (2008) The payer side: patient outcomes and cost. Am J Ther 15(Suppl 10):S20–S22

    Article  PubMed  Google Scholar 

  5. Woosley RL, Cossman J (2007) Drug development and the FDA’s critical path initiative. Clin Pharmacol Ther 81:129–133

    Article  PubMed  CAS  Google Scholar 

  6. Lesko LJ (2007) Paving the critical path: how can clinical pharmacology help achieve the vision? Clin Pharmacol Ther 81:170–177

    Article  PubMed  CAS  Google Scholar 

  7. Suryawanshi S, Zhang L, Pfister M, Meibohm B (2010) The current role of model-based drug development. Expert Opin Drug Discov 5:311–321

    Article  PubMed  CAS  Google Scholar 

  8. Allerheiligen SR (2010) Next-generation model-based drug discovery and development: quantitative and systems pharmacology. Clin Pharmacol Ther 88:135–137

    Article  PubMed  CAS  Google Scholar 

  9. Zhang L, Sinha V, Forgue ST, Callies S, Ni L, Peck R, Allerheiligen SR (2006) Model-based drug development: the road to quantitative pharmacology. J Pharmacokinet Pharmacodyn 33:369–393

    Article  PubMed  CAS  Google Scholar 

  10. Danhof M, de Lange EC, Della Pasqua OE, Ploeger BA, Voskuyl RA (2008) Mechanism-based pharmacokinetic–pharmacodynamic (PK–PD) modeling in translational drug research. Trends Pharmacol Sci 29:186–191

    Article  PubMed  CAS  Google Scholar 

  11. Gabrielsson J, Green AR (2009) Quantitative pharmacology or pharmacokinetic pharmacodynamic integration should be a vital component in integrative pharmacology. J Pharmacol Exp Ther 331:767–774

    Article  PubMed  CAS  Google Scholar 

  12. Gabrielsson J, Dolgos H, Gillberg PG, Bredberg U, Benthem B, Duker G (2009) Early integration of pharmacokinetic and dynamic reasoning is essential for optimal development of lead compounds: strategic considerations. Drug Discov Today 14:358–372

    Article  PubMed  CAS  Google Scholar 

  13. Maurer TS, Ghosh A, Haddish-Berhane N, Sawant-Basak A, Boustany-Kari CM, She L, Leininger MT, Zhu T, Tugnait M, Yang X, Kimoto E, Mascitti V, Robinson RP (2011) Pharmacodynamic model of sodium-glucose transporter 2 (SGLT2) inhibition: implications for quantitative translational pharmacology. AAPS J 13:576–584

    Article  PubMed  CAS  Google Scholar 

  14. Chang C, Byon W, Lu Y, Jacobsen LK, Badura LL, Sawant-Basak A, Miller E, Liu J, Grimwood S, Wang EQ, Maurer TS (2011) Quantitative PK–PD model-based translational pharmacology of a novel kappa opioid receptor antagonist between rats and humans. AAPS J 13:565–575

    Article  PubMed  CAS  Google Scholar 

  15. Zhou Q, Gallo JM (2011) The pharmacokinetic/pharmacodynamic pipeline: translating anticancer drug pharmacology to the clinic. AAPS J 13:111–120

    Article  PubMed  CAS  Google Scholar 

  16. Mogil JS, Davis KD, Derbyshire SW (2010) The necessity of animal models in pain research. Pain 151:12–17

    Article  PubMed  Google Scholar 

  17. Whiteside GT, Kennedy JD (2010) Consideration of pharmacokinetic pharmacodynamic relationships in the discovery of new pain drugs. In: Kruger L, Light AR (ed) Translational pain research: from mouse to man, Chapt 16. CRC Press, Boca Raton

  18. Danhof M, de JJ, de Lange EC, Della PO, Ploeger BA, Voskuyl RA (2007) Mechanism-based pharmacokinetic–pharmacodynamic modeling: biophase distribution, receptor theory, and dynamical systems analysis. Annu Rev Pharmacol Toxicol 47:357–400

    Article  PubMed  CAS  Google Scholar 

  19. Flores-Murrieta FJ, Ko HC, Flores-Acevedo DM, Lopez-Munoz FJ, Jusko WJ, Sale ME, Castaneda-Hernandez G (1998) Pharmacokinetic–pharmacodynamic modeling of tolmetin antinociceptive effect in the rat using an indirect response model: a population approach. J Pharmacokinet Biopharm 26:547–557

    Article  PubMed  CAS  Google Scholar 

  20. Krekels EH, Angesjo M, Sjogren I, Moller KA, Berge OG, Visser SA (2011) Pharmacokinetic–pharmacodynamic modeling of the inhibitory effects of naproxen on the time-courses of inflammatory pain, fever, and the ex vivo synthesis of TXB2 and PGE2 in rats. Pharm Res 28:1561–1576

    Article  PubMed  CAS  Google Scholar 

  21. Viberg A, Martino G, Lessard E, Laird JM (2012) Evaluation of an innovative population pharmacokinetic-based design for behavioral pharmacodynamic endpoints. AAPS J. 14(4):657–663

    Article  PubMed  Google Scholar 

  22. Beier H, Garrido MJ, Christoph T, Kasel D, Troconiz IF (2008) Semi-mechanistic pharmacokinetic/pharmacodynamic modelling of the antinociceptive response in the presence of competitive antagonism: the interaction between tramadol and its active metabolite on micro-opioid agonism and monoamine reuptake inhibition, in the rat. Pharm Res 25:1789–1797

    Article  PubMed  CAS  Google Scholar 

  23. Garrido MJ, Valle M, Campanero MA, Calvo R, Troconiz IF (2000) Modeling of the in vivo antinociceptive interaction between an opioid agonist, (+)-O-desmethyltramadol, and a monoamine reuptake inhibitor, (−)-O-desmethyltramadol, in rats. J Pharmacol Exp Ther 295:352–359

    PubMed  CAS  Google Scholar 

  24. Yassen A, Olofsen E, Dahan A, Danhof M (2005) Pharmacokinetic–pharmacodynamic modeling of the antinociceptive effect of buprenorphine and fentanyl in rats: role of receptor equilibration kinetics. J Pharmacol Exp Ther 313:1136–1149

    Article  PubMed  CAS  Google Scholar 

  25. Yassen A, Kan J, Olofsen E, Suidgeest E, Dahan A, Danhof M (2007) Pharmacokinetic–pharmacodynamic modeling of the respiratory depressant effect of norbuprenorphine in rats. J Pharmacol Exp Ther 321:598–607

    Article  PubMed  CAS  Google Scholar 

  26. Cox EH, Langemeijer MW, Gubbens-Stibbe JM, Muir KT, Danhof M (1999) The comparative pharmacodynamics of remifentanil and its metabolite, GR90291, in a rat electroencephalographic model. Anesthesiology 90:535–544

    Article  PubMed  CAS  Google Scholar 

  27. Drews J (2000) Drug discovery: a historical perspective. Science 287:1960–1964

    Article  PubMed  CAS  Google Scholar 

  28. Lahana R (1999) How many leads from HTS? Drug Discov Today 4:447–448

    Article  PubMed  Google Scholar 

  29. Gabrielsson J, Fjellstrom O, Ulander J, Rowley M, Van Der Graaf PH (2011) Pharmacodynamic–pharmacokinetic integration as a guide to medicinal chemistry. Curr Top Med Chem 11:404–418

    Article  PubMed  CAS  Google Scholar 

  30. Mao J (2012) Current challenges in translational pain research. Trends Pharmacol Sci 33(11):568–573

    Article  PubMed  CAS  Google Scholar 

  31. Mogil JS (2009) Animal models of pain: progress and challenges. Nat Rev Neurosci 10:283–294

    Article  PubMed  CAS  Google Scholar 

  32. Drummond GB, Vowler SL (2012) Variation: use it or misuse it—replication and its variants. Br J Pharmacol 166:1977–1980

    Article  PubMed  CAS  Google Scholar 

  33. Heinzmann S, McMahon SB (2011) New molecules for the treatment of pain. Curr Opin Support Palliat Care 5:111–115

    Article  PubMed  Google Scholar 

  34. Dray A (2003) Novel molecular targets in pain control. Curr Opin Anaesthesiol 16:521–525

    Article  PubMed  Google Scholar 

  35. Morgan P, Van Der Graaf PH, Arrowsmith J, Feltner DE, Drummond KS, Wegner CD, Street SD (2012) Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving phase II survival. Drug Discov Today 17:419–424

    Article  PubMed  CAS  Google Scholar 

  36. Kim E, Howes OD, Kim BH, Jeong JM, Lee JS, Jang IJ, Shin SG, Turkheimer FE, Kapur S, Kwon JS (2012) Predicting brain occupancy from plasma levels using PET: superiority of combining pharmacokinetics with pharmacodynamics while modeling the relationship. J Cereb Blood Flow Metab 32:759–768

    Article  PubMed  CAS  Google Scholar 

  37. Bourdet DL, Tsuruda PR, Obedencio GP, Smith JA (2012) Prediction of human serotonin and norepinephrine transporter occupancy of duloxetine by pharmacokinetic/pharmacodynamic modeling in the rat. J Pharmacol Exp Ther 341:137–145

    Article  PubMed  CAS  Google Scholar 

  38. Joshi A, Li W, Sanabria S, Holahan M, Purcell M, Declerq R, Depre M, Bormans G, Van Laere K, Hamill T (2012) Translational studies with [11C]MK-3168, a PET tracer for fatty acid amide hydrolase (FAAH). J Nucl Med 53(Supplement 1):397

    Google Scholar 

  39. Burns HD, Van Laere K, Sanabria-Bohorquez S et al (2007) [18F]MK-9470, a positron emission tomography (PET) tracer for in vivo human PET brain imaging of the cannabinoid-1 receptor. Proc Natl Acad Sci USA 104:9800–9805

    Article  PubMed  CAS  Google Scholar 

  40. Li GL, Winter H, Arends R, Jay GW, Le V, Young T, Huggins JP (2012) Assessment of the pharmacology and tolerability of PF-04457845, an irreversible inhibitor of fatty acid amide hydrolase-1, in healthy subjects. Br J Clin Pharmacol 73:706–716

    Article  PubMed  CAS  Google Scholar 

  41. Huggins JP, Smart TS, Langman S, Taylor L, Young T (2012) An efficient randomised, placebo-controlled clinical trial with the irreversible fatty acid amide hydrolase-1 inhibitor PF-04457845, which modulates endocannabinoids but fails to induce effective analgesia in patients with pain due to osteoarthritis of the knee. Pain 153:1837–1846

    Article  PubMed  CAS  Google Scholar 

  42. Ahn K, Smith SE, Liimatta MB, Beidler D, Sadagopan N, Dudley DT, Young T, Wren P, Zhang Y, Swaney S, Van BK, Blankman JL, Nomura DK, Bhattachar SN, Stiff C, Nomanbhoy TK, Weerapana E, Johnson DS, Cravatt BF (2011) Mechanistic and pharmacological characterization of PF-04457845: a highly potent and selective fatty acid amide hydrolase inhibitor that reduces inflammatory and noninflammatory pain. J Pharmacol Exp Ther 338:114–124

    Article  PubMed  CAS  Google Scholar 

  43. van Rossum J, AriensRIENS EJ (1962) Receptor-reserve and threshold-phenomena. II. Theories on drug-action and a quantitative approach to spare receptors and threshold values. Arch Int Pharmacodyn Ther 136:385–413

    PubMed  Google Scholar 

  44. Cox EH, Kerbusch T, Van Der Graaf PH, Danhof M (1998) Pharmacokinetic–pharmacodynamic modeling of the electroencephalogram effect of synthetic opioids in the rat: correlation with the interaction at the mu-opioid receptor. J Pharmacol Exp Ther 284:1095–1103

    PubMed  CAS  Google Scholar 

  45. Chizh BA, Priestley T, Rowbotham M, Schaffler K (2009) Predicting therapeutic efficacy—experimental pain in human subjects. Brain Res Rev 60:243–254

    Article  PubMed  CAS  Google Scholar 

  46. Olesen AE, Andresen T, Staahl C, Drewes AM (2012) Human experimental pain models for assessing the therapeutic efficacy of analgesic drugs. Pharmacol Rev 64:722–779

    Article  PubMed  CAS  Google Scholar 

  47. Sarton E, Olofsen E, Romberg R, den Hartigh J, Kest B, Nieuwenhuijs D, Burm A, Teppema L, Dahan A (2000) Sex differences in morphine analgesia: an experimental study in healthy volunteers. Anesthesiology 93:1245–1254

    Article  PubMed  CAS  Google Scholar 

  48. Bouw MR, Gardmark M, Hammarlund-Udenaes M (2000) Pharmacokinetic–pharmacodynamic modelling of morphine transport across the blood–brain barrier as a cause of the antinociceptive effect delay in rats—a microdialysis study. Pharm Res 17:1220–1227

    Article  PubMed  CAS  Google Scholar 

  49. Niesters M, Dahan A, Kest B, Zacny J, Stijnen T, Aarts L, Sarton E (2010) Do sex differences exist in opioid analgesia? A systematic review and meta-analysis of human experimental and clinical studies. Pain 151:61–68

    Article  PubMed  Google Scholar 

  50. Abbott FV, Palmour RM (1988) Morphine-6-glucuronide: analgesic effects and receptor binding profile in rats. Life Sci 43:1685–1695

    Article  PubMed  CAS  Google Scholar 

  51. Murthy BR, Pollack GM, Brouwer KL (2002) Contribution of morphine-6-glucuronide to antinociception following intravenous administration of morphine to healthy volunteers. J Clin Pharmacol 42:569–576

    Article  PubMed  CAS  Google Scholar 

  52. Skarke C, Darimont J, Schmidt H, Geisslinger G, Lotsch J (2003) Analgesic effects of morphine and morphine-6-glucuronide in a transcutaneous electrical pain model in healthy volunteers. Clin Pharmacol Ther 73:107–121

    Article  PubMed  CAS  Google Scholar 

  53. Romberg R, Olofsen E, Sarton E, den Hartigh J, Taschner PE, Dahan A (2004) Pharmacokinetic–pharmacodynamic modeling of morphine-6-glucuronide-induced analgesia in healthy volunteers: absence of sex differences. Anesthesiology 100:120–133

    Article  PubMed  CAS  Google Scholar 

  54. Niesters M, Dahan A (2012) Pharmacokinetic and pharmacodynamic considerations for NMDA receptor antagonists in the treatment of chronic neuropathic pain. Expert Opin Drug Metab Toxicol 8(11):1409–1417

    Article  PubMed  CAS  Google Scholar 

  55. Olofsen E, Noppers I, Niesters M, Kharasch E, Aarts L, Sarton E, Dahan A (2012) Estimation of the contribution of norketamine to ketamine-induced acute pain relief and neurocognitive impairment in healthy volunteers. Anesthesiology 117:353–364

    Article  PubMed  CAS  Google Scholar 

  56. Olesen AE, Upton R, Foster DJ, Staahl C, Christrup LL, Arendt-Nielsen L, Drewes AM (2010) A pharmacokinetic and pharmacodynamic study of oral oxycodone in a human experimental pain model of hyperalgesia. Clin Pharmacokinet 49:817–827

    Article  PubMed  CAS  Google Scholar 

  57. Olesen AE, Staahl C, Arendt-Nielsen L, Drewes AM (2010) Different effects of morphine and oxycodone in experimentally evoked hyperalgesia: a human translational study. Br J Clin Pharmacol 70:189–200

    Article  PubMed  CAS  Google Scholar 

  58. Burton MB, Gebhart GF (1998) Effects of kappa-opioid receptor agonists on responses to colorectal distension in rats with and without acute colonic inflammation. J Pharmacol Exp Ther 285:707–715

    PubMed  CAS  Google Scholar 

  59. Ross FB, Smith MT (1997) The intrinsic antinociceptive effects of oxycodone appear to be kappa-opioid receptor mediated. Pain 73:151–157

    Article  PubMed  CAS  Google Scholar 

  60. Yassen A, Olofsen E, Romberg R, Sarton E, Danhof M, Dahan A (2006) Mechanism-based pharmacokinetic–pharmacodynamic modeling of the antinociceptive effect of buprenorphine in healthy volunteers. Anesthesiology 104:1232–1242

    Article  PubMed  CAS  Google Scholar 

  61. Huang P, Kehner GB, Cowan A, Liu-Chen LY (2001) Comparison of pharmacological activities of buprenorphine and norbuprenorphine: norbuprenorphine is a potent opioid agonist. J Pharmacol Exp Ther 297:688–695

    PubMed  CAS  Google Scholar 

  62. Yassen A, Olofsen E, Kan J, Dahan A, Danhof M (2007) Animal-to-human extrapolation of the pharmacokinetic and pharmacodynamic properties of buprenorphine. Clin Pharmacokinet 46:433–447

    Article  PubMed  CAS  Google Scholar 

  63. Rothman RB, Xu H, Wang JB, Partilla JS, Kayakiri H, Rice KC, Uhl GR (1995) Ligand selectivity of cloned human and rat opioid mu receptors. Synapse 21:60–64

    Article  PubMed  CAS  Google Scholar 

  64. Leiser SC, Dunlop J, Bowlby MR, Devilbiss DM (2011) Aligning strategies for using EEG as a surrogate biomarker: a review of preclinical and clinical research. Biochem Pharmacol 81:1408–1421

    Article  PubMed  CAS  Google Scholar 

  65. Lotsch J (2005) Pharmacokinetic–pharmacodynamic modeling of opioids. J Pain Symptom Manage 29:S90–S103

    Article  PubMed  CAS  Google Scholar 

  66. Schnabel A, Hahn N, Broscheit J, Muellenbach RM, Rieger L, Roewer N, Kranke P (2012) Remifentanil for labour analgesia: a meta-analysis of randomised controlled trials. Eur J Anaesthesiol 29:177–185

    Article  PubMed  CAS  Google Scholar 

  67. Yassen A, Olofsen E, van Dorp E, Sarton E, Teppema L, Danhof M, Dahan A (2007) Mechanism-based pharmacokinetic–pharmacodynamic modelling of the reversal of buprenorphine-induced respiratory depression by naloxone : a study in healthy volunteers. Clin Pharmacokinet 46:965–980

    Article  PubMed  CAS  Google Scholar 

  68. Olofsen E, van Dorp E, Teppema L, Aarts L, Smith TW, Dahan A, Sarton E (2010) Naloxone reversal of morphine- and morphine-6-glucuronide-induced respiratory depression in healthy volunteers: a mechanism-based pharmacokinetic–pharmacodynamic modeling study. Anesthesiology 112:1417–1427

    Article  PubMed  CAS  Google Scholar 

  69. Moran MM, McAlexander MA, Biro T, Szallasi A (2011) Transient receptor potential channels as therapeutic targets. Nat Rev Drug Discov 10:601–620

    Article  PubMed  CAS  Google Scholar 

  70. Denney WS (2009) Modeling and Simulation for Determination of the Therapeutic Window of MK-2295: a TRPV1 Antagonist. PAGE. In: Abstracts of the annual meeting of the population approach group in Europe. pp. 18 Abstr 1507 [www.page-meeting.org/?abstract=1507]. Accessed 10 Sept 2012

  71. Othman AA, Nothaft W, Awni WM, Dutta S (2012) Effects of the TRPV1 antagonist ABT-102 on body temperature in healthy volunteers: pharmacokinetic/pharmacodynamic analysis of three phase 1 trials. Br J Clin Pharmacol. doi:10.1111/j.1365-2125.2012.04405.x

  72. Sheiner LB (1994) A new approach to the analysis of analgesic drug trials, illustrated with bromfenac data. Clin Pharmacol Ther 56:309–322

    Article  PubMed  CAS  Google Scholar 

  73. Mandema JW, Stanski DR (1996) Population pharmacodynamic model for ketorolac analgesia. Clin Pharmacol Ther 60:619–635

    Article  PubMed  CAS  Google Scholar 

  74. Kowalski KG, Olson S, Remmers AE, Hutmacher MM (2008) Modeling and simulation to support dose selection and clinical development of SC-75416, a selective COX-2 inhibitor for the treatment of acute and chronic pain. Clin Pharmacol Ther 83:857–866

    Article  PubMed  CAS  Google Scholar 

  75. Rohatagi S, Kastrissios H, Sasahara K, Truitt K, Moberly JB, Wada R, Salazar DE (2008) Pain relief model for a COX-2 inhibitor in patients with postoperative dental pain. Br J Clin Pharmacol 66:60–70

    Article  PubMed  CAS  Google Scholar 

  76. Rohatagi S, Kastrissios H, Gao Y, Zhang N, Xu J, Moberly J, Wada R, Yoshihara K, Takahashi M, Truitt K, Salazar D (2007) Predictive population pharmacokinetic/pharmacodynamic model for a novel COX-2 inhibitor. J Clin Pharmacol 47:358–370

    Article  PubMed  CAS  Google Scholar 

  77. Li H, Mandema J, Wada R, Jayawardena S, Desjardins P, Doyle G, Kellstein D (2012) Modeling the onset and offset of dental pain relief by ibuprofen. J Clin Pharmacol 52:89–101

    Article  PubMed  CAS  Google Scholar 

  78. Foster D, Upton R, Christrup L, Popper L (2008) Pharmacokinetics and pharmacodynamics of intranasal versus intravenous fentanyl in patients with pain after oral surgery. Ann Pharmacother 42:1380–1387

    Article  PubMed  CAS  Google Scholar 

  79. Scott JC, Ponganis KV, Stanski DR (1985) EEG quantitation of narcotic effect: the comparative pharmacodynamics of fentanyl and alfentanil. Anesthesiology 62:234–241

    Article  PubMed  CAS  Google Scholar 

  80. Scott JC, Cooke JE, Stanski DR (1991) Electroencephalographic quantitation of opioid effect: comparative pharmacodynamics of fentanyl and sufentanil. Anesthesiology 74:34–42

    Article  PubMed  CAS  Google Scholar 

  81. Yassen A, Olofsen E, Romberg R, Sarton E, Teppema L, Danhof M, Dahan A (2007) Mechanism-based PK/PD modeling of the respiratory depressant effect of buprenorphine and fentanyl in healthy volunteers. Clin Pharmacol Ther 81:50–58

    Article  PubMed  CAS  Google Scholar 

  82. Yassen A, Olofsen E, Kan J, Dahan A, Danhof M (2008) Pharmacokinetic–pharmacodynamic modeling of the effectiveness and safety of buprenorphine and fentanyl in rats. Pharm Res 25:183–193

    Article  PubMed  CAS  Google Scholar 

  83. Cullberg M, Eriksson UG, Wahlander K, Eriksson H, Schulman S, Karlsson MO (2005) Pharmacokinetics of ximelagatran and relationship to clinical response in acute deep vein thrombosis. Clin Pharmacol Ther 77:279–290

    Article  PubMed  CAS  Google Scholar 

  84. Jonsson S, Karlsson MO (2005) Estimation of dosing strategies aiming at maximizing utility or responder probability, using oxybutynin as an example drug. Eur J Pharm Sci 25:123–132

    Article  PubMed  CAS  Google Scholar 

  85. Poland B, Hodge FL, Khan A, Clemen RT, Wagner JA, Dykstra K, Krishna R (2009) The clinical utility index as a practical multiattribute approach to drug development decisions. Clin Pharmacol Ther 86:105–108

    Article  PubMed  CAS  Google Scholar 

  86. Mazoit JX, Butscher K, Samii K (2007) Morphine in postoperative patients: pharmacokinetics and pharmacodynamics of metabolites. Anesth Analg 105:70–78

    Article  PubMed  CAS  Google Scholar 

  87. Abou Hammoud H, Simon N, Urien S, Riou B, Lechat P, Aubrun F (2009) Intravenous morphine titration in immediate postoperative pain management: population kinetic-pharmacodynamic and logistic regression analysis. Pain 144:139–146

    Article  PubMed  CAS  Google Scholar 

  88. Kim Y (2011) Missing data handling in chronic pain trials. J Biopharm Stat 21:311–325

    Article  PubMed  CAS  Google Scholar 

  89. Plan EL, Elshoff JP, Stockis A, Sargentini-Maier ML, Karlsson MO (2012) Likert pain score modeling: a Markov integer model and an autoregressive continuous model. Clin Pharmacol Ther 91:820–828

    Article  PubMed  CAS  Google Scholar 

  90. Sheiner LB, Beal SL (1981) Evaluation of methods for estimating population pharmacokinetic parameters. II. Biexponential model and experimental pharmacokinetic data. J Pharmacokinet Biopharm 9:635–651

    Article  PubMed  CAS  Google Scholar 

  91. Sheiner LB, Beal SL (1980) Evaluation of methods for estimating population pharmacokinetics parameters. I. Michaelis–Menten model: routine clinical pharmacokinetic data. J Pharmacokinet Biopharm 8:553–571

    Article  PubMed  CAS  Google Scholar 

  92. Dahan A, Olofsen E, Sigtermans M, Noppers I, Niesters M, Aarts L, Bauer M, Sarton E (2011) Population pharmacokinetic–pharmacodynamic modeling of ketamine-induced pain relief of chronic pain. Eur J Pain 15:258–267

    Article  PubMed  CAS  Google Scholar 

  93. Sigtermans M, Dahan A, Mooren R, Bauer M, Kest B, Sarton E, Olofsen E (2009) S(+)-ketamine effect on experimental pain and cardiac output: a population pharmacokinetic–pharmacodynamic modeling study in healthy volunteers. Anesthesiology 111:892–903

    Article  PubMed  CAS  Google Scholar 

  94. Webster LR, Peppin JF, Murphy FT, Lu B, Tobias JK, Vanhove GF (2011) Efficacy, safety, and tolerability of NGX-4010, capsaicin 8% patch, in an open-label study of patients with peripheral neuropathic pain. Diabetes Res Clin Pract 93:187–197

    Article  PubMed  CAS  Google Scholar 

  95. Martini C, Yassen A, Olofsen E, Passier P, Stoker M, Dahan A (2012) Pharmacodynamic analysis of the analgesic effect of capsaicin 8% patch (Qutenza) in diabetic neuropathic pain patients: detection of distinct response groups. J Pain Res 5:51–59

    PubMed  CAS  Google Scholar 

  96. Backonja MM, Walk D, Edwards RR, Sehgal N, Moeller-Bertram T, Wasan A, Irving G, Argoff C, Wallace M (2009) Quantitative sensory testing in measurement of neuropathic pain phenomena and other sensory abnormalities. Clin J Pain 25:641–647

    Article  PubMed  Google Scholar 

  97. Maier C, Baron R, Tolle TR et al (2010) Quantitative sensory testing in the German Research Network on Neuropathic Pain (DFNS): somatosensory abnormalities in 1236 patients with different neuropathic pain syndromes. Pain 150:439–450

    Article  PubMed  CAS  Google Scholar 

  98. Bouhassira D, Attal N, Fermanian J, Alchaar H, Gautron M, Masquelier E, Rostaing S, Lanteri-Minet M, Collin E, Grisart J, Boureau F (2004) Development and validation of the neuropathic pain symptom inventory. Pain 108:248–257

    Article  PubMed  Google Scholar 

  99. Byon W, Ouellet D, Chew M, Ito K, Burger P, Pauer L, Zeiher B, Corrigan B (2010) Exposure-response analyses of the effects of pregabalin in patients with fibromyalgia using daily pain scores and patient global impression of change. J Clin Pharmacol 50:803–815

    Article  PubMed  CAS  Google Scholar 

  100. Lockwood PA, Cook JA, Ewy WE, Mandema JW (2003) The use of clinical trial simulation to support dose selection: application to development of a new treatment for chronic neuropathic pain. Pharm Res 20:1752–1759

    Article  PubMed  CAS  Google Scholar 

  101. Dworkin RH, Turk DC, Peirce-Sandner S et al (2012) Considerations for improving assay sensitivity in chronic pain clinical trials: IMMPACT recommendations. Pain 153:1148–1158

    Article  PubMed  CAS  Google Scholar 

  102. Lemmens HJ, Wada DR, Munera C, Eltahtawy A, Stanski DR (2006) Enriched analgesic efficacy studies: an assessment by clinical trial simulation. Contemp Clin Trials 27:165–173

    Article  PubMed  CAS  Google Scholar 

  103. Kissin I (2010) The development of new analgesics over the past 50 years: a lack of real breakthrough drugs. Anesth Analg 110:780–789

    Article  PubMed  CAS  Google Scholar 

  104. Yassen A, Kan J, Olofsen E, Suidgeest E, Dahan A, Danhof M (2006) Mechanism-based pharmacokinetic–pharmacodynamic modeling of the respiratory-depressant effect of buprenorphine and fentanyl in rats. J Pharmacol Exp Ther 319:682–692

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Global Clinical Pharmacology and Exploratory Development, Astellas Pharma Global Development Europe, Elisabethhof 1, PO BOX 108, 2350 AC, Leiderdorp, The Netherlands

    Ashraf Yassen & Paul Passier

  2. Drug Discovery Research, Astellas Pharma Inc., Ibaraki, Japan

    Yasuhisa Furuichi

  3. Division of Anesthesiology, Leiden University Medical Center, Leiden, The Netherlands

    Albert Dahan

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  1. Ashraf Yassen
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  2. Paul Passier
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  3. Yasuhisa Furuichi
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  4. Albert Dahan
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Yassen, A., Passier, P., Furuichi, Y. et al. Translational PK–PD modeling in pain. J Pharmacokinet Pharmacodyn 40, 401–418 (2013). https://doi.org/10.1007/s10928-012-9282-0

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