1932

Abstract

There are many challenges along the path to the approval of new drugs to treat CNS disorders, one of the greatest areas of unmet medical need with a large societal burden and health-care impact. Unfortunately, over the past two decades, few CNS drug approvals have succeeded, leading many pharmaceutical companies to deprioritize this therapeutic area. The reasons for the failures in CNS drug discovery are likely to be multifactorial. However, selecting the most biologically plausible molecular targets that are relevant to the disorder is a critical first step to improve the probability of success. In this review, we outline previous methods for identifying and validating novel targets for CNS drug discovery, and, cognizant of previous failures, we discuss potential new strategies that may improve the probability of success of developing novel treatments for CNS disorders.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-pharmtox-010716-104624
2017-01-06
2024-04-18
Loading full text...

Full text loading...

/deliver/fulltext/pharmtox/57/1/annurev-pharmtox-010716-104624.html?itemId=/content/journals/10.1146/annurev-pharmtox-010716-104624&mimeType=html&fmt=ahah

Literature Cited

  1. Kessler RC, Aguilar-Gaxiola S, Alonso J, Chatterji S, Lee S. 1.  et al. 2009. The global burden of mental disorders: an update from the WHO World Mental Health (WMH) surveys. Epidemiol. Psichiatr. Soc. 18:23–33 [Google Scholar]
  2. Stein DJ, Illes J. 2.  2015. Beyond scientism and skepticism: an integrative approach to global mental health. Front. Psychiatry 6:166 [Google Scholar]
  3. Arrowsmith J, Miller P. 3.  2013. Trial watch: Phase II and Phase III attrition rates 2011–2012. Nat. Rev. Drug Discov. 12:569 [Google Scholar]
  4. MacDonald ME, Ambrose CM, Duyao MP, Myers RH, Lin C. 4.  et al. 1993. A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. Cell 72:971–83 [Google Scholar]
  5. Hutson PH, Finger EN, Magliaro BC, Smith SM, Converso A. 5.  et al. 2011. The selective phosphodiesterase 9 (PDE9) inhibitor PF-04447943 (6-[(3S,4S)-4-methyl-1-(pyrimidin-2-ylmethyl)pyrrolidin-3-yl]-1-(tetrahydro-2H-pyran-4-yl)-1,5-dihydro-4H-pyrazolo[3,4-d]pyrimidin-4-one) enhances synaptic plasticity and cognitive function in rodents. Neuropharmacology 61:665–76 [Google Scholar]
  6. Christian EP, Snyder DH, Song W, Gurley DA, Smolka J. 6.  et al. 2015. EEG-β/γ spectral power elevation in rat: a translatable biomarker elicited by GABAAα2/3-positive allosteric modulators at nonsedating anxiolytic doses. J. Neurophysiol. 113:116–31 [Google Scholar]
  7. Hashimoto K. 7.  2015. Targeting of α7 nicotinic acetylcholine receptors in the treatment of schizophrenia and the use of auditory sensory gating as a translational biomarker. Curr. Pharm. Des. 21:3797–806 [Google Scholar]
  8. Chernet E, Martin LJ, Li D, Need AB, Barth VN. 8.  et al. 2005. Use of LC/MS to assess brain tracer distribution in preclinical, in vivo receptor occupancy studies: dopamine D2, serotonin 2A and NK-1 receptors as examples. Life Sci. 78:340–46 [Google Scholar]
  9. Grimwood S, Hartig PR. 9.  2009. Target site occupancy: emerging generalizations from clinical and preclinical studies. Pharmacol. Ther. 122:281–301 [Google Scholar]
  10. Willner P. 10.  1986. Validation criteria for animal models of human mental disorders: learned helplessness as a paradigm case. Prog. Neuropsychopharmacol. Biol. Psychiatry 10:677–90 [Google Scholar]
  11. Mullard A. 11.  2011. Reliability of ‘new drug target’ claims called into question. Nat. Rev. Drug Discov. 10:643–44 [Google Scholar]
  12. Prinz F, Schlange T, Asadullah K. 12.  2011. Believe it or not: How much can we rely on published data on potential drug targets?. Nat. Rev. Drug Discov. 10:712 [Google Scholar]
  13. Begley CG, Ellis LM. 13.  2012. Drug development: Raise standards for preclinical cancer research. Nature 483:531–33 [Google Scholar]
  14. Dolgin E. 14.  2014. Drug discoverers chart path to tackling data irreproducibility. Nat. Rev. Drug Discov. 13:875–76 [Google Scholar]
  15. Perrin S. 15.  2014. Preclinical research: Make mouse studies work. Nature 507:423–25 [Google Scholar]
  16. Arrowsmith J. 16.  2011. Trial watch: Phase III and submission failures: 2007–2010. Nat. Rev. Drug Discov. 10:87 [Google Scholar]
  17. Arrowsmith J. 17.  2011. Trial watch: Phase II failures: 2008–2010. Nat. Rev. Drug Discov. 10:328–29 [Google Scholar]
  18. Kramer MS, Last B, Getson A, Reines SA. 18.  1997. The effects of a selective D4 dopamine receptor antagonist (L-745,870) in acutely psychotic inpatients with schizophrenia. Arch. Gen. Psychiatry 54:567–72 [Google Scholar]
  19. Truffinet P, Tamminga CA, Fabre LF, Meltzer HY, Rivière ME, Papillon-Downey C. 19.  1999. Placebo-controlled study of the D4/5-HT2A antagonist fananserin in the treatment of schizophrenia. Am. J. Psychiatry 156:419–25 [Google Scholar]
  20. Ball WA, Snavely DB, Hargreaves RJ, Szegedi A, Lines C, Reines SA. 20.  2014. Addition of an NK1 receptor antagonist to an SSRI did not enhance the antidepressant effects of SSRI monotherapy: results from a randomized clinical trial in patients with major depressive disorder. Hum. Psychopharmacol. 29:568–77 [Google Scholar]
  21. Keller M, Montgomery S, Ball W, Morrison M, Snavely D. 21.  et al. 2006. Lack of efficacy of the substance P (neurokinin1 receptor) antagonist aprepitant in the treatment of major depressive disorder. Biol. Psychiatry 59:216–23 [Google Scholar]
  22. Kramer MS, Cutler N, Feighner J, Shrivastava R, Carman J. 22.  et al. 1998. Distinct mechanism for antidepressant activity by blockade of central substance P receptors. Science 281:1640–45 [Google Scholar]
  23. Kramer MS, Winokur A, Kelsey J, Preskorn SH, Rothschild AJ. 23.  et al. 2004. Demonstration of the efficacy and safety of a novel substance P (NK1) receptor antagonist in major depression. Neuropsychopharmacology 29:385–92 [Google Scholar]
  24. Porsolt RD, Le Pichon M, Jalfre M. 24.  1977. Depression: a new animal model sensitive to antidepressant treatments. Nature 266:730–32 [Google Scholar]
  25. Depoortère R, Dargazanli G, Estenne-Bouhtou G, Coste A, Lanneau C. 25.  et al. 2005. Neurochemical, electrophysiological and pharmacological profiles of the selective inhibitor of the glycine transporter-1 SSR504734, a potential new type of antipsychotic. Neuropsychopharmacology 30:1963–85 [Google Scholar]
  26. Moser PC, Moran PM, Frank RA, Kehne JH. 26.  1996. Reversal of amphetamine-induced behaviours by MDL 100,907, a selective 5-HT2A antagonist. Behav. Brain Res. 73:163–67 [Google Scholar]
  27. Vardigan JD, Converso A, Hutson PH, Uslaner JM. 27.  2011. The selective phosphodiesterase 9 (PDE9) inhibitor PF-04447943 attenuates a scopolamine-induced deficit in a novel rodent attention task. J. Neurogenet. 25:120–26 [Google Scholar]
  28. Aboul-Fotouh S. 28.  2015. Behavioral effects of nicotinic antagonist mecamylamine in a rat model of depression: prefrontal cortex level of BDNF protein and monoaminergic neurotransmitters. Psychopharmacology 232:1095–105 [Google Scholar]
  29. Boulay D, Pichat P, Dargazanli G, Estenne-Bouhtou G, Terranova JP. 29.  et al. 2008. Characterization of SSR103800, a selective inhibitor of the glycine transporter-1 in models predictive of therapeutic activity in schizophrenia. Pharmacol. Biochem. Behav. 91:47–58 [Google Scholar]
  30. Bugarski-Kirola D, Wang A, Abi-Saab D, Blattler T. 30.  2014. A Phase II/III trial of bitopertin monotherapy compared with placebo in patients with an acute exacerbation of schizophrenia – results from the CandleLyte study. Eur. Neuropsychopharmacol. 24:1024–36 [Google Scholar]
  31. Egan M, Zhao X, Gottwald R, Harper-Mozley L, Zhang Y. 31.  et al. 2013. Randomized crossover study of the histamine H3 inverse agonist MK-0249 for the treatment of cognitive impairment in patients with schizophrenia. Schizophr. Res. 146:224–30 [Google Scholar]
  32. Fox GB, Esbenshade TA, Pan JB, Radek RJ, Krueger KM. 32.  et al. 2005. Pharmacological properties of ABT-239 [4-(2-{2-[(2R)-2-Methylpyrrolidinyl]ethyl}-benzofuran-5-yl)benzonitrile]: II. Neurophysiological characterization and broad preclinical efficacy in cognition and schizophrenia of a potent and selective histamine H3 receptor antagonist. J. Pharmacol. Exp. Ther. 313:176–90 [Google Scholar]
  33. Haig GM, Pritchett Y, Meier A, Othman AA, Hall C. 33.  et al. 2014. A randomized study of H3 antagonist ABT-288 in mild-to-moderate Alzheimer's dementia. J. Alzheimer's Dis. 42:959–71 [Google Scholar]
  34. Moller HJ, Demyttenaere K, Olausson B, Szamosi J, Wilson E. 34.  et al. 2015. Two Phase III randomised double-blind studies of fixed-dose TC-5214 (dexmecamylamine) adjunct to ongoing antidepressant therapy in patients with major depressive disorder and an inadequate response to prior antidepressant therapy. World J. Biol. Psychiatry 16:483–501 [Google Scholar]
  35. Schoemaker JH, Jansen WT, Schipper J, Szegedi A. 35.  2014. The selective glycine uptake inhibitor org 25935 as an adjunctive treatment to atypical antipsychotics in predominant persistent negative symptoms of schizophrenia: results from the GIANT trial. J. Clin. Psychopharmacol. 34:190–98 [Google Scholar]
  36. Southam E, Cilia J, Gartlon JE, Woolley ML, Lacroix LP. 36.  et al. 2009. Preclinical investigations into the antipsychotic potential of the novel histamine H3 receptor antagonist GSK207040. Psychopharmacology 201:483–94 [Google Scholar]
  37. Vieta E, Thase ME, Naber D, D'Souza B, Rancans E. 37.  et al. 2014. Efficacy and tolerability of flexibly-dosed adjunct TC-5214 (dexmecamylamine) in patients with major depressive disorder and inadequate response to prior antidepressant. Eur. Neuropsychopharmacol. 24:564–74 [Google Scholar]
  38. Berman RM, Cappiello A, Anand A, Oren DA, Heninger GR. 38.  et al. 2000. Antidepressant effects of ketamine in depressed patients. Biol. Psychiatry 47:351–54 [Google Scholar]
  39. Browne RG. 39.  1979. Effects of antidepressants and anticholinergics in a mouse “behavioral despair” test. Eur. J. Pharmacol. 58:331–34 [Google Scholar]
  40. Drevets WC, Zarate CA Jr, Furey ML. 40.  2013. Antidepressant effects of the muscarinic cholinergic receptor antagonist scopolamine: a review. Biol. Psychiatry 73:1156–63 [Google Scholar]
  41. Geoffroy M, Scheel-Kruger J, Christensen AV. 41.  1990. Effect of imipramine in the “learned helplessness” model of depression in rats is not mimicked by combinations of specific reuptake inhibitors and scopolamine. Psychopharmacology 101:371–75 [Google Scholar]
  42. Trullas R, Skolnick P. 42.  1990. Functional antagonists at the NMDA receptor complex exhibit antidepressant actions. Eur. J. Pharmacol. 185:1–10 [Google Scholar]
  43. Zarate CA Jr., Singh JB, Carlson PJ, Brutsche NE, Ameli R. 43.  et al. 2006. A randomized trial of an N-methyl-d-aspartate antagonist in treatment-resistant major depression. Arch. Gen. Psychiatry 63:856–64 [Google Scholar]
  44. Hubbard D, Hacksell U, McFarland K. 44.  2013. Behavioral effects of clozapine, pimavanserin, and quetiapine in rodent models of Parkinson's disease and Parkinson's disease psychosis: evaluation of therapeutic ratios. Behav. Pharmacol. 24:628–32 [Google Scholar]
  45. McFarland K, Price DL, Bonhaus DW. 45.  2011. Pimavanserin, a 5-HT2A inverse agonist, reverses psychosis-like behaviors in a rodent model of Parkinson's disease. Behav. Pharmacol. 22:681–92 [Google Scholar]
  46. Marder SR. 46.  2006. Drug initiatives to improve cognitive function. J. Clin. Psychiatry 67:Suppl. 931–5 [Google Scholar]
  47. Tomarken AJ, Dichter GS, Freid C, Addington S, Shelton RC. 47.  2004. Assessing the effects of bupropion SR on mood dimensions of depression. J. Affect. Disord. 78:235–41 [Google Scholar]
  48. Cryan JF, Bruijnzeel AW, Skjei KL, Markou A. 48.  2003. Bupropion enhances brain reward function and reverses the affective and somatic aspects of nicotine withdrawal in the rat. Psychopharmacology 168:347–58 [Google Scholar]
  49. Chamberlain SR, Del Campo N, Dowson J, Muller U, Clark L. 49.  et al. 2007. Atomoxetine improved response inhibition in adults with attention deficit/hyperactivity disorder. Biol. Psychiatry 62:977–84 [Google Scholar]
  50. Liu YP, Huang TS, Tung CS, Lin CC. 50.  2015. Effects of atomoxetine on attention and impulsivity in the five-choice serial reaction time task in rats with lesions of dorsal noradrenergic ascending bundle. Prog. Neuropsychopharmacol. Biol. Psychiatry 56:81–90 [Google Scholar]
  51. Duncan GE, Paul IA, Harden TK, Mueller RA, Stumpf WE, Breese GR. 51.  1985. Rapid down regulation of beta adrenergic receptors by combining antidepressant drugs with forced swim: a model of antidepressant-induced neural adaptation. J. Pharmacol. Exp. Ther. 234:402–8 [Google Scholar]
  52. Helmeste DM. 52.  1986. Rapid down-regulation of S2 serotonin receptors by antidepressants: noradr-energic-serotonergic interactions. Life Sci. 39:223–27 [Google Scholar]
  53. Racagni G, Mocchetti I, Calderini G, Battistella A, Brunello N. 53.  1983. Temporal sequence of changes in central noradrenergic system of rat after prolonged antidepressant treatment: receptor desensitization and neurotransmitter interactions. Neuropharmacology 22:415–24 [Google Scholar]
  54. Butler PD, Barkai AI. 54.  1987. Agonist-stimulation of cerebral phosphoinositide turnover following long-term treatment with antidepressants. Adv. Exp. Med. Biol. 221:531–47 [Google Scholar]
  55. Jensen JB, Mikkelsen JD, Mork A. 55.  2000. Increased adenylyl cyclase type 1 mRNA, but not adenylyl cyclase type 2 in the rat hippocampus following antidepressant treatment. Eur. Neuropsychopharmacol. 10:105–11 [Google Scholar]
  56. Reierson GW, Mastronardi CA, Licinio J, Wong ML. 56.  2009. Repeated antidepressant therapy increases cyclic GMP signaling in rat hippocampus. Neurosci. Lett. 466:149–53 [Google Scholar]
  57. Alboni S, Benatti C, Capone G, Corsini D, Caggia F. 57.  et al. 2010. Time-dependent effects of escitalopram on brain derived neurotrophic factor (BDNF) and neuroplasticity related targets in the central nervous system of rats. Eur. J. Pharmacol. 643:180–87 [Google Scholar]
  58. Altar CA, Whitehead RE, Chen R, Wortwein G, Madsen TM. 58.  2003. Effects of electroconvulsive seizures and antidepressant drugs on brain-derived neurotrophic factor protein in rat brain. Biol. Psychiatry 54:703–9 [Google Scholar]
  59. Malberg JE, Eisch AJ, Nestler EJ, Duman RS. 59.  2000. Chronic antidepressant treatment increases neurogenesis in adult rat hippocampus. J. Neurosci. 20:9104–10 [Google Scholar]
  60. Bodick NC, Offen WW, Levey AI, Cutler NR, Gauthier SG. 60.  et al. 1997. Effects of xanomeline, a selective muscarinic receptor agonist, on cognitive function and behavioral symptoms in Alzheimer disease. Arch. Neurol. 54:465–73 [Google Scholar]
  61. Shekhar A, Potter WZ, Lightfoot J, Lienemann J, Dube S. 61.  et al. 2008. Selective muscarinic receptor agonist xanomeline as a novel treatment approach for schizophrenia. Am. J. Psychiatry 165:1033–39 [Google Scholar]
  62. Bradley SR, Lameh J, Ohrmund L, Son T, Bajpai A. 62.  et al. 2010. AC-260584, an orally bioavailable M1 muscarinic receptor allosteric agonist, improves cognitive performance in an animal model. Neuropharmacology 58:365–73 [Google Scholar]
  63. Kennedy JP, Bridges TM, Gentry PR, Brogan JT, Kane AS. 63.  et al. 2009. Synthesis and structure–activity relationships of allosteric potentiators of the M4 muscarinic acetylcholine receptor. ChemMedChem 4:1600–7 [Google Scholar]
  64. Marlo JE, Niswender CM, Days EL, Bridges TM, Xiang Y. 64.  et al. 2009. Discovery and characterization of novel allosteric potentiators of M1 muscarinic receptors reveals multiple modes of activity. Mol. Pharmacol. 75:577–88 [Google Scholar]
  65. Hardy J, Selkoe DJ. 65.  2002. The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics. Science 297:353–56 [Google Scholar]
  66. Citron M. 66.  2010. Alzheimer's disease: strategies for disease modification. Nat. Rev. Drug Discov. 9:387–98 [Google Scholar]
  67. Feldman HH, Haas M, Gandy S, Schoepp DD, Cross AJ. 67.  et al. 2014. Alzheimer's disease research and development: a call for a new research roadmap. Ann. N.Y. Acad. Sci. 1313:1–16 [Google Scholar]
  68. Morris GP, Clark IA, Vissel B. 68.  2014. Inconsistencies and controversies surrounding the amyloid hypothesis of Alzheimer's disease. Acta Neuropathol. Commun. 2:135 [Google Scholar]
  69. Johnston TM, Fox SH. 69.  2015. Symptomatic models of Parkinson's disease and L-DOPA-induced dyskinesia in non-human primates. Curr. Top Behav. Neurosci. 22:221–35 [Google Scholar]
  70. Le W, Sayana P, Jankovic J. 70.  2014. Animal models of Parkinson's disease: a gateway to therapeutics?. Neurotherapeutics 11:92–110 [Google Scholar]
  71. Crook ZR, Housman D. 71.  2011. Huntington's disease: Can mice lead the way to treatment?. Neuron 69:423–35 [Google Scholar]
  72. Gil-Mohapel JM. 72.  2012. Screening of therapeutic strategies for Huntington's disease in YAC128 transgenic mice. CNS Neurosci. Ther. 18:77–86 [Google Scholar]
  73. Bilkei-Gorzo A. 73.  2014. Genetic mouse models of brain ageing and Alzheimer's disease. Pharmacol. Ther. 142:244–57 [Google Scholar]
  74. Platt TL, Reeves VL, Murphy MP. 74.  2013. Transgenic models of Alzheimer's disease: better utilization of existing models through viral transgenesis. Biochim. Biophys. Acta 1832:1437–48 [Google Scholar]
  75. Hill MN, Hellemans KG, Verma P, Gorzalka BB, Weinberg J. 75.  2012. Neurobiology of chronic mild stress: parallels to major depression. Neurosci. Biobehav. Rev. 36:2085–117 [Google Scholar]
  76. Meissner WG, Frasier M, Gasser T, Goetz CG, Lozano A. 76.  et al. 2011. Priorities in Parkinson's disease research. Nat. Rev. Drug Discov. 10:377–93 [Google Scholar]
  77. Bibbiani F, Oh JD, Petzer JP, Castagnoli N Jr, Chen JF. 77.  et al. 2003. A2A antagonist prevents dopamine agonist-induced motor complications in animal models of Parkinson's disease. Exp. Neurol. 184:285–94 [Google Scholar]
  78. Stocchi F, Rascol O, Hauser R, Huyck S, Tzontcheva A. 78.  et al. 2014. Phase-3 clinical trial of the adenosine 2a antagonist preladenant, given as monotherapy, in patients with Parkinson's disease. Neurology 82:S7.004 [Google Scholar]
  79. Uchida S, Soshiroda K, Okita E, Kawai-Uchida M, Mori A. 79.  et al. 2015. The adenosine A2A receptor antagonist, istradefylline enhances the anti-parkinsonian activity of low doses of dopamine agonists in MPTP-treated common marmosets. Eur. J. Pharmacol. 747:160–65 [Google Scholar]
  80. Moore JD. 80.  2015. The impact of CRISPR-Cas9 on target identification and validation. Drug Discov. Today 20:450–57 [Google Scholar]
  81. Chadman KK, Yang M, Crawley JN. 81.  2009. Criteria for validating mouse models of psychiatric diseases. Am. J. Med. Genet. B Neuropsychiatr. Genet. 150B:1–11 [Google Scholar]
  82. Kazdoba TM, Leach PT, Crawley JN. 82.  2015. Behavioral phenotypes of genetic mouse models of autism. Genes Brain Behav. 15:7–26 [Google Scholar]
  83. Moore DJ, Dawson TM. 83.  2008. Value of genetic models in understanding the cause and mechanisms of Parkinson's disease. Curr. Neurol. Neurosci. Rep. 8:288–96 [Google Scholar]
  84. Nimchinsky EA, Oberlander AM, Svoboda K. 84.  2001. Abnormal development of dendritic spines in FMR1 knock-out mice. J. Neurosci. 21:5139–46 [Google Scholar]
  85. Scharf SH, Jaeschke G, Wettstein JG, Lindemann L. 85.  2015. Metabotropic glutamate receptor 5 as drug target for Fragile X syndrome. Curr. Opin. Pharmacol. 20:124–34 [Google Scholar]
  86. Waddington JL, O'Tuathaigh C, O'Sullivan G, Tomiyama K, Koshikawa N, Croke DT. 86.  2005. Phenotypic studies on dopamine receptor subtype and associated signal transduction mutants: insights and challenges from 10 years at the psychopharmacology–molecular biology interface. Psychopharmacology 181:611–38 [Google Scholar]
  87. Valverde O, Torrens M. 87.  2012. CB1 receptor-deficient mice as a model for depression. Neuroscience 204:193–206 [Google Scholar]
  88. Erickson CA, Veenstra-Vanderweele JM, Melmed RD, McCracken JT, Ginsberg LD. 88.  et al. 2014. STX209 (arbaclofen) for autism spectrum disorders: an 8-week open-label study. J. Autism Dev. Disord. 44:958–64 [Google Scholar]
  89. Menalled L, Brunner D. 89.  2014. Animal models of Huntington's disease for translation to the clinic: best practices. Mov. Disord. 29:1375–90 [Google Scholar]
  90. Silverman JL, Pride MC, Hayes JE, Puhger KR, Butler-Struben HM. 90.  et al. 2015. GABAB receptor agonist R-baclofen reverses social deficits and reduces repetitive behavior in two mouse models of autism. Neuropsychopharmacology 40:2228–39 [Google Scholar]
  91. Voikar V, Koks S, Vasar E, Rauvala H. 91.  2001. Strain and gender differences in the behavior of mouse lines commonly used in transgenic studies. Physiol. Behav. 72:271–81 [Google Scholar]
  92. Mohajeri MH, Madani R, Saini K, Lipp HP, Nitsch RM, Wolfer DP. 92.  2004. The impact of genetic background on neurodegeneration and behavior in seizured mice. Genes Brain Behav 3:228–39 [Google Scholar]
  93. Rodgers RJ, Boullier E, Chatzimichalaki P, Cooper GD, Shorten A. 93.  2002. Contrasting phenotypes of C57BL/6JOlaHsd, 129S2/SvHsd and 129/SvEv mice in two exploration-based tests of anxiety-related behaviour. Physiol. Behav. 77:301–10 [Google Scholar]
  94. Schauwecker PE. 94.  2002. Complications associated with genetic background effects in models of experimental epilepsy. Prog. Brain Res. 135:139–48 [Google Scholar]
  95. Xu B, McIntyre DC, Fahnestock M, Racine RJ. 95.  2004. Strain differences affect the induction of status epilepticus and seizure-induced morphological changes. Eur. J. Neurosci. 20:403–18 [Google Scholar]
  96. Yang J, Houk B, Shah J, Hauser KF, Luo Y. 96.  et al. 2005. Genetic background regulates semaphorin gene expression and epileptogenesis in mouse brain after kainic acid status epilepticus. Neuroscience 131:853–69 [Google Scholar]
  97. Wahlsten D, Metten P, Phillips TJ, Boehm SL II, Burkhart-Kasch S. 97.  et al. 2003. Different data from different labs: lessons from studies of gene-environment interaction. J. Neurobiol. 54:283–311 [Google Scholar]
  98. Rigby M, O'Donnell R, Rupniak NMJ. 98.  2005. Species differences in tachykinin receptor distribution: further evidence that the substance P (NK1) receptor predominates in human brain. J. Comp. Neurol. 490:335–53 [Google Scholar]
  99. Rupniak NMJ, Carlson EJ, Webb JK, Harrison T, Porsolt RD. 99.  et al. 2001. Comparison of the phenotype of NK1R−/− mice with pharmacological blockade of the substance P (NK1) receptor in assays for antidepressant and anxiolytic drugs. Behav. Pharmacol. 12:497–508 [Google Scholar]
  100. Swinney DC, Anthony J. 100.  2011. How were new medicines discovered?. Nat. Rev. Drug Discov. 10:507–19 [Google Scholar]
  101. Barros TP, Alderton WK, Reynolds HM, Roach AG, Berghmans S. 101.  2008. Zebrafish: an emerging technology for in vivo pharmacological assessment to identify potential safety liabilities in early drug discovery. Br. J. Pharmacol. 154:1400–13 [Google Scholar]
  102. Chandra N, Padiadpu J. 102.  2013. Network approaches to drug discovery. Expert Opin. Drug Discov. 8:7–20 [Google Scholar]
  103. Geerts H, Kennis L. 103.  2014. Multitarget drug discovery projects in CNS diseases: quantitative systems pharmacology as a possible path forward. Future Med. Chem. 6:1757–69 [Google Scholar]
  104. Geerts H, Spiros A, Roberts P, Carr R. 104.  2012. Has the time come for predictive computer modeling in CNS drug discovery and development?. CPT Pharmacomet. Syst. Pharmacol. 1:e16 [Google Scholar]
  105. Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N. 105.  et al. 2011. Modelling schizophrenia using human induced pluripotent stem cells. Nature 473:221–25 [Google Scholar]
  106. Imaizumi Y, Okano H. 106.  2014. Modeling human neurological disorders with induced pluripotent stem cells. J. Neurochem. 129:388–99 [Google Scholar]
  107. Li W, Chen S, Li JY. 107.  2015. Human induced pluripotent stem cells in Parkinson's disease: a novel cell source of cell therapy and disease modeling. Prog. Neurobiol. 134:161–77 [Google Scholar]
  108. Liu Y, Deng W. 108.  2015. Reverse engineering human neurodegenerative disease using pluripotent stem cell technology. Brain Res. 1638:30–41 [Google Scholar]
  109. Mattis VB, Chang CWT, Lorson CL. 109.  2012. Analysis of a read-through promoting compound in a severe mouse model of spinal muscular atrophy. Neurosci. Lett. 525:72–75 [Google Scholar]
  110. Schadt EE, Buchanan S, Brennand KJ, Merchant KM. 110.  2014. Evolving toward a human-cell based and multiscale approach to drug discovery for CNS disorders. Front. Pharmacol. 5:252 [Google Scholar]
  111. Wan W, Cao L, Kalionis B, Xia S, Tai X. 111.  2015. Applications of induced pluripotent stem cells in studying the neurodegenerative diseases. Stem Cells Int. 2015:382530 [Google Scholar]
  112. Esch EW, Bahinski A, Huh D. 112.  2015. Organs-on-chips at the frontiers of drug discovery. Nat. Rev. Drug Discov. 14:248–60 [Google Scholar]
  113. Berdichevsky Y, Staley KJ, Yarmush ML. 113.  2010. Building and manipulating neural pathways with microfluidics. Lab. Chip 10:999–1004 [Google Scholar]
  114. Anighoro A, Bajorath J, Rastelli G. 114.  2014. Polypharmacology: challenges and opportunities in drug discovery. J. Med. Chem. 57:7874–87 [Google Scholar]
  115. Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS. 115.  et al. 2010. Research Domain Criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167:748–51 [Google Scholar]
  116. Morris SE, Cuthbert BN. 116.  2012. Research domain criteria: cognitive systems, neural circuits, and dimensions of behavior. Dialogues Clin. Neurosci. 14:29–37 [Google Scholar]
/content/journals/10.1146/annurev-pharmtox-010716-104624
Loading
/content/journals/10.1146/annurev-pharmtox-010716-104624
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error