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      Blinded Prospective Evaluation of Computer-Based Mechanistic Schizophrenia Disease Model for Predicting Drug Response

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          Abstract

          The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published ‘Quantitative Systems Pharmacology’ computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA) and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D 2 antagonist and ocaperidone, a very high affinity dopamine D 2 antagonist, using only pharmacology and human positron emission tomography (PET) imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS) total score and the higher extra-pyramidal symptom (EPS) liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development.

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          Most cited references 55

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          Circuit-based framework for understanding neurotransmitter and risk gene interactions in schizophrenia.

          Many risk genes interact synergistically to produce schizophrenia and many neurotransmitter interactions have been implicated. We have developed a circuit-based framework for understanding gene and neurotransmitter interactions. NMDAR hypofunction has been implicated in schizophrenia because NMDAR antagonists reproduce symptoms of the disease. One action of antagonists is to reduce the excitation of fast-spiking interneurons, resulting in disinhibition of pyramidal cells. Overactive pyramidal cells, notably those in the hippocampus, can drive a hyperdopaminergic state that produces psychosis. Additional aspects of interneuron function can be understood in this framework, as follows. (i) In animal models, NMDAR antagonists reduce parvalbumin and GAD67, as found in schizophrenia. These changes produce further disinhibition and can be viewed as the aberrant response of a homeostatic system having a faulty activity sensor (the NMDAR). (ii) Disinhibition decreases the power of gamma oscillation and might thereby produce negative and cognitive symptoms. (iii) Nicotine enhances the output of interneurons, and might thereby contribute to its therapeutic effect in schizophrenia.
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            Atypical antipsychotics: mechanism of action.

             Philip Seeman (2002)
            Although the principal brain target that all antipsychotic drugs attach to is the dopamine D2 receptor, traditional or typical antipsychotics, by attaching to it, induce extrapyramidal signs and symptoms (EPS). They also, by binding to the D2 receptor, elevate serum prolactin. Atypical antipsychotics given in dosages within the clinically effective range do not bring about these adverse clinical effects. To understand how these drugs work, it is important to examine the atypical antipsychotics' mechanism of action and how it differs from that of the more typical drugs. This review analyzes the affinities, the occupancies, and the dissociation time-course of various antipsychotics at dopamine D2 receptors and at serotonin (5-HT) receptors, both in the test tube and in live patients. Of the 31 antipsychotics examined, the older traditional antipsychotics such as trifluperazine, pimozide, chlorpromazine, fluphenazine, haloperidol, and flupenthixol bind more tightly than dopamine itself to the dopamine D2 receptor, with dissociation constants that are lower than that for dopamine. The newer, atypical antipsychotics such as quetiapine, remoxipride, clozapine, olanzapine, sertindole, ziprasidone, and amisulpride all bind more loosely than dopamine to the dopamine D2 receptor and have dissociation constants higher than that for dopamine. These tight and loose binding data agree with the rates of antipsychotic dissociation from the human-cloned D2 receptor. For instance, radioactive haloperidol, chlorpromazine, and raclopride all dissociate very slowly over a 30-minute time span, while radioactive quetiapine, clozapine, remoxipride, and amisulpride dissociate rapidly, in less than 60 seconds. These data also match clinical brain-imaging findings that show haloperidol remaining constantly bound to D2 in humans undergoing 2 positron emission tomography (PET) scans 24 hours apart. Conversely, the occupation of D2 by clozapine or quetiapine has mostly disappeared after 24 hours. Atypicals clinically help patients by transiently occupying D2 receptors and then rapidly dissociating to allow normal dopamine neurotransmission. This keeps prolactin levels normal, spares cognition, and obviates EPS. One theory of atypicality is that the newer drugs block 5-HT2A receptors at the same time as they block dopamine receptors and that, somehow, this serotonin-dopamine balance confers atypicality. This, however, is not borne out by the results. While 5-HT2A receptors are readily blocked at low dosages of most atypical antipsychotic drugs (with the important exceptions of remoxipride and amisulpride, neither of which is available for use in Canada) the dosages at which this happens are below those needed to alleviate psychosis. In fact, the antipsychotic threshold occupancy of D2 for antipsychotic action remains at about 65% for both typical and atypical antipsychotic drugs, regardless of whether 5-HT2A receptors are blocked or not. At the same time, the antipsychotic threshold occupancy of D2 for eliciting EPS remains at about 80% for both typical and atypical antipsychotics, regardless of the occupancy of 5-HT2A receptors. The "fast-off-D2" theory, on the other hand, predicts which antipsychotic compounds will or will not produce EPS and hyperprolactinemia and which compounds present a relatively low risk for tardive dyskinesia. This theory also explains why L-dopa psychosis responds to low atypical antipsychotic dosages, and it suggests various individualized treatment strategies.
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              A meta-analysis of the efficacy of second-generation antipsychotics.

               I Glick,  Nancy Chen,  S. Davis (2003)
              Consensus panel recommendations regarding choice of an antipsychotic agent for schizophrenia differ markedly, but most consider second-generation antipsychotics (SGAs) as a homogeneous group. It has been suggested that SGAs seem falsely more efficacious than first-generation antipsychotics (FGAs) as a result of reduced efficacy due to use of a high-dose comparator, haloperidol. We performed (1) a meta-analysis of randomized efficacy trials comparing SGAs and FGAs, (2) comparisons between SGAs, (3) a dose-response analysis of FGAs and SGAs, and (4) an analysis of the effect on efficacy of an overly high dose of an FGA comparator. Literature search of clinical trials between January 1953 and May 2002 of patients with schizophrenia from electronic databases, reference lists, posters, the Food and Drug Administration, and other unpublished data. We included 124 randomized controlled trials with efficacy data on 10 SGAs vs FGAs and 18 studies of comparisons between SGAs. Two of us independently extracted the sample sizes, means, and standard deviation of the efficacy data. Using the Hedges-Olkin algorithm, the effect sizes of clozapine, amisulpride, risperidone, and olanzapine were 0.49, 0.29, 0.25, and 0.21 greater than those of FGAs, with P values of 2 x 10-8, 3 x 10-7, 2 x 10-12, and 3 x 10-9, respectively. The remaining 6 SGAs were not significantly different from FGAs, although zotepine was marginally different. No efficacy difference was detected among amisulpride, risperidone, and olanzapine. We found no evidence that the haloperidol dose (or all FGA comparators converted to haloperidol-equivalent doses) affected these results when we examined its effect by drug or in a 2-way analysis of variance model in which SGA effectiveness is entered as a second factor. Some SGAs are more efficacious than FGAs, and, therefore, SGAs are not a homogeneous group.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                14 December 2012
                : 7
                : 12
                Affiliations
                [1 ]In Silico Biosciences, Berwyn, Pennsylvania, United States of America
                [2 ]Johnson & Johnson Pharmaceutical Research and Development, Central Nervous System Development, Titusville, New Jersey, United States of America
                [3 ]Janssen Scientific Affairs, LLC, Titusville, New Jersey, United States of America
                [4 ]Department of Neuroscience, Psychiatry, and Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
                Heidelberg University, Germany
                Author notes

                Competing Interests: The authors have read the journal's policy and have the following conflicts: H.G., A.S. and P.R. are employees of In Silico Biosciences, the funder of this study. R.T. is an employee of J&J, L.A. is an employee of Janssen Scientific Affairs and A.G. is a consultant for J&J and Lundbeck and has financial relationships with Johnson & Johnson, Lundbeck, Pfizer, GSK, Puretech Ventures, Merck, Takeda, and Dainippon Sumimoto. The computer-based platform is covered by the recently granted US patent “Method and apparatus for computer modeling of the interaction between cortical and subcortical areas in the human brain” - Hugo Geerts, Athan Spiros. PCT/US2006/043887, US patent 8,150,629 B2, granted on April 30, 2012.” A patent for the composition of matter for JNJ37822681 has been applied for. There are no further patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: HG AS PR. Performed the experiments: HG. Analyzed the data: HG AS PR RT LA. Contributed reagents/materials/analysis tools: HG AS PR RT LA AG. Wrote the paper: HG AG.

                Article
                PONE-D-12-16117
                10.1371/journal.pone.0049732
                3522663
                23251349

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 11
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Biology
                Computational Biology
                Computational Neuroscience
                Neuroscience
                Computational Neuroscience
                Chemistry
                Medicinal Chemistry
                Medicine
                Clinical Research Design
                Modeling
                Qualitative Studies
                Drugs and Devices
                Drug Research and Development
                Drug Discovery
                Adverse Reactions
                Clinical Pharmacology
                Drug Interactions
                Neuropharmacology
                Psychopharmacology
                Mental Health
                Therapies
                Drug Psychotherapy
                Psychiatry
                Social and Behavioral Sciences
                Psychology
                Therapies
                Drug Psychotherapy

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