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11. Drug Repurposing of Generic Drugs: Challenges and the Potential Role for Government.

Author

Pol, K.H. van der, Aljofan, M., Blin, O., Cornel, J.H., Rongen, G.A., Woestelandt, A.G., Spedding, M., Pol, K.H. van der, Aljofan, M., Blin, O., Cornel, J.H., Rongen, G.A., Woestelandt, A.G., and Spedding, M.

Abstract

Contains fulltext : 299987.pdf (Publisher’s version ) (Open Access), Drug repurposing is the process of identifying a new use for an existing drug or active substance in an indication outside the scope of the original indication. Drug repurposing has important advantages including reduced development time and costs, and potentially large societal healthcare cost savings. However, current generic drug repurposing research faces a number of challenges in obtaining research funds. Furthermore, regardless of the success of a repurposing trial, commercial parties often lack interest in pursuing marketing authorisation for financial reasons, and academic researchers lack the knowledge, time and funding. Therefore, the new indication of a repurposed drug often does not make it 'on label'. We propose a large increase in public funding for generic drug repurposing research, including funds for the marketing authorisation process when a trial is successful, and a reduction in the regulatory burden of the marketing authorisation process for repurposed generic drugs., 01 november 2023

Published
2023

17. The grey mouse lemur: A non-human primate model for ageing studies

Author

Languille, S., Blanc, S., Blin, O., Canale, C.I., Dal-Pan, A., Devau, G., Dhenain, M., Dorieux, O., Epelbaum, J., Gomez, D., Hardy, I., Henry, P.-Y., Irving, E.A., Marchal, J., Mestre-Francés, N., Perret, M., Picq, J.-L., Pifferi, F., Rahman, A., Schenker, E., Terrien, J., Théry, M., Verdier, J.-M., and Aujard, F.

Published
2012
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20. Clinical and biomarker profiling of prodromal Alzheimerʼs disease in workpackage 5 of the Innovative Medicines Initiative PharmaCog project: a ‘European ADNI study’

Author

Galluzzi, S., Marizzoni, M., Babiloni, C., Albani, D., Antelmi, L., Bagnoli, C., Bartres-Faz, D., Cordone, S., Didic, M., Farotti, L., Fiedler, U., Forloni, G., Girtler, N., Hensch, T., Jovicich, J., Leeuwis, A., Marra, C., Molinuevo, J. L., Nobili, F., Pariente, J., Parnetti, L., Payoux, P., Del Percio, C., Ranjeva, J.-P., Rolandi, E., Rossini, P. M., Schönknecht, P., Soricelli, A., Tsolaki, M., Visser, P. J., Wiltfang, J., Richardson, J. C., Bordet, R., Blin, O., and Frisoni, G. B.

Published
2016
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25. Cross-sectional clinical, neuropsychological, neuroimaging, and neurophysiological characterization of mild cognitive impairment patients in WP5 PharmaCog/E-ADNI study: EP1105

Author

Galluzzi, S., Marizzoni, M., Babiloni, C., Bartres-Faz, D., Blin, O., Bordet, R., Bosch, B., De Anna, F., Didic, M., Farotti, L., Forloni, G., Jovicich, J., Marra, C., Marzano, N., Molinuevo, J. L., Nobili, F., Pariente, J., Parnetti, L., Payoux, P., Picco, A., Quaranta, D., Ranjeva, J.-P., Roccatagliata, L., Rossini, P. M., Salvadori, N., Schonknecht, P., Soricelli, A., Tsolaki, M., Vecchio, F., Visser, P. J., Wiltfang, J., and Frisoni, G. B.

Published
2014

27. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

Author

Hong, SJ, Dobricic, V, Ohlei, O, Bos, I, Vos, SJB, Prokopenko, D, Tijms, BM, Andreasson, U, Blennow, K, Vandenberghe, R, Gabel, S, Scheltens, P, Teunissen, CE, Engelborghs, S, Frisoni, G, Blin, O, Richardson, JC, Bordet, R, Lleo, A, Alcolea, D, Popp, J, Clark, C, Peyratout, G, Martinez-Lage, P, Tainta, M, Dobson, RJB, Legido-Quigley, C, Sleegers, K, Van Broeckhoven, C, Tanzi, RE, ten Kate, M, Wittig, M, Franke, A, Lill, CM, Barkhof, F, Lovestone, S, Streffer, J, Zetterberg, H, Visser, PJ, Bertram, L, and Neuroimaging Initiative

Subjects
s disease, wide association study, chitinase&#8208, like protein 1, neurogranin, neurofilament light, 3&#8208, biomarker, genome&#8208, Alzheimer&apos, cerebrospinal fluid
Abstract

Introduction Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Methods We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates. Results We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1. Discussion Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

Published
2021

28. Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Author

Ribaldi, F., Altomare, D., Jovicich, J., Ferrari, C., Picco, A., Pizzini, F. B., Soricelli, A., Mega, A., Ferretti, A., Drevelegas, A., Bosch, B., Muller, B. W., Marra, Camillo, Cavaliere, C., Bartres-Faz, D., Nobili, F., Alessandrini, F., Barkhof, F., Gros-Dagnac, H., Ranjeva, J. -P., Wiltfang, J., Kuijer, J., Sein, J., Hoffmann, K. -T., Roccatagliata, L., Parnetti, L., Tsolaki, M., Constantinidis, M., Aiello, M., Salvatore, M., Montalti, M., Caulo, M., Didic, M., Bargallo, N., Blin, O., Rossini, Paolo Maria, Schonknecht, P., Floridi, P., Payoux, P., Visser, P. J., Bordet, R., Lopes, R., Tarducci, R., Bombois, S., Hensch, T., Fiedler, U., Richardson, J. C., Frisoni, G. B., Marizzoni, M., Marra C. (ORCID:0000-0003-3994-4044), Rossini P. M. (ORCID:0000-0003-2665-534X), Ribaldi, F., Altomare, D., Jovicich, J., Ferrari, C., Picco, A., Pizzini, F. B., Soricelli, A., Mega, A., Ferretti, A., Drevelegas, A., Bosch, B., Muller, B. W., Marra, Camillo, Cavaliere, C., Bartres-Faz, D., Nobili, F., Alessandrini, F., Barkhof, F., Gros-Dagnac, H., Ranjeva, J. -P., Wiltfang, J., Kuijer, J., Sein, J., Hoffmann, K. -T., Roccatagliata, L., Parnetti, L., Tsolaki, M., Constantinidis, M., Aiello, M., Salvatore, M., Montalti, M., Caulo, M., Didic, M., Bargallo, N., Blin, O., Rossini, Paolo Maria, Schonknecht, P., Floridi, P., Payoux, P., Visser, P. J., Bordet, R., Lopes, R., Tarducci, R., Bombois, S., Hensch, T., Fiedler, U., Richardson, J. C., Frisoni, G. B., Marizzoni, M., Marra C. (ORCID:0000-0003-3994-4044), and Rossini P. M. (ORCID:0000-0003-2665-534X)

Abstract

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was −0.22[IQR = 0.50] for LGA-SPM8, −0.12[0.57] for LGA-SPM12, −0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.

Published
2021

29. How to Anticipate the Assessment of the Public Health Benefit of New Medicines?

Author

Alperovitch, A., Bamberger, M., Begaud, B., Blin, O., Blin, P., Breart, G., Brun Strang, C., Buyse, M., Castot, A., Chauvenet, M., Chicoye, A., David, N., De Bels, F., De Sahb Berkovitch, R., Dohin, E., Fagnani, F., Falissard, B., Gastaldi-Menager, C., Giri, I., Haim, M., Joubert, J.M., Lapeyre-Mestre, M., Lassale, C., Marchant Ramirez, I., Meyer, F., Micallef, J., Mollimard, M., Moreau-Defarges, T., Pazart, L., Perret, L., Pigeon, M., Rumeau Pichon, C., Tcheng, Ph., Woler, M., Zanetti, L., Zylberman, M., Massol, Jacques, Puech, Alain, and Boissel, Jean-Pierre

Published
2007
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30. Comment anticiper l’évaluation de l’intérêt de santé publique des médicaments ?

Author

Alperovitch, A., Bamberger, M., Bégaud, B., Blin, O., Blin, P., Bréart, G., Brun Strang, C., Buyse, M., Castot, A., Chauvenet, M., Chicoye, A., David, N., De Bels, F., De Sahb Berkovitch, R., Dohin, E., Fagnani, F., Falissard, B., Gastaldi-Menager, C., Giri, I., Haim, M., Joubert, J.M., Lapeyre-Mestre, M., Lassale, C., Marchant Ramirez, I., Meyer, F., Micallef, J., Mollimard, M., Moreau-Defarges, T., Pazart, L., Perret, L., Pigeon, M., Rumeau Pichon, C., Tcheng, Ph., Woler, M., Zanetti, L., Zylberman, M., Massol, Jacques, Puech, Alain, and Boissel, Jean-Pierre

Published
2007
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40. Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Author

Hong, SJ, Prokopenko, D, Dobricic, V, Kilpert, F, Bos, I, Vos, SJB, Tijms, BM, Andreasson, U, Blennow, K, Vandenberghe, R, Cleynen, I, Gabel, S, Schaeverbeke, J, Scheltens, P, Teunissen, CE, Niemantsverdriet, E, Engelborghs, S, Frisoni, G, Blin, O, Richardson, JC, Bordet, R, Molinuevo, JL, Rami, L, Kettunen, P, Wallin, A, Lleo, A, Sala, I, Popp, J, Peyratout, G, Martinez-Lage, P, Tainta, M, Dobson, RJB, Legido-Quigley, C, Sleegers, K, Van Broeckhoven, C, ten Kate, M, Barkhof, F, Zetterberg, H, Lovestone, S, Streffer, J, Wittig, M, Franke, A, Tanzi, RE, Visser, PJ, Bertram, L, and Alzheimers Dis Neuroimaging Initia

Abstract

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (A beta) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A beta 42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A beta 38 and CSF-A beta 40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A beta and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

Published
2020

43. Abstracts of posters

Author

Suffisseau L., Taugourdeau M. C., Goldstein F. W., Mainardi J. L., Larrouturou Ph., Romero, M., Cervino, A. R., Albertone, G., Di Pasquale, R., Venturini, F., Congedo, R., Benettolo, F., Pistolesi, C., Olivato, R., Casasin T., Agusti C., Gurrera M. T., Fabregas X., Rizo A., Badia J. M., Santa-Olalla M., Marini, P., Rampazzo, R., Scroccaro, G., Dell'Aera, M., Luzzi, R., Ciccarone, G., Martinet, N., Beney, J., Marty, S., Reymond, J. -Ph., Cairns, Chris, Morgutti M., Posco M., Moltempi M., Lonqhini P., Rossignoli A., Rihet, P., Carles, G., Braguer, D., Azulay, J. P., Pouget, J., Pelletier, J., Crevat, A., Past.o, L., Barroso, E., Pujol, R., Ferrer, I., Ibars, M., Llop, J. M., Frankfort, Ellen, van Dongen, Robert T. M., Hekster, Yechiel A., Kart, T., Rasmussen, M., Horn, A., Wested, L., Gagyi, O., Markó, E., Regazzi M. B., Martinelli L., Goggi C., Bellotti E., Molinaro M., Rinaldi M., Gavazzi A., Buggia I., Daneri A., Guarnone E., Bascapē V., Viganô M., Lazzaro, A., Palozzo, A., Banfi R., Borselli G., Fabbiani P., Marinai C., Delorme, J., Tubiana, N., Buck, M., Chinot, O., De Wever, C., Robays, H., Montoro J. B., Flores G., Juárez J. C., Juste C., Jardí R., Altisent C., Tusell J. M., Arpinelli, F., De Carli, G., Olivieri, A., Recchia, G., Rossignoli A., Longhini P., La Guidara C., Russo B., Moltempi M., Tamés, M. J., Cajaraville, G., Ponz, L., Echaniz, E., Garcia, B., van Mil, J. W. Foppe, Leufkens, Hubert G., v. Haelst, Ingrid M. M., Parel, Piet C. M., Scholten, Wim K., Sessink, F. G. M., Raschatt, R., Traversa, G., Donini, G., Arpino, C., Da Cas, R., Pasquin, P., Bernadotte af Wisborg G., Claesson C., Lundberg O., Thorslund M., Ferraro L., Marrazzo E., Ostino G., Tognoni G., Heerdink, Eibert R., Koppedraaijer, Corrie, Bakker, Albert, Bidoli E., Battistin M., Troncon M. G., Franceschi S., Serraino D., Marino, M., Matera, M. G., Berrino, L., Contaldi, C., Piucci, B., Rossi, F., Rolle C., Marrazzo E. 0., Murgia, V., Bussi, R., Schievano, P., Pedrini, A., Baraghini, M., Benini, A., Cataldo, M. M., Galletti, P., Magnani, M., Manzoli, M., Novi, M. V., Pezzi, O., Font M., Salmaso A. B., Mezzalira L., Braybrook, Saran, Walker, Roger, van Mil, J. W. F., Tromp, F. T. J., de Jong-v.d. Berg, L. T. W., Bakker, A., Paes, A. H. P., Soe-Agnie, C., Llopis, P., Tortajada, J. J., Font, I., Climente, M., Real, J. V., Almenar, D., Molins, C., Jiménez, N. V., Bellés Medall MD, Casterá Melchor DE, Marco Sena MA, Cantarinz Marti I., Abad Gimeno FJ, Török, J., Thurzó, L., Juárez J. C., Oliveras M., Hidalgo E., Cabañas M. J., Barroso C., Moraga F. A., Sánchez de Toledo J., Kollöffel, W. J., Driessen, F. G. W. H. M., Goldhoorn, P. B., Moral, M. A., Roglan, A., Mangues, M. A., Bonal, J., Clopés, A., Badell, I., Fraga, G., Deinum, J. T., van Lingen, R. A., Quak, J. M. E., Kuizenga, A. J., van Dam, J. G., Villani P., Maserati R., Viale P., Alberici F., Iacona I., Wasieczko, A., Szymura-Oleksiak, J., Wyska, E., Magulova, L., Sirotiakova, J., Letkovicova, M., Branger, E., Besse, D., Blin, O., Bille, F., Serratrice, G., Desnuelle, C., Grassin, J., Reben, I., Meunier, Ph., Antier, D., Berthet, M., Søndergaard B., Herborg H., Frøkjær B., Hepler C., Steckner, H., Bergold, A., Drings, P., Märkel, A., Manegold, C., Venning, Mary, Pazzagli, Luciana, Semmola, Maria Vittoria, Mannoni, Alessandro, Tersen I., Huchet J., Sevilla, E., Ferrari, J. M., Herreros de Tejada, A., Congedo, R., Font, M., Fraccaro, A., Osti, M., Pappagallo, G., Spolaor, A., Terrazzani, G., Vezzani, M., Edouard B., Laine G., Geeraerts D., Robays H., Carrera-Hueso, F. J., Font, B., Marquina, C., Idoate, A., Giráldez, J., Fernández, E., Lacasa, C., Guzzo, D., Martini, N., Boya, P. Giner, González, M. M. Negredo, Agulló, J. Muñoz, Mansilla, L. Lorente, Nahata, Milap C., Troncon, M. G., Cattaruzzi, C., Bilbao G., Galende I., Atañé C., Bermudez de Castro A., Delgado O., Escribano B., Frías J., Gabriel R., Gómez J. A., Gracia D., Gutiérrez E., Hellín T., Izquierdo J. L., Moreno A., Requena T., Sainz-Terreros M., Tejedor J. C., Torralba A., Vigil D., Scuffi, C., Trallori, G., Messori, A., Bardazzi, G., Bonanomi, A., Silvano, R., D'Albasio, G., Bardelli, F., Verona, Firenzee, Bardelli, F., Corrado, A., Ferriols R., Aleixander M. J., Garcia J., Faus M., Ibañez E., Alós M., Rinaldi, M., Pharmacy & Therapeutic Committee (Ps&TC), Collaborative Group, SIFO-Veneto Working Group on Clinical Trials, Working Group on the Elaboration of an Approval Conditions Document to certify the Clinical Trials Ethics Committees in the Autonomous Community of Madrid, and Area SIFO di Metanalisi

Published
1994
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