On the role of Brain Imaging in drug development for psychiatry

2021 ◽  
Vol 16 ◽  
Author(s):  
Johan A. den Boer ◽  
Erik J.F. de Vries ◽  
Ronald J.H. Borra ◽  
Aren van Waarde ◽  
Adriaan A. Lammertsma ◽  
...  

Background: Over the last decades many brain imaging studies have contributed to new insights in the pathogenesis of psychiatric disease. However, in spite of these developments, progress in the development of novel therapeutic drugs for prevalent psychiatric health conditions has been limited. Objective: In this review we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I unitsIn this review we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I units. Conclusion: Brain imaging technology has revolutionized the study of psychiatric illnesses and during the last decade neuroimaging has provided valuable insights at different levels of analysis and brain organization, such as effective connectivity (anatomical), functional connectivity patterns and neurochemical information that may support both preclinical and clinical drug development. Since there is no unifying pathophysiological theory of individual psychiatric syndromes and since many symptoms cut across diagnostic boundaries, a new theoretical framework has been proposed that may help in defining new targets for treatment and thus enhance drug development in CNS diseases. In addition, it is argued that new proposals for data-mining and mathematical modelling as well as freely available databanks for neural network and neurochemical models of rodents combined with revised psychiatric classification will lead to validated new targets for drug development.

2015 ◽  
Vol 33 (15_suppl) ◽  
pp. e13585-e13585
Author(s):  
Mohadese Behtaj ◽  
Pingfu Fu ◽  
Neelesh Sharma ◽  
Afshin Dowlati
Keyword(s):  

2001 ◽  
Vol 13 (2) ◽  
pp. 115-122 ◽  
Author(s):  
Leon Aarons ◽  
Mats O. Karlsson ◽  
France Mentré ◽  
Ferdinand Rombout ◽  
Jean-Louis Steimer ◽  
...  

2016 ◽  
Vol 35 (1) ◽  
pp. 108-114 ◽  
Author(s):  
Robin E. Norris ◽  
Mohadese Behtaj ◽  
Pingfu Fu ◽  
Afshin Dowlati
Keyword(s):  

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 943-P
Author(s):  
LAI-SAN THAM ◽  
JEANNE GEISER ◽  
CHENG CAI TANG ◽  
KAREN SCHNECK ◽  
DAVID COX ◽  
...  

Author(s):  
Lucia Dacome

Chapter 7 furthers the analysis of the role of anatomical models as cultural currencies capable of transferring value. It does so by expanding the investigation of the early stages of anatomical modelling to include a new setting. In particular, it follows the journey of the Palermitan anatomist and modeller Giuseppe Salerno and his anatomical ‘skeleton’—a specimen that represented the body’s complex web of blood vessels and was presented as the result of anatomical injections. Although Salerno was headed towards Bologna, a major centre of anatomical modelling, he ended his journey in Naples after the nobleman Raimondo di Sangro purchased the skeleton for his own cabinet of curiosities. This chapter considers the creation and viewing of an anatomical display in di Sangro’s Neapolitan Palace from a comparative perspective that highlights how geography and locality played an important part in shaping the culture of mid-eighteenth-century anatomical modelling.


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Miao-Miao Zhao ◽  
Wei-Li Yang ◽  
Fang-Yuan Yang ◽  
Li Zhang ◽  
Wei-Jin Huang ◽  
...  

AbstractTo discover new drugs to combat COVID-19, an understanding of the molecular basis of SARS-CoV-2 infection is urgently needed. Here, for the first time, we report the crucial role of cathepsin L (CTSL) in patients with COVID-19. The circulating level of CTSL was elevated after SARS-CoV-2 infection and was positively correlated with disease course and severity. Correspondingly, SARS-CoV-2 pseudovirus infection increased CTSL expression in human cells in vitro and human ACE2 transgenic mice in vivo, while CTSL overexpression, in turn, enhanced pseudovirus infection in human cells. CTSL functionally cleaved the SARS-CoV-2 spike protein and enhanced virus entry, as evidenced by CTSL overexpression and knockdown in vitro and application of CTSL inhibitor drugs in vivo. Furthermore, amantadine, a licensed anti-influenza drug, significantly inhibited CTSL activity after SARS-CoV-2 pseudovirus infection and prevented infection both in vitro and in vivo. Therefore, CTSL is a promising target for new anti-COVID-19 drug development.


Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1045
Author(s):  
Marta B. Lopes ◽  
Eduarda P. Martins ◽  
Susana Vinga ◽  
Bruno M. Costa

Network science has long been recognized as a well-established discipline across many biological domains. In the particular case of cancer genomics, network discovery is challenged by the multitude of available high-dimensional heterogeneous views of data. Glioblastoma (GBM) is an example of such a complex and heterogeneous disease that can be tackled by network science. Identifying the architecture of molecular GBM networks is essential to understanding the information flow and better informing drug development and pre-clinical studies. Here, we review network-based strategies that have been used in the study of GBM, along with the available software implementations for reproducibility and further testing on newly coming datasets. Promising results have been obtained from both bulk and single-cell GBM data, placing network discovery at the forefront of developing a molecularly-informed-based personalized medicine.


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