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López-Muñoz F, D’Ocón P, Romero A, Guerra JA, Álamo C. Role of serendipity in the discovery of classical antidepressant drugs: Applying operational criteria and patterns of discovery. World J Psychiatry 2022; 12:588-602. [PMID: 35582332 PMCID: PMC9048453 DOI: 10.5498/wjp.v12.i4.588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 11/22/2021] [Accepted: 03/17/2022] [Indexed: 02/06/2023] Open
Abstract
The role played by serendipity in the origin of modern psychopharmacology has proven to be controversial in scientific literature. In its original meaning (Walpole), serendipity refers to discoveries made through a combination of accidents and sagacity. We have implemented an operational definition of serendipity based on finding something unexpected or unintended, regardless of the systematic process that led to the accidental observation, and we have established four different patterns of serendipitous attributability. In this paper, we have analyzed the role of serendipity in the discovery and development of classical antidepressant drugs, tricyclic antidepressants and monoamine oxidase inhibitors as well as heterocyclic, “atypical” or “second generation” antidepressants. The discovery of the antidepressant properties of imipramine and iproniazid, the prototypes of tricyclic antidepressants and monoamine oxidase inhibitors, respectively, fits the mixed type II pattern; initial serendipitous discoveries (imipramine was an antipsychotic and iproniazid was an anti-tuberculosis agent) led secondarily to non-serendipitous discoveries. But the other components of these two families of drugs were developed specifically as antidepressants, modifying the chemical structure of the series leaders, thereby allowing all of them to be included in the type IV pattern, characterized by the complete absence of serendipity. Among the heterocyclic drugs, mianserin (originally developed as an antihistamine) also falls into the type II pattern.
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Affiliation(s)
- Francisco López-Muñoz
- Faculty of Health, University Camilo José Cela, Villanueva de la Cañada 28692, Madrid, Spain
- “Hospital 12 de Octubre” Research Institute (i+12), Avda. de Córdoba, s/n, Madrid 28041, Spain
| | - Pilar D’Ocón
- Department of Pharmacology, Faculty of Pharmacy, University of Valencia, Avda. Vicent Andres Estelles, s/n, Valencia 46100, Spain
| | - Alejandro Romero
- Department of Pharmacology and Toxicology, Faculty of Veterinary Medicine, Complutense University, Avda. Puerta de Hierro, s/n, Madrid 28040, Spain
| | - José A Guerra
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Complutense University, Pl. de Ramón y Cajal, s/n, Madrid 28040, Spain
| | - Cecilio Álamo
- Department of Biomedical Sciences (Pharmacology Area), Faculty of Medicine and Health Sciences, University of Alcalá, Campus Científico-Tecnológico, Crta. de Madrid-Barcelona, Alcalá de Henares 28871, Madrid, Spain
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Towards artificial intelligence in mental health by improving schizophrenia prediction with multiple brain parcellation ensemble-learning. NPJ SCHIZOPHRENIA 2019; 5:2. [PMID: 30659193 PMCID: PMC6386753 DOI: 10.1038/s41537-018-0070-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 12/06/2018] [Indexed: 12/16/2022]
Abstract
In the literature, there are substantial machine learning attempts to classify schizophrenia based on alterations in resting-state (RS) brain patterns using functional magnetic resonance imaging (fMRI). Most earlier studies modelled patients undergoing treatment, entailing confounding with drug effects on brain activity, and making them less applicable to real-world diagnosis at the point of first medical contact. Further, most studies with classification accuracies >80% are based on small sample datasets, which may be insufficient to capture the heterogeneity of schizophrenia, limiting generalization to unseen cases. In this study, we used RS fMRI data collected from a cohort of antipsychotic drug treatment-naive patients meeting DSM IV criteria for schizophrenia (N = 81) as well as age- and sex-matched healthy controls (N = 93). We present an ensemble model -- EMPaSchiz (read as ‘Emphasis’; standing for ‘Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction’) that stacks predictions from several ‘single-source’ models, each based on features of regional activity and functional connectivity, over a range of different a priori parcellation schemes. EMPaSchiz yielded a classification accuracy of 87% (vs. chance accuracy of 53%), which out-performs earlier machine learning models built for diagnosing schizophrenia using RS fMRI measures modelled on large samples (N > 100). To our knowledge, EMPaSchiz is first to be reported that has been trained and validated exclusively on data from drug-naive patients diagnosed with schizophrenia. The method relies on a single modality of MRI acquisition and can be readily scaled-up without needing to rebuild parcellation maps from incoming training images.
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Bauman MD, Schumann CM, Carlson EL, Taylor SL, Vázquez-Rosa E, Cintrón-Pérez CJ, Shin MK, Williams NS, Pieper AA. Neuroprotective efficacy of P7C3 compounds in primate hippocampus. Transl Psychiatry 2018; 8:202. [PMID: 30258178 PMCID: PMC6158178 DOI: 10.1038/s41398-018-0244-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 07/16/2018] [Accepted: 08/03/2018] [Indexed: 01/31/2023] Open
Abstract
There is a critical need for translating basic science discoveries into new therapeutics for patients suffering from difficult to treat neuropsychiatric and neurodegenerative conditions. Previously, a target-agnostic in vivo screen in mice identified P7C3 aminopropyl carbazole as capable of enhancing the net magnitude of postnatal neurogenesis by protecting young neurons from death. Subsequently, neuroprotective efficacy of P7C3 compounds in a broad spectrum of preclinical rodent models has also been observed. An important next step in translating this work to patients is to determine whether P7C3 compounds exhibit similar efficacy in primates. Adult male rhesus monkeys received daily oral P7C3-A20 or vehicle for 38 weeks. During weeks 2-11, monkeys received weekly injection of 5'-bromo-2-deoxyuridine (BrdU) to label newborn cells, the majority of which would normally die over the following 27 weeks. BrdU+ cells were quantified using unbiased stereology. Separately in mice, the proneurogenic efficacy of P7C3-A20 was compared to that of NSI-189, a proneurogenic drug currently in clinical trials for patients with major depression. Orally-administered P7C3-A20 provided sustained plasma exposure, was well-tolerated, and elevated the survival of hippocampal BrdU+ cells in nonhuman primates without adverse central or peripheral tissue effects. In mice, NSI-189 was shown to be pro-proliferative, and P7C3-A20 elevated the net magnitude of hippocampal neurogenesis to a greater degree than NSI-189 through its distinct mechanism of promoting neuronal survival. This pilot study provides evidence that P7C3-A20 safely protects neurons in nonhuman primates, suggesting that the neuroprotective efficacy of P7C3 compounds is likely to translate to humans as well.
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Affiliation(s)
- Melissa D. Bauman
- 0000 0004 1936 9684grid.27860.3bDepartment of Psychiatry and Behavioral Sciences, University of California, Davis, USA ,0000 0004 1936 9684grid.27860.3bUC Davis MIND Institute, University of California, Davis, USA ,0000 0004 1936 9684grid.27860.3bCalifornia National Primate Research Center, Davis, USA ,0000 0004 1936 9684grid.27860.3bDepartment of Public Health Sciences, University of California, Davis, USA
| | - Cynthia M. Schumann
- 0000 0004 1936 9684grid.27860.3bDepartment of Psychiatry and Behavioral Sciences, University of California, Davis, USA ,0000 0004 1936 9684grid.27860.3bUC Davis MIND Institute, University of California, Davis, USA
| | - Erin L. Carlson
- 0000 0004 1936 9684grid.27860.3bDepartment of Psychiatry and Behavioral Sciences, University of California, Davis, USA
| | - Sandra L. Taylor
- 0000 0004 1936 9684grid.27860.3bDepartment of Public Health Sciences, University of California, Davis, USA
| | - Edwin Vázquez-Rosa
- University Hospital Case Medical Center; Department of Psychiatry Case Western Reserve University; Geriatric Research Education and Clinical Centers, Louis Stokes Cleveland VAMC, Harrington Discovery Institute, Cleveland, OH 44106 USA
| | - Coral J. Cintrón-Pérez
- University Hospital Case Medical Center; Department of Psychiatry Case Western Reserve University; Geriatric Research Education and Clinical Centers, Louis Stokes Cleveland VAMC, Harrington Discovery Institute, Cleveland, OH 44106 USA
| | - Min-Kyoo Shin
- University Hospital Case Medical Center; Department of Psychiatry Case Western Reserve University; Geriatric Research Education and Clinical Centers, Louis Stokes Cleveland VAMC, Harrington Discovery Institute, Cleveland, OH 44106 USA
| | - Noelle S. Williams
- UT Southwestern Medical Center, Department of Biochemistry, Dallas, TX USA
| | - Andrew A. Pieper
- University Hospital Case Medical Center; Department of Psychiatry Case Western Reserve University; Geriatric Research Education and Clinical Centers, Louis Stokes Cleveland VAMC, Harrington Discovery Institute, Cleveland, OH 44106 USA
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