Neuropsychiatric disorders, such as schizophrenia, depression, anxiety or dementia are common and cause an enormous emotional and economic burden to patients, relatives, caregivers, and to the society.
Unfortunately, currently available drug treatments are far from satisfactory. Moreover, virtually all of these drugs are molecules (or chemically modified versions) discovered by chance several decades ago.
The failure to identify novel drugs has led major pharmaceutical companies to disengage from research and drug-discovery programs related to neuropsychiatric disorders (Nature 480, 161-162, 2011). One of the reasons for this failure is that there are no good animal models for neuropsychiatric disorders.
The discrepancy between the urgent need for improved therapeutic compounds along with their large market potential on the one hand, and the current lack of significant development of novel and improved drugs on the other, warrants alternative strategies aimed at identifying druggable targets related to neuropsychiatric disease.
GeneGuide uses a human genome-based approach to identify new drug targets and compounds for the treatment of neuropsychiatric disorders.
An valuable source of information is data available from large-scale genome-wide association studies of neuropsychiatric disorders. However, since the phenotypes used in these studies (diagnosis yes/no) are blurry and ill-suited for drug discovery, we use an additional source of information, based on the deconstruction of psychiatric categories into biologically informed physiologic dimensions measurable in healthy subjects (endophenotype/intermediate phenotype concept). Recently, we have provided empirical evidence in support of this rationale (e.g. Papassotiropoulos and de Quervain, Trends Cogn Sci, 2015; Heck et al., Neuron, 2014; Heck et al., Nature Human Behaviour 2017; Freytag et al., Nature Communications 2017).
GeneGuide exclusively licensed an incremental database from the University of Basel. This database includes over 3000 healthy subjects and a unique combination of functional and structural brain imaging, genomic, epigenomic, metabolomic, behavioral, and biological data from healthy young subjects, who underwent detailed phenotypic assessments for emotional memory, working memory, episodic memory, and other relevant neuropsychiatric traits. GeneGuide has developed a drug-discovery algorithm allowing the identification of druggable targets based on genome-wide information related to cognitive, emotional, and brain-imaging data.
Andreas Papassotiropoulos and Dominique de Quervain, the founders of GeneGuide share more than 18 years of scientific collaboration. They have published numerous milestone publications in leading journals, such as Nature, Science, Cell, Nature Neuroscience, Nature Communications, Nature Human Behaviour, Neuron, and PNAS on the neurobiological foundations of human cognitive and emotional functions and clinical trials. Click here for the full publication list.
In addition to our in-house activities dedicated at identifying new drug targets, we offer services in the following areas
Gene identification for pharmacogenetic purposes
validation and specification
GeneGuide is a spin-off company of the University of Basel, founded 2013, and directed by the two founders
Dominique de Quervain, M.D., is a full Professor at the Faculty of Medicine & Faculty of Psychology and Director of the Division of Cognitive Neuroscience, University of Basel, Switzerland. He is an expert in the fields of stress, brain imaging, and clinical trials.
Andreas Papassotiropoulos, M.D., is a full Professor at the Faculty of Medicine & Faculty of Psychology and Director of the Division of Molecular Neuroscience, University of Basel, Switzerland. He is an expert in the field of human genetics with a particular focus on psychiatry and neuroscience.
In 2019 MindGuide has been founded. MindGuide is a Division of GeneGuide and uses immersive technologies including next generation virtual reality and augmented reality to reduce anxiety, treat phobias and increase stress resilience.