Qualitative analysis of the interdisciplinary interaction between data analysis specialists and novice clinical researchers.

BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.

Clinical Research Environment in India: Challenges and Proposed Solutions.

India has compelling need and keen aspirations for indigenous clinical research. Notwithstanding this need and previously reported growth the expected expansion of Indian clinical research has not materialized. We reviewed the scientific literature, lay press reports, and ClinicalTrials.gov data for information and commentary on projections, progress, and impediments associated with clinical trials in India. We also propose targeted solutions to identified challenges. The Indian clinical trial sector grew by (+) 20.3% CAGR (compound annual growth rate) between 2005 and 2010 and contracted by (-) 14.6% CAGR between 2010 and 2013. Phase-1 trials grew by (+) 43.5% CAGR from 2005-2013, phase-2 trials grew by (+) 19.8% CAGR from 2005-2009 and contracted by (-) 12.6% CAGR from 2009-2013, and phase-3 trials grew by (+) 13.0% CAGR from 2005-2010 and contracted by (-) 28.8% CAGR from 2010-2013. This was associated with a slowing of the regulatory approval process, increased media coverage and activist engagement, and accelerated development of regulatory guidelines and recuperative initiatives. We propose the following as potential targets for restorative interventions: Regulatory overhaul (leadership and enforcement of regulations, resolution of ambiguity in regulations, staffing, training, guidelines, and ethical principles [e.g., compensation]).Education and training of research professionals, clinicians, and regulators.Public awareness and empowerment. After a peak in 2009-2010, the clinical research sector in India appears to be experiencing a contraction. There are indications of challenges in regulatory enforcement of guidelines; training of clinical research professionals; and awareness, participation, partnership, and the general image amongst the non-professional media and public. Preventative and corrective principles and interventions are outlined with the goal of realizing the clinical research potential in India.

The vertebrate taxonomy ontology: a framework for reasoning across model organism and species phenotypes.

BACKGROUND: A hierarchical taxonomy of organisms is a prerequisite for semantic integration of biodiversity data. Ideally, there would be a single, expansive, authoritative taxonomy that includes extinct and extant taxa, information on synonyms and common names, and monophyletic supraspecific taxa that reflect our current understanding of phylogenetic relationships. DESCRIPTION: As a step towards development of such a resource, and to enable large-scale integration of phenotypic data across vertebrates, we created the Vertebrate Taxonomy Ontology (VTO), a semantically defined taxonomic resource derived from the integration of existing taxonomic compilations, and freely distributed under a Creative Commons Zero (CC0) public domain waiver. The VTO includes both extant and extinct vertebrates and currently contains 106,947 taxonomic terms, 22 taxonomic ranks, 104,736 synonyms, and 162,400 cross-references to other taxonomic resources. Key challenges in constructing the VTO included (1) extracting and merging names, synonyms, and identifiers from heterogeneous sources; (2) structuring hierarchies of terms based on evolutionary relationships and the principle of monophyly; and (3) automating this process as much as possible to accommodate updates in source taxonomies. CONCLUSIONS: The VTO is the primary source of taxonomic information used by the Phenoscape Knowledgebase (http://phenoscape.org/), which integrates genetic and evolutionary phenotype data across both model and non-model vertebrates. The VTO is useful for inferring phenotypic changes on the vertebrate tree of life, which enables queries for candidate genes for various episodes in vertebrate evolution.

Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings.

This review summarizes evidence of dysregulated reward circuitry function in a range of neurodevelopmental and psychiatric disorders and genetic syndromes. First, the contribution of identifying a core mechanistic process across disparate disorders to disease classification is discussed, followed by a review of the neurobiology of reward circuitry. We next consider preclinical animal models and clinical evidence of reward-pathway dysfunction in a range of disorders, including psychiatric disorders (i.e., substance-use disorders, affective disorders, eating disorders, and obsessive compulsive disorders), neurodevelopmental disorders (i.e., schizophrenia, attention-deficit/hyperactivity disorder, autism spectrum disorders, Tourette's syndrome, conduct disorder/oppositional defiant disorder), and genetic syndromes (i.e., Fragile X syndrome, Prader-Willi syndrome, Williams syndrome, Angelman syndrome, and Rett syndrome). We also provide brief overviews of effective psychopharmacologic agents that have an effect on the dopamine system in these disorders. This review concludes with methodological considerations for future research designed to more clearly probe reward-circuitry dysfunction, with the ultimate goal of improved intervention strategies.