Convergence Science: Shaping 21st Century Psychiatry


The Medici effect is upon us in biomedicine, and it’s called convergence science.


The Medici effect encapsulates the benefits of cross-pollination and interaction between individuals and teams from different fields in the pursuit of innovation. It is named after the wealthy Medici family who helped catalyze the Renaissance by bringing together poets, philosophers, scientists, painters, and other artisans to Florence, Italy. We believe the modern Medici effect is convergence science, and it is set to revolutionize health and medicine in the 21st century given the interplays occurring among physical, computer, and life sciences.

Convergence science is defined as the merging of distinct technologies, industries, tools, disciplines, or devices into a unified whole to create new pathways and opportunities. Convergence relies on a new integrated approach to solving problems too complex for any single discipline. Sharp and Langer1 described convergence as the “third revolution” in biomedicine after the development of molecular and cellular biology (the first revolution) and genomics (the second revolution). Based on a study of scientific progress at the Massachusetts Institute of Technology, convergence science was recommended as a way to blend diverse scientific disciplines. More than an interdisciplinary science, convergence integrates distant paradigms, systems, theories, and disciplines with problem-oriented research that crosses boundaries of academic, public, and private spheres.

Learning from oncology
Oncology may be the current biomedical frontier for convergence science. Indeed, a new academic journal has just been launched: Convergent Science Physical Oncology.2 The aim of the journal is to integrate physical science with cancer biology and clinical oncology to advance the understanding and treatment of cancer in patients. The National Cancer Institute’s Center for Strategic Scientific Initiatives supports convergent approaches to cancer innovation. Their mission is to “create and implement exploratory programs focused on the development and integration of advanced technologies, transdisciplinary approaches, infrastructures, and standards to accelerate the creation of publically available, broadly accessible, multidimensional data, knowledge, and tools to empower the entire cancer research continuum for patient benefits.”

This initiative has led to Cancer Nanotechnology Excellence and Integrative Cancer Biology Program Centers to be constructed to support convergent projects. Private companies (eg, IBM and NantHealth) are already developing data intensive systems to integrate, display, and analyze-via machine learning-data from all health providers, genomic and proteomic analyses, imaging, and other medical devices, with the actionable health information available at the point of care, anywhere.

Initiatives supporting convergence science approaches for psychiatry
If convergence is an approach to complexity, then what appears promising for oncology should be even more useful for psychiatry. Indeed, this approach has already been harnessed for neuroscience. A number of large-scale convergence neuroscience initiatives are underway globally, and these initiatives are essential to making progress in neuroscience. These projects bring together researchers from a multitude of disciplines to understand the basic functioning of the human brain, and the dysfunction that occurs during illness.

One such initiative is the Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) initiative funded by public agencies, private companies, and foundations.3 The express aim of this initiative is to develop new tools and technologies that will enable the research community to obtain a dynamic picture of the brain in action. With nearly 100 billion cells making 100 trillion connections, this is no small aim and will simply not be achievable with current tools and disciplinary approaches. One of the express themes of action for the BRAIN initiative is to “cross boundaries in interdisciplinary collaborations.” The BRAIN initiative consists of teams of engineers, nanotechnologists, computational scientists, materials scientists, and neuroscientists to create the next generation of imaging tools or probes for brain activity.

Will convergence become the future of psychiatry?
Arguably, if the brain is so complex as to require a convergent approach, then the study of psychiatry (mind, brain, and behavior) is complexity on a whole different level. Although the challenge is evident, our approaches have been remarkably singular, focusing on the mind, the brain, or behavior in isolation, with too little integration across disciplines and even less assistance from the vast areas of science that are now poised to alter other areas of medicine.

What would a convergence science of mental illness look like?
A convergent approach to mental illness could begin with software engineers, informatics experts, behavioral scientists, and clinicians designing a new generation of devices to provide objective measures to augment patients’ reports of their symptoms. Imagine devices developed to provide continuous assessment of mental state, similar to the glucose or heart rate monitors available today. Passive data such as voice analytics, facial expression monitoring, actigraphy, and engagement of social networks could indicate the onset of depression or mania. Closed loop brain stimulation could detect and correct abnormal neural circuit activity, as is used today for managing epilepsy.

Implanted devices for the management of hallucinations and obsessive thoughts may seem like science fiction, but with the engineering of wireless, miniaturized electrodes, a new era is emerging for interventional neurology as well as psychiatry.4 Envisage creating social prosthetics for children with autism, similar to the cochlear implants used routinely for nerve deafness. While today’s tools such as Google Glass and Siri may not be up to the task, rapid progress in facial processing and computer engineering suggests that software could allow children with “social blindness” to read facial emotions in real time.

The application of convergence to psychiatry can be much more than smart software and social prosthetics. Convergence may include combining the current tools for diagnosis. The neurobiological mechanisms of psychiatric disorders are complex and often involve the interplay of changes in brain structure, function, neurochemistry, and neuropathology. Clark and colleagues5 have outlined the added value of multiple diagnostic modalities used in predicting the risk of transition into first episode psychosis. Karalunas and colleagues6 were able to refine subtyping of childhood ADHD by using biologically based behavioral dimensions (ie, temperament), a novel classification algorithm (ie, community detection analysis), and multiple external validators (ie, resting-state functional magnetic resonance imaging and cardiac measures of respiratory sinus arrhythmia and pre-ejection period). Diniz and colleagues7 have shown how plasma biosignatures and brain pathology relate to resistant cognitive impairment in late-life depression. They utilized comprehensive analysis of blood-based immune proteins, magnetic resonance imaging, and positron emission tomography with machine learning data analytics. While all of these examples draw from multiple data sources, the ultimate promise of convergence is the integration of biological, psychological, sociocultural, and environmental data into a more comprehensive, individualized portrayal of diagnosis (ie, precision medicine).

Early examples of convergence science for psychiatric disorders
Convergence science approaches could also aid in the development of novel treatment strategies for psychiatric disorders allowing interventions to be proactive as well as reactive. There is an increasing interest in electronic mental health interventions given enhanced computing power and the widespread availability and use of smartphones.8 Psychosocial treatments delivered via mobile health (mHealth)-the practice of medicine supported by mobile devices-have the benefit of reach, scalability, affordability, convenience, flexibility, and facilitation by a non-professional workforce. Concerns remain about acceptability to consumers, quality of interaction, and the potential for unsupervised and counterproductive therapy.

Massive open online interventions for mental health is a concept recently defined by Munoz and colleagues9 and describes mental health and substance abuse interventions, scientifically validated and available online to unlimited numbers of consumers. These researchers showed how a free, multifactorial smoking cessation program in English and Spanish could be used by 7607 participants worldwide. Their findings indicate a 50.3% quit rate over 12 months.

The field of socially assistive robotics in mental health, whereby robots assist patients through social interactions (eg, companionship, as therapeutic partner and/or coach), is receiving greater attention, particularly as computing power grows and artificial intelligence systems become more sophisticated, ubiquitous, and useful. A recent review by Rabbitt and colleagues10 has outlined potential benefits of socially assistive robotics (eg, providing therapy and monitoring where there are few mental health providers and reinforcing human-led therapy), as well as potential downsides (eg, poor quality user interface leading to frustration and cost considerations). Even in the near term, the development of monitors for the fidelity of psychosocial interventions could improve the quality of care.

Just as a glucose monitor in a contact lens provides continuous feedback for optimizing diabetes control; engineers, computer scientists, and psychiatrists can develop simple devices to assess the quality of psychiatric treatment as a path to improving outcomes. Examples in psychiatry include software and hardware for smartphones and wearable devices to monitor physical activity, sleep, social interactivity, calorimetry, and emotional tone of voice.

Implications of convergence science for psychiatry
If convergence science principles are part of the future of psychiatry, it may not be too soon to introduce this approach in the teaching of psychiatry. Additional skills may include an enhanced understanding of neuroscience, the “omics” (eg, genomics, proteomics, metabolomics), big data analytics, mHealth, economics, and policy. Yager11 suggests psychiatry training and careers are likely to undergo substantial change in the future to complement projected health burdens and innovations, postulating the development of additional psychiatric specializations in information technology and executive management (ie, combining clinical practice, administration, entrepreneurialism, and health services management).

The training of psychiatrists as clinical neuroscientists has recently been outlined, and indeed there are signs to suggest a resurgent interest in psychiatric neuroscience among medical students given the need for new discoveries and the promise of new research techniques.12 Interesting educational curricula to model include the National Institute of Mental Health (NIMH)-led, 4-day Brain Camp offered in the US to MD-PhD students; the National Neuroscience Curriculum Initiative; and the NIMH-funded, 5-day Summary Research Institute in Geriatric Mental Health.13,14

The Medici effect is upon us in biomedicine, and it’s called convergence science. We believe convergence science and its greater application to psychiatry is important to address the integration of mind, body, and behavior; the urgent need for improved quality and access to clinical care; the high burden of disease; and the promise of new technologies. As the Medici family catalyzed the Renaissance by bringing together poets, philosophers, scientists, and painters and other artisans, we believe a renaissance in psychiatry can be delivered by facilitating interactions, research, and innovations between clinical neuroscientists, molecular biologists, big data scientists, roboticists, imagers, public health experts, economists, and user interface and gamification experts.


Dr Eyre is a PhD student within the discipline of psychiatry at the University of Adelaide in Adelaide, Australia; Dr Lavretsky is Professor in Residence in the department of psychiatry at the Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA; Dr Insel is Director of the National Institute of Mental Health, Bethesda, MD. The authors report no conflicts concerning the subject matter of this article.


1. Sharp PA, Langer R. Research agenda: promoting convergence in biomedical science. Science. 2011;333:527.
2. IOPScience. Convergent Science Physical Oncology. 2015. Accessed September 29, 2015.
3. National Institutes of Health. BRAIN 2025: A Scientific Vision. Accessed September 29, 2015.
4. Williams NR, Taylor JJ, Kerns S, et al. Interventional psychiatry: why now? J Clin Psychiatry. 2014;75:895-897.
5. Clark SR, Schubert KO, Baune BT. Towards indicated prevention of psychosis: using probabilistic assessments of transition risk in psychosis prodrome. J Neural Transm. 2015;122:155-169.
6. Karalunas SL, Fair D, Musser ED, et al. Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria. JAMA Psychiatry. 2014;71:1015-1024.
7. Diniz BS, Sibille E, Ding Y, et al. Plasma biosignature and brain pathology related to persistent cognitive impairment in late-life depression. Mol Psychiatry. 2015;20:594-601.
8. Kazdin AE. Technology-based interventions and reducing the burdens of mental illness: perspectives and comments on the special series. Cogn Behav Pract. 2015;22:359-366.
9. Munoz RF, Bunge EL, Chen K, et al. Massive open online interventions: a novel model for delivering behavioral health services worldwide. Clin Psychol Sci. 2015. Accessed September 29, 2015.
10. Rabbitt SM, Kazdin AE, Scassellati B. Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use. Clin Psychol Rev. 2015;35:35-46.
11. Yager J. The practice of psychiatry in the 21st century: challenges for psychiatric education. Acad Psychiatry. 2011;35:283-292.
12. Insel TR. Director’s Blog: The Future of Psychiatry (= Clinical Neuroscience). April 2012. Accessed September 29, 2015.
13. National Institute of Mental Health (NIMH) Brain Camp. 2015. Accessed September 29, 2015.
14. Bartels SJ, Lebowitz BD, Reynolds CF III, et al. Programs for developing the pipeline of early-career geriatric mental health researchers: outcomes and implications for other fields. Acad Med. 2010;85:26-35.


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