Nanopsychiatry: Is it a big thing in small size? : Industrial Psychiatry Journal

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Is it a big thing in small size?

Prakash, Jyoti; Chaudhury, Suprakash1; Chatterjee, Kaushik2; Srivastava, Kalpana3

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Industrial Psychiatry Journal 31(2):p 181-182, Jul–Dec 2022. | DOI: 10.4103/ipj.ipj_157_22
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Nanomedicine, that is, use of nanotechnology's concepts for health and well-being, has found wide avenue in the field of diagnostics, therapeutics, and research. A question arises: Does it hold similar promises in the realm of psychiatry? Recent past has seen a lot of work in the field of nanomedicine with use of nanoparticles (1–100 nm) in pharmacology, tissue regeneration, biosensors, modeling of complex systems, and so on. Research and outcome in nanopsychiatry, although less and tardy, has been promising.[1]


Entry of a drug to target cells is determined by phagocytosis (intake of solid material), macropinoctosis (intake of liquid material), and receptor-mediated endocytosis. Important factors for target delivery are a small particle size, particle shape, contact angle between the cell membrane and particle, rigidity, surface charge, and expression of receptor and surface ligand. An additional limiting factor in psychiatry is the blood brain barrier, through which 98% of the low-molecular weight molecule fails to cross. An ideal molecule thus is a small, compact, and lipophilic one which delivers the drug inside specific cells while negates possibility of side effects by avoiding cells other than targeted cells. Nanocarriers have been found to be effective in such targeted delivery. Some of these are as under[2]:-

  1. Nanoliposomes – they can carry the drug inside the lipid bilayer. These are chemically reactive and couple to specific ligand-like antibodies, antigens, cell receptors, nucleic acid probes, and so on.
  2. Niosomes – these are non-ionic surfactant vesicles. They are similar to liposomes in physical properties with better chemical stability.
  3. Nanopowder – commonly includes silver, gold, iron oxide, or silica nanoparticles.
  4. Nanocluster – high-quality nanoparticles with precise control over particle size, shape, structure, and composition
  5. Nanocrystal – size of the material reduced to less than 100 nm by milling, high-pressure homogenization, controlled precipitation, and so on. A decreased size increases the solubility of drugs.
  6. Micelles – these gather by themselves to form a core. Hydrophobic drugs can be thus encapsulated or solubilized in the core.
  7. Carbon 60 – it contains 60 carbon atoms arranged as 20 hexagons and 12 pentagons. It can carry large drug payload in the cage-like structure.
  8. Carbon nanotube – it is adept at entering nuclei of cells. It may be used to deliver drugs and vaccines and can form the basis for gene therapies.
  9. Nanopolymers – these are two-dimensional and three-dimensional polymers formed under high-pressure and high-temperature conditions. They can open the tight junctions of the blood brain barrier and release the drug for a prolonged period.
  10. Nanoshell – It is commonly silica nanoparticles with a metal shell. It releases contents on heating and could be activated at opportune time.
  11. Dendrimers – branched macromolecules constructed around a simple core unit. They do not induce undesired immune responses.
  12. Tocosome – it has both lipidic and aqueous compartments for separate/simultaneous carriage of hydrophilic and hydrophobic material.
  13. Combination of several above molecules has been tried to increase the synergy and efficiency of drug combination.


  1. In vivo imaging – paramagnetic nanoparticle contrast agents are being used in magnetic resonance imaging for better targeted detection. It has been useful in early detection of senile plaques in Alzheimer's disease and has shown potential as an early biomarker for psychiatric disorders and as a marker of response to psychotropic medications.[3]
  2. Metabolome analysis – metabolomes are a set of metabolites, which express cellular functions and the physiological overall status of an organism at any given time, with accuracy. Nanotechnology can help develop markers in understanding severity of illness or drug effects. Its use has been explored in cancer, diabetes, CVS and CNS diseases, and so on. Analysis of metabolomes can constructively modify early stages of drug development.[4]
  3. Modeling of CNS – Inorganic synapses made of nanoparticles are capable of short-term potentiation, long-term metastable potentiation, retention, and implementation. Neural networks are two-dimensional assemblies of nanodevices to model networks that recreate neural organization. These have molecular interlock switches corresponding to synapses, nano-wires representative of axons and dendrites, and nano-circuits corresponding to neuron cell bodies. These are capable of self-stimulation and empowering themselves after specific training. These models are useful in artificial intelligence, understanding mental illnesses and effects of external disturbances, and predicting evolution and complications of the disease.[56]


There are concerns associated with risk to health with use of nanotechnology. Drugs which get into brain more efficiently may leave brain similarly. It may induce immune reactions or excessive production of free radicals. Thus, even though nanotechnology appears to hold good promises for future, sustainability of these has to stand the scrutiny of time.


1. Fond G, Macgregor A, Miot S. Nanopsychiatry-the potential role of nanotechnologies in the future of psychiatry: A systematic review Eur Neuropsychopharmacol. 2013;23:1067–71
2. Patra JK, Das G, Fraceto LF, Campos EVR, Rodriguez-Torres MDP, Acosta-Torres LS, et al Nano based drug delivery systems: recent developments and future prospects J Nanobiotechnol. 2018;16:71 doi: 10.1186/s12951-018-0392-8
3. Teleanu DM, Chircov C, Grumezescu AM, Volceanov A, Teleanu RI. Contrast agents delivery: An up-to-date review of nanodiagnostics in neuroimaging Nanomaterials. 2019;9:542 doi: 10.3390/nano9040542
4. Zhang B, Xie M, Bruschweiler-Li L, Brüschweiler R. Nanoparticle-assisted metabolomics Metabolites. 2018;8:21 doi: 10.3390/metabo8010021
5. Lao J, Xu W, Jiang C, Zhong N, Tian B, Lin H, et al Artificial synapse based on organic–inorganic hybrid perovskite with electric and optical modulation Adv Electron Mater. 2021;7:2100291 doi: 10.1002/aelm.202100291
6. Prezioso M, Merrikh-Bayat F, Hoskins B, Adam GC, Likharev KK, Strukov DB. Training and operation of an integrated neuromorphic network based on metal-oxide memristors Nature. 2015;521:61–4
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