Repetitive behavior disorders such as obsessive-compulsive disorder (OCD), tic disorder, and Tourette’s syndrome have been difficult to treat because they involve considerable complexity. For example, the symptoms of a disorder may vary from individual to individual, as may the coexistence or nonexistence of other behavioral disorders such as anxiety and depression. Additionally, the treatment of OCD, tic disorder, and Tourette’s syndrome varies depending on the disorders present in an individual patient, how long the traits of the disorder have been present, how patients respond to doses of treatment, and the effectiveness of the treatment.
Historically and even today, medical professionals have been faced with an array of potential treatments that may or may not work alone or in combination with other medications. The frustration of healthcare providers is compounded by the low level of investment in R&D by governments, which is holding back progress. Rather than inventing a new drug that would take years to reach the market, it is possible to use artificial intelligence (AI), and more specifically deep learning, to discover how existing drugs benefiting from regulatory approval can be reused for other applications.
One such example is clemastine, an antihistamine, which has been shown to prevent and reduce the occurrence of repetitive behaviors.
Repetitive disorders have been difficult to treat
OCD is a disorder in which unwanted thoughts and behaviors are repeated. Compulsive behaviors mostly appear in the form of cleaning, confirming, delaying, ordering, and other repetitive behaviors. Typically, serotonin uptake inhibitors such as clomipramine, fluoxetine, and fluvoxamine are used to treat OCD, but side effects can include anxiety, diarrhea, insomnia, vomiting, and weight gain. Disorders related to OCD include, but are not limited to, storage disorders, hair pulling disorders, and skin depilation disorders, for example.
Tics include chronic motor or vocal tics, transient tics, and Tourette’s syndrome. They are characterized by vocal tics or sudden, rapid, repetitive, rhythmic or stereotyped movements that persist for more than a year, while Public Tic is characterized by the presence of one or more motor or vocal tics that have been present for less than a year. ‘a year.
Tourette’s syndrome is a neurological abnormality that repeats unconscious and uncontrolled sounds or actions and is characterized by multiple motor and vocal tics for over a year. Tics are uncontrolled and appear in a wide variety of forms and have repetitive characteristics. In this case, dopamine receptor antagonists such as haloperidol, fluphenazine, and pimozide are used for treatment, but side effects may include cognitive decline, discomfort, and extrapyramidal symptoms.
Practitioners often find themselves frustrated because they are unable to achieve a satisfactory therapeutic effect using individual drugs or even a combination of drugs that are available today. Also, some of these drugs are restricted due to their side effects. Very often, physicians find themselves in a continual mode of trial and error, trying this or that treatment, or a combination of treatments, or adjusting drug doses to reduce a patient’s unwanted repetitive behavior.
Recently, many genetic mutations involved in the generation and function of nerve cell synapses have been discovered in patients with neuropsychiatric diseases and synaptopathy. These genetic mutations are recognized as one of the key mechanisms of neuropsychiatric diseases.
Clemastine, an antihistamine also called meclastine, is used to treat allergic rhinitis, sneezing, dermatitis, and itching. However, its therapeutic effect on repetitive behavior disorders has not been reported before. By using artificial intelligence (AI), and more specifically deep learning, it is possible to discover that clemastine effectively reduces repetitive behaviors in mice. In humans, it could prove to be the missing piece needed to prevent or reduce OCD, tic disorder and Tourette’s syndrome.
Why clemastine shows promise as an active ingredient
A pharmaceutical composition comprising clemastine or a pharmaceutically acceptable salt thereof can be used as an active ingredient for the prevention or treatment of repetitive behavioral disorders.
Clemastine is a first-generation amino alkyl ether antihistamine that binds to the histamine H1 receptor and blocks the action of endogenous histamine. It has been approved by the US Food and Drug Administration (FDA) and is currently a generic drug (eg, tabegil).
Clemastine is a pharmaceutically acceptable salt that includes physiologically acceptable inorganic and organic acids and bases. Specifically, AI has identified that the pharmaceutically acceptable clemastine sale is clemastine fumarate. The pharmaceutical composition is formulated in the form of aerosols, capsules, emulsions, external preparations, granules, sterile injection solutions, suppositories, suspensions, syrups and tablets. Clemastine or other pharmaceutically acceptable salts can also be used in foods, including beverages, gum, dietary supplements, tea, and vitamin complexes.
The pharmaceutically effective dose of clemastine is preferably from 0.1 mg/day to 5 mg/day, the latter being administered once or several times a day in dividing the dose. The amount a patient needs depends on the route of administration, age, concomitant medications, condition, severity of symptoms and gender of the person. Clemastine or a pharmaceutically acceptable salt thereof and one or more drugs may be administered simultaneously, sequentially, or in reverse order, such as serotonin reuptake inhibitors for OCD and serotonin receptor antagonists. dopamine for Tourette’s syndrome, for example.
Laboratory experiments on mice have already proven that a deficiency of SH3 scaffolding proteins and several ankyrin repeat domains (SHANK3) is a factor that induces repetitive behavior and that clemastine attenuates the increase in repetitive behavior caused by SHANK3 deficiency. We hope the AI-based discovery will amount to a step change in treatment that will benefit patients and their prescribing physicians.
Why AI-Based Drug Redirection Is Wise
Drug discovery is a long and tedious process, as traditional research takes considerable time, as does regulatory approval. In the meantime, patients with a disorder or disease may suffer unnecessarily. Medication redirection is a quicker alternative. However, the chemical details of the drug, its potential interactions with other medications, and its side effects must be considered when navigating the universe of possibilities. AI can do all of this at scale.
For drug reuse, AI analyzes the original purpose and chemical composition of a drug as well as a universe of diseases and/or disorders to find correlations and perhaps even causation. Deep learning helps identify the “unknown unknowns” such as Clemastine can be used to prevent or treat OCD and other repetitive behavior disorders.
Conclusion
AI is a powerful tool that can be used for patentable drug discovery and reuse. Given the scale and speed at which AI can operate, it has the potential to advance the state of the art in drug discovery and repurposing at a pace much faster than it was only possible to use traditional tools and humans. Additionally, this improved efficiency has the potential to reduce the drug discovery and repurposing times needed to treat patients in new and improved ways.
About Jin Han Kim
Jin Han Kim is the co-founder, chairman and CEO of Standigm, an AI-based drug discovery company based in Seoul, South Korea and subsidiaries in Cambridge, UK. Generate drug pipelines of commercial value. Kim is an expert in developing AI platforms to identify new drug candidates and has led the company since its inception in May 2015.
Prior to founding Standigm, Kim worked as a senior research scientist at Samsung Advanced Institute of Technology, where he developed an AI algorithm for DNA damage and recovery mechanisms. He previously worked as a software developer for NCSOFT and for Namo Interactive. He also served as Director of Pharmaceutical Informatics at Korea Society of Medical Informatics from January 2017 to January 2020. Kim earned his Ph.D. in Artificial Intelligence from the University of Edinburgh, his MS in Artificial Intelligence from Seoul National University, and his BS in Applied Biology and Chemistry from Seoul National University. Kim speaks Korean and English.
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