By Tsang Wai Ki, Ella
Research Question
To what extent can AI contribute to the development of personalized medicine, specifically for patients with depression?
Abstract
Depression rate has been ever-increasing in the past decade, and there are more than 10 types of antidepressants available. Currently, many doctors and healthcare workers in the past have been attempting to find the best type of antidepressants for their patients with their multiple trials, but this has led to an increase in suicidal rate every year. Thus, artificial intelligence is able to analyze patient’s genetics, facilitate remote monitoring, and track their medication records with its accurate algorithm that is able to process mass datasets quickly. This paper aims to provide a structured analysis of to what extent AI can be included in the healthcare industry in order to optimize personalized medication for patients with depression in order to balance out the undesirable side effects.
Literature Review
The recent peak of artificial intelligence technology has gained lots of attention globally, and there have been studies conducted that emphasize the effectiveness and accuracy of AI tools. Recently, back in May 2024, Oxford University invited depression patients to take part in their clinical research on how AI is able to treat each individual differently according to their needs, symptoms, genetics, and past medication history. This enhances the treatment outcomes and the patients’ wellbeing. On the other hand, there has been investigation that have showed an increase in the risk of suicidal behaviour after taking antidepressants as published on CNS Neuroscience & Therapeutics; for instance, a man was treated with a type of antidepressants, then was told to switch shortly after. The rapid change in medication was proved that it contributed to his suicidal attempts and behaviours. (“CNS Neuroscience & Therapeutics,” 2010) This case continues to add on to the importance of AI personalized prescription. One limitation in AI medication that has not been brought up is the cost; the cost of implementing a well-developed AI medication bot for individuals is quite high and cost might become a barrier to those who are struggling with finance. However, the governments can work to fund an AI bot for those who are concerned with the budget, but are hoping to receive personalized medication. Ultimately, AI is a useful tool to assist doctors in the field of medication in order to avoid severe side effects and most importantly, lowers the risk of suicides.
Introduction
In a world where artificial intelligence (AI) is able to help humans generate information quickly, process data accurately, and solve complex problems, it has emerged in many industries to help with problem solving and developing revolutionary products. On top of that, AI has also been used in the healthcare industry to speed up the process with analyzing datasets and timely interventions. (Roy, 2023) Depression has become more and more common as the society becomes more competitive, and there are approximately 280 million people around the world who are suffering from depression according to the World Health Organization (WHO). Patients with depression are constantly required to switch medications to find the one that best suits them, however, this often comes with numerous side effects, leading to suicides and worsening the patient’s mental health. What if AI can help with personalizing medications and treatments? As up to 13% of the depressed population every year take their own lives due to the side effects of depression. (Pompili et al., 2010) AI technology allows patients with depression to be prescribed with personalized medications by analyzing one’s genetics, monitoring them remotely while making changes to medication dosage accordingly, and tracking their past medication history in order to minimize the risk of worsening one’s depression.
How Can It Help?
With AI being so advanced and accurate, it can help with analyzing one’s genetics in order to avoid prescribing the wrong medication. Antidepressants are one of the most frequently used medications for those with depression, but it comes with lots of side effects such as nausea, dizziness, and sleepless nights. Nowadays, doctors often rely on the trial-and-error process to find the best medication that suits the patients, and sometimes make mistakes. The process of finding an appropriate medication is often torturing and painful, pushing those who are already in pain to take their own lives. For instance, recently in New Zealand, a young lady with depression was given the wrong medication and had a severe allergic reaction to it, leaving her feeling “burned from the inside”. (English, 2024) This case highlights the errors that come with humans prescribing antidepressants or other medications, and hence AI can help with analyzing one’s data and suggesting the medicine that best suits one. AI is capable of identifying patterns and records that may suggest the patient’s certain conditions or symptoms, and “analyze medical images such as CT and MRI scans or X-rays to detect anomalies”. (Monash University, 2023) Therefore, AI can propose a few promising and appropriate medication options for doctors to prescribe, reducing the time and side effects of transitioning depression medications. Recently, there has been a trial conducted at the University of Oxford, England, where patients with depression use “Petrushka”, an AI algorithm, to tailor make their very own medication plan and to choose the antidepressant that best fits them. Professor Andrea Cipriani emphasizes that AI can personalize treatments and can be as precise as possible since they should not be only looking at the average data. (University of Oxford, 2024) In the near future, doctors will be able to get a list of medication suggestions by simply putting in the patient’s data and AI will analyze the dataset and identify patterns, aiming to lower the side effects and the risk of worsening one’s depression.
Whilst it typically takes up to 8 weeks for patients’ signs of depression to improve after taking antidepressants, most patients are able to feel a change in their bodies as well as side effects just after a couple of days, and AI is able to help with remote patient monitoring, allowing patients to receive medications based on their real-time and up-to-date symptoms. (Smedley, 2022) Hence, patients will not need to visit the doctor in order to receive updated prescriptions and concise medical advice. AI technology is able to generate predictive analytics with the input of the patient’s data while notifying the doctors and gathering data from the patient’s genetics as previously mentioned. For instance, AI has helped a patient with heart failure to prevent heart failure exacerbation as it found inconsistent patterns in their heart rate, alerting the patient in time to adjust their medication. (Murphy, 2024) This case has proven AI’s alertness and higher pace of processing information than doctors. Doctors can train the AI programs to give medical advice based on their updated symptoms and signs of depression, allowing more accurate doses of depression medication while balancing the outcomes. Thus, AI can soon take up the role of advising and monitoring patients while they are on their depression medication, and enables the customization of medication dosages, in order to avoid intensifying one’s depression symptoms and side effects.
Last but not least, doctors can utilize AI tools and algorithms to track the patient’s past medication history as patients in order to avoid prescribing the same type of medication that the patient has received before, enhancing patient’s safety and preventing the switch of medication and side effects The algorithm of AI is able to interpret and go over a patient’s medication history in a short amount of time. According to PsychCentral, a website that specializes in discussing about the different kinds of mental health medications, that if one rapidly switches between various types of antidepressants, the patient will likely be experiencing the side effects of both new and old medication, such as loss of appetite, heartburn, and headaches, worsening their physical feelings, and often leading to suicides. On top of that, patients who have been constantly switching antidepressants over a long period of time are likely to develop “antidepressant tolerance”, lowering the effectiveness of other types of medication on the patient.
(Elmer, 2022) In 2008, a man with depression was firstly prescribed imipramine, and then switched to escitalopram, and the side effects that came with the switch of medication tortured him, ultimately worsening his depression and he admitted that he had suicidal thoughts. (Reeves & Ladner, 2010) AI algorithm can help with tracking the patient’s past medication history in order to avoid the change of drugs, as it can quickly interpret and analyze what medication is best suited for the patient. This can be done to evade the switch of medication and exacerbate their depressed emotions. AI enables doctors to be notified of the types of antidepressants that the patient has been prescribed through analyzing their medical record, speeding up the process for the doctors while trying to find a suitable medication for them.
Rebuttal
While many might argue that AI provides negative diagnosis, there have been cases that have proven that AI is more accurate than doctors as they have the ability to analyze an image and people’s genes, and then generate suggestions. For example, recently in England, there was a patient who noticed lumps in her breast, but the 11 doctors have claimed that she was cancer-free. However, AI noticed a very tiny 6mm tumor in her breast, and she ended up only needing 5 days of radiotherapy. (Kleinman, 2024) On top of that, many people oppose AI due to its incomplete data sets and doubt its ability to make accurate medical decisions. The Amsterdam University Research Center has proven that AI is able to help predict the patient’s antidepressants response, as it is able to predict the efficiency of the medication to specific patients in order to prevent the switch of medications and minimize the risk of suicides. (News Medical) To sum it up, AI has the ability to help with personalizing medication while keeping its data accurate and precise, as a means to optimize drug efficacy and to balance the side effects to lower the risk of suicidal behaviors.
Conclusion
In conclusion, by evaluating and analyzing one’s genetics, monitoring them remotely, and adjusting the dosage of medication if necessary, as well as tracking their past medication history, AI enables a personalized medication approach for depression patients, reducing the risk of suicides and undesirable side effects. With AI’s ability to process mass datasets quickly, AI is able to offer constructive insights into the genetics, clinical, and lifestyle factors in aims to generate a list of drug suggestions for doctors. Through incorporating artificial intelligence (AI) into the healthcare industry in order to help patients with depression to find their best-suited medicine without having to endure side effects. The integration of AI technology enhances the efficiency and advances data analysis, allowing depression patients to receive the best care that they need according to their conditions.
References
Elmer, J. (2022, January 19). What to Expect When Switching Antidepressants. PsychCentral. https://psychcentral.com/health/switching-antidepressants
English. (2024, May 8). NDTV. NDTV.com.
https://www.ndtv.com/feature/new-zealand-woman-burned-from-the-inside-after-severe-reaction -from-depression-medication-5614905
Kleinman, Z. (2024, March 21). NHS AI test spots tiny cancers missed by doctors. BBC News. https://www.bbc.com/news/technology-68607059
Monash University. (2023, January 13). AI in healthcare: Career scope in Australia. Monash Online. https://online.monash.edu/news/ai-in-healthcare/
Murphy, J. (2024, August 23). How is AI Used in Remote Patient Monitoring? Tenovi. https://www.tenovi.com/ai-in-remote-patient-monitoring/
Pompili, M., Serafini, G., Innamorati, M., Ambrosi, E., Giordano, G., Girardi, P., Tatarelli, R., & Lester, D. (2010). Antidepressants and Suicide Risk: A Comprehensive Overview. Pharmaceuticals, 3(9), 2861–2883. https://doi.org/10.3390/ph3092861
Reeves, R. R., & Ladner, M. E. (2010). Antidepressant-Induced Suicidality: An Update. CNS Neuroscience & Therapeutics, 16(4), no-no. https://doi.org/10.1111/j.1755-5949.2010.00160.x
Roy, A. (2023, July 28). Artificial intelligence: 10 promising interventions for healthcare. NIHR Evidence.
https://evidence.nihr.ac.uk/collection/artificial-intelligence-10-promising-interventions-for-health care/
Smedley, T. (2022, August 10). How Long Does It Take for Antidepressants to Start Working? GoodRx. https://www.goodrx.com/conditions/depression/time-for-antidepressants-to-work
(13 C.E., May). AI to help personalise treatment for depression as part of major trial Department of Psychiatry, Medical Sciences Division; Oxford University.
https://www.psych.ox.ac.uk/news/ai-to-help-personalise-treatment-for-depression-in-oxfordshire -as-part-of-major-trial
