ARTIFICIAL INTELLIGENCE IMPACT ON HEALTHCARE: ADVANCED DRUG DISCOVERY AND BEYOND
Main Article Content
Keywords
Artificial Intelligence, Machine Learning, Artificial Neural Network, Convolutional Neural Network
Abstract
Artificial Intelligence is the advance of human technology which can work as human brain with the help of prefeed data, AI can take the decision and implement by their own. With the help of AI car can be drive without driver in recent time, this can be done with the help of data about the driving of car is installed in the system of car with the sensors. Recently AI is used in pharmaceutical industry more frequently. In this review we discussed about types of AI and how AI can be used in the process of drug discovery and development. The use of AI in recent pandemic i.e., Covid 19 treatment and its diagnosis from various tools explained. Diagnosis of life-threatening disease like cancer can be done with the help of Machine Learning tools like CNN which show a proper image based on input data. Artificial intelligence plays crucial role in personalized medicine which uses patient’s genetic profile to decide for prevention, diagnosis, and treatment of disease. The algorithm of Machine Learning which is a sub-field of AI is very useful in clinical trial which can predict a toxicity of a compound and can select the accurate candidate for clinical trial. Recently researchers using AI to predict the bioavailability of a compound and can making the prediction that how the compound will interact with proteins which will be beneficial and can reduce the cost of discovery of compound.
References
1. Shah N. Artificial Intelligence in Pharma Industry-A Review. Asian Journal of Pharmaceutics (AJP). 2023;17(2).
2. Patel J, Patel D, Meshram D. Artificial Intelligence in Pharma Industry-A Rising Concept. Journal of Advancement in Pharmacognosy. 2021;1(2).
3. Bhattamisra SK, Banerjee P, Gupta P, Mayuren J, Patra S, Candasamy M. Artificial Intelligence in Pharmaceutical and Healthcare Research. Big Data and Cognitive Computing. 2023;7(1):10.
4. Comito C, Pizzuti C. Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review. Artificial intelligence in medicine. 2022 1; 128:102286.
5. Gupta R, Srivastava D, Sahu M, Tiwari S, Ambasta RK, Kumar P. Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular diversity. 2021:1315-60.
6. Selvaraj C, Chandra I, Singh SK. Artificial intelligence, and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Molecular diversity. 2021:1-21.
7. Mak KK, Pichika MR. Artificial intelligence in drug development: present status and future prospects. Drug discovery today. 2019;24(3):773-80.
8. Borkotoky S, Joshi A, Kaushik V, Jha AN. Machine Learning and Artificial Intelligence in Therapeutics and Drug Development Life Cycle. IntechOpen; 2022.
9. Machine learning: What it is, tutorial, definition, types-javatpoint (no date) www.javatpoint.com. Available at: https://www.javatpoint.com/machine-learning (Accessed: 22 August 2023).
10. Tarle S, Kakad A, Shaikh Mr. Overview: Embracing Tools of Artificial Intelligence In Pharmaceuticals.2023 Vol. 04, Issue 06
11. Within3. Generative AI and Chatgpt in pharma [Internet]. 2023 [cited 2023 Aug 22]. Available from: https://within3.com/blog/generative-ai-chatgpt-in-pharma.
12. What is Artificial Intelligence (AI)? [Internet]. [cited 2023 Aug 22]. Available from: https://www.ibm.com/topics/artificial-intelligence.
13. [Internet]. [cited 2023 Aug 22]. Available from: https://www.g2.com/articles/history-of-artificial-intelligence.
14. What are the types of artificial intelligence? Branches of ai [Internet]. 2023 [cited 2023 Aug 22]. Available from: https://www.edureka.co/blog/types-of-artificial-intelligence.
15. Four types of AI: Getting to know artificial intelligence [Internet]. [cited 2023 Aug 22]. Available from: https://www.coursera.org/articles/types-of-ai
16. Marko (2023) theory of mind AI: The power of empathy, Medium. Available at:http// pub.towardsai.net/theory-of-mind-AI-the-power-of-empathy(Assessed 22 august 2023)
17. Mea. Self-awareness in Ai [Internet]. Medium; 2020 [cited 2023 Aug 22]. Available from: https://meaxr.medium.com/self-awareness-in-AI.
18. Chen H, Engkvist O, Wang Y, Olivecrona M, Blaschke T. The rise of deep learning in drug discovery. Drug discovery today. 2018;23(6):1241-50.
19. Lu M, Yin J, Zhu Q, Lin G, Mou M, Liu F, Pan Z, You N, Lian X, Li F, Zhang H. Artificial intelligence in pharmaceutical sciences. Engineering. 2023.
20. Dreiseitl S, Ohno-Machado L. Logistic regression and artificial neural network classification models: a methodology review. Journal of biomedical informatics. 2002 ;35(5-6):352-9.
21. Senior AW, Evans R, Jumper J, Kirkpatrick J, Sifre L, Green T, Qin C, Žídek A, Nelson AW, Bridgland A, Penedones H. Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13). Proteins: structure, function, and bioinformatics. 2019 ;87(12):1141-8.
22. Burley SK, Berman HM. Open-access data: A cornerstone for artificial intelligence approaches to protein structure prediction. Structure. 2021 ;29(6):515-20.
23. Prasad K, Kumar V. Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2. Current Research in Pharmacology and Drug Discovery. 2021 1; 2:100042.
24. Schenone M, Dančík V, Wagner BK, Clemons PA. Target identification and mechanism of action in chemical biology and drug discovery. Nature chemical biology. 2013;9(4):232-40.
25. Liu Z, Roberts RA, Lal-Nag M, Chen X, Huang R, Tong W. AI-based language models powering drug discovery and development. Drug Discovery Today. 2021;26(11):2593-607.
26. Qureshi R, Irfan M, Gondal TM, Khan S, Wu J, Hadi MU, Heymach J, Le X, Yan H, Alam T. AI in Drug Discovery, and its Clinical Relevance. Heliyon. 2023.
27. Paul D, Sanap G, Shenoy S, Kalyane D, Kalia K, Tekade RK. Artificial intelligence in drug discovery and development. Drug discovery today. 2021(1):80.
28. Öztürk H, Özgür A, Ozkirimli E. DeepDTA: deep drug–target binding affinity prediction. Bioinformatics. 2018;34(17): i821-9.
29. Raies AB, Bajic VB. In silico toxicology: computational methods for the prediction of chemical toxicity. Wiley Interdisciplinary Reviews: Computational Molecular Science. 2016;6(2):147-72.
30. Basile AO, Yahi A, Tatonetti NP. Artificial intelligence for drug toxicity and safety. Trends in pharmacological sciences. 2019;40(9):624-35.
31. Awwalu J, Garba AG, Ghazvini A, Atuah R. Artificial intelligence in personalized medicine application of AI algorithms in solving personalized medicine problems. International Journal of Computer Theory and Engineering. 2015;7(6):439.
32. Chakravarty K, Antontsev V, Bundey Y, Varshney J. Driving success in personalized medicine through AI-enabled computational modeling. Drug Discovery Today. 2021 1;26(6):1459-65.
33. GS G. Personalized medicine: revolutionizing drug discovery and patient care. Trends Biotechnol. 2001; 19:491-6.
34. Malik YS, Sircar S, Bhat S, Ansari MI, Pande T, Kumar P, Mathapati B, Balasubramanian G, Kaushik R, Natesan S, Ezzikouri S. How artificial intelligence may help the Covid‐19 pandemic: Pitfalls and lessons for the future. Reviews in medical virology. 2021(5):1-1.
35. Khan M, Mehran MT, Haq ZU, Ullah Z, Naqvi SR, Ihsan M, Abbass H. Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review. Expert systems with applications. 2021 15; 185:115695.
36. Harrer S, Shah P, Antony B, Hu J. Artificial intelligence for clinical trial design. Trends in pharmacological sciences. 2019 1;40(8):577-91.
37. Delso G, Cirillo D, Kaggie JD, Valencia A, Metser U, Veit-Haibach P. How to design AI-driven clinical trials in nuclear medicine. InSeminars in nuclear medicine 2021 (Vol. 51, No. 2, pp. 112-119). WB Saunders.
38. Cirillo D, Catuara-Solarz S, Morey C, Guney E, Subirats L, Mellino S, Gigante A, Valencia A, Rementeria MJ, Chadha AS, Mavridis N. Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. NPJ digital medicine. 2020 ;3(1):81.
39. Noorbakhsh-Sabet N, Zand R, Zhang Y, Abedi V. Artificial intelligence transforms the future of health care. The American journal of medicine. 2019 Jul 1;132(7):795-801.
40. Jolly J. How AI is revolutionizing clinical trials and research? [Internet]. Saxon. 2023 [cited 2023]. Available from: https://saxon.ai/blogs/empowering-clinical-trials-and-research-impact-of-ai-in-medicine
41. Mirbabaie M, Stieglitz S, Frick NR. Artificial intelligence in disease diagnostics: A critical review and classification on the current state of research guiding future direction. Health and Technology. 2021;11(4):693-731.
42. Ahn JC, Connell A, Simonetto DA, Hughes C, Shah VH. Application of artificial intelligence for the diagnosis and treatment of liver diseases. Hepatology. 2021;73(6):2546-63.
43. Ahsan MM, Luna SA, Siddique Z. Machine-learning-based disease diagnosis: A comprehensive review. InHealthcare (Vol. 10, No. 3, p. 541). MDPI 2022.
44. Deng Y, Qin HY, Zhou YY, Liu HH, Jiang Y, Liu JP, Bao J. Artificial intelligence applications in pathological diagnosis of gastric cancer. Heliyon. 2022 Dec.
45. Kalyane D, Sanap G, Paul D, Shenoy S, Anup N, Polaka S, Tambe V, Tekade RK. Artificial intelligence in the pharmaceutical sector: current scene and future prospect. InThe future of pharmaceutical product development and research 2020 (pp. 73-107). Academic Press.
46. Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ digital medicine. 2020;3(1):118.
47. Johnson KB, Wei WQ, Weeraratne D, Frisse ME, Misulis K, Rhee K, Zhao J, Snowdon JL. Precision medicine, AI, and the future of personalized health care. Clinical and translational science. 2021(1):86-93.
48. Popa SL, Pop C, Dita MO, Brata VD, Bolchis R, Czako Z, Saadani MM, Ismaiel A, Dumitrascu DI, Grad S, David L. Deep learning, and antibiotic resistance. Antibiotics. 2022 Nov 21;11(11):1674.
49. Food and Drug Administration. Proposed regulatory framework for modifications to artificial intelligence/machine learning (AI/ML)-based software as a medical device (SaMD) 2019.
50. King MR. The future of AI in medicine: a perspective from a Chatbot. Annals of Biomedical Engineering. 2023;51(2):291-5.
51. Briganti G, Le Moine O. Artificial intelligence in medicine: today and tomorrow. Frontiers in medicine. 2020; 7:27.
52. Hatherley JJ. Limits of trust in medical AI. Journal of medical ethics. 2020 ;46(7):478-81.
2. Patel J, Patel D, Meshram D. Artificial Intelligence in Pharma Industry-A Rising Concept. Journal of Advancement in Pharmacognosy. 2021;1(2).
3. Bhattamisra SK, Banerjee P, Gupta P, Mayuren J, Patra S, Candasamy M. Artificial Intelligence in Pharmaceutical and Healthcare Research. Big Data and Cognitive Computing. 2023;7(1):10.
4. Comito C, Pizzuti C. Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review. Artificial intelligence in medicine. 2022 1; 128:102286.
5. Gupta R, Srivastava D, Sahu M, Tiwari S, Ambasta RK, Kumar P. Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular diversity. 2021:1315-60.
6. Selvaraj C, Chandra I, Singh SK. Artificial intelligence, and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Molecular diversity. 2021:1-21.
7. Mak KK, Pichika MR. Artificial intelligence in drug development: present status and future prospects. Drug discovery today. 2019;24(3):773-80.
8. Borkotoky S, Joshi A, Kaushik V, Jha AN. Machine Learning and Artificial Intelligence in Therapeutics and Drug Development Life Cycle. IntechOpen; 2022.
9. Machine learning: What it is, tutorial, definition, types-javatpoint (no date) www.javatpoint.com. Available at: https://www.javatpoint.com/machine-learning (Accessed: 22 August 2023).
10. Tarle S, Kakad A, Shaikh Mr. Overview: Embracing Tools of Artificial Intelligence In Pharmaceuticals.2023 Vol. 04, Issue 06
11. Within3. Generative AI and Chatgpt in pharma [Internet]. 2023 [cited 2023 Aug 22]. Available from: https://within3.com/blog/generative-ai-chatgpt-in-pharma.
12. What is Artificial Intelligence (AI)? [Internet]. [cited 2023 Aug 22]. Available from: https://www.ibm.com/topics/artificial-intelligence.
13. [Internet]. [cited 2023 Aug 22]. Available from: https://www.g2.com/articles/history-of-artificial-intelligence.
14. What are the types of artificial intelligence? Branches of ai [Internet]. 2023 [cited 2023 Aug 22]. Available from: https://www.edureka.co/blog/types-of-artificial-intelligence.
15. Four types of AI: Getting to know artificial intelligence [Internet]. [cited 2023 Aug 22]. Available from: https://www.coursera.org/articles/types-of-ai
16. Marko (2023) theory of mind AI: The power of empathy, Medium. Available at:http// pub.towardsai.net/theory-of-mind-AI-the-power-of-empathy(Assessed 22 august 2023)
17. Mea. Self-awareness in Ai [Internet]. Medium; 2020 [cited 2023 Aug 22]. Available from: https://meaxr.medium.com/self-awareness-in-AI.
18. Chen H, Engkvist O, Wang Y, Olivecrona M, Blaschke T. The rise of deep learning in drug discovery. Drug discovery today. 2018;23(6):1241-50.
19. Lu M, Yin J, Zhu Q, Lin G, Mou M, Liu F, Pan Z, You N, Lian X, Li F, Zhang H. Artificial intelligence in pharmaceutical sciences. Engineering. 2023.
20. Dreiseitl S, Ohno-Machado L. Logistic regression and artificial neural network classification models: a methodology review. Journal of biomedical informatics. 2002 ;35(5-6):352-9.
21. Senior AW, Evans R, Jumper J, Kirkpatrick J, Sifre L, Green T, Qin C, Žídek A, Nelson AW, Bridgland A, Penedones H. Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13). Proteins: structure, function, and bioinformatics. 2019 ;87(12):1141-8.
22. Burley SK, Berman HM. Open-access data: A cornerstone for artificial intelligence approaches to protein structure prediction. Structure. 2021 ;29(6):515-20.
23. Prasad K, Kumar V. Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2. Current Research in Pharmacology and Drug Discovery. 2021 1; 2:100042.
24. Schenone M, Dančík V, Wagner BK, Clemons PA. Target identification and mechanism of action in chemical biology and drug discovery. Nature chemical biology. 2013;9(4):232-40.
25. Liu Z, Roberts RA, Lal-Nag M, Chen X, Huang R, Tong W. AI-based language models powering drug discovery and development. Drug Discovery Today. 2021;26(11):2593-607.
26. Qureshi R, Irfan M, Gondal TM, Khan S, Wu J, Hadi MU, Heymach J, Le X, Yan H, Alam T. AI in Drug Discovery, and its Clinical Relevance. Heliyon. 2023.
27. Paul D, Sanap G, Shenoy S, Kalyane D, Kalia K, Tekade RK. Artificial intelligence in drug discovery and development. Drug discovery today. 2021(1):80.
28. Öztürk H, Özgür A, Ozkirimli E. DeepDTA: deep drug–target binding affinity prediction. Bioinformatics. 2018;34(17): i821-9.
29. Raies AB, Bajic VB. In silico toxicology: computational methods for the prediction of chemical toxicity. Wiley Interdisciplinary Reviews: Computational Molecular Science. 2016;6(2):147-72.
30. Basile AO, Yahi A, Tatonetti NP. Artificial intelligence for drug toxicity and safety. Trends in pharmacological sciences. 2019;40(9):624-35.
31. Awwalu J, Garba AG, Ghazvini A, Atuah R. Artificial intelligence in personalized medicine application of AI algorithms in solving personalized medicine problems. International Journal of Computer Theory and Engineering. 2015;7(6):439.
32. Chakravarty K, Antontsev V, Bundey Y, Varshney J. Driving success in personalized medicine through AI-enabled computational modeling. Drug Discovery Today. 2021 1;26(6):1459-65.
33. GS G. Personalized medicine: revolutionizing drug discovery and patient care. Trends Biotechnol. 2001; 19:491-6.
34. Malik YS, Sircar S, Bhat S, Ansari MI, Pande T, Kumar P, Mathapati B, Balasubramanian G, Kaushik R, Natesan S, Ezzikouri S. How artificial intelligence may help the Covid‐19 pandemic: Pitfalls and lessons for the future. Reviews in medical virology. 2021(5):1-1.
35. Khan M, Mehran MT, Haq ZU, Ullah Z, Naqvi SR, Ihsan M, Abbass H. Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review. Expert systems with applications. 2021 15; 185:115695.
36. Harrer S, Shah P, Antony B, Hu J. Artificial intelligence for clinical trial design. Trends in pharmacological sciences. 2019 1;40(8):577-91.
37. Delso G, Cirillo D, Kaggie JD, Valencia A, Metser U, Veit-Haibach P. How to design AI-driven clinical trials in nuclear medicine. InSeminars in nuclear medicine 2021 (Vol. 51, No. 2, pp. 112-119). WB Saunders.
38. Cirillo D, Catuara-Solarz S, Morey C, Guney E, Subirats L, Mellino S, Gigante A, Valencia A, Rementeria MJ, Chadha AS, Mavridis N. Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. NPJ digital medicine. 2020 ;3(1):81.
39. Noorbakhsh-Sabet N, Zand R, Zhang Y, Abedi V. Artificial intelligence transforms the future of health care. The American journal of medicine. 2019 Jul 1;132(7):795-801.
40. Jolly J. How AI is revolutionizing clinical trials and research? [Internet]. Saxon. 2023 [cited 2023]. Available from: https://saxon.ai/blogs/empowering-clinical-trials-and-research-impact-of-ai-in-medicine
41. Mirbabaie M, Stieglitz S, Frick NR. Artificial intelligence in disease diagnostics: A critical review and classification on the current state of research guiding future direction. Health and Technology. 2021;11(4):693-731.
42. Ahn JC, Connell A, Simonetto DA, Hughes C, Shah VH. Application of artificial intelligence for the diagnosis and treatment of liver diseases. Hepatology. 2021;73(6):2546-63.
43. Ahsan MM, Luna SA, Siddique Z. Machine-learning-based disease diagnosis: A comprehensive review. InHealthcare (Vol. 10, No. 3, p. 541). MDPI 2022.
44. Deng Y, Qin HY, Zhou YY, Liu HH, Jiang Y, Liu JP, Bao J. Artificial intelligence applications in pathological diagnosis of gastric cancer. Heliyon. 2022 Dec.
45. Kalyane D, Sanap G, Paul D, Shenoy S, Anup N, Polaka S, Tambe V, Tekade RK. Artificial intelligence in the pharmaceutical sector: current scene and future prospect. InThe future of pharmaceutical product development and research 2020 (pp. 73-107). Academic Press.
46. Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ digital medicine. 2020;3(1):118.
47. Johnson KB, Wei WQ, Weeraratne D, Frisse ME, Misulis K, Rhee K, Zhao J, Snowdon JL. Precision medicine, AI, and the future of personalized health care. Clinical and translational science. 2021(1):86-93.
48. Popa SL, Pop C, Dita MO, Brata VD, Bolchis R, Czako Z, Saadani MM, Ismaiel A, Dumitrascu DI, Grad S, David L. Deep learning, and antibiotic resistance. Antibiotics. 2022 Nov 21;11(11):1674.
49. Food and Drug Administration. Proposed regulatory framework for modifications to artificial intelligence/machine learning (AI/ML)-based software as a medical device (SaMD) 2019.
50. King MR. The future of AI in medicine: a perspective from a Chatbot. Annals of Biomedical Engineering. 2023;51(2):291-5.
51. Briganti G, Le Moine O. Artificial intelligence in medicine: today and tomorrow. Frontiers in medicine. 2020; 7:27.
52. Hatherley JJ. Limits of trust in medical AI. Journal of medical ethics. 2020 ;46(7):478-81.
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Published
Nov 29, 2023
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How to Cite
Pranay Kurariya, Akash Yadav, & Dinesh Kumar Jain. (2023). ARTIFICIAL INTELLIGENCE IMPACT ON HEALTHCARE: ADVANCED DRUG DISCOVERY AND BEYOND. Journal of Population Therapeutics and Clinical Pharmacology, 30(18), 2898–2908. https://doi.org/10.53555/jptcp.v30i18.3041
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Author Biographies
Pranay Kurariya
IPS Academy College of Pharmacy, Knowledge Village, Rajendra Nagar, A.B. Road, Indore- 452012, India
Akash Yadav
IPS Academy College of Pharmacy, Knowledge Village, Rajendra Nagar, A.B. Road, Indore- 452012, India
Dinesh Kumar Jain
IPS Academy College of Pharmacy, Knowledge Village, Rajendra Nagar, A.B. Road, Indore- 452012, India