جایگاه هوش مصنوعی در علوم دارویی

نوع مقاله : Review Article

نویسندگان

1 دکترای بیوتکنولوژی دارویی، گروه بیوتکنولوژی، دانشکده‌ی داروسازی، دانشگاه علوم پزشکی تهران، تهران، ایران

2 کارشناس ارشد مکاترونیک، دانشکده‌ی مکانیک، دانشگاه سمنان، سمنان، ایران

3 دانشیار بیوتکنولوژی دارویی، گروه بیوتکنولوژی، دانشکده‌ی داروسازی، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران

10.48305/jims.v43.i813.0451

چکیده

مقاله مروری




مقدمه: کشف و توسعه‌ی دارو جنبه‌های مختلف سلامت انسان را تحت تأثیر قرار می‌دهد و به طور چشمگیری بر بازار دارو تأثیر می‌گذارد. با این حال، سرمایه‌گذاری در یک داروی جدید اغلب به دلیل فرایند طولانی و پیچیده تحقیق و توسعه‌ی دارو یک چالش پیچیده و سخت است.
روش‌ها: با پیشرفت تکنولوژی تجربی و سخت‌افزار کامپیوتر، هوش مصنوعی اخیراً به عنوان ابزاری پیشرو در تجزیه و تحلیل داده‌های فراوان و با ابعاد بالا ظاهر شده است. رشد انفجاری در اندازه داده‌های زیستی مزایایی را در به کارگیری هوش مصنوعی در تمام مراحل تحقیق و توسعه‌ی دارویی فراهم می‌کند.
یافته‌ها: مشابه مدل یادگیری انسان، یادگیری ماشین و یادگیری عمیق می‌توانند به تدریج ویژگی‌های مختلف داده‌ها را تشخیص دهند و پارامترهای مدل خود را از طریق تکرارهای مداوم به روز کنند تا زمانی که یک مدل معتبر تشکیل شود.
نتیجه‌گیری: این مقاله با مروری کوتاه بر مدل‌های رایج هوش مصنوعی در زمینه‌ی کشف دارو آغاز می‌شود. سپس، کاربردهای خاص آنها را در مراحل مختلف تحقیق و توسعه دارویی، مانند کشف هدف، کشف و طراحی دارو، تحقیقات پیش بالینی و تأثیرات در بازار دارویی، به طور خلاصه مورد بحث قرار می‌دهد. در نهایت، محدودیت‌های عمده‌ی هوش مصنوعی در تحقیق و توسعه‌ی دارویی مورد بحث قرار گرفته است.

تازه های تحقیق

مرضیه ثنائی: Google Scholar   

حمید باخرد: Google Scholar 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The Role of Artificial Intelligence in Pharmaceutical Sciences

نویسندگان [English]

  • Marzieh Sanaei 1
  • Mohammad Ebrahim Delzendeh Nedamani 2
  • Hamid Bakherad 3
1 PhD. Pharmaceutical Biotechnology, School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
2 MSc of Mechatronics, School of Mechanics, Semnan University, Semnan, Iran
3 Associate Professor of Biotechnology, School of Pharmacy, Isfahan University of Medical Sciences, Isfahan, Iran
چکیده [English]

Background: Drug discovery and development affects human health and the drug market. However, investing in a new drug is often a complex and difficult challenge due to the long and complex drug research and development process.
Methods: With the advancement of experimental technology and computer hardware, artificial intelligence has recently emerged as a tool for analyzing abundant and high-dimensional data. Explosive growth in the size of biological data provides advantages in applying artificial intelligence in all stages of pharmaceutical research and development.
Findings: Similar to human learning models, machine learning and deep learning can gradually recognize different features of data, and update their model parameters through continuous iterations until a valid model is formed.
Conclusion: This article begins with a brief overview of common AI models in drug discovery. Then, it briefly discusses their specific applications in different drug research and development phases, such as target discovery, drug discovery and design, preclinical research, and effects on the drug market. Finally, major limitations of artificial intelligence in pharmaceutical research and development are discussed.

کلیدواژه‌ها [English]

  • Drug design
  • Artificial intelligence
  • Deep learning
  • Machine learning

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مجله دانشکده پزشکی اصفهان
دوره 43، شماره 813
هفته 1، تیر
خرداد و تیر 1404
صفحه 451-462

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سابقه مقاله

  • تاریخ دریافت: 23 آبان 1403
  • تاریخ پذیرش: 21 خرداد 1404

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