The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies

Роль искусственного интеллекта в разработке лекарственных средств: проблемы, возможности и стратегии
Rebeca García‐Fandiño, Ángel Piñeiro, Alexandre Blanco-González, Alfonso Cabezón, Alejandro Seco-González, Daniel Conde-Torres, Paula Antelo-Riveiro
2023-06-18

AI in drug discoverydata augmentationexperimental integrationexplainable AIpharmaceutical research
Artificial intelligence (AI) has the potential to revolutionize the drug discovery process, offering improved efficiency, accuracy, and speed. However, the successful application of AI is dependent on the availability of high-quality data, the addressing of ethical concerns, and the recognition of the limitations of AI-based approaches. In this article, the benefits, challenges, and drawbacks of AI in this field are reviewed, and possible strategies and approaches for overcoming the present obstacles are proposed. The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods, as well as the potential advantages of AI in pharmaceutical research, are also discussed. Overall, this review highlights the potential of AI in drug discovery and provides insights into the challenges and opportunities for realizing its potential in this field. Note from the human authors: This article was created to test the ability of ChatGPT, a chatbot based on the GPT-3.5 language model, in terms of assisting human authors in writing review articles. The text generated by the AI following our instructions (see Supporting Information) was used as a starting point, and its ability to automatically generate content was evaluated. After conducting a thorough review, the human authors practically rewrote the manuscript, striving to maintain a balance between the original proposal and the scientific criteria. The advantages and limitations of using AI for this purpose are discussed in the last section.
1
AI could improve the efficiency, accuracy, and speed of drug discovery, but its successful application depends on high-quality data and addressing ethical concerns.
2
AI offers potential advantages across pharmaceutical research, but realizing this potential requires combining computational approaches with scientific and experimental validation.
3
Data augmentation, explainable AI, and integration with traditional experimental methods are proposed as strategies to overcome current obstacles.
4
The article itself evaluates ChatGPT-assisted review writing, reporting that human authors substantially rewrote the generated manuscript to meet scientific standards.
5
The review identifies limitations and drawbacks of AI-based drug discovery approaches that must be recognized when deploying these methods.

AI applications in the drug discovery process

The benefits, challenges, limitations, and implementation strategies of AI for improving drug discovery efficiency, accuracy, and speed

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Publication Date
2023-06-18
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Authors
Rebeca García‐Fandiño
Ángel Piñeiro
Alexandre Blanco-González
Alfonso Cabezón
Alejandro Seco-González
Daniel Conde-Torres
Paula Antelo-Riveiro
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