mlsanityData to 14 Oct 2026

ChatGPT in Drug Discovery: A Case Study on Anti-Cocaine Addiction Drug Development with Chatbots

arXiv 2308.06920 ↗First posted 14 Aug 2023cs.AI cs.HC q-bio.BMcited by 4

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Abstract (arXiv)

The birth of ChatGPT, a cutting-edge language model-based chatbot developed by OpenAI, ushered in a new era in AI. However, due to potential pitfalls, its role in rigorous scientific research is not clear yet. This paper vividly showcases its innovative application within the field of drug discovery. Focused specifically on developing anti-cocaine addiction drugs, the study employs GPT-4 as a virtual guide, offering strategic and methodological insights to researchers working on generative models for drug candidates. The primary objective is to generate optimal drug-like molecules with desired properties. By leveraging the capabilities of ChatGPT, the study introduces a novel approach to the drug discovery process. This symbiotic partnership between AI and researchers transforms how drug development is approached. Chatbots become facilitators, steering researchers towards innovative methodologies and productive paths for creating effective drug candidates. This research sheds light on the collaborative synergy between human expertise and AI assistance, wherein ChatGPT's cognitive abilities enhance the design and development of potential pharmaceutical solutions. This paper not only explores the integration of advanced AI in drug discovery but also reimagines the landscape by advocating for AI-powered chatbots as trailblazers in revolutionizing therapeutic innovation.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 6 of its 52 references that are in the map. First posted on arXiv 14 Aug 2023.

Builds on

6 of 52 references.

References · 6

  1. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generationcited by 516
  2. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 313
  3. 2023Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potentialcited by 39
  4. 2021Proteome-informed machine learning studies of cocaine addictioncited by 4
  5. 2022Generative artificial intelligence-enabled dynamic detection of nicotine-related circuitscited by 1
  6. 2023Revolutionizing Single Cell Analysis: The Power of Large Language Models for Cell Type Annotationcited by 1

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Cited by year

Citing papers per year: 2023: 1; 2024: 2; 2025: 1.

4 papers.

  1. 2023ChatGPT for Computational Topologycited by 3
  2. 2024From RAG to QA-RAG: Integrating Generative AI for Pharmaceutical Regulatory Compliance Processcited by 0
  3. 2024DropMicroFluidAgents (DMFAs): Autonomous Droplet Microfluidic Research Framework Through Large Language Model Agentscited by 0
  4. 2025Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule Generationcited by 0