ArticleJournal of chemical information and modeling2023
ChatGPT in Drug Discovery: A Case Study on Anticocaine Addiction Drug Development with Chatbots.
Article in Journal of chemical information and modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review.Acta neuropsychiatrica · 2024Pooled it
- A review of recent advances in generative artificial intelligence models for biomolecular sciences.Acta pharmaceutica Sinica. B · 2026Review
- A Review of Topological Data Analysis and Topological Deep Learning in Molecular Sciences.Journal of chemical information and modeling · 2025Review
- AI-enabled language models (LMs) to large language models (LLMs) and multimodal large language models (MLLMs) in drug discovery and development.Journal of advanced research · 2025Review
- Auxiliary Discrminator Sequence Generative Adversarial Networks for Few Sample Molecule Generation.Journal of chemical information and modeling · 2025Article
- Artificial intelligence approaches for anti-addiction drug discovery.Digital discovery · 2025Review
- A review of transformer models in drug discovery and beyond.Journal of pharmaceutical analysis · 2025Review
- Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members' vision - part 2.The journal of headache and pain · 2025Review
- Bioinformatics and biomedical informatics with ChatGPT: Year one review.Quantitative biology (Beijing, China) · 2024Article
- In silico molecular targets, docking, dynamics simulation and physiologically based pharmacokinetics modeling of oritavancin.BMC pharmacology & toxicology · 2024Article
- DrugReAlign: a multisource prompt framework for drug repurposing based on large language models.BMC biology · 2024Article
- Generative artificial intelligence performs rudimentary structural biology modeling.Scientific reports · 2024Article
- Article
- CHATGPT FOR COMPUTATIONAL TOPOLOGY.Foundations of data science (Springfield, Mo.) · 2024Article
- Generative artificial intelligence performs rudimentary structural biology modeling.bioRxiv : the preprint server for biology · 2024Article
- Large language models facilitating modern molecular biology and novel drug development.Frontiers in pharmacology · 2024Review
- The Potential Applications and Challenges of ChatGPT in the Medical Field.International journal of general medicine · 2024Review
- Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.Frontiers in artificial intelligence · 2023Review
- Transformer technology in molecular science.Wiley interdisciplinary reviews. Computational molecular scienceArticle
- Performance of chatbots in queries concerning fundamental concepts in photochemistry.Photochemistry and photobiologyArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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 anticocaine 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 toward 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 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.