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ZENODO
Report . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2024
License: CC BY
Data sources: Datacite
ZENODO
Report . 2024
License: CC BY
Data sources: Datacite
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Large Language Models for Early Phase GenAI Drug Discovery

Authors: Kawchak, Kevin;

Large Language Models for Early Phase GenAI Drug Discovery

Abstract

Large Language Model (LLM) performance for drug discovery applications has improved in 2024 with the release of models such as Llama 3 70B and GPT 4o. State of the art drug synthesis utility can be achieved today when appropriate prompts are submitted with proper LLM settings using an API or Chat framework. The barrier to entry for medicinal chemists to design effective drug synthesis has been improved, while also providing expert chemists with greater chemical natural language processing than prior AI technologies. These enhanced functionalities are achieved through convenient and effective conversational innovation between AI and humans, often resembling dialogue with traditional medical experts.

Keywords

Prompt Engineering, Drug Synthesis, LLMs, Cancer

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Related to Research communities
Cancer Research