What question did this study set out to answer?

The aim is to evaluate the current capabilities and limitations of machine learning in predicting reaction properties.

Toward on-the-fly prediction of reaction energetics for high-throughput screening

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Perspective discusses challenges in predicting reaction properties using machine learning for synthesis planning, indicating future directions.

The aim is to evaluate the current capabilities and limitations of machine learning in predicting reaction properties.
Assessment of existing machine learning models for reaction prediction
Analysis of data quality and availability
Critical review of molecular representations and architectures used in the field.
Identified limitations in data quality and availability for reaction predictions
Highlighted challenges in molecular representations needed for accurate predictions
Outlined potential pathways for improving machine learning models for on-the-fly predictions.

Landsheere et al. (2026) studied this question.

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Perspective discusses challenges in predicting reaction properties using machine learning for synthesis planning, indicating future directions.