Machine Learning Models for Predicting Drug Clearance from Animal Study Variables

Machine learning models for predicting drug clearance, developed by Remya Ampadi Ramachandran and published on figshare in May 2026. The dataset is 107.3 KB in size and is licensed for open use under CC-BY-4.0. It likely contains tabular data derived from pharmacokinetic animal studies and experimental design parameters.

Use Cases

• Training ML models to predict drug clearance based on pharmacokinetic animal variables mentioned in the description
• Benchmarking predictive performance of unified models against traditional allometric scaling methods
• Analyzing the influence of study design parameters on drug clearance predictions

Strengths

• Openly licensed under CC-BY-4.0, permitting broad reuse and modification
• Focus on a specific, high-impact pharmacology task: predicting drug clearance

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

figshare

Collection Method

Likely contains data synthesized or derived from pharmacokinetic animal studies, as inferred from the title.

Time Range

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Freshness

Last updated 2026-05 06 17:34:53; freshness should be verified

Geography

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