Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data

Fraction unbound in plasma (<i>F</i><sub>up</sub>) is a crucial parameter in physiologically based toxicokinetic (PBTK) models, representing the fraction of a chemical compound that is not sequestered by plasma proteins when present in the bloodstream. This is often used as a...

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Bibliographic Details
Main Author:	Gabriel Sinclair (10688582) (author)
Other Authors:	Nathaniel Charest (6837398) (author), Barbara A. Wetmore (69814) (author), Olivia Frazier (20140679) (author), Hunter A. Fisher (21760768) (author), Rogelio Tornero-Velez (1806901) (author)
Published:	2025
Subjects:	Biochemistry Inorganic Chemistry Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified transfer learning approaches physiologically based toxicokinetic future experimental characterization evaluating transfer learning added value compared specific chemical classes broad chemical library small data set </ sub >) pfas structural space </ sub knowledge space f </ >< sub chemical compound tuning process prior publication polyfluoroalkyl substances plasma proteins plasma (< physiological effects pfas ). often used human plasma formulating recommendations crucial parameter bioaccumulative potential algorithmic solution
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Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data

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