Breaking the 1% unbound threshold: an IQ consortium whitepaper on the evaluation of plasma protein binding of highly...

The reliable measurement of plasma protein binding (PPB) is crucial for understanding drug pharmacokinetics and predicting drug-drug interactions (DDIs). Historically, regulatory guidelines had imposed a cutoff of 1% for the unbound fraction (f_u) of highly bound drugs, leading to concerns about overestimating DDI risks and triggering unnecessary clinical DDI trials. In this study, an IQ working group comprising 11 member companies evaluated the interlab accuracy and precision of the PPB determination of 20 compounds highly bound to plasma proteins with f_u values <1%. Utilizing equilibrium dialysis and 2 alternative methodologies-flux dialysis and plasma P450 IC₅₀ shift method-this collaborative effort aimed to rigorously assess the limits and reproducibility of f_u measurement. Results demonstrated that f_u values as low as ∼0.003% can potentially under optimized conditions be reliably quantified, challenging the necessity of a fixed cutoff. The findings suggest that the bioanalytical sensitivity, qualification of the PPB assays in the appropriate unbound fraction range, and compound properties dictate the lower limit for f_u, rather than an arbitrary threshold. In addition to advancing scientific knowledge of PPB, this work provides robust scientific justification to revise f_u criteria during the elaboration of international harmonized guidelines, allowing the use of f_u values <1% in DDI risk assessments when appropriate qualified methods are being used. Ultimately, increased confidence in low f_u values supports more efficient development of safe and efficacious drugs by improving understanding of drug pharmacological and toxicological profiles and by reducing the number of false positive DDI studies. SIGNIFICANCE STATEMENT: This study demonstrates that plasma protein binding of drugs with <1% unbound fraction can be accurately and reliably measured using qualified methodologies. By challenging the traditional 1% cutoff, our findings ultimately allow for more accurate predictions of drug pharmacological and toxicological profiles (eg, drug-drug interactions and safety margins).