Regulatory agencies have recently issued drug-drug interaction guidelines, which require determination of plasma protein binding (PPB). To err on the conservative side, the agencies recommend that a 0.01 lower limit of fraction unbound (fu) be used for highly bound compounds (>99%), irrespective of the actual measured values. While this may avoid false negatives, the recommendation would likely result in a high rate of false positive predictions, resulting in unnecessary clinical studies and more stringent inclusion/exclusion criteria, which may add cost and time in delivery of new medicines to patients. In this perspective, we provide a review of current approaches to measure PPB, and important determinants in enabling the accuracy and precision in these measurements. The ability to measure fu is further illustrated by a cross-company data comparison of PPB for warfarin and itraconazole, demonstrating good concordance of the measured fu values. The data indicate that fu values of ≤0.01 may be determined accurately across laboratories when appropriate methods are used. These data, along with numerous other examples presented in the literature, support the use of experimentally measured fu values for drug-drug interaction predictions, rather than using the arbitrary cutoff value of 0.01 as recommended in current regulatory guidelines.

Sacubitril/valsartan (LCZ696) has been approved for the treatment of heart failure. Sacubitril is an in vitro inhibitor of organic anion-transporting polypeptides (OATPs). In clinical studies, LCZ696 increased atorvastatin Cmax by 1.7-fold and area under the plasma concentration-time curve by 1.3-fold, but had little or no effect on simvastatin or simvastatin acid exposure. A physiologically based pharmacokinetics modeling approach was applied to explore the underlying mechanisms behind the statin-specific LCZ696 drug interaction observations. The model incorporated OATP-mediated clearance (CLint,T) for simvastatin and simvastatin acid to successfully describe the pharmacokinetic profiles of either analyte in the absence or presence of LCZ696. Moreover, the model successfully described the clinically observed drug effect with atorvastatin. The simulations clarified the critical parameters responsible for the observation of a low, yet clinically relevant, drug-drug interaction DDI between sacubitril and atorvastatin and the lack of effect with simvastatin acid. Atorvastatin is administered in its active form and rapidly achieves Cmax that coincide with the low Cmax of sacubitril. In contrast, simvastatin requires a hydrolysis step to the acid form and therefore is not present at the site of interactions at sacubitril concentrations that are inhibitory. Similar models were used to evaluate the drug-drug interaction risk for additional OATP-transported statins which predicted to maximally result in a 1.5-fold exposure increase.

Quantitative bioanalysis of dried plasma spots (DPS) is not subject to the impact of hematocrit and sample non-homogeneity that are often encountered in dried blood spot (DBS) assay. In the present report, an evaluation of plasma microsampling for DPS has been conducted for the first time using ritonavir as a model compound orally administered to dogs. For this evaluation, an LC-MS/MS method was developed and validated according to the current health authorities' guidance and industry practice for the analysis of ritonavir in DPS samples. The measured ritonavir concentrations in the DPS samples prepared using SAFE-TEC devices and directly from the conventional wet plasma using standard pipette were compared with each other and against those of conventional wet plasma. Both DPS results correlated well with each other and were comparable to those of the wet plasma. Good incurred sample reanalysis results were obtained for the two sets of DPS samples and wet plasma as well. The current plasma microsampling for DPS can serve as an alternative to DPS sampling via standard pipetting and wet plasma in in vivo studies.