Examination of Physiologically‐Based Pharmacokinetic Models of Rosuvastatin

Abstract

Physiologically‐based pharmacokinetic (PBPK) modeling is increasingly used to predict drug disposition and drug–drug interactions (DDIs). However, accurately predicting the pharmacokinetics of transporter substrates and transporter‐mediated DDIs (tDDIs) is still challenging. Rosuvastatin is a commonly used substrate probe in DDI risk assessment for new molecular entities (NMEs) that are potential organic anion transporting polypeptide 1B or breast cancer resistance protein transporter inhibitors, and as such, several rosuvastatin PBPK models have been developed to try to predict the clinical DDI and support NME drug labeling. In this review, we examine five representative PBPK rosuvastatin models, discuss common challenges that the models have come across, and note remaining gaps. These shared learnings will help with the continuing efforts of rosuvastatin model validation, provide more information to understand transporter‐mediated drug disposition, and increase confidence in tDDI prediction.

Quantitative prediction of breast cancer resistant protein mediated drug‐drug interactions using physiologically‐based pharmacokinetic modeling

“…Bowman et al recently summarized the rosuvastatin PBPK models reported in the literature and reviewed the current gaps. 31 These earlier studies evaluating rosuvastatin DDIs via PBPK primarily focused on hepatic OAT1B‐based interactions with inhibitors, such as rifampicin and cyclosporine 31 , 32 ; and we are not aware of any reports describing PBPK model performance for BCRP‐based interactions extensively. The rosuvastatin DDIs assessed here primarily involve BCRP inhibition (capmatinib, darolutamide, fenebrutinib, fostamatinib, elbasvir/grazoprevir, and velpatasvir).…”

Critical Assessment of pH‐Dependent Lipophilicity Profiles of Small Molecules: Which One Should We Use and In Which Cases?

“…measurements and biological activities. [103][104][105][106][107][108][109][110][111][112][113][114] In some cases, the experimental logP N , pK a, and log P app IP were reported, but otherwise they were determined using ChemAxon. The LipE was then simulated using Equation 1 and Equation 2 and compared to their experimental values.…”

Reimagining the Framework Supporting the Static Analysis of Transporter Drug Interaction Risk; Integrated Use of Biomarkers to Generate Pan‐Transporter Inhibition Signatures

“…This is already evident for biomarkers like CPI, NMN, and PDA and no doubt that future efforts will encompass others like TAU, GCDCA-S, and IBC. 5,[78][79][80][81][82][83][84][85] Further progress will require the refinement of PBPK model compound files for each biomarker, which will necessitate the acquisition of basic information (e.g., BPR, renal FR, synthesis rate, turnover, and ft). In this regard, it is important to understand that SLC biomarker PKs and response to perpetrator drugs may be impacted by disease, organ impairment, (epi)genetics, gender, pregnancy, age, smoking, food intake, exercise, diurnal effects, and any myriad of other factors that might modulate their formation and clearance.…”

“…It goes without saying, that the development, validation, and use of PBPK models for SLC biomarkers will continue to loom large, as will their integrated use with models describing the PK profile of transporter probe drugs (e.g., furosemide, rosuvastatin, and metformin) to support IVIVE. This is already evident for biomarkers like CPI, NMN, and PDA and no doubt that future efforts will encompass others like TAU, GCDCA‐S, and IBC 5,78–85 . Further progress will require the refinement of PBPK model compound files for each biomarker, which will necessitate the acquisition of basic information (e.g., BPR, renal FR, synthesis rate, turnover, and ft).…”

“…Across the drug development community, generation of in vitro SLC inhibition data (e.g., half-maximal inhibitory concentration (IC 50 )) has become routine, as has the prediction of DDIs using simple static approaches and more dynamic physiologically-based pharmacokinetic (PBPK) models. [4][5][6][7] In large part, such efforts have been galvanized by agency (regulator)-authored guidance documents, which provide a framework supporting transporter DDI risk assessment, and the availability of preferred probe drugs to enable the study of clinical DDIs involving specific SLC transporters (Figure 1). 8,9 Consequently, there are numerous reports describing DDI studies using single drug probes (at therapeutic, subtherapeutic, or micro-doses) or multidrug cocktails.…”