Evaluation of drug–drug interaction potential for pemigatinib using physiologically based pharmacokinetic modeling

Precision Oncology Targeting FGFRs: A Systematic Review on Pre-clinical Activity and Clinical Outcomes of Pemigatinib

Fibroblast Growth Factor Receptors (FGFRs) are emerging as key factors involved in tumorigenesis, tumor microenvironment remodeling and acquired resistance to targeted therapies. Pemigatinib is a Tyrosine-Kinase Inhibitor that selectively targets aberrant FGFR1, FGFR2 and FGFR3. Pemigatinib is now approved for advanced-stage cholangiocarcinoma (CCA) but data suggests that other tumor histotypes exhibit FGFR alterations, thus hypothesizing its potential efficacy in other cancer settings. The present systematic review, based on PRISMA guidelines, aims to synthetize and critically interpret the results of all available preclinical and clinical evidence regarding Pemigatinib use in cancer. In April 2024, an extensive search was performed in PubMed, MEDLINE, and Scopus databases using the keyword "Pemigatinib". Twenty-seven studies finally met all inclusion criteria. The promising results emerging from Pemigatinib preclinical and clinical studies pave the way for Pemigatinib extension to multiple solid cancer settings.

Pemigatinib: A Review in Advanced Cholangiocarcinoma

Pemigatinib (Pemazyre®), a selective, potent, reversible, oral inhibitor of fibroblast growth factor receptor (FGFR) 1-3, has received conditional (in the EU) or accelerated (in the USA) approval for the treatment of adults with previously treated, unresectable locally-advanced or metastatic cholangiocarcinoma (CCA) with an FGFR2 gene fusion or rearrangement. Over the course of a single-arm, phase 2 study (FIGHT-202), just over a third of patients with pretreated, advanced CCA [almost exclusively intrahepatic CCA (iCCA)] harbouring an FGFR2 fusion or rearrangement who received pemigatinib once daily (2 weeks on, 1 week off) had an objective response; nearly half had stable disease. Median progression-free survival and overall survival at the time of the final analysis were 7.0 months and 17.5 months, respectively. Pemigatinib was generally well tolerated and had a manageable safety profile. The most common treatment-related adverse event, hyperphosphataemia, was exclusively grade 1-2 in severity and, similarly, observed ocular and nail toxicities were rarely grade ≥ 3 in severity. Pending confirmation of its clinical benefits in an ongoing cisplatin plus gemcitabine-controlled, phase 3 study (FIGHT-302), pemigatinib provides a valuable targeted therapy for pretreated patients with advanced (i)CCA harbouring a FGFR2 fusion or rearrangement.

A New Version of the Tissue Composition-Based Model for Improving the Mechanism-Based Prediction of Volume of Distribution at Steady-State for Neutral Drugs

In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vdss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vdss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vdss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vdss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. And more than 95% of the predictions were within threefold error and patient interindividual differences can be predicted with the TCM-New, greatly exceeding the accuracy of the published models. Overall, the new TCM incorporating BPR significantly improved the Vdss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.

Population pharmacokinetic and exposure-response analyses of pemigatinib in patients with advanced solid tumors including cholangiocarcinoma

Pemigatinib is a selective, potent, oral inhibitor of fibroblast growth factor receptor (FGFR)1-3 with efficacy in patients with previously treated, advanced/metastatic cholangiocarcinoma (CCA) with FGFR2 alterations. A previously developed population pharmacokinetic (PK) model of pemigatinib was refined using an updated dataset with 467 participants from seven clinical studies, including patients with CCA. Updated PK model parameters were used to evaluate the association between pemigatinib exposure and efficacy and safety. Pemigatinib PK was adequately described by a two-compartment model with linear elimination and sequential zero- and first-order absorption. The final model successfully minimized, had a successful covariance step, and showed unbiased goodness-of-fit. Estimated first-order absorption rate constant and apparent clearance were 3.7/h and 10.7 L/h, respectively. Sex, baseline body weight, and concomitant use of phosphate binders, proton pump inhibitors, or histamine-2 antagonists significantly impacted PK parameters; however, the impact of covariates on PK exposure was not clinically significant. Steady-state pemigatinib exposure and mean change from baseline in serum phosphate concentration were associated with objective response rate in a bell-shaped relationship and were significantly associated with increased hyperphosphatemia. Pemigatinib exposure was associated with treatment-emergent adverse events, such as decreased appetite, nausea, and stomatitis, although the relationships were shallow. Overall, analyses indicate that 13.5 mg pemigatinib once daily in 21-day cycles (2 weeks on, 1 week off) offers a favorable benefit-risk profile in patients with advanced/metastatic or surgically unresectable CCA and is the optimal dose for clinical development.

Evaluation of the Mass Balance and Metabolic Profile of Futibatinib in Healthy Participants

Futibatinib, a selective, irreversible fibroblast growth factor receptor 1-4 inhibitor, was recently approved for FGFR2 rearrangement-positive cholangiocarcinoma. This Phase I study evaluated the mass balance and metabolic profile of 14 C-futibatinib single oral 20-mg dose in healthy participants (n = 6). Futibatinib was rapidly absorbed; median time to peak drug concentration was 1.0 hours. The mean elimination half-life in plasma was 2.3 hours for futibatinib, and 11.9 hours for total radioactivity. Mean recovery of total radioactivity was 70% of the dose, with 64% recovered in feces and 6% in urine. The major excretion route was fecal; negligible levels were excreted as parent futibatinib. Futibatinib was the most abundant plasma component, comprising 59% of circulating radioactivity (CRA). The most abundant metabolites were cysteinylglycine-conjugated futibatinib in plasma (13% CRA) and reduction of desmethyl futibatinib in feces (17% of dose). In human hepatocytes, 14 C-futibatinib metabolites included glucuronide and sulfate of desmethyl futibatinib, whose formation was inhibited by 1-aminobenzotriazole (a pan-cytochrome P450 inhibitor), and glutathione- and cysteine-conjugated futibatinib. These data indicate the primary metabolic pathways of futibatinib are O-desmethylation and glutathione conjugation, with cytochrome P450 enzyme-mediated desmethylation as the main oxidation pathway. 14 C-futibatinib was well tolerated in this Phase 1 study.

Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward

The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.