Development, Verification, and Prediction of Osimertinib Drug-Drug Interactions Using PBPK Modeling Approach to Inform Drug Label

Integrated PBPK-EO modeling of osimertinib to predict plasma concentrations and intracranial EGFR engagement in patients with brain metastases

The purpose of this study was to develop and validate a physiologically based pharmacokinetic (PBPK) model combined with an EGFR occupancy (EO) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and the intracranial time-course of EGFR (T790M and L858R mutants) engagement in patient populations. The PBPK model was also used to investigate the key factors affecting OSI pharmacokinetics (PK) and intracranial EGFR engagement, analyze resistance to the target mutation C797S, and determine optimal dosing regimens when used alone and in drug-drug interactions (DDIs). A population PBPK-EO model of OSI was developed using physicochemical, biochemical, binding kinetic, and physiological properties, and then validated using nine clinical PK studies, observed EO study, and two clinical DDI studies. The PBPK-EO model demonstrated good consistency with observed data, with most prediction-to-observation ratios falling within the range of 0.7 to 1.3 for plasma AUC, Cmax, Ctrough and intracranial free concentration. The simulated time-course of C797S occupancy by the PBPK model was much lower than T790M and L858R occupancy, providing an explanation for OSI on-target resistance to the C797S mutation. The PBPK model identified ABCB1 CLint,u, albumin level, and EGFR expression as key factors affecting plasma Ctrough and intracranial EO for OSI. Additionally, PBPK-EO simulations indicated that the optimal dosing regimen for OSI in patients with brain metastases is either 80 mg once daily (OD) or 160 mg OD, or 40 mg or 80 mg twice daily (BID). When used concomitantly with CYP enzyme perpetrators, the PBPK-EO model suggested appropriate dosing regimens of 80 mg OD with fluvoxamine (FLUV) itraconazole (ITR) or fluvoxamine (FLUC) for co-administration and an increase to 160 mg OD with rifampicin (RIF) or efavirenz (EFA). In conclusion, the PBPK-EO model has been shown to be capable of simulating the pharmacokinetic concentration-time profiles and the time-course of EGFR engagement for OSI, as well as determining the optimum dosing in various clinical situations.

Exploring inter-ethnic and inter-patient variability and optimal dosing of osimertinib: a physiologically based pharmacokinetic modeling approach

Purpose: This study aimed to develop and validate a physiologically based pharmacokinetic (PBPK) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and pulmonary EGFRm+ (T790M and L858R mutants) inhibition in Caucasian, Japanese, and Chinese populations. The PBPK model was also utilized to investigate inter-ethnic and inter-patient differences in OSI pharmacokinetics (PK) and determine optimal dosing regimens. Methods: Population PBPK models of OSI for healthy and disease populations were developed using physicochemical and biochemical properties of OSI and physiological parameters of different groups. And then the PBPK models were validated using the multiple clinical PK and drug-drug interaction (DDI) study data. Results: The model demonstrated good consistency with the observed data, with most of prediction-to-observation ratios of 0.8-1.25 for AUC, Cmax, and Ctrough. The PBPK model revealed that plasma exposure of OSI was approximately 2-fold higher in patients compared to healthy individuals, and higher exposure observed in Caucasians compared to other ethnic groups. This was primarily attributed to a lower CL/F of OSI in patients and Caucasian. The PBPK model displayed that key factors influencing PK and EGFRm+ inhibition differences included genetic polymorphism of CYP3A4, CYP1A2 expression, plasma free concentration (fup), albumin level, and auto-inhibition/induction on CYP3A4. Inter-patient PK variability was most influenced by CYP3A4 variants, fup, and albumin level. The PBPK simulations indicated that the optimal dosing regimen for patients across the three populations of European, Japanese, and Chinese ancestry was OSI 80 mg once daily (OD) to achieve the desired range of plasma Ctrough (328-677 nmol/L), as well as 80 mg and 160 mg OD for desirable pulmonary EGFRm+ inhibition (>80%). Conclusion: In conclusion, this study's PBPK simulations highlighted potential ethnic and inter-patient variability in OSI PK and EGFRm+ inhibition between Caucasian, Japanese, and Chinese populations, while also providing insights into optimal dosing regimens of OSI.

Physiologically Based Pharmacokinetic Modeling to Simulate CYP3A4-Mediated Drug-Drug Interactions for Pyrotinib

INTRODUCTION

Pyrotinib is a newly developed tyrosine kinase inhibitor whose in vivo clearance relies heavily on cytochrome P450 3A4 (CYP3A4) activity. Clinical trials are ongoing to explore the effects of coadministration with CYP3A4 perpetrators on pyrotinib exposure. The present study aims to utilize physiologically based pharmacokinetic (PBPK) modeling to predict CYP3A4-based drug interactions of pyrotinib.

METHODS

Pyrotinib PBPK model was developed in the PK-Sim® multicompartmental physiology structure. Physiochemical parameters were obtained from the literature, and clearance-related parameters were optimized by fitting clinical single-dose pharmacokinetic data. Pharmacokinetic parameters from the model output were compared with the observed data to validate the model predictive performance. Using validated CYP3A4 perpetrator models, we conducted PBPK simulations for drug interactions in a virtual population to explore the impacts of comedication with these perpetrators.

RESULTS

The PBPK model accurately describes pyrotinib single- and multi-dose pharmacokinetics. The model also predicts dramatic exposure change of pyrotinib in the presence of itraconazole and rifampicin, though the impact of rifampicin is somewhat underestimated. According to model predictions, coadministration with typical potent or moderate CYP3A4 perpetrators increases pyrotinib concentration by over sixfold, extinguishing the possibility of dose adjustment for pyrotinib. A weak CYP3A4 inhibitor has minimal influence on pyrotinib pharmacokinetics.

CONCLUSION

PBPK modeling provides valuable information to avoid irrational medication when receiving pyrotinib chemotherapy.

Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs

INTRODUCTION

Physiologically based pharmacokinetics (PBPK) models are increasingly used in the drug research and development, especially in anti-cancer drugs. Between 2001 and 2020, a total of 89 small-molecule targeted antitumor drugs were approved in China and the United States, some of which already included PBPK modeling in their application or approval packages. This article intended to review the prevalence and application of PBPK model in these drugs.

METHOD

Article search was performed in the PubMed to collect English research articles on small-molecule targeted anti-cancer drugs using PBPK modeling. The selected articles were classified into nine categorizes according to the application areas and further analyzed.

RESULT

From 2001 to 2020, more than 60% of small-molecule targeted anti-cancer drugs (54/89) were studied using PBPK model with a wide range of application. Ninety research articles were included, of which 48 involved enzyme-mediated drug-drug interaction (DDI). Of these retrieved articles, Simcyp, GastroPlus, and PK-Sim were the most widely model building platforms, which account for 63.8%, 15.2%, and 8.6%, respectively.

CONCLUSION

PBPK modeling is commonly and widely used to research small-molecule targeted anti-cancer drugs.

3D printing combined with biopredictive dissolution and PBPK/PD modeling optimization and personalization of pharmacotherapy: Are we there yet?

Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.

A Prospective Cohort Study Assessing the Relationship between Plasma Levels of Osimertinib and Treatment Efficacy and Safety

Osimertinib is a standard treatment for patients with EGFR-mutated non-small cell lung carcinoma (NSCLC). We evaluated the relationship between plasma osimertinib concentrations and treatment outcome in patients with NSCLC for this cohort study. The plasma levels of osimertinib and its metabolite AZ5104 were measured a week after the start of treatment (P1). The primary endpoint was to evaluate the correlation between plasma concentration and adverse events (AEs). The correlation with treatment efficacy was one of the secondary endpoints. In patients with CNS metastases, the concentration in the cerebrospinal fluid was also measured. Forty-one patients were enrolled. The frequency of AEs was highest for rash, followed by anorexia and thrombocytopenia. Thirty-eight cases provided measurements for P1. The median plasma concentration of osimertinib was 227 ng/mL, and that of AZ5104 was 16.5 ng/mL. The mean CNS penetration rate of two cases was 3.8%. The P1 in the group with anorexia was significantly higher than that in the group without anorexia (385.0 ng/mL vs. 231.5 ng/mL, p = 0.009). Divided into quartiles by P1 trough level, Q2 + Q3 (164-338 ng/mL) had longer PFS, while Q1 and Q4 had shorter PFS. An appropriate plasma level of osimertinib may avoid some adverse events and induce long PFS. Further large-scale trials are warranted.

Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

Understanding the Risk of Drug Interactions Between Ritonavir-Containing COVID-19 Therapies and Small-Molecule Kinase Inhibitors in Patients With Cancer

PURPOSE

The introduction of COVID-19 therapies containing ritonavir has markedly expanded the scope of use for this medicine. As a strong cytochrome P450 3A4 inhibitor, the use of ritonavir is associated with a high drug interaction risk. There are currently no data to inform clinician regarding the likely magnitude and duration of interaction between ritonavir-containing COVID-19 therapies and small-molecule kinase inhibitors (KIs) in patients with cancer.

METHODS

Physiologically based pharmacokinetic modeling was used to conduct virtual clinical trials with a parallel group study design in the presence and absence of ritonavir (100 mg twice daily for 5 days). The magnitude and time course of changes in KI exposure when coadministered with ritonavir was evaluated as the primary outcome.

RESULTS

Dosing of ritonavir resulted in a > 2-fold increase in steady-state area under the plasma concentration-time curve and maximal concentration for six of the 10 KIs. When the KI was coadministered with ritonavir, dose reductions to between 10% and 75% of the original dose were required to achieve an area under the plasma concentration-time curve within 1.25-fold of the value in the absence of ritonavir.

CONCLUSION

To our knowledge, this study provides the first data to assist clinicians' understanding of the drug interaction risk associated with administering ritonavir-containing COVID-19 therapies to patients with cancer who are currently being treated with KIs. These data may support clinicians to make more informed dosing decisions for patients with cancer undergoing treatment with KIs who require treatment with ritonavir-containing COVID-19 antiviral therapies.

SeDeM tool-driven full factorial design for osmotic drug delivery of tramadol HCl: Formulation development, physicochemical evaluation, and in-silico PBPK modeling for predictive pharmacokinetic evaluation using GastroPlus™

The study is based on using SeDeM expert system in developing controlled-release tramadol HCl osmotic tablets and its in-silico physiologically based pharmacokinetic (PBPK) modeling for in-vivo pharmacokinetic evaluation. A Quality by Design (QbD) based approach in developing SeDEM-driven full factorial osmotic drug delivery was applied. A 2⁴ Full-factorial design was used to make the trial formulations of tramadol HCl osmotic tablets using NaCl as osmogen, Methocel K4M as rate controlling polymer, and avicel pH 101 as diluent. The preformulation characteristics of formulations (F1-F16) were determined by applying SeDeM Expert Tool. The formulation was optimized followed by in-vivo predictive pharmacokinetic assessment using PBPK “ACAT” model of GastroPlus™. The FTIR results showed no interaction among the ingredients. The index of good compressibility (ICG) values of all trial formulation blends were ≥5, suggesting direct compression is the best-suited method. Formulation F3 and F4 were optimized based on drug release at 2, 10, and 16 h with a zero-order kinetic release (r² = 0.992 and 0.994). The SEM images confirmed micropores formation on the surface of the osmotic tablet after complete drug release. F3 and F4 were also stable (shelf life 29.41 and 23.46 months). The in vivo simulation of the pharmacokinetics of the PBPK in-silico model revealed excellent relative bioavailability of F3 and F4 with reference to tramadol HCl 50 mg IR formulations. The SeDeM expert tool was best utilized to evaluate the compression characteristics of selected formulation excipients and their blends for direct compression method in designing once-daily osmotically controlled-release tramadol HCl tablets. The in-silico GastroPlus™ PBPK modeling provided a thorough pharmacokinetic assessment of the optimized formulation as an alternative to tramadol HCl in vivo studies.

Effects of CYP3A4/5 and ABC transporter polymorphisms on osimertinib plasma concentrations in Japanese patients with non-small cell lung cancer

The effects of polymorphisms in CYP3A4 (20230G > A), CYP3A5 (6986A > G), ABCB1 (1236C > T, 2677G > T/A, 3435C > T), ABCG2 (421C > A), and ABCC2 (-24C > T) on the area under the concentration-time curve (AUC) of osimertinib in 23 patients with non-small cell lung cancer were investigated. Blood sampling was performed just prior to and at 1, 2, 4, 6, 8, 12, and 24 h after osimertinib administration at the steady-state on day 15 after beginning therapy. The osimertinib AUC_0-24 was significantly correlated with age (P = 0.038), serum albumin (P = 0.002), and serum creatinine (P = 0.012). Additionally, there were significant differences in the AUC_0-24 of osimertinib among the groups administered vonoprazan, histamine 2-receptor antagonists or esomeprazole, and no acid suppressants (P = 0.021). By contrast, there were no significant differences in the AUC_0-24 of osimertinib between genotypes of CYP3A4/5 or ABC transporters. Furthermore, there were no significant differences in the AUC_0-24 of osimertinib between patients with diarrhea, skin rash, or hepatotoxicity and those without these conditions. In multivariate analysis, only serum albumin value was an independent factor predicting the AUC_0-24 of osimertinib. Analysis of CYP3A4/5 and ABC transporter polymorphisms before osimertinib therapy may not predict the efficacy or side effects of osimertinib. The lower serum albumin values were associated with an increase in the AUC_0-24 of osimertinib; however, further studies are needed to assess the factors contributing to the interindividual variability of osimertinib pharmacokinetics.

[Application of MIDD in Clinical Research of Antitumor Drugs]

The antitumor drug has become one of the focused areas in new drug research and development. Their clinical research generally consumes a long period of time, with high cost and high risk. Model-informed drug development (MIDD) integrates and quantitatively analyzes physiological, pharmacological, and disease progression information through modeling and simulation, which can reduce the cost of drug development and improve the efficiency of clinical research. In this essay, Osimertinib and Pembrolizumab are given as examples to illustrate the specific application of MIDD in different phases of clinical research, aiming to provide references for the application of MIDD to guide the clinical research of antitumor drugs.
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Quantitative Prediction of Drug Interactions Caused by Cytochrome P450 2B6 Inhibition or Induction

BACKGROUND

Numerous drugs have the potential to be affected by cytochrome P450 (CYP) 2B6-mediated drug-drug interactions (DDIs).

OBJECTIVES

In this work, we extend a static approach to the prediction of the extent of pharmacokinetics DDIs between substrates and inhibitors or inducers of CYP2B6.

METHODS

This approach is based on the calculation of two parameters (the contribution ratio [CR], representing the fraction of dose of the substrate metabolized via this pathway and the inhibitory or inducing potency of the perpetrator [IR or IC, respectively]) calculated from the area under the concentration-time curve (AUC) ratios obtained in in-vivo DDI studies.

RESULTS

Forty-eight studies involving 5 substrates, 11 inhibitors and 18 inducers of CYP2B6 (overall 15 inhibition and 33 induction studies) were divided into test and validation sets and considered for estimation of the parameters. The proposed approach demonstrated a fair accuracy for predicting the extent of DDI related to CYP2B6 inhibition and induction, all predictions related to the validation test (N = 18) being 50-200% of the observed ratios.

CONCLUSIONS

This methodology can be used for proposing initial dose adaptations to be adopted, for example in clinical use or for designing DDI studies involving this enzyme.

Application of physiologically based pharmacokinetic modelling for the prediction of drug-drug interactions involving anlotinib as a perpetrator of cytochrome P450 enzymes

Anlotinib is a small molecule of novel tyrosine kinase inhibitor initially approved to treat non-small cell lung cancer in China. Drug-drug interaction (DDI) is an extrinsic factor important for the appropriate use of anlotinib in clinical practice. In vitro experiments demonstrated that anlotinib is a substrate of cytochrome P450 (CYP) enzymes and moderate inhibitor of several common ones; however, no clinical DDI studies have been performed to investigate inhibitory effects of anlotinib on these CYP enzymes. Thus, its drug label recommends avoiding co-administration with substrates of these enzymes, which have narrow therapeutic windows. In this study, we performed a CYP450 inhibition study, followed by gathering in vitro and clinical pharmacokinetic data to build the first physiologically based pharmacokinetic (PBPK) model of anlotinib. The verified model was subsequently used to predict the DDI mediated by anlotinib. As a result, the marginal plasma exposure changes of typical CYP3A and CYP2C9 substrates were less than the bioequivalence threshold, indicating that anlotinib has a very low potential of causing clinically meaningful DDI through the inhibition of several major CYP enzymes. According to the FDA's latest guideline on DDI, the established model with the simulation results may support the revision of anlotinib labelling without further clinical studies, lifting unnecessary restrictions on anlotinib regimens.

The Influence of CYP3A4 Genetic Polymorphism and Proton Pump Inhibitors on Osimertinib Metabolism

The aim of this study was to 1) investigate the effects of 27 CYP3A4 variants on the metabolism of osimertinib and 2) study the interactions between osimertinib and others as well as the underlying mechanism. A recombinant human CYP3A4 enzymatic incubation system was developed and employed to determine the kinetic profile of CYP3A4 variants. Ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) was applied to detect the concentration of the main metabolite, AZ5104. The results demonstrated that the relative clearance rates of CYP3A4.19, 10, 18, 5, 16, 14, 11, 2, 13, 12, 7, 8, and 17 in catalyzing osimertinib were significantly reduced to a minimum of 25.68% compared to CYP3A4.1, while those of CYP3A4.29, 32, 33, 28, 15, 34, and 3 were obviously enhanced, ranging from 114.14% to 284.52%. The activities of the remaining variants were almost equal to those of CYP3A4.1. In addition, 114 drugs were screened to determine the potential interaction with osimertinib based on the rat liver microsome (RLM) reaction system. Sixteen of them inhibited the production of AZ5104 to 20% or less, especially proton pump inhibitors, among which the IC₅₀ of rabeprazole was 6.49 ± 1.17 μM in RLM and 20.39 ± 2.32 μM in human liver microsome (HLM), with both following competitive and non-competitive mixed mechanism. In an in vivo study, Sprague–Dawley (SD) rats were randomly divided into groups, with six animals per group, receiving osimertinib with or without rabeprazole, omeprazole, and lansoprazole. We found that the AUC_(0–t), AUC_(0–∞), and C_max of osimertinib decreased significantly after co-administration with rabeprazole orally, but they increased remarkably when osimertinib was administered through intraperitoneal injection. Taken together, our data demonstrate that the genetic polymorphism and proton pump inhibitors remarkably influence the disposition of osimertinib, thereby providing basic data for the precise application of osimertinib.

Antifungal Drugs TDM: Trends and Update

PURPOSE

The increasing burden of invasive fungal infections results in growing challenges to antifungal (AF) therapeutic drug monitoring (TDM). This review aims to provide an overview of recent advances in AF TDM.

METHODS

We conducted a PubMed search for articles during 2016-2020 using "TDM" or "pharmacokinetics" or "drug-drug-interaction" with "antifungal," consolidated for each AF. Selection was limited to English language articles with human data on drug exposure.

RESULTS

More than 1000 articles matched the search terms. We selected 566 publications. The latest findings tend to confirm previous observations in real-life clinical settings. The pharmacokinetic variability related to special populations is not specific but must be considered. AF benefit-to-risk ratio, drug-drug interaction (DDI) profiles, and minimal inhibitory concentrations for pathogens must be known to manage at-risk situations and patients. Itraconazole has replaced ketoconazole in healthy volunteers DDI studies. Physiologically based pharmacokinetic modeling is widely used to assess metabolic azole DDI. AF prophylactic use was studied more for Aspergillus spp. and Mucorales in oncohematology and solid organ transplantation than for Candida (already studied). Emergence of central nervous system infection and severe infections in immunocompetent individuals both merit special attention. TDM is more challenging for azoles than amphotericin B and echinocandins. Fewer TDM requirements exist for fluconazole and isavuconazole (ISZ); however, ISZ is frequently used in clinical situations in which TDM is recommended. Voriconazole remains the most challenging of the AF, with toxicity limiting high-dose treatments. Moreover, alternative treatments (posaconazole tablets, ISZ) are now available.

CONCLUSIONS

TDM seems to be crucial for curative and/or long-term maintenance treatment in highly variable patients. TDM poses fewer cost issues than the drugs themselves or subsequent treatment issues. The integration of clinical pharmacology into multidisciplinary management is now increasingly seen as a part of patient care.

PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease

The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18–60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%–60%) and the plasma concentrations increased (170%–400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.

Pulmonary delivery of osimertinib liposomes for non-small cell lung cancer treatment: formulation development and in vitro evaluation

Osimertinib (OB) is a third-generation irreversible tyrosine kinase inhibitor targeting the epidermal growth factor receptor (EGFR), overexpressed in non-small cell lung cancer. Systemic administration of drug often results in poor drug levels at the primary tumor in the lungs and is associated with systemic side effects. In this study, we developed inhalable OB liposomes that can locally accumulate at the tumor site thereby limiting systemic toxicity. OB was loaded into liposomes via active and passive loading methods. The OB active liposomes achieved a higher encapsulation (78%) compared to passive liposomes (25%). The liposomes (passive and active) exhibited excellent aerosolization performance with an aerodynamic diameter of 4 µm and fine particle fraction of 82%. In H1975 cells, OB active and passive liposomes reduced IC₅₀ by 2.2 and 1.2-fold, respectively, compared to free drug. As the OB active liposomes demonstrated higher cytotoxicity compared to OB passive liposomes, they were further investigated for in vitro anti-cancer activity. The OB active liposomes inhibited tumor cell migration and colonization as determined by the scratch assay and clonogenic assay, respectively. Furthermore, the 3D spheroid studies showed that the liposomes were successful in inhibiting tumor growth. These results highlight the potential of OB liposomes to suppress lung cancer. Owing to these attributes, the inhalable OB liposomes can potentially promote better therapeutic outcomes with limited systemic toxicity.

A Review of CYP3A Drug-Drug Interaction Studies: Practical Guidelines for Patients Using Targeted Oral Anticancer Drugs

Many oral anticancer drugs are metabolized by CYP3A. Clinical drug-drug interaction (DDI) studies often only examine the effect of strong CYP3A inhibitors and inducers. The effect of moderate or weak inhibitors or inducers can be examined using physiologically based pharmacokinetic simulations, but data from these simulations are not always available early after approval of a drug. In this review we provide recommendations for clinical practice on how to deal with DDIs of oral anticancer drugs if only data from strong CYP3A inhibitors or inducers is available. These recommendations were based on reviewed data of oral anticancer drugs primarily metabolized by CYP3A and approved for the treatment of solid tumors from January 1st, 2013 to December 31st, 2015. In addition, three drugs that were registered before the new EMA guideline was issued (i.e., everolimus, imatinib, and sunitinib), were reviewed. DDIs are often complex, but if no data is available from moderate CYP3A inhibitors/inducers, a change in exposure of 50% compared with strong inhibitors/inducers can be assumed. No a priori dose adaptations are indicated for weak inhibitors/inducers, because their interacting effect is small. In case pharmacologically active metabolites are involved, the metabolic pathway, the ratio of the parent to the metabolites, and the potency of the metabolites should be taken into account.

Evaluation of the pharmacokinetic effects of itraconazole on alflutinib (AST2818): an open-label, single-center, single-sequence, two-period randomized study in healthy volunteers

Alflutinib (AST2818) is a newly developed third-generation EGFR tyrosine kinase inhibitor for the treatment of lung cancer patients with T790M-resistant mutations. It is metabolized mainly by the CYP3A4 enzyme. At the same time, it has the potential to induce CYP3A4. In this study, we aimed to estimate the effect of itraconazole (a strong inhibitor of CYP3A4) on the pharmacokinetics of alflutinib. For this aim, a single-center, open-label, single-sequence, two-period trial was designed. The pharmacokinetic parameters of AST2818 and its active metabolite AST5902 were established from blood concentration measurements, and adverse events (AEs) of two periods of treatment were documented. For AST2818, the C_max, AUC_0-t, and AUC_0-∞ in period II (coadministration of itraconazole) increased by 6.5 ng/mL, 1263.0 h*ng/mL, and 1067.0 h*ng/mL, respectively. And the corresponding 90% CIs were 1.23 (1.14-1.32), 2.41 (2.29-2.54), and 2.22 (2.11-2.34), respectively. The C_max, AUC_0-t, and AUC_0-∞ of AST5902 in period II decreased by 4.849 ng/mL, 415.60 h*ng/mL, and 391.4 h*ng/mL, respectively. Moreover, the corresponding 90% CIs were 0.09 (0.08-0.10), 0.18 (0.17-0.19), and 0.14 (0.13-0.15), respectively. Nonetheless, in period II, plasma concentrations of total active components (AST2818 and AST5902) changed marginally. The AUC_0-∞ of total active components increased 60%, and the corresponding C_max increased 8%. Possible treatment-related AEs assessed by investigators were fewer in period II (23.3% vs 36.7%). In conclusion, the total exposure of AST2818 and active metabolite AST5902 increased following the coadministration of itraconazole, but it was still safe and well-tolerated.

Effects of Itraconazole and Rifampin on the Pharmacokinetics of Mobocertinib (TAK-788), an Oral Epidermal Growth Factor Receptor Inhibitor, in Healthy Volunteers

Mobocertinib (TAK‐788) is an investigational oral tyrosine kinase inhibitor targeting epidermal growth factor receptor and human epidermal growth factor 2. A phase 1 open‐label, 2‐period, fixed‐sequence, 2‐part study (NCT03928327) characterized effects of a strong CYP3A4 inhibitor (itraconazole) and inducer (rifampin) on the pharmacokinetics (PK) of mobocertinib and its active metabolites, AP32960 and AP32914. Healthy volunteers (n = 12 per part) received a single dose of mobocertinib alone (20 mg, part 1; 160 mg, part 2) and with multiple doses of itraconazole 200 mg once daily (part 1) or rifampin 600 mg once daily (part 2). Coadministration of itraconazole with mobocertinib increased the combined molar area under the plasma concentration‐time curve from time 0 to infinity (AUC_0‐∞) of mobocertinib, AP32960, and AP32914 by 527% (geometric least‐squares mean [LSM] ratio, 6.27; 90% confidence interval [CI], 5.20‐7.56). Coadministration of rifampin with mobocertinib decreased the combined molar AUC_0‐∞ of mobocertinib, AP32960, and AP32914 by 95% (geometric LSM ratio, 0.05; 90%CI, 0.04‐0.07). Based on these results, the strong CYP3A inhibitor itraconazole and inducer rifampin significantly influenced the PK of mobocertinib and its active metabolites. Coadministration of mobocertinib with moderate and strong CYP3A inhibitors or inducers is not recommended in ongoing clinical trials.

In vitro inhibition of human UDP-glucuronosyltransferase (UGT) 1A1 by osimertinib, and prediction of in vivo drug-drug interactions

Osimertinib is the only third-generation epidermal growth factor receptor tyrosine-kinase inhibitor (EGFR-TKI) approved by Food and Drug Administration (FDA). This study aimed to know the inhibitory effect of osimertinib on human UDP-glucosyltransferases (UGTs) and human liver microsomes (HLMs), as well as to identify its potential to cause drug-drug interaction (DDI) arising from the modulation of UGT activity. High inhibitory effect of osimertinib was shown towards UGT1A1, 1A3, 1A6, 1A7, 1A8, 1A10, 2B7 and 2B15. Especially, osimertinib exhibited competitive inhibition against UGT1A1 with a K_i,u of 0.87 ± 0.12 μM. It also noncompetitively inhibited SN-38 glucuronidation in pooled HLMs with a K_i,u of 3.32 ± 0.25 μM. Results from quantitative prediction study indicated that osimertinib administered at 80 mg/day may result in a 4.83 % increase in the AUC of drugs mainly metabolized by UGT1A1, implying low risk of DDI via liver metabolism. However, the ratios of [I]_gut/K_i,u are much higher than 11 in HLMs and recombinant UGT1A1, indicating a risk for interaction in intestine. The effects of osimertinib on intestinal UGT should be paid more attention on to avoid unnecessary clinical DDI risks.

Translational pharmacokinetic-pharmacodynamic modeling of preclinical and clinical data of the oral MET inhibitor tepotinib to determine the recommended phase II dose

Tepotinib is a highly selective and potent MET inhibitor in development for the treatment of patients with solid tumors. Given the favorable tolerability and safety profiles up to the maximum tested dose in the first‐in‐human (FIH) trial, an efficacy‐driven translational modeling approach was proposed to establish the recommended phase II dose (RP2D). To study the in vivo pharmacokinetics (PKs)/target inhibition/tumor growth inhibition relationship, a subcutaneous KP‐4 pancreatic cell‐line xenograft model in mice with sensitivity to MET pathway inhibition was selected as a surrogate tumor model. Further clinical PK and target inhibition data (derived from predose and postdose paired tumor biopsies) from a FIH study were integrated with the longitudinal PKs and target inhibition profiles from the mouse xenograft study to establish a translational PK/pharmacodynamic (PD) model. Preclinical data showed that tumor regression with tepotinib treatment in KP‐4 xenograft tumors corresponded to 95% target inhibition. We therefore concluded that a PD criterion of sustained, near‐to‐complete (>95%) phospho‐MET inhibition in tumors should be targeted for tepotinib to be effective. Simulations of dose‐dependent target inhibition profiles in human tumors that exceeded the PD threshold in more than 90% of patients established an RP2D of tepotinib 500 mg once daily. This translational mathematical modeling approach supports an efficacy‐driven rationale for tepotinib phase II dose selection of 500 mg once daily. Tepotinib at this dose has obtained regulatory approval for the treatment of patients with non‐small cell lung cancer harboring MET exon 14 skipping.

Food constituent- and herb-drug interactions in oncology: Influence of quantitative modelling on Drug labelling

AIMS

Herbal products, spices and/or fruits are perceived as inherently healthy; for instance, St. John's wort (SJW) is marketed as a natural antidepressant and patients often self-administer it concomitantly with oncology medications. However, food constituents/herbs can interfere with drug pharmacokinetics, with risk of altering pharmacodynamics and efficacy. The objective of this work was to develop a strategy to prioritize herb- or food constituent-drug interactions (FC-DIs) to better assess oncology drug clinical risk.

METHODS

Physiologically based pharmacokinetic (PBPK) models were developed by integrating in vitro parameters with the clinical pharmacokinetics of food constituents in grapefruit juice (bergamottin), turmeric (curcumin) or SJW (hyperforin). Perpetrator files were linked to verified victim PBPK models through appropriate interaction mechanisms (cytochrome P450 3A, breast cancer resistance protein, P-glycoprotein) and applied in prospective PBPK simulations to inform the likelihood and magnitude of changes in exposure to osimertinib, olaparib or acalabrutinib.

RESULTS

Reported FC-DIs with oncology drugs were well recovered, with absolute average fold error values of 1.10 (bergamottin), 1.05 (curcumin) and 1.01 (hyperforin). Prospective simulations with grapefruit juice and turmeric showed clinically minor to insignificant changes in exposure (<1.50-fold) to acalabrutinib, osimertinib and olaparib, but predicted 1.57-fold FC-DI risk between acalabrutinib and curcumin. Moderate DDI risk was expected when acalabrutinib, osimertinib or olaparib were dosed with SJW.

CONCLUSIONS

A model-informed decision tree based on mechanistic understanding of transporter and/or enzyme-mediated FC-DI is proposed based on bergamottin, curcumin and hyperforin FC-DI clinical data. Adopting this quantitative modelling approach should streamline herbal product safety assessments, assist in FC-DI management, and ultimately promote safe clinical use of oncology drugs.

Pharmacokinetics under the COVID-19 storm

AIMS

The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs.

METHODS

Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks. These models were also used to predict epithelial lining fluid (ELF) exposure, which is relevant for COVID-19 patients under elevated cytokine levels.

RESULTS

The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs, but dose adjustments may be warranted for COVID-19 patients also exhibiting hepatic/renal impairment. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs, except for hydroxychloroquine, azithromycin, atazanavir and lopinavir/ritonavir.

CONCLUSION

We demonstrate that systematically collated data on absorption, distribution, metabolism and excretion, human PK parameters, DDIs and organ impairment can be used to verify simulated plasma and lung tissue exposure for drugs repurposed for COVID-19, justifying broader patient recruitment criteria. In addition, the PBPK model developed was used to study the effect of age and ethnicity on the PK of repurposed drugs, and to assess the correlation between lung exposure and relevant potency values from in vitro studies for SARS-CoV-2.

Model-Informed Pediatric Dose Selection for Dapagliflozin by Incorporating Developmental Changes

This analysis reports a quantitative modeling and simulation approach for oral dapagliflozin, a primarily uridine diphosphate-glucuronosyltransferase (UGT)-metabolized human sodium-glucose cotransporter 2 selective inhibitor. A mechanistic dapagliflozin physiologically based pharmacokinetic (PBPK) model was developed using in vitro metabolism and clinical pharmacokinetic (PK) data and verified for context of use (e.g., exposure predictions in pediatric subjects aged 1 month to 18 years). Dapagliflozin exposure is challenging to predict in pediatric populations owing to differences in UGT1A9 ontogeny maturation and paucity of clinical PK data in younger age groups. Based on the exposure-response relationship of dapagliflozin, twofold acceptance criteria were applied between model-predicted and observed drug exposures and PK parameters (area under the curve and maximum drug concentration) in various scenarios, including monotherapy in healthy adults (single/multiple dose), monotherapy in hepatically or renally impaired patients, and drug-drug interactions with UGT1A9 modulators, such as mefenamic acid and rifampin. The PBPK model captured the observed exposure within twofold of the observed monotherapy data in adults and adolescents and in special population. As a guide to determining dosing regimens in pediatric studies, the verified PBPK model, along with UGT enzyme ontogeny maturation understanding, was used for predictions of dapagliflozin monotherapy exposures in pediatric subjects aged 1 month to 18 years that best matched exposure in adult patients with a 10-mg single dose of dapagliflozin.

EGFR inhibitors switch keratinocytes from a proliferative to a differentiative phenotype affecting epidermal development and barrier function

BACKGROUND

Cutaneous adverse drug reactions (CADR) associated with oncology therapy involve 45-100% of patients receiving kinase inhibitors. Such adverse reactions may include skin inflammation, infection, pruritus and dryness, symptoms that can significantly affect the patient's quality of life. To prevent severe skin damages dose adjustment or drug discontinuation is often required, interfering with the prescribed oncology treatment protocol. This is particularly the case of Epidermal Growth Factor Receptor inhibitors (EGFRi) targeting carcinomas. Since the EGFR pathway is pivotal for epidermal keratinocytes, it is reasonable to hypothesize that EGFRi also affect these cells and therefore interfere with the epidermal structure formation and skin barrier function.

METHODS

To test this hypothesis, the effects of EGFRi and Vascular Endothelial Growth Factor Receptor inhibitors (VEGFRi) at therapeutically relevant concentrations (3, 10, 30, 100 nM) were assessed on proliferation and differentiation markers of human keratinocytes in a novel 3D micro-epidermis tissue culture model.

RESULTS

EGFRi directly affect basal keratinocyte growth, leading to tissue size reduction and switching keratinocytes from a proliferative to a differentiative phenotype, as evidenced by decreased Ki67 staining and increased filaggrin, desmoglein-1 and involucrin expression compared to control. These effects lead to skin barrier impairment, which can be observed in a reconstructed human epidermis model showing a decrease in trans-epidermal water loss rates. On the other hand, pan-kinase inhibitors mainly targeting VEGFR barely affect keratinocyte differentiation and rather promote a proliferative phenotype.

CONCLUSIONS

This study contributes to the mechanistic understanding of the clinically observed CADR during therapy with EGFRi. These in vitro results suggest a specific mode of action of EGFRi by directly affecting keratinocyte growth and barrier function.

A Physiologically Based Pharmacokinetic Model to Predict Potential Drug-Drug Interactions and Inform Dosing of Acumapimod, an Oral p38 MAPK Inhibitor

Acumapimod, an investigational oral p38 mitogen‐activated protein kinase inhibitor for treatment during severe acute exacerbations of chronic obstructive pulmonary disease, is metabolized primarily by cytochrome P450 3A4 (CYP3A4) and is a P‐glycoprotein (P‐gp) substrate. Concerns about drug–drug interactions (DDIs) have meant patients receiving drugs that inhibit CYP3A4 were ineligible for acumapimod trials. We report on how 2 acumapimod clinical DDI studies and a physiologically‐based pharmacokinetic (PBPK) model assessing how co‐administration of a weak (azithromycin) and strong (itraconazole) CYP3A4 inhibitor affected acumapimod systemic exposure, informed decision making and supported concomitant use of CYP3A4 and P‐gp inhibitors. Studies MBCT102 and MBCT103, respectively, demonstrated that co‐administration of azithromycin or itraconazole had no clinically meaningful impact on acumapimod pharmacokinetics. Findings were consistent with PBPK model results. Safety profiles were similar when acumapimod was co‐administered with azithromycin or itraconazole. These studies highlight the value of PBPK modeling in drug development, and its potential to inform DDI investigations.

BEBT-109, a pan-mutant-selective EGFR inhibitor with potent antitumor activity in EGFR-mutant non-small cell lung cancer

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BEBT-109 is a potent pan-mutant-selective EGFR inhibitor.

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Pharmacokinetic profiles of BEBT-109 minimize the off-target toxicity.

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Two major metabolites of BEBT-109 show no wild-type EGFR inhibition.

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BEBT-109 demonstrates potent antitumor activity in the clinical trial.

EGFR mutation-positive NSCLC tumors are highly heterogeneous, therefore, exploring an agent simultaneously targeting multiple EGFR mutations may be valuable for clinical practice. Compared with osimertinib, BEBT-109 shows more sensitive and extensive antitumor activity in EGFR mutant NSCLC, while sparing wild-type EGFR cell lines. Meanwhile, unlike the metabolite of osimertinib AZ5104, the main metabolites of BEBT-109 are found lacking in activity against wild-type EGFR cell lines. Preclinical and clinical studies demonstrate a unique pharmacokinetic profiles of BEBT-109 with rapid absorption and quick in vivo clearance without accumulation, which are conducive to minimizing the off-target toxicity of the covalent irreversible EGFR inhibitor. Oral administration of BEBT-109 induces tumor regression in EGFR exon 20 insertion xenografts, and even tumor disappearance in PC-9, HCC827 and H1975 xenograft models. Furthermore, in clinical trials, the objective responses were observed in NSCLC patients with EGFR T790M mutation in the first and second dosing cohorts. These findings demonstrate that BEBT-109, a potent pan-mutant-selective EGFR inhibitor with improved pharmacokinetic properties, might offer a promising new option for the treatment of multiple mutant-EGFR-driven NSCLC.

Myositis - A common but underreported adverse effect of osimertinib: Case series and review of the literature

BACKGROUND

Lung cancer is the second most common cancer in both men and women and the leading cause of cancer death worldwide. The development of novel tyrosine kinase inhibitors (TKIs) represented a paradigm shift in the management of lung cancer and has resulted in markedly prolonged survival. Osimertinib is a TKI that was fast-tracked by the United States Food and Drug Administration in 2015 and subsequently approved for the treatment of metastatic epidermal growth factor receptor T790M mutation-positive non-small cell lung cancer. However, despite the generally favorable outcomes associated with osimertinib, rapid development and deployment of any new drug increases the risk of unforeseen adverse effects. Post-marketing surveillance studies therefore play an important role in further elucidating the risks and benefits of novel anti-neoplastic agents.

MATERIAL AND METHODS

We describe four patients with non-small cell lung cancer who developed myositis after beginning treatment with osimertinib. In addition, we review the literature on osimertinib-associated myositis. Using PubMed, the following terms were searched and relevant citations assessed: creatine phosphokinase, myositis, osimertinib, rhabdomyolysis, osimertinib, and Tagrisso.

CASE PRESENTATION

Thirty-eight patients were treated with osimertinib in our community clinic. Four with non-small cell lung cancer developed myositis after beginning treatment. The onset of symptoms and/or elevation of creatine phosphokinase occurred between two weeks and eleven months after osimertinib was initiated. Alternative causes for myositis were not identified. In two patients, myositis resolved within one month of withdrawing treatment. Two other patients continued osimertinib treatment with close monitoring.

CONCLUSION

Myositis is a serious and potentially underreported adverse effect of osimertinib. Previous studies suggest that osimertinib-associated myositis is rare, occurring in less than 1% of patients. However, myositis occurred in over 10% of patients treated with osimertinib in our clinic population. We suggest regular monitoring for myositis among patients being treated with osimertinib and dose-reduction or cessation of treatment if clinically indicated.

Inhibition and induction of CYP enzymes in humans: an update

The cytochrome P450 (CYP) enzyme family is the most important enzyme system catalyzing the phase 1 metabolism of pharmaceuticals and other xenobiotics such as herbal remedies and toxic compounds in the environment. The inhibition and induction of CYPs are major mechanisms causing pharmacokinetic drug–drug interactions. This review presents a comprehensive update on the inhibitors and inducers of the specific CYP enzymes in humans. The focus is on the more recent human in vitro and in vivo findings since the publication of our previous review on this topic in 2008. In addition to the general presentation of inhibitory drugs and inducers of human CYP enzymes by drugs, herbal remedies, and toxic compounds, an in-depth view on tyrosine-kinase inhibitors and antiretroviral HIV medications as victims and perpetrators of drug–drug interactions is provided as examples of the current trends in the field. Also, a concise overview of the mechanisms of CYP induction is presented to aid the understanding of the induction phenomena.

Role of OATP1B1 and OATP1B3 in Drug-Drug Interactions Mediated by Tyrosine Kinase Inhibitors

Failure to recognize important features of a drug's pharmacokinetic characteristics is a key cause of inappropriate dose and schedule selection, and can lead to reduced efficacy and increased rate of adverse drug reactions requiring medical intervention. As oral chemotherapeutic agents, tyrosine kinase inhibitors (TKIs) are particularly prone to cause drug-drug interactions as many drugs in this class are known or suspected to potently inhibit the hepatic uptake transporters OATP1B1 and OATP1B3. In this article, we provide a comprehensive overview of the published literature and publicly-available regulatory documents in this rapidly emerging field. Our findings indicate that, while many TKIs can potentially inhibit the function of OATP1B1 and/or OATP1B3 and cause clinically-relevant drug-drug interactions, there are many inconsistencies between regulatory documents and the published literature. Potential explanations for these discrepant observations are provided in order to assist prescribing clinicians in designing safe and effective polypharmacy regimens, and to provide researchers with insights into refining experimental strategies to further predict and define the translational significance of TKI-mediated drug-drug interactions.

Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy

BACKGROUND

DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery.

METHODS

The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing.

RESULTS

This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies.

CONCLUSION

Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

A Drug-Drug Interaction Study to Evaluate the Effect of TAS-303 on CYP3A Activity in the Small Intestine and Liver

TAS‐303 (4‐piperidinyl 2,2‐diphenyl‐2‐[propoxy‐1,1,2,2,3,3,3‐d₇] acetate hydrochloride) is a novel selective noradrenaline reuptake inhibitor being developed for the treatment of stress urinary incontinence. An in vitro study and a physiologically based pharmacokinetic model simulation showed that TAS‐303 had inhibitory potential against cytochrome P450 (CYP) 3A. This open‐label, single‐group study investigated the effect of TAS‐303 on CYP3A activity by evaluating the pharmacokinetics (PK) of single‐dose oral simvastatin 5 mg or intravenous midazolam 1 mg after repeated oral administration of TAS‐303 3 mg in 12 healthy participants. TAS‐303 plus simvastatin resulted in a 1.326‐fold and a 1.420‐fold increase of simvastatin in peak plasma concentration and area under the plasma concentration‐time curve from time zero to time t, where t is the final time of detection (AUC_0‐t), respectively. The addition of midazolam resulted in a 1.090‐fold increase in the midazolam AUC_0‐t. TAS‐303 had a weak PK interaction with simvastatin but no apparent interaction with midazolam. TAS‐303 at 3 mg/day is a weak inhibitor of intestinal but not hepatic CYP3A activity. No clinically important safety concerns related to TAS‐303 were raised.

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

Comparative review of drug-drug interactions with epidermal growth factor receptor tyrosine kinase inhibitors for the treatment of non-small-cell lung cancer

The development of small-molecule tyrosine kinase inhibitors (TKIs) that target the epidermal growth factor receptor (EGFR) has revolutionized the management of non-small-cell lung cancer (NSCLC). Because these drugs are commonly used in combination with other types of medication, the risk of clinically significant drug–drug interactions (DDIs) is an important consideration, especially for patients using multiple drugs for coexisting medical conditions. Clinicians need to be aware of the potential for clinically important DDIs when considering therapeutic options for individual patients. In this article, we describe the main mechanisms underlying DDIs with the EGFR-TKIs that are currently approved for the treatment of NSCLC, and, specifically, the potential for interactions mediated via effects on gastrointestinal pH, cytochrome P450-dependent metabolism, uridine diphosphate-glucuronosyltransferase, and transporter proteins. We review evidence of such DDIs with the currently approved EGFR-TKIs (gefitinib, erlotinib, afatinib, osimertinib, and icotinib) and discuss several information sources that are available online to aid clinical decision-making. We conclude by summarizing the most clinically relevant DDIs with these EFGR-TKIs and provide recommendations for managing, minimizing, or avoiding DDIs with the different agents.

Evaluation of Maternal Drug Exposure Following the Administration of Antenatal Corticosteroids During Late Pregnancy Using Physiologically-Based Pharmacokinetic Modeling

Betamethasone and dexamethasone are the most widely studied antenatal corticosteroids (ACS) administered to pregnant women, just prior to the birth of a preterm neonate, to accelerate fetal lung maturation. Although betamethasone, predominantly used in developed countries, has been shown to be an effective and safe intervention for reducing neonatal mortality, the choice of ACS and optimal dosing in low and middle income countries (LMICs) remains unclear. This is primarily because the exposure-response relationships have not been established for ACS despite the long history of use. As the first step toward the optimal use of ACS in LMICs, we developed physiologically-based pharmacokinetic (PBPK) models to describe the kinetics of ACS following i.v., p.o., or i.m. dosing. In vitro data describing the cytochrome P450 3A4 enzyme contribution were incorporated and this was refined using clinical data. The models can be applied prospectively to predict kinetics of ACS in pregnant women receiving various dosing regimens.

Interaction between phytotherapy and oral anticancer agents: prospective study and literature review

Cancer is becoming more prevalent in elderly patient. Due to polypharmacy, older adults with cancer are predisposed to drug-drug interactions. There is also an increasing interest in the use of complementary and alternative medicine (CAM). Thirty to seventy percent of patients with cancer have used CAM. Through pharmaceutical counseling sessions, we can provide advices on herb-drug interactions (HDI). All the patients seen in pharmaceutical counseling sessions were prospectively included. Information was collected during these sessions: prescribed medication (oral anticancer agents (OAA) and other drugs), CAM (phytotherapy especially), and use of over-the-counter (OTC) drugs. If pharmacist considered an interaction or an intervention clinically relevant, the oncologist was notified. Then, a literature review was realized to identify the potential HDI (no interactions, precautions for use, contraindication). Among 201 pharmacist counseling sessions, it resulted in 104 interventions related to 46 HDI, 28 drug-drug interactions and 30 others (wrong dosage, omission…). To determine HDI, we review 73 medicinal plants which are used by our patients with cancer and 31 OAA. A total of 1829 recommendations were formulated about 59 (75%) medical plants and their interaction with an OAA. Herb-drug interactions should not be ignored by healthcare providers in their management of cancer patients in daily practice.

Modulation of Fexofenadine Pharmacokinetics by Osimertinib in Patients With Advanced EGFR-Mutated Non-Small Cell Lung Cancer

Osimertinib is a potent, third-generation, irreversible, central nervous system active epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) that selectively inhibits EGFR-TKI sensitizing and EGFR T790M resistance mutations. It is approved for first-line treatment of patients with advanced non-small cell lung cancer (NSCLC) whose tumors have EGFR exon 19 deletions or exon 21 L858R mutations, and for patients with T790M-positive advanced NSCLC whose disease has progressed on or after EGFR-TKI therapy. This study investigated the pharmacokinetics (PK) of fexofenadine (P-glycoprotein substrate) following single- and multiple-dose osimertinib in patients with advanced NSCLC who have progressed on prior EGFR-TKI therapy. This open-label, phase 1 study (NCT02908750) comprised the PK phase and continued access phase. The former comprised 2 distinct periods with a 3- to 7-day washout: treatment period 1 (n = 24, fexofenadine 120 mg, day 1) and treatment period 2 (fexofenadine 120 mg + osimertinib 80 mg single dose on days 1 and 39 and osimertinib 80 mg once daily from days 4 to 41). Patients could continue osimertinib 80 mg once daily based on investigator's discretion in the continued access phase. Fexofenadine area under the plasma concentration-time curve and maximum concentration increased by 56% (90% confidence interval [CI], 35.4-78.6) and 76% (90%CI, 49.3-108.3) following coadministration with osimertinib single dose, and by 27% (90%CI, 11.2-45.8) and 25% (90%CI, 5.6-48.1) when given with osimertinib at steady state, respectively. Following osimertinib coadministration, median fexofenadine time to maximum concentration increased by approximately 30 minutes compared with time to maximum concentration following fexofenadine alone. No new osimertinib safety findings were observed. The increase in fexofenadine exposure following osimertinib coadministration shows osimertinib as a weak P-glycoprotein inhibitor.

Effect of multiple-dose osimertinib on the pharmacokinetics of simvastatin and rosuvastatin

AIM

We report on two Phase 1, open-label, single-arm studies assessing the effect of osimertinib on simvastatin (CYP3A substrate) and rosuvastatin (breast cancer resistance protein substrate [BCRP] substrate) exposure in patients with advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer who have progressed after treatment with an EGFR tyrosine kinase inhibitor, to determine, upon coadministration, whether osimertinib could affect the exposure of these agents.

METHODS

Fifty-two patients in the CYP3A study (pharmacokinetic [PK] analysis, n = 49), and 44 patients in the BCRP study were dosed (PK analysis, n = 44). In the CYP3A study, patients received single doses of simvastatin 40 mg on Days 1 and 31, and osimertinib 80 mg once daily on Days 3-32. In the BCRP study, single doses of rosuvastatin 20 mg were given on Days 1 and 32, and osimertinib 80 mg once daily on Days 4-34.

RESULTS

Geometric least squares mean (GLSM) ratios (90% confidence intervals) of simvastatin plus osimertinib for area under the plasma concentration-time curves from zero to infinity (AUC) were 91% (77-108): entirely contained within the predefined no relevant effect limits, and C_max of 77% (63, 94) which was not contained within the limits. GLSM ratios of rosuvastatin plus osimertinib for AUC were 135% (115-157) and C_max were 172 (146, 203): outside the no relevant effect limits.

CONCLUSIONS

Osimertinib is unlikely to have any clinically relevant interaction with CYP3A substrates and has a weak inhibitory effect on BCRP. No new safety concerns were identified in either study.

In silico models in drug development: where we are

The use and utility of computational models in drug development has significantly grown in the last decades, fostered by the availability of high throughput datasets and new data analysis strategies. These in silico approaches are demonstrating their ability to generate reliable predictions as well as new knowledge on the mode of action of drugs and the mechanisms underlying their side effects, altogether helping to reduce the costs of drug development. The aim of this review is to provide a panorama of developments in the field in the last two years.

Physiologically Based Pharmacokinetic Modeling for Olaparib Dosing Recommendations: Bridging Formulations, Drug Interactions, and Patient Populations

We report physiologically based pharmacokinetic-modeling analyses to determine olaparib (tablet or capsule) drug-drug interactions (DDIs). Verified DDI simulations provided dose recommendations for olaparib coadministration with clinically relevant CYP3A4 modulators to eliminate potential risk to patient safety or olaparib efficacy. When olaparib is given with strong/moderate CYP3A inhibitors, the dose should be reduced to 100/150 mg b.i.d. (tablet), and 150/200 mg b.i.d. (capsule). Olaparib administration is not recommended with strong/moderate CYP3A inducers. No dose reductions are required with weak CYP3A inhibitors/inducers. Olaparib was shown to be a weak inhibitor of CYP3A (1.6-fold increase in exposure of a sensitive CYP3A probe) and to have no effect on P-glycoprotein or UGT1A1 substrates. Finally, this model was used to simulate exposure in scenarios where clinical data of olaparib are lacking, such as severe renal or hepatic impairment populations, and provided initial dosing recommendations in pediatric patients.