Predicting drug-drug interactions in breast cancer patients treated with CDK4/6 inhibitors and forward planning

INTRODUCTION

Cyclin-dependent kinase (CDK) 4/6 inhibitors are cornerstones in the treatment of Hormone Receptor (HR) positive and Human Epidermal Growth factor (HER2) negative metastatic breast cancer. Given their widespread use in the metastatic setting and emerging use in the adjuvant setting, studying drug-drug interactions (DDI) of these medications is of utmost importance.

AREAS COVERED

This review provides key background information on the CDK4/6 inhibitors, palbociclib, ribociclib, and abemaciclib. We discuss drug-drug interactions including those with proton pump inhibitors as well as CYP3A substrates, inhibitors, and inducers. We describe the effect of these drugs on membrane transporters and their substrates as well as those drugs that increase risk of CDK4/6 toxicities. Finally, we explore future directions for strategies to minimize drug-drug interactions.

EXPERT OPINION

It is crucial to be mindful of medications that may interfere with drug absorption, such as proton pump inhibitors, as well as those that interfere with drug metabolism, such as CYP3A4 inhibitors and inducers. Additionally, special consideration should be given to populations at higher risk for polypharmacy, such as older patients with greater comorbidities. These interactions and patient characteristics should be considered when developing individual treatment plans with CDK4/6 inhibitors.

Differences in metabolic transport and resistance mechanisms of Abemaciclib, Palbociclib, and Ribociclib

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) play a crucial role in cancer treatment, particularly in breast cancer, and their mechanism of drug resistance is a topic of global interest in research. Hence, it is vital to comprehend the distinctions between various CDK4/6i, including their mechanisms of action and resistance mechanisms. This article aims to summarize the metabolic and transport variations as well as the differences in resistance among the three FDA-approved CDK4/6 inhibitors: Abemaciclib, Palbociclib, and Ribociclib. It also aims to discuss how these differences impact the effectiveness and safety of anticancer drugs. It was conducted in March 2023 to search PubMed, Embase, and Web of Science for literature related to this topic. Despite all being CDK4/6i, differences in their metabolism and transport were found, which are related to their chemical structure. Moreover, there are variations in preclinical pharmacology, pharmacokinetics, and clinical safety and efficacy of the different inhibitors. Genetic mutations, drug tolerance, and other factors may influence CDK4/6 resistance mechanisms. Currently, the resistance mechanisms differences of the three drugs remain largely unknown, and there are differences in the resistance mechanisms among them, necessitating further exploration and research.

Isotretinoin and its Metabolites Alter mRNA of Multiple Enzyme and Transporter Genes In Vitro, but Downregulation of Organic Anion Transporting Polypeptide Does Not Translate to the Clinic

Isotretinoin [13-cis-retinoic acid (13cisRA)] is widely used for the treatment of neuroblastoma and acne. It acts via regulating gene transcription through binding to retinoic acid receptors. Yet, the potential for isotretinoin to cause transcriptionally mediated drug-drug interactions (DDIs) has not been fully explored. We hypothesized that isotretinoin and its active metabolites all-trans-retinoic acid (atRA) and 4-oxo-13cisRA would alter the transcription of enzymes and transporters in the human liver via binding to nuclear receptors. The goal of this study was to define the DDI potential of isotretinoin and its metabolites resulting from transcriptional regulation of cytochrome P450 and transporter mRNAs. In human hepatocytes (n = 3), 13cisRA, atRA, and 4-oxo-13cisRA decreased OATP1B1, CYP1A2, CYP2C9, and CYP2D6 mRNA and increased CYP2B6 and CYP3A4 mRNA in a concentration-dependent manner. The EC50 values for OATP1B1 mRNA downregulation ranged from 2 to 110 nM, with maximum effect (Emax ) ranging from 0.17- to 0.54-fold. Based on the EC50 and Emax values and the known circulating concentrations of 13cisRA and its metabolites after isotretinoin dosing, a 55% decrease in OATP1B1 activity was predicted in vivo. In vivo DDI potential was evaluated clinically in participants dosed with isotretinoin for up to 32 weeks using coproporphyrin-I (CP-I) as an OATP1B1 biomarker. CP-I steady-state serum concentrations were unaltered following 2, 8, or 16 weeks of isotretinoin treatment. These data show that isotretinoin and its metabolites alter transcription of multiple enzymes and transporters in vitro, but translation of these changes to in vivo drug-drug interactions requires clinical evaluation for each enzyme. SIGNIFICANCE STATEMENT: Isotretinoin and its metabolites alter the mRNA expression of multiple cytochrome P450s (CYPs) and transporters in human hepatocytes, suggesting that isotretinoin may cause clinically significant drug-drug interactions (DDIs). Despite the observed changes in organic anion transporting polypeptide 1B1 (OATP1B1) mRNA in human hepatocytes, no clinical DDI was observed when measuring a biomarker, coproporphyrin-I. Further work is needed to determine whether these findings can be extrapolated to a lack of a DDI with CYP1A2, CYP2B6, and CYP2C9 substrates.

Abemaciclib in Combination With Endocrine Therapy for Patients With Hormone Receptor-Positive, HER2-Negative Metastatic Breast Cancer: A Phase 1b Study

Background

Cyclin-dependent kinases (CDK) 4 and 6 regulate G1 to S cell cycle progression and are often altered in cancers. Abemaciclib is a selective inhibitor of CDK4 and CDK6 approved for administration on a continuous dosing schedule as monotherapy or as combination therapy with an aromatase inhibitor or fulvestrant in patients with advanced or metastatic breast cancer. This Phase 1b study evaluated the safety and tolerability, pharmacokinetics, and antitumor activity of abemaciclib in combination with endocrine therapy for metastatic breast cancer (MBC), including aromatase inhibitors (letrozole, anastrozole, or exemestane) or tamoxifen.

Patients and Methods

Women ≥18 years old with hormone receptor positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) MBC were eligible for enrollment. Eligibility included measurable disease or non-measurable but evaluable bone disease by Response Evaluation Criteria in Solid Tumours (RECIST) v1.1, Eastern Cooperative Oncology Group performance status 0–1, and no prior chemotherapy for metastatic disease. Adverse events were graded by the National Cancer Institute Common Terminology Criteria for Adverse Events v4.0 and tumor response were assessed by RECIST v1.1.

Results

Sixty-seven patients were enrolled and received abemaciclib 200 mg every 12 hours in combination with letrozole (Part A, n=20), anastrozole (Part B, n=16), tamoxifen (Part C, n=16), or exemestane (Part D, n=15). The most common treatment-emergent adverse events (TEAE) were diarrhea, fatigue, nausea, and abdominal pain. Grade 4 TEAEs were reported in five patients (one each with hyperglycemia, hypertension, neutropenia, procedural hemorrhage, and sepsis). There was no effect of abemaciclib or endocrine therapy on the pharmacokinetics of any combination study drug. Across all treated patients, the median progression-free survival was 25.4 months (95% confidence interval: 18.0, 35.8). The objective response rate was 38.9% in 36 patients with measurable disease.

Conclusions

Abemaciclib in combination with multiple endocrine therapy options exhibited manageable safety and promising antitumor activity in patients with HR+, HER2- MBC.

Clinical Trial Registration

https://clinicaltrials.gov/, identifier NCT02057133

Pharmacogenomics Testing in Phase I Oncology Clinical Trials: Constructive Criticism Is Warranted

Simple Summary

Phase I clinical trials are a cornerstone of pharmaceutical development in oncology. Many studies have now attempted to incorporate pharmacogenomics into phase I studies; however, many of these studies have fundamental flaws that that preclude interpretation and application of their findings. Study populations are often small and heterogeneous with multiple disease states, multiple dose levels, and prior therapies. Genetic testing typically includes few variants in candidate genes that do no encapsulate the full range of phenotypic variability in protein function. Moreover, a plurality of these studies do not present scientifically robust clinical or preclinical justification for undertaking pharmacogenomics studies. A significant amount of progress in understanding pharmacogenomic variability has occurred since pharmacogenomics approaches first began appearing in the literature. This progress can be immediately leveraged for the vast majority of Phase I studies. The purpose of this review is to summarize the current literature pertaining to Phase I incorporation of pharmacogenomics studies, analyze potential flaws in study design, and suggest approaches that can improve design of future scientific efforts.

Abstract

While over ten-thousand phase I studies are published in oncology, fewer than 1% of these studies stratify patients based on genetic variants that influence pharmacology. Pharmacogenetics-based patient stratification can improve the success of clinical trials by identifying responsive patients who have less potential to develop toxicity; however, the scientific limits imposed by phase I study designs reduce the potential for these studies to make conclusions. We compiled all phase I studies in oncology with pharmacogenetics endpoints (n = 84), evaluating toxicity (n = 42), response or PFS (n = 32), and pharmacokinetics (n = 40). Most of these studies focus on a limited number of agent classes: Topoisomerase inhibitors, antimetabolites, and anti-angiogenesis agents. Eight genotype-directed phase I studies were identified. Phase I studies consist of homogeneous populations with a variety of comorbidities, prior therapies, racial backgrounds, and other factors that confound statistical analysis of pharmacogenetics. Taken together, phase I studies analyzed herein treated small numbers of patients (median, 95% CI = 28, 24–31), evaluated few variants that are known to change phenotype, and provided little justification of pharmacogenetics hypotheses. Future studies should account for these factors during study design to optimize the success of phase I studies and to answer important scientific questions.

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug-drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity. We developed an original machine learning approach for the prediction of drug-like molecules inhibiting CYP2C9. We created new predictive models by integrating CYP2C9 protein structure and dynamics knowledge, an original selection of physicochemical properties of CYP2C9 inhibitors, and machine learning modeling. We tested the machine learning models on publicly available data and demonstrated that our models successfully predicted CYP2C9 inhibitors with an accuracy, sensitivity and specificity of approximately 80%. We experimentally validated the developed approach and provided the first identification of the drugs vatalanib, piriqualone, ticagrelor and cloperidone as strong inhibitors of CYP2C9 with IC values <18 μM and sertindole, asapiprant, duvelisib and dasatinib as moderate inhibitors with IC50 values between 40 and 85 μM. Vatalanib was identified as the strongest inhibitor with an IC50 value of 0.067 μM. Metabolism assays allowed the characterization of specific metabolites of abemaciclib, cloperidone, vatalanib and tarafenacin produced by CYP2C9. The obtained results demonstrate that such a strategy could improve the prediction of drug-drug interactions in clinical practice and could be utilized to prioritize drug candidates in drug discovery pipelines.

Quantification of abemaciclib and metabolites: evolution of bioanalytical methods supporting a novel oncolytic agent

Aim: Bioanalytical methods undergo many revisions and modifications throughout drug development to meet the objectives of the study and development program. Results: Validated LC-MS/MS methodology used to quantify abemaciclib and four metabolites in human plasma is described. The method, initially validated to support the first-in-human study, was successfully modified to include additional metabolites as in vitro and in vivo information about the activity and abundance of human metabolites became available. Consistent performance of the method over time was demonstrated by an incurred sample reanalysis passing rate exceeding 95%, across clinical studies. An overview of the numerous methods involved during the development of abemaciclib, including the quantification of drugs evaluated as combination regimens and used as substrates during drug-drug interaction studies, is presented. Conclusion: Robust bioanalytical methods need to be designed with the flexibility required to support the evolving study objectives associated with registration and post-registration trials.