Pharmacokinetic/Pharmacodynamic modeling of abexinostat-induced thrombocytopenia across different patient populations: application for the determination of the maximum tolerated doses in both lymphoma and solid tumour patients

The Bioequivalence of Abexinostat (CRA-024781) Tosylate Tablets (20 mg) in Chinese Healthy Subjects Under Fasting Conditions

This study aimed to investigate the pharmacokinetic parameters of single oral administration of postchange and prechange abexinostat (CRA-024781) tosylate tablets in Chinese healthy subjects under fasting conditions, and assess the bioequivalence (BE) of the 2 formulations (Test [T1] and Reference [T2]). This study was a randomized, open-label, 2-formulation, fasting administration, single-dose, 2-sequence, 2-cycle, crossover BE study. Thirty-six subjects were enrolled in the study and 33 subjects completed 2 cycles. The plasma concentrations were determined by liquid chromatography-tandem mass spectrometry. The 90% confidence intervals (CIs) for the Cmax, AUC0-t, and AUC0-∞ of CRA-024781 and its 2 major metabolites (PCI-27789 and PCI-27887, both metabolites are pharmacologically inactive on HDAC1) fell within the acceptable range of 80%-125%. The results suggest that the CRA-024781 test preparation (Test [T1]) is bioequivalent to the reference preparation (Reference [T2]) in healthy Chinese subjects under fasting conditions.

Leveraging modeling and simulation to optimize the therapeutic window for epigenetic modifier drugs

Dysregulated epigenetic processes can lead to altered gene expression and give rise to malignant transformation and tumorigenesis. Epigenetic drugs aim to revert the phenotype of cancer cells to normally functioning cells, and are developed and applied to treat both hematological and solid cancers. Despite this promising therapeutic avenue, the successful development of epigenetic modulators has been challenging. We argue that besides identifying the right responder patient population, the selection of an optimized dosing regimen is equally important. For the majority of epigenetic modulators, hematological adverse effects such as thrombocytopenia, anemia or neutropenia are frequently observed and may limit their therapeutic potential. Therefore, one of the key challenges is to identify a dosing regimen that maximizes drug efficacy and minimizes toxicity. This requires a good understanding of the quantitative relationship between the administered dose, the drug exposure and the magnitude and duration of drug response related to safety and efficacy. With case examples, we highlight how modeling and simulation has been successfully applied to address those questions. As an outlook, we suggest the combination of efficacy and safety prediction models that capture the quantitative, mechanistic relationships governing the balance between their safety and efficacy dynamics. A stepwise approach for its implementation is presented. Utilizing in silico explorations, the impact of dosing regimen on the therapeutic window can be explored. This will serve as a basis to select the most promising dosing regimen that maximizes efficacy while minimizing adverse effects and to increase the probability of success for the given epigenetic drug.

Systems Modeling to Quantify Safety Risks in Early Drug Development: Using Bifurcation Analysis and Agent-Based Modeling as Examples

Quantitative Systems Toxicology (QST) models, recapitulating pharmacokinetics and mechanism of action together with the organic response at multiple levels of biological organization, can provide predictions on the magnitude of injury and recovery dynamics to support study design and decision-making during drug development. Here, we highlight the application of QST models to predict toxicities of cancer treatments, such as cytopenia(s) and gastrointestinal adverse effects, where narrow therapeutic indexes need to be actively managed. The importance of bifurcation analysis is demonstrated in QST models of hematologic toxicity to understand how different regions of the parameter space generate different behaviors following cancer treatment, which results in asymptotically stable predictions, yet highly irregular for specific schedules, or oscillating predictions of blood cell levels. In addition, an agent-based model of the intestinal crypt was used to simulate how the spatial location of the injury within the crypt affects the villus disruption severity. We discuss the value of QST modeling approaches to support drug development and how they align with technological advances impacting trial design including patient selection, dose/regimen selection, and ultimately patient safety.

Utilization of Physiologically Based Pharmacokinetic Modeling in Clinical Pharmacology and Therapeutics: an Overview

The purpose of this review was to assess the advancement of applications for physiologically based pharmacokinetic (PBPK) modeling in various therapeutic areas. We conducted a PubMed search, and 166 articles published between 2012 and 2018 on FDA-approved drug products were selected for further review. Qualifying publications were summarized according to therapeutic area, medication(s) studied, pharmacokinetic model type utilized, simulator program used, and the applications of that modeling. The results showed a 13-fold increase in the number of papers published from 2012 to 2018, with the largest proportion of articles dedicated to the areas of infectious diseases, oncology, and neurology, and application extensions including prediction of drug-drug interactions due to metabolism and/or transporter-mediated effects and understanding drug kinetics in special populations. In addition, we profiled several high-impact studies whose results were used to guide package insert information and formulate dose recommendations. These results show that while utilization of PBPK modeling has drastically increased over the past several years, regulatory support, lack of easy-to-use systems for clinicians, and challenges with model validation remain major challenges for the widespread adoption of this practice in institutional and ambulatory settings. However, PBPK modeling will continue to be a useful tool in the future to assess therapeutic drug monitoring and the growing field of personalized medicine.

Optimizing drug development in oncology by clinical trial simulation: Why and how?

In therapeutic research, the safety and efficacy of pharmaceutical products are necessarily tested on humans via clinical trials after an extensive and expensive preclinical development period. Methodologies such as computer modeling and clinical trial simulation (CTS) might represent a valuable option to reduce animal and human assays. The relevance of these methods is well recognized in pharmacokinetics and pharmacodynamics from the preclinical phase to postmarketing. However, they are barely used and are poorly regarded for drug approval, despite Food and Drug Administration and European Medicines Agency recommendations. The generalization of CTS could be greatly facilitated by the availability of software for modeling biological systems, by clinical trial studies and hospital databases. Data sharing and data merging raise legal, policy and technical issues that will need to be addressed. Development of future molecules will have to use CTS for faster development and thus enable better patient management. Drug activity modeling coupled with disease modeling, optimal use of medical data and increased computing speed should allow this leap forward. The realization of CTS requires not only bioinformatics tools to allow interconnection and global integration of all clinical data but also a universal legal framework to protect the privacy of every patient. While recognizing that CTS can never replace 'real-life' trials, they should be implemented in future drug development schemes to provide quantitative support for decision-making. This in silico medicine opens the way to the P4 medicine: predictive, preventive, personalized and participatory.

A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model of the histone deacetylase (HDAC) inhibitor vorinostat for pediatric and adult patients and its application for dose specification

PURPOSE

This study aimed at recommending pediatric dosages of the histone deacetylase (HDAC) inhibitor vorinostat and potentially more effective adult dosing regimens than the approved standard dosing regimen of 400 mg/day, using a comprehensive physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling approach.

METHODS

A PBPK/PD model for vorinostat was developed for predictions in adults and children. It includes the maturation of relevant metabolizing enzymes. The PBPK model was expanded by (1) effect compartments to describe vorinostat concentration-time profiles in peripheral blood mononuclear cells (PBMCs), (2) an indirect response model to predict the HDAC inhibition, and (3) a thrombocyte model to predict the dose-limiting thrombocytopenia. Parameterization of drug and system-specific processes was based on published and unpublished in silico, in vivo, and in vitro data. The PBPK modeling software used was PK-Sim and MoBi.

RESULTS

The PBPK/PD model suggests dosages of 80 and 230 mg/m² for children of 0-1 and 1-17 years of age, respectively. In comparison with the approved standard treatment, in silico trials reveal 11 dosing regimens (9 oral, and 2 intravenous infusion rates) increasing the HDAC inhibition by an average of 31%, prolonging the HDAC inhibition by 181%, while only decreasing the circulating thrombocytes to a tolerable 53%. The most promising dosing regimen prolongs the HDAC inhibition by 509%.

CONCLUSIONS

Thoroughly developed PBPK models enable dosage recommendations in pediatric patients and integrated PBPK/PD models, considering PD biomarkers (e.g., HDAC activity and platelet count), are well suited to guide future efficacy trials by identifying dosing regimens potentially superior to standard dosing regimens.

Inhibiting Histone Deacetylase as a Means to Reverse Resistance to Angiogenesis Inhibitors: Phase I Study of Abexinostat Plus Pazopanib in Advanced Solid Tumor Malignancies

Purpose This phase I trial evaluated epigenetic modulation of vascular endothelial growth factor (VEGF) and hypoxia-inducible factor by using a histone deacetylase abexinostat in combination with pazopanib to enhance response and reverse resistance. Patients and Methods Pazopanib was administered once a day on days 1 to 28 and abexinostat was administered orally twice a day on days 1 to 5, 8 to 12, and 15 to 19 (schedule A) or on days 1 to 4, 8 to 11, and 15 to 18 (schedule B). Dose escalation (3 + 3 design) in all solid tumors was followed by dose expansion in renal cell carcinoma (RCC). Results Fifty-one patients with RCC (N = 22) were enrolled, including 30 (59%) with one or more lines of prior VEGF-targeting therapy. Five dose-limiting toxicities, including fatigue (n = 2), thrombocytopenia (n = 2), and elevated AST/ALT (n = 1), were observed with schedule A; one dose-limiting toxicity was observed (elevated AST/ALT) was observed with schedule B. Grade ≥ 3 related adverse events included fatigue (16%), thrombocytopenia (16%), and neutropenia (10%). The recommended phase II dose was established as abexinostat 45 mg/m² twice a day administered per schedule B plus pazopanib 800 mg/d. Objective response rate was 21% overall and 27% in the RCC subset. Median duration of response was 9.1 months (1.2 to > 49 months). Eight patients (16%) had durable control of disease for > 12 months. Durable tumor regressions were observed in seven (70%) of 10 patients with pazopanib-refractory disease, including one patients with RCC with ongoing response > 3.5 years. Peripheral blood histone acetylation and HDAC2 gene expression were associated with durable response to treatment. Conclusion Abexinostat is well tolerated in combination with pazopanib, allowing prolonged exposure and promising durable responses in pazopanib- and other VEGF inhibitor-refractory tumors, which supports epigenetically mediated reversal of treatment resistance.

Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment

Purpose

Adverse effects related to anti-cancer drug treatment influence patient’s quality of life, have an impact on the realized dosing regimen, and can hamper response to treatment. Quantitative models that relate drug exposure to the dynamics of adverse effects have been developed and proven to be very instrumental to optimize dosing schedules. The aims of this review were (i) to provide a perspective of how adverse effects of anti-cancer drugs are modeled and (ii) to report several model structures of adverse effect models that describe relationships between drug concentrations and toxicities.

Methods

Various quantitative pharmacodynamic models that model adverse effects of anti-cancer drug treatment were reviewed.

Results

Quantitative models describing relationships between drug exposure and myelosuppression, cardiotoxicity, and graded adverse effects like fatigue, hand-foot syndrome (HFS), rash, and diarrhea have been presented for different anti-cancer agents, including their clinical applicability.

Conclusions

Mathematical modeling of adverse effects proved to be a helpful tool to improve clinical management and support decision-making (especially in establishment of the optimal dosing regimen) in drug development. The reported models can be used as templates for modeling a variety of anti-cancer-induced adverse effects to further optimize therapy.

A Phase I/II Multicenter, Open-Label Study of the Oral Histone Deacetylase Inhibitor Abexinostat in Relapsed/Refractory Lymphoma

PURPOSE

Additional targeted therapeutics are needed for the treatment of lymphoma. Abexinostat is an oral pan-histone deacetylase inhibitor (HDACi) displaying potent activity in preclinical models. We conducted a multicenter phase I/II study (N = 55) with single-agent abexinostat in relapsed/refractory lymphoma.

EXPERIMENTAL DESIGN

In phase I, 25 heavily pretreated patients with any lymphoma subtype received oral abexinostat ranging from 30 to 60 mg/m(2) twice daily 5 days/week for 3 weeks or 7 days/week given every other week. Phase II evaluated abexinostat at the maximum tolerated dose in 30 patients with relapsed/refractory follicular lymphoma or mantle cell lymphoma.

RESULTS

The recommended phase II dose was 45 mg/m(2) twice daily (90 mg/m(2) total), 7 days/week given every other week. Of the 30 follicular lymphoma and mantle cell lymphoma patients enrolled in phase II, 25 (14 follicular lymphoma, 11 mantle cell lymphoma) were response-evaluable. Tumor size was reduced in 86% of follicular lymphoma patients with an investigator-assessed ORR of 64.3% for evaluable patients [intent-to-treat (ITT) ORR 56.3%]. Median duration of response was not reached, and median progression-free survival (PFS) was 20.5 months (1.2-22.3+). Of responding follicular lymphoma patients, 89% were on study/drug >8 months. In mantle cell lymphoma, the ORR was 27.3% for evaluable patients (ITT ORR 21.4%), and median PFS was 3.9 months (range, 0.1-11.5). Grade 3-4 treatment-related adverse events (phase II) with ≥ 10% incidence were thrombocytopenia (20%), fatigue (16.7%), and neutropenia (13.3%) with rare QTc prolongation and no deaths.

CONCLUSIONS

The pan-HDACi, abexinostat, was overall well tolerated and had significant clinical activity in follicular lymphoma, including highly durable responses in this multiply relapsed patient population.

The role of epigenetics in kidney malignancies

Introduction

Renal cell carcinomas (RCC) are collectively the third most common type of genitourinary neoplasms, surpassed only by prostate and bladder cancer. Cure rates for renal cell carcinoma are related to tumor grade and stage; therefore, diagnostic methods for early detection and new therapeutic modalities are of paramount importance. Epigenetics can be defined as inherited modifications in gene expression that are not encoded in the DNA sequence itself. Epigenetics may play an important role in the pursuit of early diagnosis, accurate prognostication and identification of new therapeutic targets.

Material and methods

We used PubMed to conduct a comprehensive search of the English medical literature using search terms including epigenetics, DNA methylation, histone modification, microRNA regulation (miRNA) and RCC. In this review, we discuss the potential application of epigenetics in the diagnosis, prognosis and treatment of kidney cancer.

Results

During the last decade, many different types of epigenetic alterations of DNA have been found to be associated with malignant renal tumors. This has led to the research of the diagnostic and prognostic implications of these changes in renal malignancies as well as to the development of novel drugs to target these changes, with the aim of achieving a survival benefit.

Conclusions

Epigenetics has become a promising field in cancer research. The potential to achieve early detection and accurate prognostication in kidney cancer might be feasible through the application of epigenetics. The possibility to reverse these epigenetic changes with new therapeutic agents motivates researchers to continue pursuing better treatment options for kidney cancer and other malignancies.