Body of evidence and approaches applied in the clinical development programme of fixed-dose combinations in the European Union from 2010 to 2016.

AIMS: To provide insights into the clinical development pathway for fixed-dose combinations (FDCs), to consider strategies, and to elucidate the path to approval by assessing the body of evidence, as summarized in the European Public Assessment Reports. METHODS: The main resource was the European Public Assessment Reports for 36 FDCs, which included 239 clinical trials with 157 514 patients. The analyses focused on how prior knowledge of the active substances or combination, use of pharmacokinetic-pharmacodynamic modelling, and clinical trial design choice impact the size and strategy of the clinical development programme. RESULTS: FDC products primarily comprised 2 previously approved components (21/36, 71%) and had only 1 approved combination (21/36, 71%). Utilizing previously approved active substances resulted in fewer clinical trials, arms and patients, but FDC doses studied in the clinical development programme. Furthermore, dose-finding trials were performed for less than half of FDCs consisting of 2 previously approved active substances. The standard approach to demonstrate contribution of active substances was through a factorial or single combination study. Finally, the use of pharmacokinetic modelling showed a significant decrease in the number of FDC doses studied. CONCLUSIONS: The field of FDCs seems to be on the rise, utilizing new molecular entities, prior knowledge and re-profiling drugs. However, a way to move FDC development forward might be through new regulatory and scientific paradigms, in which it is encouraged to utilize model-based approaches to develop FDCs with multiple dose levels and dose ratios for exposure-based treatment that will enable personalization.

Pharmacodynamic modelling reveals synergistic interaction between docetaxel and SCO-101 in a docetaxel-resistant triple negative breast cancer cell line.

One of the primary barriers in treating cancer patients is the development of resistance to the available treatments. This is the case for treatment of triple negative breast cancer (TNBC) with docetaxel, which is part of the neoadjuvant treatment for TNBC. The novel compound SCO-101 is under investigation for its potential treatment effect in several types of drug resistant cancer. The aim of this study was to establish a pharmacodynamic model that captures the effect of docetaxel, SCO-101, and the combination on cell survival in docetaxel resistant MDA-MB-231 TNBC cells. Several combination models were compared and a recently published combination model, the general pharmacodynamic interaction model (GPDI), provided the best fit. The model allowed for description and quantification of the interaction between docetaxel and SCO-101 with respects to both maximal effect and potency. Based on this model, SCO-101 has a synergistic effect with docetaxel. This synergy is not present in the maximal effect, but the combination of SCO-101 and docetaxel showed an approximately 60% increase in potency compared to docetaxel alone. Furthermore, the predicted model surface for the combination provided key information regarding promising dose ratios and dose levels for further studies of the combination. Lastly, the study presents a use case for the GPDI model, which provides a way to quantify and interpret drug-drug interactions.

Demonstrating Contribution of Components of Fixed-Dose Drug Combinations Through Longitudinal Exposure-Response Analysis.

Exposure-response (ER) modeling for fixed-dose combinations (FDC) has previously been found to have an inflated false positive rate (FP), i.e., observing a significant effect of FDC components when no true effect exists. Longitudinal exposure-response (LER) analysis utilizes the time course of the data and is valid for several clinical endpoints for FDCs. The aim of the study was to investigate if LER is applicable for the validation of FDCs by demonstrating the contribution of each component to the overall effect without inflation of FP rates. FP and FN rates associated with ER and LER analysis were investigated using stochastic simulation and estimation. Four hundred thirty-two scenarios with varying numbers of patients, duration, sampling frequency, dose distribution, design, and drug activity were analyzed using a range of linear, log-linear, and non-linear models to asses FP and FN rates. Lastly, the impact of the clinical trial parameters was investigated. LER analyses provided well-controlled FP rates of the expected 5% or less; however, in low information clinical trials consisting of 30 patients, 4 samples, and 20 days, LER analyses lead to inflated FN rates. Parameter investigation showed that when the clinical trial includes sufficient patients, duration, samples, and an appropriate trial design, the FN rates are in general below the expected 5% for LER analysis. Based on the results, LER analysis can be used for the validation of FDCs and fixed ratio drug combinations. The method constitutes a new avenue for providing evidence that demonstrates the contribution of each component to the overall clinical effect.

Assessment of different 3D culture systems to study tumor phenotype and chemosensitivity in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant disease with a very poor prognosis, due to the influence of the tumor stroma, which promotes tumor growth, early invasion and chemoradiation resistance. Efforts to develop models for identifying novel anticancer therapeutic compounds have been hampered by the limited ability of in vitro models to mimic these in vivo tumor-stroma interactions. This has led to the development of various three-dimensional (3D) culture platforms recapitulating the in vivo tumor-stroma crosstalk and designed to better understand basic cancer processes and screen drug action. However, a consensus for different experimental 3D platforms is still missing in PDAC. We compared four PDAC cell lines of different malignancy grown in 2D monolayers to three of the more commonly used 3D techniques (ultralow adhesion concave microwells, Matrigel inclusion and organotypic systems) and to tumors derived from their orthotopic implantation in mice. In these 3D platforms, we observed that cells grow with very different tumor morphologies and the organotypic setting most closely resembles the tumor cytoarchitecture obtained by orthotopically implanting the four cell lines in mice. We then analyzed the molecular and cellular responses of one of these cell lines to epidermal growth factor receptor (EGFR) stimulation with EGF and inhibition with erlotinib and found that only in the 3D platforms, and especially the organotypic, cells: i) responded to EGF by changing the expression of signalling components underlying cell-stroma crosstalk and tissue architecture, growth, invasion and drug resistance (E-cadherin, EGFR, ezrin, ß1 integrin, NHERF1 and HIF-1α) similar to those reported in vivo; ii) had stimulated growth and increased erlotinib sensitivity in response to EGF, more faithfully mimicking their known in vivo behaviour. Altogether, these results, indicate the organotypic as the most relevant physiological 3D system to study the complex tumor stroma interactions driving progression and determining chemio-resistance.

Monocarboxylate Transporters MCT1 and MCT4 Regulate Migration and Invasion of Pancreatic Ductal Adenocarcinoma Cells.

OBJECTIVES: Novel treatments for pancreatic ductal adenocarcinoma (PDAC) are severely needed. The aim of this work was to explore the roles of H-lactate monocarboxylate transporters 1 and 4 (MCT1 and MCT4) in PDAC cell migration and invasiveness. METHODS: Monocarboxylate transporter expression, localization, activity, and function were explored in human PDAC cells (MIAPaCa-2, Panc-1, BxPC-3, AsPC-1) and normal human pancreatic ductal epithelial (HPDE) cells, by quantitative polymerase chain reaction, immunoblotting, immunocytochemistry, lactate flux, migration, and invasion assays. RESULTS: MCT1 and MCT4 (messenger RNA, protein) were robustly expressed in all PDAC lines, localizing to the plasma membrane. Lactate influx capacity was highest in AsPC-1 cells and lowest in HPDE cells and was inhibited by the MCT inhibitor α-cyano-4-hydroxycinnamate (4-CIN), MCT1/MCT2 inhibitor AR-C155858, or knockdown of MCT1 or MCT4. PDAC cell migration was largely unaffected by MCT1/MCT2 inhibition or MCT1 knockdown but was reduced by 4-CIN and by MCT4 knockdown (BxPC-3). Invasion measured in Boyden chamber (BxPC-3, Panc-1) and spheroid outgrowth (BxPC-3) assays was attenuated by 4-CIN and AR-C155858 and by MCT1 or MCT4 knockdown. CONCLUSIONS: Human PDAC cells exhibit robust MCT1 and MCT4 expression and partially MCT1- and MCT4-dependent lactate flux. PDAC cell migration is partially dependent on MCT4; and invasion, on MCT1 and MCT4. Inhibition of MCT1 and MCT4 may have clinical relevance in PDAC.