Pegylated liposome encapsulating docetaxel using microfluidic mixing technique: Process optimization and results in breast cancer models.

The development of nanoparticles could help to improve the efficacy/toxicity balance of drugs. This project aimed to develop liposomes and immunoliposomes using microfluidic mixing technology.Various formulation tests were carried out to obtain liposomes that met the established specifications. The liposomes were then characterized in terms of size, polydispersity index (PDI), docetaxel encapsulation rate and lamellarity. Antiproliferative activity was tested in human breast cancer models ranging from near-negative (MDA-MB-231), positive (MDA-MB-453) to HER2 positive. Pharmacokinetic studies were performed in C57BL/6 mice.Numerous batches of liposomes were synthesised using identical molar ratios and by varying the microfluidic parameters TFR, FRR and buffer. All synthesized liposomes have a size < 200 nm, but only Lipo-1, Lipo-6, Lipo-7, Lipo-8 have a PDI < 0.2, which meets our initial requirements. The size of the liposomes was correlated with the total FRR, for a 1:1 FRR the size is 122.2 ± 12.3 nm, whereas for a 1:3 FRR the size obtained is 163.4 ± 34.0 nm (p = 0.019. Three batches of liposomes were obtained with high docetaxel encapsulation rates > 80 %. Furthermore, in vitro studies on breast cancer cell lines demonstrated the efficacy of liposomes obtained by microfluidic mixing technique. These liposomes also showed improved pharmacokinetics compared to free docetaxel, with a longer half-life and higher AUC (3-fold and 3.5-fold increase for the immunoliposome, respectively).This suggests that switching to the microfluidic process will produce batches of liposomes with the same characteristics in terms of in vitro properties and efficacy, as well as the ability to release the encapsulated drug over time in vivo. This time-efficiency of the microfluidic technique is critical, especially in the early stages of development.

Conditional generation of free radicals by selective activation of alkoxyamines: towards more effective and less toxic targeting of brain tumors.

Brain tumors are an important cause of suffering and death. Glioblastoma are the most frequent primary tumors of the central nervous system in adults. They are associated with a very poor prognosis, since only 10% of GBM patients survive 5 years after diagnosis. Medulloblastoma are the most frequent brain malignancies in childhood; they affect the cerebellum in children under 10 years of age in 75% of cases. The current multimodal treatment comes at the expense of serious and often long-lasting side effects. Herein, we propose the synthesis of a library of novel alkoxyamines as anticancer drug candidates. The most efficient molecule, ALK4, was selected based on its ability to inhibit both survival and migration of GBM and MB cells in 2D cultures and in 3D tumor spheroids. A fluorescent derivative was used to show the early cytosolic accumulation of ALK4 in tumor cells. Spontaneous homolysis of ALK4 led to the release of alkyl radicals, which triggered the generation of reactive oxygen species, fragmentation of the mitochondrial network and ultimately apoptosis. To control its homolytic process, the selected alkoxyamine was bioconjugated to a peptide selectively recognized by matrix metalloproteases. This bioconjugate, named ALK4-MMPp, successfully inhibited survival, proliferation, and invasion of GBM and MB tumor micromasses. We further developed innovative brain and cerebellum organotypic models to monitor treatment response over time. It confirmed that ALK4-MMPp significantly impaired tumor progression, while no significant damage was observed on normal brain tissue. Lastly, we showed that ALK4-MMPp was well-tolerated in vivo by zebrafish embryos. This study provides a new strategy to control the activation of alkoxyamines, and revealed the bioconjugate ALK4-MMPp bioconjugate as a good anticancer drug candidate.

Nanotherapeutics Plus Immunotherapy in Oncology: Who Brings What to the Table?

While the number of oncology-related nanotherapeutics and immunotherapies is constantly increasing, cancer patients still suffer from a lack of efficacy and treatment resistance. Among the investigated strategies, patient selection and combinations appear to be of great hope. This review will focus on combining nanotherapeutics and immunotherapies together, how they can dually optimize each other to face such limits, bringing us into a new field called nano-immunotherapy. While looking at current clinical trials, we will expose how passive immunotherapies, such as antibodies and ADCs, can boost nanoparticle tumor uptake and tumor cell internalization. Conversely, we will study how immunotherapies can benefit from nanotherapeutics which can optimize their lipophilicity, permeability, and distribution (e.g., greater tumor uptake, BBB crossing, etc.), tumor, tumor microenvironment, and immune system targeting properties.

Tumor growth monitoring in breast cancer xenografts: A good technique for a strong ethic.

PURPOSE: Although recent regulations improved conditions of laboratory animals, their use remains essential in cancer research to determine treatment efficacy. In most cases, such experiments are performed on xenografted animals for which tumor volume is mostly estimated from caliper measurements. However, many formulas have been employed for this estimation and no standardization is available yet. METHODS: Using previous animal studies, we compared all formulas used by the scientific community in 2019. Data were collected from 93 mice orthotopically xenografted with human breast cancer cells. All formulas were evaluated and ranked based on correlation and lower mean relative error. They were then used in a Gompertz quantitative model of tumor growth. RESULTS: Seven formulas for tumor volume estimation were identified and a statistically significant difference was observed among them (ANOVA test, p < 2.10-16), with the ellipsoid formula (1/6 π × L × W × (L + W)/2) being the most accurate (mean relative error = 0.272 ± 0.201). This was confirmed by the mathematical modeling analysis where this formula resulted in the smallest estimated residual variability. Interestingly, such result was no longer valid for tumors over 1968 ± 425 mg, for which a cubic formula (L x W x H) should be preferred. MAIN FINDINGS: When considering that tumor volume remains under 1500mm3, to limit animal stress, improve tumor growth monitoring and go toward mathematic models, the following formula 1/6 π × L × W x (L + W)/2 should be preferred.

Enhanced Antisense Oligonucleotide Delivery Using Cationic Liposomes Grafted with Trastuzumab: A Proof-of-Concept Study in Prostate Cancer.

Prostate cancer (PCa) is the second most common cancer in men worldwide and the fifth leading cause of death by cancer. The overexpression of TCTP protein plays an important role in castration resistance. Over the last decade, antisense technology has emerged as a rising strategy in oncology. Using antisense oligonucleotide (ASO) to silence TCTP protein is a promising therapeutic option-however, the pharmacokinetics of ASO does not always meet the requirements of proper delivery to the tumor site. In this context, developing drug delivery systems is an attractive strategy for improving the efficacy of ASO directed against TCTP. The liposome should protect and deliver ASO at the intracellular level in order to be effective. In addition, because prostate cancer cells express Her2, using an anti-Her2 targeting antibody will increase the affinity of the liposome for the cell and optimize the intratumoral penetration of the ASO, thus improving efficacy. Here, we have designed and developed pegylated liposomes and Her2-targeting immunoliposomes. Mean diameter was below 200 nm, thus ensuring proper enhanced permeation and retention (EPR) effect. Encapsulation rate for ASO was about 40%. Using human PC-3 prostate cancer cells as a canonical model, free ASO and ASO encapsulated into either liposomes or anti-Her2 immunoliposomes were tested for efficacy in vitro using 2D and 3D spheroid models. While the encapsulated forms of ASO were always more effective than free ASO, we observed differences in efficacy of encapsulated ASO. For short exposure times (i.e., 4 h) ASO liposomes (ASO-Li) were more effective than ASO-immunoliposomes (ASO-iLi). Conversely, for longer exposure times, ASO-iLi performed better than ASO-Li. This pilot study demonstrates that it is possible to encapsulate ASO into liposomes and to yield antiproliferative efficacy against PCa. Importantly, despite mild Her2 expression in this PC-3 model, using a surface mAb as targeting agent provides further efficacy, especially when exposure is longer. Overall, the development of third-generation ASO-iLi should help to take advantage of the expression of Her2 by prostate cancer cells in order to allow greater specificity of action in vivo and thus a gain in efficacy.

Population modeling of tumor growth curves and the reduced Gompertz model improve prediction of the age of experimental tumors.

Tumor growth curves are classically modeled by means of ordinary differential equations. In analyzing the Gompertz model several studies have reported a striking correlation between the two parameters of the model, which could be used to reduce the dimensionality and improve predictive power. We analyzed tumor growth kinetics within the statistical framework of nonlinear mixed-effects (population approach). This allowed the simultaneous modeling of tumor dynamics and inter-animal variability. Experimental data comprised three animal models of breast and lung cancers, with 833 measurements in 94 animals. Candidate models of tumor growth included the exponential, logistic and Gompertz models. The exponential and-more notably-logistic models failed to describe the experimental data whereas the Gompertz model generated very good fits. The previously reported population-level correlation between the Gompertz parameters was further confirmed in our analysis (R2 > 0.92 in all groups). Combining this structural correlation with rigorous population parameter estimation, we propose a reduced Gompertz function consisting of a single individual parameter (and one population parameter). Leveraging the population approach using Bayesian inference, we estimated times of tumor initiation using three late measurement timepoints. The reduced Gompertz model was found to exhibit the best results, with drastic improvements when using Bayesian inference as compared to likelihood maximization alone, for both accuracy and precision. Specifically, mean accuracy (prediction error) was 12.2% versus 78% and mean precision (width of the 95% prediction interval) was 15.6 days versus 210 days, for the breast cancer cell line. These results demonstrate the superior predictive power of the reduced Gompertz model, especially when combined with Bayesian estimation. They offer possible clinical perspectives for personalized prediction of the age of a tumor from limited data at diagnosis. The code and data used in our analysis are publicly available at https://github.com/cristinavaghi/plumky.

Tumor uptake and associated greater efficacy of anti-Her2 immunoliposome does not rely on Her2 expression status: study of a docetaxel-trastuzumab immunoliposome on Her2+ breast cancer model (SKBR3).

Nanoparticles have been used for decades in breast cancer. More recently, anti-human epidermal receptor 2 (Her2) immunoliposomes are of rising interest. However, recent studies have questioned the actual relevance of using anti-Her2 antibodies to improve liposome distribution and efficacy. Using standard thin-film method and maleimide linker, we have synthesized a 140-nm docetaxel-trastuzumab immunoliposome. This nanoparticle was then tested on a canonical Her2-overexpressing breast cancer model (i.e., SKBR3), using 3D spheroids and xenografted mice. Its efficacy was compared with free docetaxel + trastuzumab, liposomal docetaxel + free trastuzumab and to reference antibody-drug conjugate trastuzumab-emtansine (T-DM1). Immunoliposomes resulted in better efficacy as compared with all other treatments, both in vitro and in vivo. To explain such an improvement, immunoliposome biodistribution was investigated using live imaging in xenografted mice. Surprisingly, no difference in tumor uptake was found between anti-Her2 immunoliposomes and standard docetaxel liposomes (i.e., 1.9 ± 1.2 vs. 1.7 ± 0.5% at the end of treatment and 1.4 ± 0.6 vs. 1.6 ± 0.4% at the end of the study, respectively, P > 0.05). We hypothesized that passive targeting (i.e., enhanced permeation and retention effect) contributed more to tumor distribution than active targeting and that the observed differences in efficacy could come from a better internalization of immunoliposomes into Her2+ cells as compared with standard liposomes, and not from a higher specificity towards tumor tissue.

Is There Any Room for Pharmacometrics With Immuno-Oncology Drugs? Input from the EORTC-PAMM Course on Preclinical and Early-phase Clinical Pharmacology.

As part of the Pharmacology & Molecular Mechanisms (PAMM) Group, European Organization for Research and Treatment on Cancer (EORTC) 2019 winter Meeting Educational sessions, special focus has been placed on strategies to be undertaken to reduce the attrition rate when developing immune-oncology drugs. Immune checkpoint inhibitors have been game-changing drugs in several settings over the past decade such as melanoma and lung cancer. However, during the last years a rising number of studies failing to further improve clinical outcome in patients with cancer was recorded. Extensive pharmacometrics such as pharmacokinetics/pharmacodynamics modeling support should help to overcome the current glass ceiling that has apparently been reached with immuno-oncology drugs (IOD). In particular, it should help in the issue of setting up combinatorial regimen (i.e. combining immune checkpoint inhibitors with cytotoxics, anti-angiogenesis or targeted therapies) that can no longer be addressed when following standard trial-and-error approaches, but rather by using mathematical-derived algorithms as decision-making tools by investigators for rational design. In routine clinical setting, developing therapeutic drug monitoring of immune checkpoint inhibitors with adaptive dosing strategies has been a long-neglected strategy. Still, substantial improvements might be achieved using dedicated tools for precision medicine and personalized medicine in immunotherapy.

From 3D spheroids to tumor bearing mice: efficacy and distribution studies of trastuzumab-docetaxel immunoliposome in breast cancer.

PURPOSE: Nanoparticles are of rising interest in cancer research, but in vitro canonical cell monolayer models are not suitable to evaluate their efficacy when prototyping candidates. Here, we developed three-dimensional (3D) spheroid models to test the efficacy of trastuzumab-docetaxel immunoliposomes in breast cancer prior to further testing them in vivo. MATERIALS AND METHODS: Immunoliposomes were synthesized using the standard thin film method and maleimide linker. Two human breast cancer cell lines varying in Her2 expression were tested: Her2+ cells derived from metastatic site: mammary breast MDA-MB-453 and triple-negative MDA-MB-231 cells. 3D spheroids were developed and tested with fluorescence detection to evaluate viability. In vivo efficacy and biodistribution studies were performed on xenograft bearing nude mice using fluorescent and bioluminescent imaging. RESULTS: In vitro, antiproliferative efficacy was dependent upon cell type, size of the spheroids, and treatment scheduling, resulting in subsequent changes between tested conditions and in vivo results. Immunoliposomes performed better than free docetaxel + free trastuzumab and ado-trastuzumab emtansine (T-DM1). On MDA-MB-453 and MDA-MB-231 cell growth was reduced by 76% and 25%, when compared to free docetaxel + free trastuzumab and by 85% and 70% when compared to T-DM1, respectively. In vivo studies showed tumor accumulation ranging from 3% up to 15% of the total administered dose in MDA-MB-453 and MDA-MB-231 bearing mice. When compared to free docetaxel + free trastuzumab, tumor growth was reduced by 89% (MDA-MB-453) and 25% (MDA-MB-231) and reduced by 66% (MDA-MB-453) and 29% (MDA-MB-231) when compared to T-DM1, an observation in line with data collected from 3D spheroids experiments. CONCLUSION: We demonstrated the predictivity of 3D in vitro models when developing and testing nanoparticles in experimental oncology. In vitro and in vivo data showed efficient drug delivery with higher efficacy and prolonged survival with immunoliposomes when compared to current anti-Her2 breast cancer strategies.

Turning cold tumors into hot tumors: harnessing the potential of tumor immunity using nanoparticles.

INTRODUCTION: Immune checkpoint inhibitors have considerably changed the landscape of oncology. However apart from world-acclaimed success stories limited to melanoma and lung cancer, many solid tumors failed to respond to immune checkpoint inhibitors due to limited immunogenicity, unfavorable tumor micro-environments (TME), lack of infiltrating T lymphocytes or increases in Tregs. Areas covered: Combinatorial strategies are foreseen as the future of immunotherapy and using cytotoxics or modulating agents is expected to boost the efficacy of immune checkpoint inhibitors. In this respect, nanoparticles displaying unique pharmacokinetic features such as tumor targeting properties, optimal payload delivery and long-lasting interferences with TME, are promising candidates for such combinations. This review covers the basis, expectancies, limits and pitfalls of future combination between nanoparticles and immune check point inhibitors. Expert opinion: Nanoparticles allow optimal delivery of variety of payloads in tumors while sparing healthy tissue, thus triggering immunogenic cell death. Depleting tumor stroma could further help immune cells and monoclonal antibodies to better circulate in the TME, plus immune-modulating properties of the charged cytotoxics. Finally, nanoparticles themselves present immunogenicity and antigenicity likely to boost immune response at the tumor level.

Pharmacokinetics variability: Why nanoparticles are not just magic-bullets in oncology.

Developing nanoparticles to improve the specificity of anticancer agents towards tumor tissue and to better control drug delivery is a rising strategy in oncology. An increasing number of forms (e.g., conjugated nanoparticles, liposomes, immunoliposomes…) are now available on the shelves and numerous other scaffolds (e.g., dendrimeres, nanospheres, squalenes …) are currently at various stages of development. However, as of today most nanoparticles made available remain lipidic carriers. Pharmacokinetic variability is a major, yet largely underestimated issue with liposomal nanoparticles. A wide variety of causes (e.g., tumor type and disease staging, comorbidities, patient's immune system) can explain this variability, which can in return negatively impact pharmacodynamic endpoints such as poor efficacy or severe toxicities. This review aims to cover the main causes for erratic pharmacokinetics observed with most nanoparticles, especially liposomes used in oncology. Should the main causes of such variability be identified, specific studies in non-clinical or clinical development stages could be undertaken using dedicated models (i.e., mechanistic or semi-mechanistic mathematical models such as PBPK approaches) to better describe nanoparticles pharmacokinetics and decipher PK/PD relationships. In addition, identifying relevant biomarkers or parameters likely to impact nanoparticles pharmacokinetics would allow for either the modification of their characteristics to reduce the influence of the expected variability during development phases or the development of biomarker-based adaptive dosing strategies to maintain an optimal efficacy/toxicity balance. Broadly, we call for the development of comprehensive distribution studies and state-of-the-art modeling support to better understand and anticipate nanoparticle pharmacokinetics in oncology.

Docetaxel-trastuzumab stealth immunoliposome: development and in vitro proof of concept studies in breast cancer.

BACKGROUND: Trastuzumab plus docetaxel is a mainstay to treat HER2-positive breast cancers. However, developing nanoparticles could help to improve the efficacy/toxicity balance of this doublet by improving drug trafficking and delivery to tumors. This project aimed to develop an immunoliposome in breast cancer, combining docetaxel encapsulated in a stealth liposome engrafted with trastuzumab, and comparing its performances on human breast cancer cell lines with standard combination of docetaxel plus trastuzumab. METHODS: Several strategies to engraft trastuzumab to pegylated liposomes were tested. Immunoliposomes made of natural (antibody nanoconjugate-1 [ANC-1]) and synthetic lipids (ANC-2) were synthesized using standard thin film method and compared in size, morphology, docetaxel encapsulation, trastuzumab engraftment rates and stability. Antiproliferative activity was tested on human breast cancer models ranging from almost negative (MDA-MB-231), positive (MDA-MB-453) to overexpressing (SKBR3) HER2. Finally, cell uptake of ANC-1 was studied by electronic microscopy. RESULTS: ANC-1 showed a greater docetaxel encapsulation rate (73%±6% vs 53%±4%) and longer stability (up to 1 week) as compared with ANC-2. Both ANC presented particle size ≤150 nm and showed similar or higher in vitro antiproliferative activities than standard treatment, ANC-1 performing better than ANC-2. The IC50s for docetaxel combined to free trastuzumab were 8.7±4, 2±0.7 and 6±2 nM with MDA-MB-231, MDA-MB-453 and SKBR3, respectively. The IC50s for ANC-1 were 2.5±1, 1.8±0.6 and 3.4±0.8 nM and for ANC-2 were 1.8±0.3 nM, 2.8±0.8 nM and 6.8±1.8 nM with MDA-MB-231, MDA-MB-453 and SKBR3, respectively. Cellular uptake appeared to depend on HER2 expression, the higher the expression, the higher the uptake. CONCLUSION: In vitro results suggest that higher antiproliferative efficacy and efficient drug delivery can be achieved in breast cancer models using nanoparticles.

Seek and destroy: improving PK/PD profiles of anticancer agents with nanoparticles.

INTRODUCTION: The Pharmacokinetics/pharmacodynamics (PK/PD) relationships with cytotoxics are usually based on a steepening concentration-effect relationship; the greater the drug amount, the greater the effect. The Maximum Tolerated Dose paradigm, finding the balance between efficacy, while keeping toxicities at their manageable level, has been the rule of thumb for the last 50-years. Developing nanodrugs is an appealing strategy to help broaden this therapeutic window. The fact that efficacy and toxicity with cytotoxics are intricately linked is primarily due to the complete lack of specificity toward the tumor tissue during their distribution phase. Because nanoparticles are expected to better target tumor tissue while sparing healthy cells, accumulating large amounts of cytotoxics in tumors could be achieved in a safer way. Areas covered: This review aims at presenting how nanodrugs present unique features leading to reconsidering PK/PD relationships of anticancer agents. Expert commentary: The constant interplay between carrier PK, interactions with cancer cells, payload release, payload PK, target expression and target engagement, makes picturing the exact PK/PD relationships of nanodrugs particularly challenging. However, those improved PK/PD relationships now make the once contradictory higher efficacy and lower toxicities requirement an achievable goal in cancer patients.

Antiviral efficacy of favipiravir against Ebola virus: A translational study in cynomolgus macaques.

BACKGROUND: Despite repeated outbreaks, in particular the devastating 2014-2016 epidemic, there is no effective treatment validated for patients with Ebola virus disease (EVD). Among the drug candidates is the broad-spectrum polymerase inhibitor favipiravir, which showed a good tolerance profile in patients with EVD (JIKI trial) but did not demonstrate a strong antiviral efficacy. In order to gain new insights into the antiviral efficacy of favipiravir and improve preparedness and public health management of future outbreaks, we assess the efficacy achieved by ascending doses of favipiravir in Ebola-virus-infected nonhuman primates (NHPs). METHODS AND FINDINGS: A total of 26 animals (Macaca fascicularis) were challenged intramuscularly at day 0 with 1,000 focus-forming units of Ebola virus Gabon 2001 strain and followed for 21 days (study termination). This included 13 animals left untreated and 13 treated with doses of 100, 150, and 180 mg/kg (N = 3, 5, and 5, respectively) favipiravir administered intravenously twice a day for 14 days, starting 2 days before infection. All animals left untreated or treated with 100 mg/kg died within 10 days post-infection, while animals receiving 150 and 180 mg/kg had extended survival (P < 0.001 and 0.001, respectively, compared to untreated animals), leading to a survival rate of 40% (2/5) and 60% (3/5), respectively, at day 21. Favipiravir inhibited viral replication (molecular and infectious viral loads) in a drug-concentration-dependent manner (P values < 0.001), and genomic deep sequencing analyses showed an increase in virus mutagenesis over time. These results allowed us to identify that plasma trough favipiravir concentrations greater than 70-80 µg/ml were associated with reduced viral loads, lower virus infectivity, and extended survival. These levels are higher than those found in the JIKI trial, where patients had median trough drug concentrations equal to 46 and 26 µg/ml at day 2 and day 4 post-treatment, respectively, and suggest that the dosing regimen in the JIKI trial was suboptimal. The environment of a biosafety level 4 laboratory introduces a number of limitations, in particular the difficulty of conducting blind studies and performing detailed pharmacological assessments. Further, the extrapolation of the results to patients with EVD is limited by the fact that the model is fully lethal and that treatment initiation in patients with EVD is most often initiated several days after infection, when symptoms and high levels of viral replication are already present. CONCLUSIONS: Our results suggest that favipiravir may be an effective antiviral drug against Ebola virus that relies on RNA chain termination and possibly error catastrophe. These results, together with previous data collected on tolerance and pharmacokinetics in both NHPs and humans, support a potential role for high doses of favipiravir for future human interventions.

Claramines: A New Class Of Broad-Spectrum Antimicrobial Agents With Bimodal Activity.

The emergence of multidrug-resistant bacteria and pathogens has created an urgent need for the development of new antibiotics. Herein we report our investigations into the broad-spectrum activity of an easily prepared water-soluble polyaminosterol compound, namely claramine A1, against both drug-sensitive and drug-resistant Gram-negative and Gram-positive bacterial strains. We also report its peculiar mechanism of action, which differs from that of all the other well-known classes of antibiotics, toward Gram-negative and Gram-positive bacteria. Given their low cytotoxicity, this class of compounds based on claramine A1 could constitute an effective response to combat the emergence of multidrug-resistant bacteria and nosocomial diseases.

Favipiravir pharmacokinetics in Ebola-Infected patients of the JIKI trial reveals concentrations lower than targeted.

BACKGROUND: In 2014-2015, we assessed favipiravir tolerance and efficacy in patients with Ebola virus (EBOV) disease (EVD) in Guinea (JIKI trial). Because the drug had never been used before for this indication and that high concentrations of the drugs were needed to achieve antiviral efficacy against EBOV, a pharmacokinetic model had been used to propose relevant dosing regimen. Here we report the favipiravir plasma concentrations that were achieved in participants in the JIKI trial and put them in perspective with the model-based targeted concentrations. METHODS AND FINDINGS: Pre-dose drug concentrations were collected at Day-2 and Day-4 of treatment in 66 patients of the JIKI trial and compared to those predicted by the model taking into account patient's individual characteristics. At Day-2, the observed concentrations were slightly lower than the model predictions adjusted for patient's characteristics (median value of 46.1 versus 54.3 µg/mL for observed and predicted concentrations, respectively, p = 0.012). However, the concentrations dropped at Day-4, which was not anticipated by the model (median values of 25.9 and 64.4 µg/mL for observed and predicted concentrations, respectively, p<10-6). There was no significant relationship between favipiravir concentrations and EBOV viral kinetics or mortality. CONCLUSIONS: Favipiravir plasma concentrations in the JIKI trial failed to achieve the target exposure defined before the trial. Furthermore, the drug concentration experienced an unanticipated drop between Day-2 and Day-4. The origin of this drop could be due to severe sepsis conditions and/or to intrinsic properties of favipiravir metabolism. Dose-ranging studies should be performed in healthy volunteers to assess the concentrations and the tolerance that could be achieved with high doses. TRIAL REGISTRATION: ClinicalTrials.gov NCT02329054.

Beating the odds: efficacy and toxicity of dihydropyrimidine dehydrogenase-driven adaptive dosing of 5-FU in patients with digestive cancer.

AIMS: 5-FU is the backbone of most regimens in digestive oncology. Administration of standard 5-FU leads to 15-30% of severe side effects, and lethal toxicities are regularly reported with fluoropyrimidine drugs. Dihydropyrimidine dehydrogenase (DPD) deficiency is a pharmacogenetic syndrome responsible for most cases of life-threatening toxicities upon 5-FU intake, and pre-treatment checking for DPD status should help to reduce both incidence and severity of side effects through adaptive dosing strategies. METHODS: We have used a simple method for rapidly establishing the DPD phenotype of patients with cancer and used it prospectively in 59 routine patients treated with 5-FU-based therapy for digestive cancers. No patient with total DPD deficiency was found but 23% of patients exhibited poor metabolizer phenotype, and one patient was phenotyped as profoundly deficient. Consequently, 5-FU doses in poor metabolizer patients were cut by an average 35% as compared with non deficient patients (2390 ± 1225 mg vs. 3653 ± 1371 mg, P < 0.003, t-test). RESULTS: Despite this marked reduction in 5-FU dosing, similar efficacy was achieved in the two subsets (clinical benefit: 40 vs. 43%, stable disease: 40 vs. 37%, progressive disease: 20% in both subsets, P = 0.893, Pearson's chi-square). No difference in toxicities was observed (P = 0.104, Fisher's exact test). Overall, only 3% of early severe toxicities were recorded, a value markedly lower than the 15-30% ones usually reported with 5-FU. CONCLUSIONS: This feasibility study shows how simplified DPD-based adaptive dosing of 5-FU can reduce sharply the incidence of treatment-related severe toxicities while maintaining efficacy as part of routine clinical practice in digestive oncology.