Functional characterization of the Pneumocystis jirovecii potential drug targets dhfs and abz2 involved in folate biosynthesis.

Pneumocystis species are fungal parasites colonizing mammal lungs with strict host specificity. Pneumocystis jirovecii is the human-specific species and can turn into an opportunistic pathogen causing severe pneumonia in immunocompromised individuals. This disease is currently the second most frequent life-threatening invasive fungal infection worldwide. The most efficient drug, cotrimoxazole, presents serious side effects, and resistance to this drug is emerging. The search for new targets for the development of new drugs is thus of utmost importance. The recent release of the P. jirovecii genome sequence opens a new era for this task. It can now be carried out on the actual targets to be inhibited instead of on those of the relatively distant model Pneumocystis carinii, the species infecting rats. We focused on the folic acid biosynthesis pathway because (i) it is widely used for efficient therapeutic intervention, and (ii) it involves several enzymes that are essential for the pathogen and have no human counterparts. In this study, we report the identification of two such potential targets within the genome of P. jirovecii, the dihydrofolate synthase (dhfs) and the aminodeoxychorismate lyase (abz2). The function of these enzymes was demonstrated by the rescue of the null allele of the orthologous gene of Saccharomyces cerevisiae.

Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

Nouveaux traitements de l'hépatite C: aspects pharmacologiques et potentiel d'interaction [New hepatitis C treatments: pharmacological considerations and potential for drug interactions].

Progress in the understanding of the hepatitis C virus life cycle allowed the development of new, very promising antiviral therapies. Although these new drugs have a favourable profile in terms of efficacy, tolerance and interaction potential, their prescription in the setting of comedication and impaired renal or hepatic function remains a challenge. Here, we provide a summary of pharmacological considerations, focusing on sofosbuvir, simeprevir and daclatasvir. A better understanding of their metabolic pathways and transporters may help the prescriber to identify and manage drug interactions especially in patients under immunosuppressive or anti-HIV therapy. Recommendations for the prescription of these drugs in specific situations are also discussed.

Impact of the introduction of real-time therapeutic drug monitoring on empirical doses of carbapenems in critically ill burn patients.

PURPOSE: Adequate empirical antibiotic dose selection for critically ill burn patients is difficult due to extreme variability in drug pharmacokinetics. Therapeutic drug monitoring (TDM) may aid antibiotic prescription and implementation of initial empirical antimicrobial dosage recommendations. This study evaluated how gradual TDM introduction altered empirical dosages of meropenem and imipenem/cilastatin in our burn ICU. METHODS: Imipenem/cilastatin and meropenem use and daily empirical dosage at a five-bed burn ICU were analyzed retrospectively. Data for all burn admissions between 2001 and 2011 were extracted from the hospital's computerized information system. For each patient receiving a carbapenem, episodes of infection were reviewed and scored according to predefined criteria. Carbapenem trough serum levels were characterized. Prior to May 2007, TDM was available only by special request. Real-time carbapenem TDM was introduced in June 2007; it was initially available weekly and has been available 4 days a week since 2010. RESULTS: Of 365 patients, 229 (63%) received antibiotics (109 received carbapenems). Of 23 TDM determinations for imipenem/cilastatin, none exceeded the predefined upper limit and 11 (47.8%) were insufficient; the number of TDM requests was correlated with daily dose (r=0.7). Similar numbers of inappropriate meropenem trough levels (30.4%) were below and above the upper limit. Real-time TDM introduction increased the empirical dose of imipenem/cilastatin, but not meropenem. CONCLUSIONS: Real-time carbapenem TDM availability significantly altered the empirical daily dosage of imipenem/cilastatin at our burn ICU. Further studies are needed to evaluate the individual impact of TDM-based antibiotic adjustment on infection outcomes in these patients.

Implementation of bayesian therapeutic drug monitoring in modern patient care

The variability observed in drug exposure has a direct impact on the overall response to drug. The largest part of variability between dose and drug response resides in the pharmacokinetic phase, i.e. in the dose-concentration relationship. Among possibilities offered to clinicians, Therapeutic Drug Monitoring (TDM; Monitoring of drug concentration measurements) is one of the useful tool to guide pharmacotherapy. TDM aims at optimizing treatments by individualizing dosage regimens based on blood drug concentration measurement. Bayesian calculations, relying on population pharmacokinetic approach, currently represent the gold standard TDM strategy. However, it requires expertise and computational assistance, thus limiting its large implementation in routine patient care. The overall objective of this thesis was to implement robust tools to provide Bayesian TDM to clinician in modern routine patient care. To that endeavour, aims were (i) to elaborate an efficient and ergonomic computer tool for Bayesian TDM: EzeCHieL (ii) to provide algorithms for drug concentration Bayesian forecasting and software validation, relying on population pharmacokinetics (iii) to address some relevant issues encountered in clinical practice with a focus on neonates and drug adherence. First, the current stage of the existing software was reviewed and allows establishing specifications for the development of EzeCHieL. Then, in close collaboration with software engineers a fully integrated software, EzeCHieL, has been elaborated. EzeCHieL provides population-based predictions and Bayesian forecasting and an easy-to-use interface. It enables to assess the expectedness of an observed concentration in a patient compared to the whole population (via percentiles), to assess the suitability of the predicted concentration relative to the targeted concentration and to provide dosing adjustment. It allows thus a priori and a posteriori Bayesian drug dosing individualization. Implementation of Bayesian methods requires drug disposition characterisation and variability quantification trough population approach. Population pharmacokinetic analyses have been performed and Bayesian estimators have been provided for candidate drugs in population of interest: anti-infectious drugs administered to neonates (gentamicin and imipenem). Developed models were implemented in EzeCHieL and also served as validation tool in comparing EzeCHieL concentration predictions against predictions from the reference software (NONMEM®). Models used need to be adequate and reliable. For instance, extrapolation is not possible from adults or children to neonates. Therefore, this work proposes models for neonates based on the developmental pharmacokinetics concept. Patients' adherence is also an important concern for drug models development and for a successful outcome of the pharmacotherapy. A last study attempts to assess impact of routine patient adherence measurement on models definition and TDM interpretation. In conclusion, our results offer solutions to assist clinicians in interpreting blood drug concentrations and to improve the appropriateness of drug dosing in routine clinical practice.

Age and adverse drug reactions from psychopharmacological treatment: data from the AMSP drug surveillance programme in Switzerland.

QUESTION UNDER STUDY: The frequency of severe adverse drug reactions (ADRs) from psychotropic drugs was investigated in hospitalised psychiatric patients in relation to their age. Specifically, the incidence of ADRs in patients up to 60 years was compared to that of patients older than 60 years. METHODS: Prescription rates of psychotropic drugs and reports of severe ADRs were collected in psychiatric hospitals in Switzerland between 2001 and 2010. The data stem from the drug surveillance programme AMSP. RESULTS: A total of 699 patients exhibited severe ADRs: 517 out of 28,282 patients up to 60 years (1.8%); 182 out of 11,446 elderly patients (1.6%, ns). Logistic regression analyses showed a significantly negative relationship between the incidence of ADRs and patients' age in general and in particular for weight gain, extrapyramidal motor system (EPMS) symptoms, increased liver enzymes and galactorrhoea. A significantly negative relationship was observed for age and the dosages of olanzapine, quetiapine, risperidone, valproic acid and lamotrigine. When comparing age groups, frequency of ADRs was lower in general for antipsychotic drugs and anticonvulsants, in particular for valproic acid in the elderly. Weight gain was found to be lower in the elderly for antipsychotic drugs, in particular for olanzapine. For the group of mood-stabilising anticonvulsants (carbamazepine, lamotrigine and valproic acid) the elderly exhibited a lower incidence of reported allergic skin reactions. CONCLUSION: The results suggest that for psychiatric inpatients the incidence of common severe ADRs (e.g., weight gain or EPMS symptoms) arising from psychotropic medication decreases with the age of patients.

Genomics and drug profiling of fatal TCF3-HLF-positive acute lymphoblastic leukemia identifies recurrent mutation patterns and therapeutic options.

TCF3-HLF-positive acute lymphoblastic leukemia (ALL) is currently incurable. Using an integrated approach, we uncovered distinct mutation, gene expression and drug response profiles in TCF3-HLF-positive and treatment-responsive TCF3-PBX1-positive ALL. We identified recurrent intragenic deletions of PAX5 or VPREB1 in constellation with the fusion of TCF3 and HLF. Moreover somatic mutations in the non-translocated allele of TCF3 and a reduction of PAX5 gene dosage in TCF3-HLF ALL suggest cooperation within a restricted genetic context. The enrichment for stem cell and myeloid features in the TCF3-HLF signature may reflect reprogramming by TCF3-HLF of a lymphoid-committed cell of origin toward a hybrid, drug-resistant hematopoietic state. Drug response profiling of matched patient-derived xenografts revealed a distinct profile for TCF3-HLF ALL with resistance to conventional chemotherapeutics but sensitivity to glucocorticoids, anthracyclines and agents in clinical development. Striking on-target sensitivity was achieved with the BCL2-specific inhibitor venetoclax (ABT-199). This integrated approach thus provides alternative treatment options for this deadly disease.

Therapeutic drug monitoring of targeted anticancer therapy.

New oral targeted anticancer therapies are revolutionizing cancer treatment by transforming previously deadly malignancies into chronically manageable conditions. Nevertheless, drug resistance, persistence of cancer stem cells, and adverse drug effects still limit their ability to stabilize or cure malignant diseases in the long term. Response to targeted anticancer therapy is influenced by tumor genetics and by variability in drug concentrations. However, despite a significant inter-patient pharmacokinetic variability, targeted anticancer drugs are essentially licensed at fixed doses. Their therapeutic use could however be optimized by individualization of their dosage, based on blood concentration measurements via the therapeutic drug monitoring (TDM). TDM can increase the probability of therapeutic responses to targeted anticancer therapies, and would help minimize the risk of major adverse reactions.

Mechanisms of Antifungal Drug Resistance.

Antifungal therapy is a central component of patient management for acute and chronic mycoses. Yet, treatment choices are restricted because of the sparse number of antifungal drug classes. Clinical management of fungal diseases is further compromised by the emergence of antifungal drug resistance, which eliminates available drug classes as treatment options. Once considered a rare occurrence, antifungal drug resistance is on the rise in many high-risk medical centers. Most concerning is the evolution of multidrug- resistant organisms refractory to several different classes of antifungal agents, especially among common Candida species. The mechanisms responsible are mostly shared by both resistant strains displaying inherently reduced susceptibility and those acquiring resistance during therapy. The molecular mechanisms include altered drug affinity and target abundance, reduced intracellular drug levels caused by efflux pumps, and formation of biofilms. New insights into genetic factors regulating these mechanisms, as well as cellular factors important for stress adaptation, provide a foundation to better understand the emergence of antifungal drug resistance.

Tipping the balance both ways: drug resistance and virulence in Candida glabrata.

Among existing fungal pathogens, Candida glabrata is outstanding in its capacity to rapidly develop resistance to currently used antifungal agents. Resistance to the class of azoles, which are still widely used agents, varies in proportion (from 5 to 20%) depending on geographical area. Moreover, resistance to the class of echinocandins, which was introduced in the late 1990s, is rising in several institutions. The recent emergence of isolates with acquired resistance to both classes of agents is a major concern since alternative therapeutic options are scarce. Although considered less pathogenic than C. albicans, C. glabrata has still evolved specific virulence traits enabling its survival and propagation in colonized and infected hosts. Development of drug resistance is usually associated with fitness costs, and this notion is documented across several microbial species. Interestingly, azole resistance in C. glabrata has revealed the opposite. Experimental models of infection showed enhanced virulence of azole-resistant isolates. Moreover, azole resistance could be associated with specific changes in adherence properties to epithelial cells or innate immunity cells (macrophages), both of which contribute to virulence changes. Here we will summarize the current knowledge on C. glabrata drug resistance and also discuss the consequences of drug resistance acquisition on the balance between C. glabrata and its hosts.

Types of stereoselectivity in drug metabolism: a heuristic approach.

Stereochemical factors are known to play a significant role in the metabolism of drugs and other xenobiotics. Following Prelog's lead, types of metabolic stereoselectivity can be categorized as (i) substrate stereoselectivity (the differential metabolism of two or more stereoisomeric substrates) and (ii) product stereoselectivity (the differential formation of two or more stereoisomeric metabolites from a single substrate). Combinations of the two categories exist as (iii) substrate-product stereoselectivities, meaning that product stereoselectivity itself is substrate stereoselective. Here, published examples of metabolic stereoselectivities are examined in the light of these concepts. In parallel, a graphical scheme is presented with a view to facilitate learning and help researchers to solve classification problems.

Assessing the Paradox Between Transmitted and Acquired HIV Type 1 Drug Resistance Mutations in the Swiss HIV Cohort Study From 1998 to 2012.

BACKGROUND: Transmitted human immunodeficiency virus type 1 (HIV) drug resistance (TDR) mutations are transmitted from nonresponding patients (defined as patients with no initial response to treatment and those with an initial response for whom treatment later failed) or from patients who are naive to treatment. Although the prevalence of drug resistance in patients who are not responding to treatment has declined in developed countries, the prevalence of TDR mutations has not. Mechanisms causing this paradox are poorly explored. METHODS: We included recently infected, treatment-naive patients with genotypic resistance tests performed ≤1 year after infection and before 2013. Potential risk factors for TDR mutations were analyzed using logistic regression. The association between the prevalence of TDR mutations and population viral load (PVL) among treated patients during 1997-2011 was estimated with Poisson regression for all TDR mutations and individually for the most frequent resistance mutations against each drug class (ie, M184V/L90M/K103N). RESULTS: We included 2421 recently infected, treatment-naive patients and 5399 patients with no response to treatment. The prevalence of TDR mutations fluctuated considerably over time. Two opposing developments could explain these fluctuations: generally continuous increases in the prevalence of TDR mutations (odds ratio, 1.13; P = .010), punctuated by sharp decreases in the prevalence when new drug classes were introduced. Overall, the prevalence of TDR mutations increased with decreasing PVL (rate ratio [RR], 0.91 per 1000 decrease in PVL; P = .033). Additionally, we observed that the transmitted high-fitness-cost mutation M184V was positively associated with the PVL of nonresponding patients carrying M184V (RR, 1.50 per 100 increase in PVL; P < .001). Such association was absent for K103N (RR, 1.00 per 100 increase in PVL; P = .99) and negative for L90M (RR, 0.75 per 100 increase in PVL; P = .022). CONCLUSIONS: Transmission of antiretroviral drug resistance is temporarily reduced by the introduction of new drug classes and driven by nonresponding and treatment-naive patients. These findings suggest a continuous need for new drugs, early detection/treatment of HIV-1 infection.