Combination of the Glutaminyl Cyclase Inhibitor PQ912 (Varoglutamstat) and the Murine Monoclonal Antibody PBD-C06 (m6) Shows Additive Effects on Brain Aβ Pathology in Transgenic Mice

Compelling evidence suggests that pyroglutamate-modified Aβ (pGlu3-Aβ; AβN3pG) peptides play a pivotal role in the development and progression of Alzheimer’s disease (AD). Approaches targeting pGlu3-Aβ by glutaminyl cyclase (QC) inhibition (Varoglutamstat) or monoclonal antibodies (Donanemab) are currently in clinical development. Here, we aimed at an assessment of combination therapy of Varoglutamstat (PQ912) and a pGlu3-Aβ-specific antibody (m6) in transgenic mice. Whereas the single treatments at subtherapeutic doses show moderate (16–41%) but statistically insignificant reduction of Aβ42 and pGlu-Aβ42 in mice brain, the combination of both treatments resulted in significant reductions of Aβ by 45–65%. Evaluation of these data using the Bliss independence model revealed a combination index of ≈1, which is indicative for an additive effect of the compounds. The data are interpreted in terms of different pathways, in which the two drugs act. While PQ912 prevents the formation of pGlu3-Aβ in different compartments, the antibody is able to clear existing pGlu3-Aβ deposits. The results suggest that combination of the small molecule Varoglutamstat and a pE3Aβ-directed monoclonal antibody may allow a reduction of the individual compound doses while maintaining the therapeutic effect.

Covid-19 meets game theory: a proposed experiment

Researchers around the globe are searching for a "combo-drug" against Covid-19 by trying to combine various existing drugs. Given a set of such drugs, various algorithms (based, for example, on artificial intelligence) are used to identify the efficacy of different shares of the constituent drugs in the combo-drug. Namely, the relative weight of each drug in a "cooperative" scheme of therapy is sought-after. In the current note we propose to identify these weights using the theory of cooperative games, and in particular the Shapley value, one of the fundamental solution concepts of such games. We derive the weight of each drug by its (normalized) average marginal contribution over all possible "coalitions" of drugs it is used with, where a drug's marginal contribution to a coalition is defined as the increase in the coalition's probability to act against a virus should the drug become its "member". Hence we endow each drug with a consistent measure of significance (which is due to the consistency that Shapley value is associated with). At a theoretical level, we build the cooperative game, and compute the Shapley values, within a milestone model in drug combination theory, the Bliss independence model. At a practical level, the predictions of our game-theoretic model can be tested by using in-vitro experiments, namely experiments that are conducted in test tubes.

Activity of Amphotericin B Formulations and Voriconazole, alone or in combination, against Biofilms of Scedosporium and Fusarium spp.

Scedosporium and Fusarium species are emerging opportunistic pathogens, causing invasive fungal diseases in humans, particularly in immunocompromised patients. Biofilm-related infections are associated with increased morbidity and mortality. We herein assessed the ability of Scedosporium apiospermum ( SA ) and Fusarium solani species complex ( FSSC ) isolates to form biofilms and evaluated the efficacy of deoxycholate amphotericin B (D-AMB), liposomal amphotericin B (L-AMB) and voriconazole (VRC), alone or in combination, against mature biofilms. Biofilm formation was assessed by safranin staining and spectrophotometric measurement of optical density. Planktonic and biofilm damage was assessed by XTT reduction assay. Planktonic cell and biofilm MIC50’s were determined as the minimum concentrations that caused ≥50% fungal damage compared to untreated controls. The combined activity of L-AMB (0.5-32 mg/L) with VRC (0.125-64 mg/L) against biofilms was determined by the checkerboard microdilution method and analyzed by the Bliss independence model. Biofilm MIC50’s of D-AMB and L-AMB against SA isolates were 1 and 2 mg/L and against FSSC isolates were 0.5 and 1 mg/L, respectively. Biofilm MIC50’s of VRC against SA and FSSC were 32 mg/L and >256 mg/L, respectively. Synergistic effects were observed at 2-4 mg/L of L-AMB combined with 4-16 mg/L of VRC against SA biofilms (mean ΔE±standard error: 17% ± 3.7%). Antagonistic interactions were found at 0.5-4 mg/L of L-AMB combined with 0.125-16 mg/L of VRC against FSSC isolates with -28% ± 2%. D-AMB and L-AMB were more efficacious against SA and FSSC biofilms than VRC.

What individual antimicrobials add to Mycobacterium avium complex therapies; an in vitro perspective

Objective: For Mycobacterium avium complex pulmonary disease (MAC-PD), current treatment regimens yield low cure rates. To obtain an evidence based combination therapy we assessed the in vitro activity of six drugs - clarithromycin (CLR), rifampicin (RIF), ethambutol (EMB), amikacin (AMK), clofazimine (CFZ), and minocycline (MIN) alone and in combinations against Mycobacterium avium and studied the contributions of individual antibiotics to efficacy. Methods: The MICs of all antibiotics against M. avium ATCC 700898 were determined by broth microdilution. We performed time-kill kinetic assays (TKA) of all single drugs and clinically relevant two, three, four and five drug combinations against M. avium. Pharmacodynamic interactions of these combinations were assessed using area under the time-kill curve-derived effect size and Bliss independence. Results: Adding a second drug yielded an average increase of the effect size (E) of 18.7 ± 32.9% log10 cfu/mL*day, though antagonism was seen in some combinations. Adding a third drug showed a lower increase in effect size (+12.2 ± 11.5%). The rifampicin-clofazimine-clarithromycin (E=102 log10 cfu/mL*day), rifampicin-amikacin-clarithromycin (E=101 log10 cfu/mL*day) and amikacin-minocycline-ethambutol (E=97.8 log10 cfu/mL*day) regimens proved more active than the recommended rifampicin-ethambutol-clarithromycin regimen (E=89.1 log10 cfu/mL*day). The addition of a fourth drug had little impact on effect size (+4.54 ± 3.08%). Conclusions: In vitro, several two- and three-drug regimens are as effective as the currently recommended regimen for MAC-PD. Adding a fourth drug to any regimen had little additional effect. In vitro, the most promising regimen would be rifampicin-amikacin-macrolide or rifampicin-clofazimine-macrolide.

In vitro and in vivo interaction of caspofungin with isavuconazole against Candida auris planktonic cells and biofilms

The in vitro and in vivo efficacy of caspofungin was determined in combination with isavuconazole against Candida auris. Drug–drug interactions were assessed utilising the fractional inhibitory concentration indices (FICIs), the Bliss independence model and an immunocompromised mouse model. Median planktonic minimum inhibitory concentrations (pMICs) of 23 C. auris isolates were between 0.5 and 2 mg/L and between 0.015 and 4 mg/L for caspofungin and isavuconazole, respectively. Median pMICs for caspofungin and isavuconazole in combination showed 2–128-fold and 2–256-fold decreases, respectively. Caspofungin and isavuconazole showed synergism in 14 out of 23 planktonic isolates (FICI range 0.03–0.5; Bliss cumulative synergy volume range 0–4.83). Median sessile MICs (sMIC) of 14 biofilm-forming isolates were between 32 and >32 mg/L and between 0.5 and >2 mg/L for caspofungin and isavuconazole, respectively. Median sMICs for caspofungin and isavuconazole in combination showed 0–128-fold and 0-512-fold decreases, respectively. Caspofungin and isavuconazole showed synergistic interaction in 12 out of 14 sessile isolates (FICI range 0.023–0.5; Bliss cumulative synergy volume range 0.13–234.32). In line with the in vitro findings, synergistic interactions were confirmed by in vivo experiments. The fungal kidney burden decreases were more than 3 log volumes in mice treated with combination of 1 mg/kg caspofungin and 20 mg/kg isavuconazole daily; this difference was statistically significant compared with control mice (p<0.001). Despite the favourable effect of isavuconazole in combination with caspofungin, further studies are needed to confirm the therapeutic advantage of this combination when treating an infection caused by C. auris.

The Neosartorya fischeri Antifungal Protein 2 (NFAP2): A New Potential Weapon against Multidrug-Resistant Candida auris Biofilms

Candida auris is a potential multidrug-resistant pathogen able to persist on indwelling devices as a biofilm, which serve as a source of catheter-associated infections. Neosartorya fischeri antifungal protein 2 (NFAP2) is a cysteine-rich, cationic protein with potent anti-Candida activity. We studied the in vitro activity of NFAP2 alone and in combination with fluconazole, amphotericin B, anidulafungin, caspofungin, and micafungin against C. auris biofilms. The nature of interactions was assessed utilizing the fractional inhibitory concentration index (FICI), a Bliss independence model, and LIVE/DEAD viability assay. NFAP2 exerted synergy with all tested antifungals with FICIs ranging between 0.312–0.5, 0.155–0.5, 0.037–0.375, 0.064–0.375, and 0.064–0.375 for fluconazole, amphotericin B, anidulafungin, caspofungin, and micafungin, respectively. These results were confirmed using a Bliss model, where NFAP2 produced 17.54 μM2%, 2.16 μM2%, 33.31 μM2%, 10.72 μM2%, and 111.19 μM2% cumulative synergy log volume in combination with fluconazole, amphotericin B, anidulafungin, caspofungin, and micafungin, respectively. In addition, biofilms exposed to echinocandins (32 mg/L) showed significant cell death in the presence of NFAP2 (128 mg/L). Our study shows that NFAP2 displays strong potential as a novel antifungal compound in alternative therapies to combat C. auris biofilms.

Assessing the Effect of Mycotoxin Combinations: Which Mathematical Model Is (the Most) Appropriate?

In the past decades, many studies have examined the nature of the interaction between mycotoxins in biological models classifying interaction effects as antagonisms, additive effects, or synergisms based on a comparison of the observed effect with the expected effect of combination. Among several described mathematical models, the arithmetic definition of additivity and factorial analysis of variance were the most commonly used in mycotoxicology. These models are incorrectly based on the assumption that mycotoxin dose-effect curves are linear. More appropriate mathematical models for assessing mycotoxin interactions include Bliss independence, Loewe’s additivity law, combination index, and isobologram analysis, Chou-Talalays median-effect approach, response surface, code for the identification of synergism numerically efficient (CISNE) and MixLow method. However, it seems that neither model is ideal. This review discusses the advantages and disadvantages of these mathematical models.

Combinatorial Antimicrobial Susceptibility Testing Enabled by Non-Contact Printing

We demonstrate the utility of non-contact printing to fabricate the mAST—an easy-to-operate, microwell-based microfluidic device for combinatorial antibiotic susceptibility testing (AST) in a point-of-care format. The wells are prefilled with antibiotics in any desired concentration and combination by non-contact printing (spotting). For the execution of the AST, the only requirements are the mAST device, the sample, and the incubation chamber. Bacteria proliferation can be continuously monitored by using an absorbance reader. We investigate the profile of resistance of two reference Escherichia coli strains, report the minimum inhibitory concentration (MIC) for single antibiotics, and assess drug–drug interactions in cocktails by using the Bliss independence model.

Phenotype-Based Probabilistic Analysis of Heterogeneous Responses to Cancer Drugs and Their Combination Efficacy

Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish the efficacy of cancer drugs. Efficacious combination therapies are thus needed to block drug-tolerant cells via minimizing the impact of heterogeneity. Probabilistic models such as Bliss independence are developed to evaluate drug interactions and their combination efficacy based on probabilities of specific actions mediated by drugs individually and in combination. In practice, however, these models are often applied to conventional dose-response curves in which a normalized parameter with a value between zero and one, generally referred to as fraction of cells affected (fa), is used to evaluate the efficacy of drugs and their combined interactions. We use basic probability theory, computer simulations, time-lapse live cell microscopy, and single-cell analysis to show that fa metrics may bias our assessment of drug efficacy and combination effectiveness. This bias may be corrected when dynamic probabilities of drug-induced phenotypic events, i.e. induction of cell death and inhibition of division, at a single-cell level are used as metrics to assess drug efficacy. Probabilistic phenotype metrics offer the following three benefits. First, in contrast to the commonly used fa metrics, they directly represent probabilities of drug action in a cell population. Therefore, they deconvolve differential degrees of drug effect on tumor cell killing versus inhibition of cell division, which may not be correlated for many drugs. Second, they increase the sensitivity of short-term drug response assays to cell-to-cell heterogeneities and the presence of drug-tolerant subpopulations. Third, their probabilistic nature allows them to be used directly in unbiased evaluation of synergistic efficacy in drug combinations using probabilistic models such as Bliss independence. Altogether, we envision that probabilistic analysis of single-cell phenotypes complements currently available assays via improving our understanding of heterogeneity in drug response, thereby facilitating the discovery of more efficacious combination therapies to block drug-tolerant cells.Author SummaryResistance to therapy due to tumor cell heterogeneity poses a major challenge to the use of cancer drugs. Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish therapeutic efficacy, even in populations of cells scored as highly sensitive based on drug potency. Overcoming such heterogeneity and blocking subpopulations of drug-tolerant cells motivate efforts toward identifying efficacious combination therapies. The success of these efforts depends on our ability to distinguish how heterogeneous populations of cells respond to individual drugs, and how these responses are influenced by combined drug interactions. In this paper, we propose mathematical and experimental frameworks to evaluate time-dependent drug interactions based on probabilistic metrics that quantify drug-induced tumor cell killing or inhibition of division at a single-cell level. These metrics can reveal heterogeneous drug responses and their changes with time and drug combinations. Thus, they have important implications for designing efficacious combination therapies, especially those designed to block or overcome drug-tolerant subpopulations of cancer cells.

Farnesol increases the activity of echinocandins against Candida auris biofilms

Candida auris biofilms exhibit decreased susceptibility to echinocandins, which is associated with poorer clinical outcomes. Farnesol is a quorum-sensing molecule enhancing the activity of antifungals; therefore, we evaluated the in vitro effect of farnesol with anidulafungin, caspofungin, or micafungin against biofilms using fractional inhibitory concentration indexes (FICI), Bliss independence model, LIVE/DEAD-assay and scanning electron microscopy. Based on mathematical models, farnesol caused synergism in eleven out of twelve cases (FICIs range 0.133-0.507; Bliss synergy volume range 70.39–204.6 μM2%). This was confirmed by microscope images of combination-exposed biofilms. Our study showed the prominent effect of farnesol with echinocandins against C. auris biofilms.