Systematic measurement of combination-drug landscapes to predict in vivo treatment outcomes for tuberculosis

AbstractA lengthy multidrug chemotherapy is required to achieve a durable cure in tuberculosis. Variation in Mycobacterium tuberculosis drug response is created by the differing microenvironments in lesions, which generate different bacterial drug susceptibilities. To better realize the potential of combination therapy to shorten treatment duration, multidrug therapy design should deliberately explore the vast combination space. We face a significant scaling challenge in making systematic drug combination measurements because it is not practical to use animal models for comprehensive drug combination studies, nor are there well-validated high-throughput in vitro models that predict animal outcomes. We hypothesized that we could both prioritize combination therapies and quantify the predictive power of various in vitro models for drug development using a dataset of drug combination dose responses measured in multiple in vitro models. We systematically measured M. tuberculosis response to all 2- and 3-drug combinations among ten antibiotics in eight conditions that reproduce lesion microenvironments. Applying machine learning to this comprehensive dataset, we developed classifiers predictive of multidrug treatment outcome in a mouse model of disease relapse. We trained classifiers on multiple mouse models and identified ensembles of in vitro models that best describe in vivo treatment outcomes. Furthermore, we found that combination synergies are less important for predicting outcome than metrics of potency. Here, we map a path forward to rationally prioritize combinations for animal and clinical studies using systematic drug combination measurements with validated in vitro models. Our pipeline is generalizable to other difficult-to-treat diseases requiring combination therapies.One Sentence SummarySignatures of in vitro potency and drug interaction measurements predict combination therapy outcomes in mouse models of tuberculosis.

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Changes in Granulocyte Fibrinolytic Activity (FA) Induced by In Vivo Treatment with Lysine Acetylsalicylate (LAS)

Thrombosis and Haemostasis ◽

10.1055/s-0038-1653473 ◽

1981 ◽

Vol 46 (04) ◽

pp. 761-761 ◽

Cited By ~ 2

Author(s):

Franco Ghezzo ◽

Paola Trinchero ◽

Luigi Pegoraro

Keyword(s):

Fibrinolytic Activity ◽

Lysine Acetylsalicylate ◽

In Vivo Treatment

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The effect of in vivo treatment with triiodothyronine on the in vitro synthesis of protein-poly(ADP)-ribose adducts by isolated cardiocyte nuclei and the separation of poly(ADP)-ribosylated proteins by phenol extraction and electrophoresis.

Journal of Biological Chemistry ◽

10.1016/s0021-9258(17)44217-7 ◽

1983 ◽

Vol 258 (20) ◽

pp. 12587-12593

Author(s):

G Jackowski ◽

E Kun

Keyword(s):

In Vitro Synthesis ◽

Phenol Extraction ◽

In Vivo Treatment

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Current Stimuli-Responsive Mesoporous Silica Nanoparticles for Cancer Therapy

Pharmaceutics ◽

10.3390/pharmaceutics13010071 ◽

2021 ◽

Vol 13 (1) ◽

pp. 71

Author(s):

Thashini Moodley ◽

Moganavelli Singh

Keyword(s):

Cancer Therapy ◽

Mesoporous Silica ◽

Silica Nanoparticles ◽

Mesoporous Silica Nanoparticles ◽

Therapeutic Agents ◽

Metal Species ◽

Stimuli Responsive ◽

Combination Drug ◽

Incidence And Mortality

With increasing incidence and mortality rates, cancer remains one of the most devastating global non-communicable diseases. Restricted dosages and decreased bioavailability, often results in lower therapeutic outcomes, triggering the development of resistance to conventionally used drug/gene therapeutics. The development of novel therapeutic strategies using multimodal nanotechnology to enhance specificity, increase bioavailability and biostability of therapeutics with favorable outcomes is critical. Gated vectors that respond to endogenous or exogenous stimuli, and promote targeted tumor delivery without prematurely cargo loss are ideal. Mesoporous silica nanoparticles (MSNs) are effective delivery systems for a variety of therapeutic agents in cancer therapy. MSNs possess a rigid framework and large surface area that can incorporate supramolecular constructs and varying metal species that allow for stimuli-responsive controlled release functions. Its high interior loading capacity can incorporate combination drug/gene therapeutic agents, conferring increased bioavailability and biostability of the therapeutic cargo. Significant advances in the engineering of MSNs structural and physiochemical characteristics have since seen the development of nanodevices with promising in vivo potential. In this review, current trends of multimodal MSNs being developed and their use in stimuli-responsive passive and active targeting in cancer therapy will be discussed, focusing on light, redox, pH, and temperature stimuli.

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