Open Labs Fellow/s

Rebeca Bailo
Jordana Galizia

GSK’s contribution

GSK R&D contribution has been, so far, critical for the successful development of the former TC256 project, leading to this current proposal. We envision GSK R&D contribution to this new project as a continuation of current scientific and operational support that can be structured within several main activities:
• Access to compounds and screening infrastructure: the microplate reader EnVision is critical to meet the throughput requirements of the project in a timely manner.
• Mass spectroscopy analytical capacity to characterize the medium degradation kinetics of drugs used in the OPTIKA screening and drug concentrations in the different hollow fiber compartments.
• Data analysis and modeling support to integrate PD (in vitro activity) and PK (drug degradation) drug’s parameters.
• Data analysis and modeling support to integrate data generated under this project proposal with currently available preclinical and clinical data and to develop a machine learning/AI model to predict up
to 4-way drug interactions.
• Capacity to perform murine in vivo models of Mtb infection to evaluate drug combinations.

Project Description

The goal of this project is thus to provide robust in vitro evidence to rationalize the selection of new
therapeutic regimen options for TB treatment.
Recent years have seen a resurgence of new drug-like chemical entities with anti-mycobacterial activity, a number of which progressing into clinical trials [1].
Understanding how to develop these compounds into therapeutically effective multi-drug regimens remains, however, an unresolved question. Traditional efforts to identify new potential drug combinations involve empirical phenotypic screening for in vitro synergies at the microbiological level. This is typically done by checkerboard assays (CBA) able to interrogate 2-way drug interactions but with limited power to identify 3-way or higher order drug interactions. A new technology called DiaMOND (diagonal measurement of n-way drug interactions) has overcome this limitation by reducing the number of interactions that require testing and vastly simplified the ability to identify favourable combinations of 3, 4 or even higher number of drugs [2]. However, both CBA and DiaMOND remain inherently rooted in the use of the Fractional Inhibitory Concentration Index (FICI), a measurement of growth inhibition, as the metric of drug activity, rather than bacterial killing, which remains unmeasured [3]. In addition, any synergistic combinations identified by FICI-based readouts require secondary validation by time kill assays (TKA) that significantly, and in some cases prohibitively, increase the complexity and duration of combination testing.
TKAs are the most valuable assay in static in vitro pharmacokinetic (PK) and pharmacodynamics (PD) studies and rely on Colony Forming Unit (CFU) enumeration at different time points (instead of a fixed time point as in the case of CBA or DiaMOND). TKAs are also the basis of mathematical modelling of antimicrobial drug action; however, TKA throughput in Mtb is typically limited to the working capacity of the technical operator, ca. 30 samples; this limited throughput capacity creates a barrier when it comes to validate 3 or
higher n-way interactions.
Project vision/goal. During the course of a previous Tres Cantos Funded project (TC256), we developed a new methodology named OPTIKA (Optimized Time Kill Assays, described below) that increased the capacity of traditional TKAs by more than 30-fold. OPTIKA allows facile high throughput interrogation of n-way drug interactions that are also dynamic and include direct measures of cidality. In doing so, we can now more rapidly and rigorously identify new potential triple drug interactions by coupling OPTIKA to in vivo studies and dynamic PKPD models using the Hollow Fibre System for Tuberculosis. The goal of this project is thus to provide robust preclinical evidence to suggest new therapeutic regimen options for TB treatment.
1. https://www.newtbdrugs.org/
2. Cokol M. et al. Efficient measurement and factorization of high-order drug interactions in Mycobacterium tuberculosis. 2017. Sci. Adv. 3 (10) e1701881.
2. Gómara M. and Ramón-García S. The FICI paradigm: Correcting flaws in antimicrobial in vitro synergy screens at their inception. 2019. Biochemical Pharmacology 163: 299–307.

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