Hollow Fiber System Model of Tuberculosis

Pre-clinical hollow fiber system model of tuberculosis (HFS-TB), PK/PD and translation for TB combination regimens to patients program

Hollow Fiber System Model of Tuberculosis

HFS-TB

Log-phase, intracellular, semidormant, NRP, PBMCs and model organisms

Monotherapy PK/PD

Microbial kill, resistance suppression, toxicity, whole genome sequencing (resistant mutants)

Combination Therapy Factorial Design

Microbial kill, resistance suppression, -slopes, time- to-extinction

Combination Therapy Regimen Ranking

Microbial kill, resistance suppression, y-slopes, time-to-extinction

Combination Therapy Morphism Maps and Translation To Patients

Patient predicted y-slopes, time-to-extinction, time-to-cure, biomarkers for relapse

The HFS-TB model turned 20 years old in 2021. The HFS-TB model is a system of models and not a single model:

1. Extracellular log-phase growth
2. Intracellular in human cell lines
3. Intracellular in human peripheral blood mononuclear cells
4. Semidormant under acidic conditions
5. Non-replicating persistor models
6. Model organsims
7. TB meningitis model with a blood-brain barrier of human-derived cells

All of our HFS-TB models havestandardized SOPs and QCprocedures, run in replicates and wecan perform > 100 hollow fibers inparallel.

The HFS-TB model has been presented to regulatory authorities as a drug development tool (DOT) with qualification opinion here.

EMA CHMP Qualification Opinion:

The HFS-TB model is qualified to be used in anti-TB drug development program as an additional and complementary tool to existing methodology to inform selection of dose and treatment regimen, including combination of 2 or more anti-Mycobacterium tuberculosis drugs, to maximize bactericidal effects and minimize emergence of drug resistance.

HFS-TB can be used in regulatory submissions throughout the drug development process for a product, especially for more informed design and interpretation of Phase I, Phase II and Phase III clinical studies.

CHMP recommends that the HFS-TB model may be useful as follows:

To provide preliminary proof of concept for developing a specific drug or combination to treat tuberculosis

To select the pharmacodynamic target (e.g. Time/MIC, AUC/MIC)

To provide date to support PK/PD analyses leading to initial dose selection for non-clinical and clinical studies, with the aim of limiting the number of regimens that are to be tested in vivo. HFS-TB may be used to limit doses tested both in single drug and combination regimes in vivo.

To assist in confirming dose regimens for later clinical trials taking into account the accumulated human PK data in healthy volunteers and then patients as well as available information on exposure-response relationships.

VIEW HFS-TB CASE STUDIES

HFS-TB Case Studies

Quantitative Forecasting Accuracy

Overview of HFS-TB model in predicting efficacy

Cumulative Fraction of Response for Once and Twice Daily Delamanid

Prediction of delamanid efficacy in patients with pulmonary multi-drug resistant tuberculosis

HFS-TB Combination Regimen Optimization Case Studies

Concentration-Dependent Synergy and Antagonism of Linezolid and Moxifloxacin

Combination optimization for pediatric tuberculosis treatments

A Faropenam, Linezolid and Moxifloxacin Regimen for Drug-Susceptible and Multidrug Resistant Tuberculosis

Combination optimization for pediatric tuberculosis treatments

Mapping Patient Responses toHFS-TB Microbial Responses

Kill Slopes and Time-to-Cure Derived in HFS-TB is Translated to Patients

Bypasses problem of one-to-one translation observed with other preclinical models (e.g. 0% relapse in preclinical model has been equated to 0% relapse in patients given the same duration of therapy) – failed paradigm.

Ranking of regimens is based on combined kill slopes and time-to-extinction which is predicted to identify ultra-short therapy duration.

PREDICTING PATIENT RESPONSES CASE STUDIES

Map Therapy Duration from Preclinical Models

Duration of pretomanid / moxifloxacin / pyrazinamide therapy

Concentration-Dependent Synergy and Antagonism of Linezolid and Moxifloxacin

Combination optimization for pediatric tuberculosis treatments

A Faropenam, Linezolid and Moxifloxacin Regimen for Drug-Susceptible and Multidrug Resistant Tuberculosis

Combination optimization for pediatric tuberculosis treatments

Efficacy Versus Hepatoxocity of High-dose Rifampin, Pyrazinamide and Moxifloxacin

Praedicare has developed clinical endpoints and biomarkers of response for patients treated for TB for use in clinical trials and patient care

Our mathematical modeling and patented approaches that utilize patient sputum bacillary changes to identify kill slopes thresholds in the first 8 weeks that predict time-to-cure months to years later are biomarkers that can be used for clinical trial endpoints.

Our models and biomarker can be used to rank combination regimens, design clinical trials (sample size, minimal sputum sampling schedule and narrowing 95% confidence intervals for the desired patient responses. We have developed SOPs and QCs for the models and their implementation.