Hollow Fiber System Model of Tuberculosis
Hollow Fiber System Model of Tuberculosis
HFS-TB
Log-phase, intracellular, semidormant, NRP, PBMCs and model organisms
Monotherapy Pharmacokinetics/
Pharmacodynamics
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
Hollow Fiber System Model of Tuberculosis
HFS-TB
Log-phase, intracellular, semidormant, NRP, PBMCs and model organisms
Monotherapy Pharmacokinetics/
Pharmacodynamics
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:
Extracellular log-phase growth
Intracellular in human cell lines
Intracellular in human peripheral blood mononuclear cells
Semidormant under acidic conditions
Non-replicating persistor models
Model organsims
TB meningitis model with a blood-brain barrier of human-derived cells
The HFS-TB model turned 20 years old in 2021. The HFS-TB model is a system of models and not a single model:
Extracellular log-phase growth
Intracellular in human cell lines
Intracellular in human peripheral blood mononuclear cells
Semidormant under acidic conditions
Non-replicating persistor models
Model organsims
TB meningitis model with a blood-brain barrier of human-derived cells
All of our HFS-TB models have standardized Standard Operating Procedures and Quality Control procedures, run in replicates
and we can perform greater than 100 hollow fibers in parallel.
The HFS-TB model has been presented to regulatory authorities as a drug development tool 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 Pharmacokinetics/Pharmacodynamics 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 Pharmacokinetics data in healthy volunteers and then patients as well as available information on exposure-response relationships.
All of our HFS-TB models have standardized Standard Operating Procedures and Quality Control procedures, run in replicates
and we can perform greater than 100 hollow fibers in parallel.
The HFS-TB model has been presented to regulatory authorities as a drug development tool 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 Pharmacokinetics/Pharmacodynamics 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 Pharmacokinetics 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
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.
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.
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56
Number of Biopharma
Companies Worked With
Number of Projects
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INTERESTED IN LEARNING MORE?
Contact Us Today
19
Number of Biopharma
Companies Worked With
51
Number of Projects
Worked On