Translational Model‐Informed Approach for Selection of Tuberculosis Drug Combination Regimens in Early Clinical Development

Abstract

The development of optimal treatment regimens in tuberculosis (TB) remains challenging due to the need of combination therapy and possibility of pharmacodynamic (PD) interactions. Preclinical information about PD interactions needs to be used more optimally when designing early bactericidal activity (EBA) studies. In this work, we developed a translational approach which can allow for forward translation to predict efficacy of drug combination in EBA studies using the Multistate Tuberculosis Pharmacometric (MTP) and the General Pharmacodynamic Interaction (GPDI) models informed by in vitro static time-kill data. These models were linked with translational factors to account for differences between the in vitro system and humans. Our translational MTP-GPDI model approach was able to predict the EBA 0-2 days , EBA 0-5 days , and EBA 0-14 days from different EBA studies of rifampicin and isoniazid in monotherapy and combination. Our translational model approach can contribute to an optimal dose selection of drug combinations in early TB clinical trials.A more effective regimen with a shorter treatment duration is an urgent need to provide more efficient treatment options for patients with pulmonary tuberculosis (TB). Since TB treatment requires multidrug regimens, pharmacodynamics (PD) interactions can be a challenge for developing optimal regimens. The typical early bactericidal activity (EBA) study in a TB phase IIa trial acts as the first "proof-of-concept" study of microbiological activity in humans when the drug is given as monotherapy for 2 weeks. Few EBA studies have explored combinations of drugs, 1,2 but traditionally the EBA studies have played a role in dose selection for the phase IIb trials where the results from the EBA study informs the combination regimen to be evaluated. However, the most optimal dose in monotherapy may not be the optimal dose for combination treatment. Therefore, it is not possible to study the most optimal dose combinations in humans due to the many possible combinations. An alternative is to use preclinical in vitro information where it is possible to study a large set of combinations in order to define the PD interaction space. However, prediction of clinical efficacy based on in vitro information needs to account for translational factors such as human pharmacokinetics (PK), target site exposure, and mycobacterial factors, such as bacterial growth phase, postantibiotic effect (PAE), and minimum inhibitory concentration (MIC) distribution. 3

Model-Informed Drug Discovery and Development Strategy for the Rapid Development of Anti-Tuberculosis Drug Combinations

“…It has been successfully applied to describe in vitro [121], mouse [122], and clinical data [123]. In addition, the MTP model has been successfully used in an MID3 approach, to predict observations from early clinical studies using clinical dose-response forecasting from preclinical in vitro studies of rifampicin and in combination with isoniazid [15,16]. This model has been selected by The Impact and Influence Initiative of the Quantitative Pharmacology (QP) Network of the American society of Clinical Pharmacology and Therapeutics (ASCPT) to highlight the most impactful examples of QP applications where the role of quantitative translational pharmacology has bridged science and practice to make better, faster, and more efficient decisions in drug discovery and development [25].…”

“…Based on the exposure-response relationship in animals, and/or pure in vitro predictions, the first in-human (FIH) and early bactericidal activity (EBA) trials can be designed. These steps all require a mathematical translational approach, taking into account the PK-PD and translational factors to account for differences between preclinical species and patients [15,16].…”

Quantification of Natural Growth of Two Strains of Mycobacterium Marinum for Translational Antituberculosis Drug Development

“…The MTP model has been successfully used in translation of pharmacological findings of M. tuberculosis treatment in vitro, 12 to mice 13 and humans. [14][15][16][17][18] To include the zebrafish in the translational pipeline for tuberculosis drug development, it is necessary to study the natural growth of M. marinum and quantitatively compare this to M. tuberculosis.…”

“…For each strain, three biological replicates from individually grown colonies were collected in individual tubes per time point, with a start inoculum at OD 600 of 0.05, approximating 1× 10 6 CFU/ mL. At different time points (0, 8,11,18,23,28,36,42,49,56,64,69,77,85,92,112,114, and 221 days), the viability of the cultures, defined as CFUs per mL, was determined by plating a series of 10-fold dilutions (ranging from 1:10 to 1:1,000,000) in triplicate on Difco Middlebrook 7H10 agar (BD Biosciences) containing 5% glycerol (Sigma-Aldrich, Saint Louis, MO) and 10% BBLTM Middlebrook Oleic Albumin Dextrose Catalase Enrichment (BD Biosciences).…”

A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for translational medicine within tuberculosis

“…Besides its ability to describe the growth of M. tuberculosis it has also been used to quantify drug effects (i.e. PKPD relationships) in both pre-clinical and clinical settings for both mono therapy [14][15][16][17][18] and when combined with the General Pharmacodynamic Interaction (GPDI) model [19] for assessment of different drug combinations of anti-TB drugs and PD interactions [16,20,21]. Due to the ability of the MTP model to capture both pre-clinical and clinical observations it has also been used as the basis of translational efforts [22], predicting rifampicin drug effects in short-term clinical studies based on in vitro quantified rifampicin drug effects [23].…”