II-054 Van der Feltz Isabella

Delpazolid population pharmacokinetics and pharmacodynamics in patients with pulmonary tuberculosis

Isabella van der Feltz(1), Lilian Tina Minja(2), Lindsey te Brake(1), Ivan Noreña(3), Beno Huglin(2), Alphonce Liyoyo(4), Mohammed Rassool(5), Modulakgotla Sebe(6), Leticia Wildner(7), Timothy McHugh(7) , Michael Hoelscher(8), Young Cho(9), Yunhee Lee(9), Patrick Phillips(10), Martin Boeree(11), Rob Aarnoutse(1), Norbert Heinrich(3), Elin Svensson(1,12)

1. Department of Pharmacy, Radboud Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands 2. Ifakara Health Institute, Dar es Salaam, Tanzania 3. LMU University Hospital, Munich, Germany 4. Kibong'oto Infectious Diseases Hospital, Sanya Juu, Tanzania 5. Clinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, Helen Joseph Hospital, University of the Witwatersrand, Johannesburg, South Africa 6. The Aurum Institute, Tembisa, South Africa 7. UCL Centre for Clinical Microbiology, Division of Infection and Immunity, University College London, London, United Kingdom 8. Klinikum der Universität München, Munich, Germany 9. Legochem Biosciences, Daejeon, South-Korea 10. UCSF Center for Tuberculosis, University of California San Francisco, San Francisco, USA 11. Radboudumc Centre for Infectious Diseases, Department of Pulmonary Diseases, Radboud Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands 12. Department of Pharmacy, Uppsala University, Uppsala, Sweden

Introduction: Linezolid is currently recommended for the treatment of multidrug-resistant tuberculosis (MDR-TB) by the WHO. However, this drug is associated with severe adverse effects such as myelosuppression and peripheral neuropathy [1]. Delpazolid, a new oxazolidinone, has demonstrated early bactericidal activity with a favorable safety profile when administered up to 14 days [2]. Therefore, if shown effective and with a lower risk of adverse effects over longer treatment durations [3], delpazolid could be a promising alternative for linezolid in MDR-TB treatment.

Objectives: The objectives of the DElpazolid dose-finding and COmbination DEvelopment (DECODE) study focus on evaluating delpazolid pharmacokinetics (PK) and pharmacodynamics (PD) in pulmonary tuberculosis (TB) patients. The primary PK objective was to describe delpazolid PK through development of a population PK model. The primary efficacy objective was to establish an exposure-response model (PD) for delpazolid.

Methods: The DECODE study was a phase 2b, open-label, randomized, controlled dose-ranging trial performed in South Africa and Tanzania. 76 adult patients with newly diagnosed, drug-sensitive pulmonary TB were included. Delpazolid was administered in combination with standard-dose bedaquiline, delamanid and moxifloxacin over 16 weeks. Patients were randomized into one of the five arms receiving 0 mg, 400 mg, 800 mg, or 1200 mg QD, or 800 mg BID, respectively. Intensive PK sampling was conducted in all patients on day 14 of treatment, with samples taken at 0 (pre-dose) and 1, 2, 4, 8, 12, and 24 hours after dosing. Drug concentrations in plasma were determined using a validated LC-MS/MS combination assay covering all analytes. Sputum samples were collected every week during the treatment period. Delpazolid efficacy was evaluated by measuring the change in mycobacterial load in sputum over time. It was quantified by time to positivity (TTP), the time from start of incubation to detection of mycobacteria by their metabolic activity in mycobacterial growth incubator tubes (MGIT).[4, 5] A population PK-PD model was developed using non-linear mixed effects methodology implemented in NONMEM. First, the population PK model was developed. Subsequently the exposure-response (PD) model was made with the individual exposure metrics from the PK model and the TTP efficacy data. The censoring limit used for TTP was 25 days.[6]

Results: The population PK model was developed based on 402 plasma concentrations from 60 patients (14 women and 46 men). A two-compartment model with first-order absorption, first-order elimination and a proportional residual error described delpazolid PK well. The final model included allometric scaling based on fat-free mass (FFM).[7] Delpazolid clearance was 38.1 L/h (95% CI 34.5-41.7) for a FFM of 58kg. Based on individual predictions, median AUC0-24 (mg/L*h) values were 10.1 for 400 mg, 28.6 for 800 mg, 47.0 for 1200 mg (all QD), and 68.5 for 800mg BID. 2312 TTP results from 75 participants (1 person withdrawn before PK sampling was excluded) were used. A bi-linear model with upper limit of quantification at 25 days described log-transformed TTP data well. A linear effect of delpazolid AUC0-24 up 50 mg/L*h on the second slope  could be detected (p=0.025). The estimated maximal effect was 38% steeper second slope, but the 95% confidence interval was wide (4.2 – 83%). The observed median AUC0-24 of the 1200 mg delpazolid dose (47.0 mg/L*h) was close to the exposure estimated to generate maximal effect.

Conclusions: Delpazolid exposures increased linearly with dose. The results from the PK-PD modelling indicate that delpazolid adds efficacy on top of the strong backbone regime consisting of bedaquiline, delamanid and moxifloxacin. From an efficacy standpoint, a dose of 1200 mg would be reasonable to move forward in development. 

References:

  1. Jaspard, M., et al., Linezolid-Associated Neurologic Adverse Events in Patients with Multidrug-Resistant Tuberculosis, France. Emerg Infect Dis, 2020. 26(8): p. 1792-1800.
  2. Kim, J.S., et al., Early Bactericidal Activity of Delpazolid (LCB01-0371) in Patients with Pulmonary Tuberculosis. Antimicrob Agents Chemother, 2022. 66(2): p. e0168421.
  3. Cho, Y.L. and J. Jang, Development of Delpazolid for the Treatment of Tuberculosis. Applied Sciences, 2020. 10(7): p. 2211.
  4. Diacon, A.H., et al., Time to positivity in liquid culture predicts colony forming unit counts of Mycobacterium tuberculosis in sputum specimens. Tuberculosis, 2014. 94(2): p. 148-151.
  5. Koele, S.E., et al., Early bactericidal activity studies for pulmonary tuberculosis: a systematic review of methodological aspects. Int J Antimicrob Agents, 2023: p. 106775.
  6. Dufault, S., When is a negative MGIT really a negative? Identifying the useful range of time-to-positivity for modeling early treatment response. Bay Area Tuberculosis Science Symposium, 7 sept 2023 PP-10.
  7. Janmahasatian, S., et al., Quantification of lean bodyweight. Clin Pharmacokinet, 2005. 44(10): p. 1051-65.

Reference: PAGE 32 (2024) Abstr 10888 [www.page-meeting.org/?abstract=10888]

Poster: Drug/Disease Modelling - Infection

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