In vitro and in vivo pharmacokinetic characterization, chiral conversion and PBPK scaling towards human PK simulation of S-MRI-1867, a drug candidate for Hermansky-Pudlak syndrome pulmonary fibrosis
Bibliographic record
Abstract
Hermansky-Pudlak syndrome (HPS) is a rare autosomal recessive disorder that affects lysosome-related organelles, often leading to fatal pulmonary fibrosis (PF). The search for a treatment for HPS pulmonary fibrosis (HPSPF) is ongoing. S-MRI-1867, a dual cannabinoid receptor 1 (CB1R)/inducible nitric oxide synthase (iNOS) inhibitor, has shown great promise for the treatment of several fibrotic diseases, including HPSPF. In this study, we investigated the in vitro ADME characteristics of S-MRI-1867, as well as its pharmacokinetic (PK) properties in mice, rats, dogs, and monkeys. S-MRI-1867 showed low aqueous solubility (< 1 µg/mL), high plasma protein binding (>99%), and moderate to high metabolic stability. In its preclinical PK studies, S-MRI-1867 exhibited moderate to low plasma clearance (CLp) and high steady-state volume of distribution (Vdss) across all species. Despite the low solubility and P-gp efflux, S-MRI-1867 showed great permeability and metabolic stability leading to a moderate bioavailability (21-60%) across mouse, rat, dog, and monkey. Since the R form of MRI-1867 is CB1R-inactive, we investigated the potential conversion of S-MRI-1867 to R-MRI-1867 in mice and found that the chiral conversion was negligible. Furthermore, we developed and validated a PBPK model that adequately fits the PK profiles of S-MRI-1867 in mice, rats, dogs, and monkeys using various dosing regimens. We employed this PBPK model to simulate the human PK profiles of S-MRI-1867, enabling us to inform human dose selection and support the advancement of this promising drug candidate in the treatment of HPSPF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".