Investigation of the Effect of Lasmiditan on the Pharmacokinetics of P‐Glycoprotein and Breast Cancer Resistance Protein Substrates
Bibliographic record
Abstract
Abstract Lasmiditan is an in vitro inhibitor of P‐glycoprotein (P‐gp) and breast cancer resistance protein (BCRP) efflux transporters. We aimed to confirm predictions from physiologically based pharmacokinetic models of lasmiditan, and assess the safety and tolerability of rosuvastatin and dabigatran co‐administered with lasmiditan. In this open‐label, post‐marketing drug–drug interaction, phase 1 clinical trial, eligible participants were adults aged 21‐70 years with a body mass index of 18.5‐35.0 kg/m2. Part 1 (P‐gp, 150 mg dabigatran etexilate with 200 mg lasmiditan) and part 2 (BCRP, 10 mg rosuvastatin with 200 mg lasmiditan) employed similar designs: a single dose of probe substrate administered on day −2 with pharmacokinetic evaluation; 1‐week washout; lasmiditan administered on days 8 and 9 alone; lasmiditan co‐administered with a single dose of probe substrate on day 10, with pharmacokinetic evaluation of probe substrate and lasmiditan. Sixty‐six participants were included in part 1 and 30 participants were included in part 2. Following dabigatran co‐administration with lasmiditan, versus dabigatran alone, 90% confidence intervals for geometric least‐squares (LS) mean ratios of area under the plasma concentration–time curve from time 0 extrapolated to infinity (AUC0–∞) and maximum observed drug concentration (Cmax) were not contained within the non‐effect boundaries (0.80 to 1.25). Dabigatran AUC0–∞ increased by 25% and Cmax increased by 22%. The median time of maximum observed drug concentration (tmax) for dabigatran was 2.0 to 3.0 hours. Following rosuvastatin co‐administration with lasmiditan, versus rosuvastatin alone, 90%CIs for geometric LS mean ratios of AUC0–∞ and Cmax were contained within non‐effect boundaries (0.80‐1.25). Rosuvastatin AUC0–∞ increased by 15% and Cmax increased by 7%. The median tmax for rosuvastatin was 4.0 hours. Results suggest that lasmiditan has a weak effect on P‐gp substrates and no clinically relevant effect on BCRP substrates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".