DDIS-11. TTI-2341: A NOVEL, ORALLY BIOAVAILABLE, BRAIN-PENETRANT, COVALENT EPIDERMAL GROWTH FACTOR RECEPTOR (EGFR) INHIBITOR FOR TREATMENT OF GLIOBLASTOMA MULTIFORME (GBM) AND BRAIN METASTASES OF NON-SMALL CELL LUNG CANCER (NSCLC)
Bibliographic record
Abstract
Aberrant EGFR activity is implicated in certain central nervous system (CNS) tumors, including GBM and brain metastases of NSCLC, which occur in almost half of NSCLC patients. Current approved EGFR inhibitors, however, have very limited efficacy against those CNS tumors due to insufficient penetration of the blood-brain barrier (BBB). Thus, there is a strong unmet medical need to develop novel EGFR inhibitors that are able to effectively access the CNS. Here we report that TTI-2341, a novel covalent orally active EGFR inhibitor, demonstrates superior brain penetration and is reasonably well tolerated in preclinical studies. TTI-2341 displays potent inhibition of wild type and mutant EGFR (including resistance-associated variants L858R and T790M) with nanomolar or lower IC50s in vitro, while exhibiting selectivity for the EGFR family of kinases. TTI-2341 strongly inhibits auto-phosphorylation of EGFR at 10nM in GBM DKMG cells. Furthermore, TTI-2341 has equal or superior anti-proliferative activity compared to the benchmark marketed covalent EGFR inhibitor afatinib among most NSCLC and CNS tumor cell lines tested. ADME studies show that TTI-2341 has 3-fold higher cell permeability and 5-fold less efflux ratio than afatinib in Caco-2 cells, and is not a substrate of PgP (Efflux < 2 in MDCK-MDR1 cells). Importantly, TTI-2341 has superior oral bioavailability (86%), 13-fold higher Kpuu (unbound drug brain-to-plasma ratio) and 6-fold higher brain exposure compared to afatinib. Results from the 7-day repeat dose toxicology study in rats demonstrate that TTI-2341 is well tolerated up to a dose level of 8 mg/kg with no prominent signs of CNS toxicity by clinical and histopathological assessments. Together, these results indicate that TTI-2341 achieves superior brain penetration compared to afatinib. Our data highlight the potential of TTI-2341 to achieve best-in-class status among covalent EGFR inhibitors for the treatment of CNS tumors.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".