Challenges and Perspectives on the Development of Small-Molecule EGFR Inhibitors against T790M-Mediated Resistance in Non-Small-Cell Lung Cancer
Bibliographic record
Abstract
Because of the development of drug-resistance mutations, particularly the "gatekeeper" threonine(790)-to-methionine(790) (T790M) mutation in the ATP-binding pocket of the epidermal growth factor receptor (EGFR), the current generation of EGFR tyrosine kinase inhibitors lost their clinical efficacy. Recently, a large number of small-molecule inhibitors with striking inhibitory potency against EGFR mutants with the T790M change have been identified. In particular, the inhibitors rociletinib and osimertinib, which can selectively target both sensitizing mutations and the T790M resistance while sparing the wild-type (WT) form of the receptor, have been designated as breakthrough therapies in the treatment of mutant non-small-cell lung cancer (NSCLC) by the U.S. FDA in 2014. We hope that this review on the small-molecule EGFR T790M inhibitors, along with their discovery strategies, will assist in the design of future T790M-containing EGFR inhibitors with high levels of selectivity over WT EGFR, broad kinase selectivity, and desirable physicochemical properties.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".