Personalized Medicines: Reforming Diagnostics and Therapeutics
Bibliographic record
Abstract
Since the first use of the term ‘Personalized Medicine’ (PM) in 1990, many research and review articles have coined this term. Nevertheless, this topic has not been widely researched about till now. The PMs are the application of genomic and molecular data for developing therapies with unprecedentedly higher efficiencies, better safety, lower ADR’s, and reduced costs of therapies. PMs are developed through molecular level knowledge of the drug targets and diseases, which leads to the promise of the right treatment for right patient at the right time. This paper gives a comprehensive view of PMs. For this purpose, this paper is divided into following sections: defining personalized medicines; the history and evolution of personalized medicines; the human genome project; drug discovery & development process; merits of personalized medicines; applications of personalized medicines; challenges on the road of personalized medicines; regulatory evolution in the generation of personalized medicines; role of US FDA in the era of personalized medicines and, conclusion.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".