Novel drugs approved by the EMA, the FDA, and the MHRA in 2023: A year in review
Bibliographic record
Abstract
In 2023, seventy novel drugs received market authorization for the first time in either Europe (by the EMA and the MHRA) or in the United States (by the FDA). Confirming a steady recent trend, more than half of these drugs target rare diseases or intractable forms of cancer. Thirty drugs are categorized as "first-in-class" (FIC), illustrating the quality of research and innovation that drives new chemical entity discovery and development. We succinctly describe the mechanism of action of most of these FIC drugs and discuss the therapeutic areas covered, as well as the chemical category to which these drugs belong. The 2023 novel drug list also demonstrates an unabated emphasis on polypeptides (recombinant proteins and antibodies), Advanced Therapy Medicinal Products (gene and cell therapies) and RNA therapeutics, including the first-ever approval of a CRISPR-Cas9-based gene-editing cell therapy.
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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".