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Record W4411002193 · doi:10.1093/ajhp/zxaf147

Recent and anticipated novel drug approvals (2Q 2025 through 1Q 2026)

2025· article· en· W4411002193 on OpenAlexaboutno aff
Matthew H Rim, Collin Dean, Enela Aliaj, Matthew Dandino, Tyler Howse, Andrew M Levitsky

Bibliographic record

VenueAmerican Journal of Health-System Pharmacy · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsFormularyPipeline (software)DrugMedicineFood and drug administrationQuarter (Canadian coin)Drug approvalFamily medicineMedical emergencyPharmacologyEngineering

Abstract

fetched live from OpenAlex

PURPOSE: Health-system pharmacists play a crucial role in monitoring the pharmaceutical pipeline to manage formularies, allocate resources, and optimize clinical programs for new therapies. This article aims to support pharmacists by providing updates on new and anticipated novel drug approvals. SUMMARY: Selected drug approvals anticipated in the 12-month period covering the second quarter of 2025 through the first quarter of 2026 are reviewed. The analysis emphasizes drugs expected to have significant clinical and financial impact in hospitals and clinics, as selected from 58 novel drugs awaiting US Food and Drug Administration (FDA) approval. This year's pipeline features novel therapies for rare diseases, targeted cancer treatments, and new agents for various diseases states. CONCLUSION: Novel therapies continue to strengthen the current drug pipeline.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.100
GPT teacher head0.377
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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