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Record W4255275834 · doi:10.1021/cen-09433-notw11

Piramal to acquire API maker Ash Stevens

2016· article· en· W4255275834 on OpenAlexaboutno aff
Rick Mullin

Bibliographic record

VenueC&EN Global Enterprise · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPharmaceutical industryBusinessMedicinePharmacology

Abstract

fetched live from OpenAlex

India’s Piramal Pharma Solutions is expanding its presence in North America with the roughly $50 million acquisition of Ash Stevens, a Riverview, Mich.-based contract manufacturer of high-potency active pharmaceutical ingredients (APIs). The deal underscores continued growth in the contract API market, where Piramal is one of several companies adding capacity through expansion or acquisition. It also highlights growing interest in U.S. production of APIs, even as it marks the end of the road for one of the longest-standing independent drug chemical makers in the U.S. More than 50 years old, Ash Stevens has been FDA-approved to manufacture APIs for 12 drugs, including Ariad Pharmaceuticals’ Iclusig and Millennium Pharmaceuticals’ Velcade. Piramal CEO Vivek Sharma notes that Ash Stevens broadens his company’s services in the key North American market, where Piramal acquired Coldstream Laboratories, a Lexington, Ky.-based maker of injectable drug products, in 2015 and Torcan, a Toronto API manufacturer, in 2005.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.015

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 head0.030
GPT teacher head0.284
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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