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Enregistrement W1587138241

The NIH Promotes Drug Repurposing and Rescue

2012· article· en· W1587138241 sur OpenAlexaboutno aff
Thomas A. Hemphill

Notice bibliographique

RevueResearch-Technology Management · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueHealth and Medical Research Impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDrug repositioningRepurposingMedicineDrugApproved drugPharmacyPharmacologyCancer drugsCommercializationBusinessFamily medicineEngineeringMarketing
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In a recent clinical study conducted by Pfizer Inc., pharmaceutical researchers found that the company's new drug Xalkori, originally targeted as a treatment for adult lung cancer, showed great promise against two rare childhood cancers. The drug eradicated the cancer in seven of eight children with a childhood form of lymphoma and in two other children with a lethal form of a nervous-system cancer called neuroblastoma. Xalkori's success is one example of drug repurposing, pharmaceutical research to find new uses for FDA-approved compounds. This innovative approach to developing cost-effective, timely new pharmaceutical therapies is necessary to eliminate the backlog of untreated diseases--biomedical researchers have successfully identified the causes of nearly 4,500 diseases but have created new therapies for only 250 of them. This situation is exacerbated by the time and money required to develop a new drug compound--up to 14 years and upwards of $1 billion to move a drug from discovery to commercialization. The National Institutes of Health (NIH), under the directorship of Dr. Francis S. Collins, recently added its imprimatur to two promising areas of pharmaceutical and biologic research: drug repurposing and drug rescue. The successful repurposing of established drugs to treat other ailments includes the statin class of cholesterol reducing drugs, with Lipitor now repurposed to prevent strokes. Drug rescue is defined as research involving abandoned small molecules and biologics that have not been approved by the U.S. Food and Drug Administration (FDA). These rescued molecular compounds are usually abandoned by pharmaceutical companies in the drug discovery or preclinical testing phase, typically because they do not prove effective for the specific use for which they were developed. Some of these compounds may be useful in treating other diseases for which they have not been tested. New analytical tools are making it possible for scientists to identify likely candidates for repurposing or rescuing. In a recent study, a team of Stanford researchers combed through computerized databases to see how 100 diseases altered the activity of thousands of genes, identifying for each disease a genetic signature defined by specific genetic activity patterns. The researchers then subjected 164 drugs to a similar analysis, characterizing each with a genetic signature based on activity patterns in human cell samples treated with the drug. A computational analysis software program developed by the researchers was used to compare drug and disease signatures, resulting in statistical pairings that allowed researchers to infer that a drug might work to successfully treat a particular disease. In 2011, the Stanford researchers reported that they had uncovered potential drug treatments for 53 human diseases ranging from cancers to Crohn's disease and cardiovascular conditions. Abandoned drugs will follow a similar research process to search for new indications. In an April 2011 NIH-pharmaceutical industry roundtable whose findings were published in the report Exploring New Uses for Abandoned and Approved Therapeutics, participants called for increased NIH engagement and expanded partnerships to support drug repurposing and rescue efforts. Collins has responded robustly, establishing the NIH National Center for Translational Sciences (NCATS), which will work to eliminate the bottlenecks in the drug development and commercialization process and accelerate the translation of basic research into new treatments for human diseases and conditions. NCATS is the home for two pilot programs focusing on drug repurposing and rescue. The first program, the NCATS Pharmaceutical Collection, is a publicly accessible database of 3,800 small-molecule compounds approved by regulatory agencies in the United States, Canada, Europe, and Japan, as well as all compounds that have been registered for human clinical trials in the United States. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,014
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,033
Score d'incertitude au seuil0,111

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0140,014
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0020,002
Études des sciences et des technologies0,0020,003
Communication savante0,0070,005
Science ouverte0,0030,007
Intégrité de la recherche0,0130,013
Charge utile insuffisante (le modèle a refusé de juger)0,0330,019

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,162
Tête enseignante GPT0,481
Écart entre enseignants0,319 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2012
Routes d'admission1
Résumé présentoui

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