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Enregistrement W2053696982 · doi:10.1038/sj.mt.6300099

RNAi Gets Vote of Confidence from Big Pharma

2007· editorial· en· W2053696982 sur OpenAlexaboutno aff
Robert Frederickson

Notice bibliographique

RevueMolecular Therapy · 2007
Typeeditorial
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueRNA Interference and Gene Delivery
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRNA interferenceBiologyBusinessComputational biologyBiotechnologyGeneticsGeneRNA

Résumé

récupéré en direct d'OpenAlex

The development of new technology is an important force driving advances in the medical and biological sciences. The advent of recombinant DNA technology, the development of the polymerase chain reaction, and advances in DNA sequencing and array technology were key events in the so-called genomic revolution in the second half of the last century. These technologies proved to be important to the success of massively parallel analyses that are critical for comparative genomics and systems approaches in biology and drug discovery. Another important new technology that appeared in the waning years of the last century was the application of RNA interference (RNAi) in mammalian cells. First discovered in plants and Caenorhabditis elegans, RNAi is a powerful mechanism for sequence-specific inhibition of gene expression that has greatly facilitated the study of gene function. In October, co-discoverers Craig Mello and Andrew Fire received the Nobel Prize in medicine for the discovery of this powerful and promising technology. However, as recently discussed in these pages1Rossi J Helping RNAi Deliver.Mol Ther. 2005; 11: 653Abstract Full Text Full Text PDF PubMed Scopus (5) Google Scholar, 2Frederickson RM Nucleic acid medicines move towards the clinic.Mol Ther. 2005; 12: 775Abstract Full Text Full Text PDF PubMed Scopus (6) Google Scholar (reviewed in 3Behlke MA Progress towards in vivo use of siRNAs.Mol Ther. 2006; 13: 644-670Abstract Full Text Full Text PDF PubMed Scopus (455) Google Scholar), RNAi also forms the basis of a new class of therapeutic agent to modify gene expression in target cells, based on delivery of either short inhibitory RNAs (siRNA) or viral or nonviral vectors carrying genes encoding small hairpin RNA (shRNA) that is subsequently processed to siRNA. The evaluation of RNAi-based therapies in animal models and preclinical studies has accelerated dramatically in the last few years, and a handful of companies have been established with the aim of developing the technology to create therapeutic agents. One of these is the aptly named Sirna Therapeutics. Originally founded in 1992 as Ribozyme Pharmaceuticals, the company reorganized to focus on RNAi in 2003, a move that has been cited as a major factor contributing to the turnaround in the foundering fortunes of its predecessor. These fortunes took a great leap forward in October with the announcement of the acquisition of Sirna by Merck for US$1.3 billion—a 100% premium on Sirna's recent stock price. The move surprised many workers in the field because, despite some promising clinical data on the use of RNAi-therapeutic Sirna-027 for the treatment of age-related macular degeneration (AMD), Sirna's drug pipeline is modest. It will be at least five years before any of Sirna's drug leads could reach the market, whereas most acquisitions by Big Pharma are of companies with more near-term prospects. However, the purchase is seen as a major vote of confidence in the commercial potential of RNAi technology on the part of a pharmaceutical giant, and Merck's move may have more to do with acquisition of Sirna's intellectual property and know-how in the area so as to position the company better to compete for the therapeutic development of RNAi technology. Merck has been involved in the field since its 2001 acquisition of Rosetta Inpharmatics. The company is also collaborating with Alnylam, another major player in the RNAi field, to develop RNAi treatments for spinal cord injury. Also in October, the Oligonucleotide Therapeutics Society (OTS) held its second annual meeting at Rockefeller University in association with the New York Academy of Sciences. The agenda included several talks describing clinical results with siRNA-based therapies. Several agents exhibited modest efficacy in patients, providing the validation necessary for continued clinical study of this class of therapeutic. Sirna presented results of an open-label, dose-escalation phase I trial of Sirna-027 that forms the basis for the initiation of a phase II dose-finding study in patients with active choroidal neovascularization secondary to AMD. Acuity Pharmaceuticals is also targeting AMD with siRNA, and reported phase II results for their drug, bevasiranib, which targets the same gene that Sirna-027 does, vascular endothelial growth factor (VEGF). The study confirmed the safety of the drug shown in earlier studies, and also showed that there was little evidence for leakage of the drug into the bloodstream. Bevasiranib is delivered intravitreally, and there had been some concern about the potential for an inhibitor of a growth factor to gain access to the general circulation. Overall, the results demonstrated an effect at all doses with encouraging durability of response in patients with early aggressive AMD, and the company notes that it is moving toward a phase III study of bevasiranib in combination with VEGF antagonists. Alnylam discussed its recent experiences with ALN-RSV01, an inhaled siRNA therapeutic targeted to the N protein important for the replication of respiratory syncytial virus (RSV). This virus is a major pathogen, affecting 100,000 young children annually. A phase I analysis of the compound in over 100 healthy volunteers was accompanied by mild adverse events following nasal delivery. Alnylam is currently planning an “RSV Challenge” study in which healthy volunteers will be exposed to RSV to assess the activity of ALN-RSV01, which has shown activity in preclinical studies in animal models. siRNAs are only the newest class of oligonucleotide-based therapeutics, which have been under study for decades. Several other updates at the OTS meeting described the latest findings on the response of patients to antisense DNA–based therapeutics. Isis Pharmaceuticals presented phase II trial results demonstrating the effectiveness of two antisense DNA–based agents, ISIS 301012 (targeted to apo-100) and ISIS 113715 (targeted to PTP-1B) in hypercholesterolemic and diabetic patients, respectively. Studies are currently under way to evaluate the drugs over longer periods of time and as combination therapies with more traditional drugs treating high cholesterol and diabetes. Genta Incorporated presented updated safety and efficacy data from a randomized phase III trial of Genasense (Bcl-2 antisense) in patients with melanoma and chronic lymphocytic leukemia (CLL). In preclinical studies, Genasense has shown sensitizing activity in combination with chemotherapy, radiation, and other therapeutics. The new results showed modest but measurable effects on survival and tumor responses in combination with chemotherapy in melanoma and CLL patients, and the results will form the basis of global regulatory applications and further clinical studies. Topigen presented results of a phase I trial of ASM8, a drug comprising two separate phosphorothioate antisense compounds targeting the chemokine receptor CCR3 and the common beta-chain subunit of the receptors for interleukin-3 (IL-3) and interleukin-5 (IL-5) and granulocyte-macrophage colony-stimulating factor (GM-CSF). ASM8 was previously shown to be well tolerated and effective to treat animal models of asthma in preclinical studies. ASM8 was well tolerated in healthy volunteers, and a phase II study is under way in Canada to evaluate safety and tolerability further and to compare the allergen-induced asthmatic response of the drug against that with a placebo control. Coley Pharmaceuticals described particularly promising results in a study examining the effects on the immune system of CpG oligonucleotide ligands. The latter are TLR9 agonists that can activate plasmacytoid dendritic cells to stimulate both the innate immune system and antigen-specific T-cell responses. PF-3512676 is currently being analyzed in two phase III trials involving 1,600 patients with advanced lung cancer with and without chemotherapy, following previous results showing an objective disease regression in a number of cancers when used as a monotherapy. Another CpG drug, CPG 10101, has shown significant effects on hepatitis C virus (HCV) viral load in patients with this prevalent infection. A triple therapy of CPG 10101, ribavirin, and interferon showed particularly promising results in previously treated HCV patients who subsequently relapsed following the initial therapy. Overall, Big Pharma's RNAi buy-in and promising clinical results in patients suggest a robust future for the development of RNAi-based drugs. Nevertheless, the latest clinical studies show that more traditional DNA antisense drugs are alive and well. Important challenges remain, such as the development of ways to improve the bioavailability, toxicity, and stability of RNA- and DNA-based medicine. Problems of off-target effects remain a concern and deserve continued attention. Finally, recent data linking certain RNA motifs, as well as triphosphate RNAs, to stimulation of the innate immune system (see 4Schlee M Hornung V Hartmann G siRNA and isRNA: two edges of one sword.Mol Ther. 2006; 14: 463-470Abstract Full Text Full Text PDF PubMed Scopus (197) Google Scholar for review) predict potential uses of “immune stimulatory” (is)RNA as adjuvant effectors, as has been shown for DNA CpGs.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,228
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,013
Tête enseignante GPT0,283
Écart entre enseignants0,270 · 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 tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreÉditorial

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

En bref

Citations4
Publié2007
Routes d'admission1
Résumé présentoui

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