Evidence map›Paper›PMID 35188649›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Increasing the Value of Data Within a Large Pharmaceutical Company Through In Silico Models.

Alessandro Brigo, Doha Naga, Wolfgang Muster

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alessandro BrigoRoche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Centre Basel, Basel, Switzerland. alessandro.brigo@roche.com.
Doha NagaRoche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Centre Basel, Basel, Switzerland.
Wolfgang MusterRoche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Centre Basel, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present contribution describes how in silico models and methods are applied at different stages of the drug discovery process in the pharmaceutical industry. A description of the most relevant computational methods and tools is given along with an evaluation of their performance in the assessment of potential genotoxic impurities and the prediction of off-target in vitro pharmacology. The challenges of predicting the outcome of highly complex in vivo studies are discussed followed by considerations on how novel ways to manage, store, exchange, and analyze data may advance knowledge and facilitate modeling efforts. In this context, the current status of broad data sharing initiatives, namely, eTOX and eTransafe, will be described along with related projects that could significantly reduce the use of animals in drug discovery in the future.

Indexed as

Drug DiscoveryPharmaceutical PreparationsAnimalsComputer SimulationDrug IndustryInformation DisseminationPharmaceutical PreparationsComputational toxicologyData sharingDrug discoveryICH M7Lead optimizationMachine learningOff-target pharmacologySEND format

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.