Dataset Information

Investigating the Behavior of Published PAINS Alerts Using a Pharmaceutical Company Data Set.

ABSTRACT: Biochemical assay interference is becoming increasingly recognized as a significant waste of resource in drug discovery, both in industry and academia. A seminal publication from Baell and Holloway raised the awareness of this issue, and they published a set of alerts to identify what they described as PAINS (pan-assay interference compounds). These alerts have been taken up by drug discovery groups, even though the original paper had a somewhat limited data set. Here, we have taken Lilly's far larger internal data set to assess the PAINS alerts on four criteria: promiscuity (over six assay formats including AlphaScreen), compound stability, cytotoxicity, and presence of a high Hill slope as a surrogate for non-1:1 protein-ligand binding. It was found that only three of the alerts show pan-assay promiscuity, and the alerts appear to encode primarily AlphaScreen promiscuous molecules. Although not enriching for pan-assay promiscuity, many of the alerts do encode molecules that are unstable, show cytotoxicity, and increase the prevalence of high Hill slopes.

SUBMITTER: Vidler LR

PROVIDER: S-EPMC6088356 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Investigating the Behavior of Published PAINS Alerts Using a Pharmaceutical Company Data Set.

Vidler Lewis R LR Watson Ian A IA Margolis Brandon J BJ Cummins David J DJ Brunavs Michael M

ACS medicinal chemistry letters 20180710 8

Biochemical assay interference is becoming increasingly recognized as a significant waste of resource in drug discovery, both in industry and academia. A seminal publication from Baell and Holloway raised the awareness of this issue, and they published a set of alerts to identify what they described as PAINS (pan-assay interference compounds). These alerts have been taken up by drug discovery groups, even though the original paper had a somewhat limited data set. Here, we have taken Lilly's far ...[more]

PMID: 30128069

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Project description:ImportanceThe pharmaceutical industry has made substantial investments in developing processes for sharing individual-participant data (IPD) from clinical trials. However, the utility and completeness of shared IPD and supporting documents must be evaluated to ensure the potential for scientific advancements from the data sharing ecosystem can be realized.ObjectiveTo assess the utility and completeness of IPD and supporting documents provided from industry-sponsored clinical trials.Design, setting, and participantsFrom February 9, 2022, to February 9, 2023, 91 of 203 clinical trials supporting US Food and Drug Administration registrations of anticancer medicines for the treatment of solid tumors from the past decade were confirmed as eligible for IPD request. This quality improvement study performed a retrospective audit of the utility and completeness of the IPD and supporting documents provided from the 91 clinical trials for a planned meta-analysis.ExposuresRequest for IPD from 91 clinical oncology trials indicated as eligible for the request.Main outcomes and measuresThe utility and completeness of the IPD and supporting documents provided.ResultsThe IPD packages were obtained from 70 of 91 requested clinical trials (77%). The median time to data provision was 123 (range, 117-352) days. Redactions were observed in 18 of the acquired IPD packages (26%) for outcome data, 11 (16%) for assessment variables, and 19 (27%) for adjustment data. Additionally, 20 IPD packages (29%) lacked a clinical study report, 4 (6%) had incomplete or missing data dictionaries, and 20 (29%) were missing anonymization or redaction description files. Access to IPD from 21 eligible trials (23%) was not granted.Conclusions and relevanceIn this quality improvement study, there was substantial variability within the provided IPD packages regarding the completeness of key data variables and supporting documents. To improve the data sharing ecosystem, key areas for enhancement include (1) ensuring that clinical trials are eligible for IPD sharing, (2) making eligible IPD transparently accessible, and (3) ensuring that IPD packages meet a standard of utility and completeness.

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Dataset Information

Investigating the Behavior of Published PAINS Alerts Using a Pharmaceutical Company Data Set.

Publications

Investigating the Behavior of Published PAINS Alerts Using a Pharmaceutical Company Data Set.

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