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Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network.

ABSTRACT: As the major issue to limit the use of drugs, drug safety leads to the attrition or failure in clinical trials of drugs. Therefore, it would be more efficient to minimize therapeutic risks if it could be predicted before large-scale clinical trials. Here, we integrated a network topology analysis with cheminformatics measurements on drug information from the DrugBank database to detect the discrepancies between approved drugs and withdrawn drugs and give drug safety indications. Thus, 47 approved drugs were unfolded with higher similarity measurements to withdrawn ones by the same target and confirmed to be already withdrawn or discontinued in certain countries or regions in subsequent investigations. Accordingly, with the 2D chemical fingerprint similarity calculation as a medium, the method was applied to predict pharmacovigilance for natural products from an in-house traditional Chinese medicine (TCM) database. Among them, Silibinin was highlighted for the high similarity to the withdrawn drug Plicamycin although it was regarded as a promising drug candidate with a lower toxicity in existing reports. In summary, the network approach integrated with cheminformatics could provide drug safety indications effectively, especially for compounds with unknown targets or mechanisms like natural products. It would be helpful for drug safety surveillance in all phases of drug development.

SUBMITTER: Xue M

PROVIDER: S-EPMC3657406 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network.

Xue Mengzhu M Zhang Shoude S Cai Chaoqian C Yu Xiaojuan X Shan Lei L Liu Xiaofeng X Zhang Weidong W Li Honglin H

Evidence-based complementary and alternative medicine : eCAM 20130429

As the major issue to limit the use of drugs, drug safety leads to the attrition or failure in clinical trials of drugs. Therefore, it would be more efficient to minimize therapeutic risks if it could be predicted before large-scale clinical trials. Here, we integrated a network topology analysis with cheminformatics measurements on drug information from the DrugBank database to detect the discrepancies between approved drugs and withdrawn drugs and give drug safety indications. Thus, 47 approve ...[more]

PMID: 23737823

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Project description:Background: Hypertension, a risk factor for cardiovascular events, is often associated with chronic kidney disease. This is called hypertensive nephropathy (HN), which negatively affects physical fitness and body mass, leading to economic burden. Traditional Chinese medicine injections (TCMIs) are common traditional Chinese-patent medicine preparations in China. There was a lack of evidence to prove which TCMIs combine with ADs (TCMIs+ADs) may be a therapeutic option for HN. Thus, we systematically reviewed the efficacy and safety of various TCMIs + ADs in patients with HN. Methods: We conducted a comprehensive search of PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, and VIP information resource integration service platform databases for relevant Chinese- and English-language randomized controlled trials (RCTs) published from database inception until May 2021. Literature screening, data extraction, and quality assessment was performed by two reviewers independently but using the same criteria. We performed the effect modeling to analyze the data for all outcomes and ranked each intervention using the P-score. Furthermore, sensitivity analysis, meta-regression, and funnel plots were used to test the stability, heterogeneity, and publication bias, respectively. Results: We included 69 RCTs with 6373 patients and including six TCMIs + ADs. Network analysis indicated that the ginkgo leaf extract and dipyridamole combined with ADs (GLED + ADs) was the most efficacious in terms of 24-h urinary protein excretion [mean difference (MD) = -0.70, 95% confidence interval (CI): -0.82 to -0.58; P-score = 1] and systolic blood pressure (MD = -12.95, 95% CI: -21.03 to -4.88; P-score = 0.88), whereas the salvianolate combined with ADs (SA + ADs) showed the highest effectiveness for diastolic blood pressure (MD = -6.88, 95% CI: -10.55 to -3.21; P-score = 0.9). Based on the combined P-score of network meta-analysis results (88% and 85.26%) and sensitivity analysis results (72% and 71.54%), the biplots showed that the GLED + ADs was the most efficacious intervention in all TCMIs + ADs for primary outcomes, followed by the SA + ADs and sodium tanshinone IIA sulfonate combined with ADs (STS + ADs). There was no significant difference in terms of safety between TCMIs + ADs and ADs alone. Conclusion: Of all the TCMIs + ADs, GLED + ADs, SA + ADs, and STS + ADs may demonstrate a higher efficacy than ADs alone for HN. Weighing with the potential benefits and limitations in methodology, potential heterogeneity and outcomes, we should use various TCMIs with caution in clinical practice. Nevertheless, additional high-quality RCTs are warranted and future research should focus on the clinical value of core outcomes to confirm the effectiveness and safety of TCMIs for HN. Systematic Review Registration: clinicaltrials.gov, identifier CRD42020205358.

Project description:Background: Intrahepatic cholestasis of pregnancy (ICP) seriously threatens the health of pregnant women and newborns. A various number of Chinese prescriptions and patent medicines combined with ursodeoxycholic acid (UDCA) are used for treating ICP in China. However, there are still many doubts in choosing the suitable therapeutic drugs for the treatment of ICP in clinical practice. Methods: Several electronic databases, including PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Biology Medicine disc (CBM), Wanfang, and VIP, were comprehensively searched from the database inception to February 22, 2021. Randomized controlled trials (RCTs) reporting the use of UDCA only, Chinese prescriptions plus UDCA, and patent medicine plus UDCA for the treatment of ICP were collected according to their inclusion and exclusion criteria. Cochrane Reviewers' Handbook version 5.2 was applied for the risk assessment of the included trials. STATA 16.0 software was used for network meta-analysis (NMA). The pruritus score and the serum levels of total bile acid (TBA), alanine aminotransferase (ALT), and aspartate transaminase (AST) in ICP patients served as the primary outcomes. Moreover, this study had been registered in PROSPERO (https://www.crd.york.ac.uk/PROSPERO/#joinuppage), and the registration number is CRD42020188831. Results: Thirty-eight RCTs comprising 3,841 patients meeting the inclusion criteria were included in the network meta-analysis. The NMA results showed that compared with UDCA used alone, Yinchenhao decoction (seven different Chinese prescriptions or patent medicines) plus UDCA dramatically alleviated the primary outcomes of ICP, including the pruritus score, as well as the serum levels of TBA, ALT, and AST. The NMA results showed that the optimal drug ratio for the treatment of ICP was different from the dosage ratio of traditional Yinchenhao decoction. Significantly, the intervention plan f (IP-f) group [the similar prescription of Yinchenhao decoction 2 (Artemisia capillaris Thunb >15 g, Gardenia >9 g, and Rhubarb <5 g) + UDCA] was the best therapeutics among the eight therapies. Conclusion: Overall, the combined use of Chinese prescriptions or patent medicine with UDCA was generally better than UDCA used alone. The dose of IP-f might be a beneficial therapeutic method for the clinical medication of ICP. Clinical Trail Registration: https://www.crd.york.ac.uk/, identifier CRD42020188831.

Dataset Information

Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network.

Publications

Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network.

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