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Compound Data Mining for Drug Discovery
2016In recent years, there has been unprecedented growth in compound activity data in the public domain. These compound data provide an indispensable resource for drug discovery in academic environments as well as in the pharmaceutical industry. To handle large volumes of heterogeneous and complex compound data and extract discovery-relevant knowledge from
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TRPs: Modulation by Drug-Like Compounds
2014Drug-like compounds that exert biological activity towards TRP channels are either being used as cell biological tools or further developed into pharmacological lead structures aiming at therapeutic use in diseased states. Although drug-likeliness is not easy to predict, common rules include a relatively low molecular weight, physicochemical ...
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Prediction of Transporter-Mediated Drug–Drug Interactions Using Endogenous Compounds
Clinical Pharmacology & Therapeutics, 2012Therapy with two or more drugs is more the rule than the exception, particularly in aging societies. Drug-drug interactions are frequently undesirable and may lead to increased toxicity and mortality. Inhibition of transporters is one major mechanism underlying drug-drug interactions.
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Antibody–drug conjugates: Smart chemotherapy delivery across tumor histologies
Ca-A Cancer Journal for Clinicians, 2022Paolo Tarantino +2 more
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Magistral Compounding with 3D Printing: A Promising Way to Achieve Personalized Medicine
Therapeutic Innovation and Regulatory Science, 2022Susanne Kaae +2 more
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