The potential impact of using human genetic data linked to longitudinal electronic medical records on drug development is extraordinary; however, the practical application of these data necessitates some organizational innovations. Vanderbilt has created resources such as an easily queried database of >2.6 million de-identified electronic health records linked to BioVU, which is a DNA biobank with more than 230,000 unique samples. To ensure these data are used to maximally benefit and accelerate both de novo drug discovery and drug repurposing efforts, we created the Accelerating Drug Development and Repurposing Incubator, a multidisciplinary think tank of experts in various therapeutic areas within both basic and clinical science as well as experts in legal, business, and other operational domains. The Incubator supports a diverse pipeline of drug indication finding projects, leveraging the natural experiment of human genetics.
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http://dx.doi.org/10.1089/adt.2016.772 | DOI Listing |
BMC Cancer
January 2025
Department of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Peking, Beijing, 100023, People's Republic of China.
Background: Pancreatic cancer is a highly aggressive neoplasm characterized by poor diagnosis. Amino acids play a prominent role in the occurrence and progression of pancreatic cancer as essential building blocks for protein synthesis and key regulators of cellular metabolism. Understanding the interplay between pancreatic cancer and amino acid metabolism offers potential avenues for improving patient clinical outcomes.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
National and Local United Engineering Lab of Druggability and New Drugs Evaluation, Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, Guangdong Province Engineering Laboratory for Druggability and New Drug Evaluation, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China.
Sorting nexins (SNXs) as the key regulators of sorting cargo proteins are involved in diverse diseases. SNXs can form the specific reverse vesicle transport complex (SNXs-retromer) with vacuolar protein sortings (VPSs) to sort and modulate recovery and degradation of cargo proteins. Our previous study has shown that SNX3-retromer promotes both STAT3 activation and nuclear translocation in cardiomyocytes, suggesting that SNX3 might be a critical regulator in the heart.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, The Fourth Affiliated Hospital of Soochow University, Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Key Laboratory of Drug Research for Prevention and Treatment of Hyperlipidemic Diseases, Soochow University, Suzhou, 215123, China.
Gastric cancer is a malignant gastrointestinal disease characterized by high morbidity and mortality rates worldwide. The occurrence and progression of gastric cancer are influenced by various factors, including the abnormal alternative splicing of key genes. Recently, RBM39 has emerged as a tumor biomarker that regulates alternative splicing in several types of cancer.
View Article and Find Full Text PDFAAPS PharmSciTech
January 2025
OSIS, Silver Spring, Maryland, U.S.A.
Travel restrictions during the novel coronavirus, SARS-CoV-2 (COVID-19) public health emergency affected the U.S. Food and Drug Administration's (FDA) ability to conduct on-site bioavailability/bioequivalence (BA/BE) and Good Laboratory Practice (GLP) nonclinical inspections.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Exscientia, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K.
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several times more computationally demanding than MM simulations, so there is a trade-off between speed and accuracy. One possible compromise are hybrid machine learning/molecular mechanics (ML/MM) approaches with mechanical embedding that treat the intramolecular interactions of the ligand at the ML level and the protein-ligand interactions at the MM level.
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