AIMC Topic: Biological Products
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Design of novel orotransmucosal vaccine-delivery platforms using artificial intelligence.
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Dec 28, 2020
The linings of the oral cavity are excellent needle-free vaccination sites, able to induce immune responses at distal sites and confer systemic protection. However, owing to the mucosal tissues' intrinsic characteristics, the design of effective anti...
Development challenges of high concentration monoclonal antibody formulations.
Drug discovery today. Technologies
Nov 24, 2020
High concentration monoclonal antibody drug products represent a special segment of biopharmaceuticals. In contrast to other monoclonal antibody products, high concentration monoclonal antibodies are injected subcutaneously helping increase patient c...
Virtual Screening for Reactive Natural Products and Their Probable Artifacts of Solvolysis and Oxidation.
Biomolecules
Oct 27, 2020
Chemically unstable natural products are prone to show their reactivity in the procedures of extraction, purification, or identification and turn into contaminants as so-called "artifacts". However, identification of artifacts requires considerable i...
Computational planning of the synthesis of complex natural products.
Nature
Oct 13, 2020
Training algorithms to computationally plan multistep organic syntheses has been a challenge for more than 50 years. However, the field has progressed greatly since the development of early programs such as LHASA, for which reaction choices at each s...
Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.
Biomolecules
Sep 28, 2020
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...
Privileged Scaffold Analysis of Natural Products with Deep Learning-based Indication Prediction Model.
Molecular informatics
May 14, 2020
Natural products play a vital role in the drug discovery and development process as an important source of reliable and novel lead structures. But the existing criteria for drug leads were usually developed for synthetic compounds and cannot be direc...
The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics.
BMC medical genomics
Apr 3, 2020
In this editorial, we briefly summarized the International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) that was held on June 9-11, 2019 at Columbus, Ohio, USA. We further introduced the 19 research articles included in this suppl...
A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products.
Journal of the American Chemical Society
Feb 21, 2020
This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural produc...
Predicting the Associations between Meridians and Chinese Traditional Medicine Using a Cost-Sensitive Graph Convolutional Neural Network.
International journal of environmental research and public health
Jan 23, 2020
Natural products are the most important and commonly used in Traditional Chinese Medicine (TCM) for healthcare and disease prevention in East-Asia. Although the Meridian system of TCM was established several thousand years ago, the rationale of Merid...
Application of a kNN-based similarity method to biopharmaceutical manufacturing.
Biotechnology progress
Dec 16, 2019
Machine learning-based similarity analysis is commonly found in many artificial intelligence applications like the one utilized in e-commerce and digital marketing. In this study, a kNN-based (k-nearest neighbors) similarity method is proposed for ra...
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