Advance in Synthetic Data: Current State and Challenges

Advance in Synthetic Data: Current State and Challenges

Data is essential for decision making and its importance is expanding after the emergence of artificial intelligence (AI)-based technologies and methods. Even before the advent of AI, statistical analysis of real data has been widely performed to support the humans’ predictions. In the field of healthcare, however, data collection encounters the challenges of privacy due...

A Rewritten Textbook in Era of Digitalization, Personalization, Collaboration and Innovation

Innovation in technology have brought about paradigm shifts in pharmaceutical science. The landscape of pharmaceutical industry has changed its appearance over the decades, driven by the necessity to adapt itself to consumer expectation, regulatory forces and demographic shifts. It is substantially required for pharma to keep themselves updated and adjusted to the upcoming era so...

De novo Design and Efficient Synthesis of Orally Bioavailable Small Cyclic Peptides

Cyclic peptides gather interests of many pharmaceutical companies due to the known high potency against various protein targets. The conformationally restricted structure with three-dimensional architecture has enabled us to target proteins called undruggable so far. There are still scarce number of cyclic peptide drug in the market but the number is increasing in this century.1)...

Geometric Deep Learning for Structure-Based Drug Discovery

Humans and molecules are living in the same, three-dimensional world. Drug discovery and development is a great work of managing our internal and enemies’ (like virus’) external system by a precisely and optimally elaborated molecule. Molecule-molecule interaction like PPI needs to be analyzed in a three-dimensional world for deep recognition, hence prediction and design of...

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