Insilico to present recent advances in AI for aging biomarkers and age management research

Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for drug discovery, biomarker development and aging research, is pleased to announce the presentation of its Director of Drug Discovery, Dr. Ivan Ozerov, at the 24th Clinical Applications for Age Management Medicine Conference, April 27, 2018, organized by Age Management Medicine Group.

Dr. Ozerov's presentation "Artificial Intelligence for Aging Biomarkers & Age Management Research" will focus on the recent advances in machine learning techniques that outperform classical approaches in biomarker development and complex genomics, transcriptomics and proteomics problems. The session will be devoted to the development of aging biomarkers and customer-oriented age-management systems that utilize multiple AI-driven approaches stacked into an ensemble and trained on multiple medical and biological data.

"We are very happy to present our research at Clinical Applications for Age Management Medicine Conference, which brings together the leading scientists in aging research. The topic of aging biomarkers is rapidly gaining popularity, and we are happy to be at the leading edge of research and one of the innovation drivers in this area", said Alex Zhavoronkov, PhD, the founder and CEO of Insilico Medicine, Inc.

The 24th Clinical Applications for Age Management Medicine Conference aims to introduce and update physicians on the latest science-based clinical information and sophisticated clinical applications during the eye-opening presentations and interactive panel discussions. The conference's agenda includes the highly instructive topics such as cancer and aging biomarkers, genetics and epigenetics in the clinic, stress management in the prevention of dementia, Alzheimer's, and Parkinson's disease, and many others. The event will be held on April 26-29, 2018.

Insilico Medicine is regularly publishing research papers in peer-reviewed journals. It is the first company applied deep generative adversarial networks (GANs) to the generation of new molecular structures with specified parameters and published seminal papers in Oncotarget and Molecular Pharmaceutics. Another paper published in Molecular Pharmaceutics in 2016 and demonstrated the proof of concept of the application of deep neural networks for predicting the therapeutic class of the molecule using the transcriptional response data, received the American Chemical Society Editors' Choice Award. One of the recent papers published in November 2017 described the application of the next-generation AI and blockchain technologies to return the control over personal data back to the individual. One of the latest paper published in the Journals of Gerontology demonstrated the application of the deep neural networks to assessing the biological age of the patients. The most recent paper published in the Oncotarget journal presented the roadmap to enhancing radioresistance for space exploration and colonization.