Insilico Medicine to present its latest research at ICML 2019
Insilico Medicine scientists to present their latest achievements in applications of machine learning to drug discovery at the ICML EXPO
Credit: Insilico Medicine
Tuesday, June 4, 2019 Insilico Medicine, a biotech company developing the end-to-end drug discovery pipeline utilizing the next generation artificial intelligence, will present its latest research at the 36th International Conference on Machine Learning in Long Beach, CA, on June 9th. Insilico Medicine is also very proud to be one of the sponsors of the event this year, which will give a unique opportunity to present our brand and to communicate with the most skilled people of artificial intelligence research.
The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is one of the fastest growing artificial intelligence conferences in the world. Between June 9 and June 15, 2019, at the Long Beach Convention & Entertainment Center in Long Beach, California, ICML will host over 8,000 participants. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.
This year the event kicks off with the ICML Expo held at the Long Beach Convention Center on June 9th. The main focus of the Expo workshop is the application of deep learning techniques to solving problems in drug discovery. In particular, Insilico Medicine scientists will present the applications of modern generative models giving an overview of current architectures and techniques, alongside with the company’s drug discovery pipeline which utilizes multiple data types, in order to identify the most promising targets and generate novel molecular structures with the desired set of parameters.
“We are proud to be the sponsors of ICML 2019 and have our scientists on the ground to learn and exchange ideas. In my opinion, aging research and drug discovery are the two most impactful and altruistic directions every AI scientist should consider contributing to. If you are in Los Angeles on June 9th, please register for the ICML Conference, visit our sessions and consider joining the effort,” said Alex Zhavoronkov, Ph.D, Founder and CEO of Insilico Medicine.
“With the cutting-edge neural network architectures, we can solve previously incurable diseases. With new algorithms, we can generate molecular structures satisfying challenging properties of promising drugs such as high activity, ease of synthesis and low toxicity,” – said Daniil Polykovskiy, Senior Research Scientist at Insilico Medicine.
“Every year ICML gathers researchers from industry and academia bridging the gap between domains and driving the field forward. We at Insilico Medicine are applying cutting-edge research in machine learning to drug discovery and biomarker development. This event is an excellent opportunity to share experience and discuss recent progress, and we are excited to present our scientific advancements,” – said Alex Zhebrak, CTO of Insilico Medicine.
You can find Insilico Medicine team during the ICML 2019 week (June 9-12) at the Insilico Medicine Booth #224.
Expo details: Sunday, June 9th:
Talk “Generative Models for Drug discovery”
Hall B, at 10:30 am
Workshop “Machine Learning for Drug discovery”
Room 103, at 2 pm.
For further information, images or interviews, please contact:
Contact: Klug Gehilfe
Conference Website: https:/
Insilico Medicine is regularly publishing research papers in peer-reviewed journals. The company was first to apply the generative adversarial networks (GANs) to the generation of the new molecular structures with the specified parameters and published a seminal peer-reviewed paper submitted in June 2016. The concept was further extended and augmented with advanced memory and reinforcement learning. One of the latest papers published in the Journals of Gerontology demonstrated the application of the deep neural networks to assessing the biological age of the patients. The latest special issue in Molecular Pharmaceutics featured several research papers by Insilico Medicine. Insilico published an overview of its results in aging research including the development of AI aging biomarkers, target identification, cross-species comparison and geroprotector discovery in Aging Research Reviews, one of the highest-impact journals in the field.
About Insilico Medicine, Inc
Insilico Medicine is an artificial intelligence company headquartered in Rockville, with R&D and management resources in Belgium, Russia, UK, Taiwan, and Korea sourced through hackathons and competitions. The company and its scientists are dedicated to extending human productive longevity and transforming every step of the drug discovery and drug development process through excellence in biomarker discovery, drug development, digital medicine, and aging research.
Insilico pioneered the applications of the generative adversarial networks (GANs) and reinforcement learning for generation of novel molecular structures for the diseases with a known target and with no known targets. In addition to working collaborations with the large pharmaceutical companies, the company is pursuing internal drug discovery programs in cancer, dermatological diseases, fibrosis, Parkinson’s Disease, Alzheimer’s Disease, ALS, diabetes, sarcopenia, and aging. Through a partnership with LifeExtension.com, the company launched a range of nutraceutical products compounded using the advanced bioinformatics techniques and deep learning approaches. It also provides a range of consumer-facing applications including Young.AI.
In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. In 2018, the company was named one of the global top 100 AI companies by CB Insights. In 2018 it received the Frost & Sullivan 2018 North American Artificial Intelligence for Aging Research and Drug Development Award accompanied with the industry brief. Brief company video: https:/