CureMatch Presents Winning Personalized Medicine & Drug Discovery Abstract at AIMed
Laguna Niguel, CA – December 13, 2017: Igor F. Tsigelny, Ph.D. and Eden Romm of CureMatch will be presenting at AIMed, the most comprehensive conference on Artificial Intelligence (AI) in medicine, on Wednesday, December 13. Romm and Tsigelny along with Valentina L. Kouznetsova authored “Machine-Learning Models for Selection of Drug-Candidates for Treatment of Alzheimer’s Disease”, one of six winning abstracts out of 138 total submissions.
Eden Romm, a medical student at University of California, Santa Barbara and a CureMatch intern will present the poster during the Data and Intelligence IIB: Best Abstracts session in the main auditorium from 10:45-11:45 AM. Igor F. Tsigelny presents another poster during the Abstract Presentations and Reception from 5:30-7:30 on December 13, as well.
Artificial Intelligence in medicine requires interfacing clinical information with analytics to facilitate a data-to-information continuum and ultimately transform knowledge into actionable intelligence. Precision medicine with its complexity and enormity of data to be analyzed is particularly well suited for the portfolio of AI methodologies such as deep learning as similar patients can be identified and assessed. Precision medicine at its highest level requires a disruptive computational platform for new biomedical knowledge discovery.
In, “Machine-Learning Models for Selection of Drug-Candidates for Treatment of Alzheimer’s Disease”, the authors examined the structural, physical, and chemical characteristics of more than a hundred possible drugs for the treatment of Alzheimer’s disease. A machine-learning model was developed for predicting new inhibitors using these descriptors. The method used to build this model is not specific to molecules useful in the fight against Alzheimer’s Disease. For example, new Cancer drugs can be found using this AI approach.
Tsigelny and Romm are research pioneers in intelligent systems and computing. As applied to oncology, the implications of the molecular basis of cancer drugs is extremely important to physicians making decisions on proper tumor treatment. Personalized medicine developments leads to optimal cancer survival rates.
CureMatch is a digital health company which assists physicians with specific treatment decisions on a patient-by-patient basis. Factoring genomics and proteomics information, millions of potential combinations of cancer drugs in massive clinical and pharmacological knowledge databases are scored. Personalized Combination Therapy™ options are ranked using the actionable intelligence generated by proprietary algorithms scouring evidence-based, custom-curated databases. Improved outcomes are the result of matching treatments at the molecular level.
AIMed is the most comprehensive, multidisciplinary conference on artificial intelligence in medicine. We seek to break new ground in the worlds of decision support & hospital monitoring, medical imaging & biomedical diagnostics, precision medicine & drug discovery, cloud computing & big data, digital medicine & wearable technology, and robotic technology and virtual assistants. Our conference, held December 11-14 at the beautiful Ritz-Carlton Laguna Niguel, brings together the leading minds from the worlds of medicine, data science and more.
Link to Winning Abstract
“Machine-Learning Models for Selection of Drug-Candidates for Treatment of Alzheimer’s Disease” https://ai-med.io/
CureMatch®, Inc. is a San Diego-based digital health company focused on personalized medicine and combination therapy in oncology. CureMatch’s Decision Support System guides oncologists in the selection of cancer drugs that are customize for individual patients based on their molecular tumor profile. CureMatch enables oncologists to become experts in personalized medicine by providing them with actionable intelligence towards advanced cancer treatment options. www.curematch.com.
Name: Larissa Anderson