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CIO Applications Weekly Brief

Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from CIO Applications

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Editor's Pick (1 - 4 of 8)
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Efficient Data Management in the Healthcare Space

Efficient Data Management in the Healthcare Space
Jim Simpson, SVP & CIO, AVMED

Transform Healthcare with a Passion for Innovation

Transform Healthcare with a Passion for Innovation
Patrick Hale, Chief Information Officer, VITAS® Healthcare

Significant technological change often means a cultural shift for the organization, critical learnings from Orlando Health

Significant technological change often means a cultural shift for...
NovletMattis, Chief Information Officer, Orlando Health

Disrupting the CIO Comfort Zone to Innovate and Transform How Behavioral Health Clinics Use Electronic Health Records

Disrupting the CIO Comfort Zone to Innovate and Transform How...
Wes Williams, VP & CIO, Mental Health Center Of Denver

Connected Care

Connected Care
Samuel Alfano , Do, Medical Director, Clinical Informatics, Crozer-Keystone Health System

Navigate an Exceptional Consumer Healthcare Journey

Navigate an Exceptional Consumer Healthcare Journey
Scott Doolittle, CFO, Quantum Health

Keeping Pace with a Changing Healthcare Environment through Academic Detailing

Keeping Pace with a Changing Healthcare Environment through...
Joy Leotsakos, Senior Clinical Pharmacist, Atrius Health

Fulfilling the Promises of Health Information Technology

Fulfilling the Promises of Health Information Technology
Donna Lee Armaignac, Director Best Practice, Baptist Health South Florida

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Making a Breakthrough in Drug Discovery with AI

By CIO Applications| Friday, January 25, 2019
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The discovery of drugs is a long and often an arduous process with the typical marketing time of 14 years, and the cost of the drug is billions. AI offers a way of accelerating development and reducing costs. The development of drugs depends in part on biomedical data. Such data are always highly complex, and the interactions between hundreds of biological entities are also complex.

Today, research at the cutting edge of cancer research involves billions of permutations which could occur. Some cancers grow every two seconds and never die; some grow 16 times every second and die every five days, and some grow every five days, never die. Each calls for a different approach, therapy, or management method.

Science and technology strive to understand the discovery of drugs. It is necessary to know how it works, how to control it, and how to avoid further imbalance in a patient.

Open source software is not available for the required analytical types, and proprietary algorithms are required. BioSymetrics uses AI to process raw phenotypes, imaging, drugs, and genomic data sets and enables researchers to integrate rapid analytics and machine learning capabilities into existing business processes to improve care, improve discoveries, gain business insight, and enable fast data-driven decision-making.

Cambridge Cancer Genomics, a U.S. research foundation, predicts cancer progression from tumor DNA in blood samples using AI technology. The technology allows researchers to determine earlier treatment response and relapse and to use Bayesian adaptive clinical trial design to increase the success of late-stage studies.

CytoReason, an Israel-based bioinformatics company, uses AI to organize and standardize immune-related gene, protein, cell, and microbiome data into a single cell-level, machine-readable immune system view. Company researchers can gain new insights into disease mechanisms, clinical markers, and drug discovery and validation.

Standigm uses state-of-the-art AI technologies to detect and develop drugs, understand how drug compounds interact with people in the real world. The current focus of the company is to forecast new indications for existing medicines. In EU, there is a legislative proposal for new regulations on medical devices, which offers software for medical devices with the purpose of prediction and prognosis.

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