NutriGuard™ selected finalist for the Best Health Data Driven Innovation Award at DES#2023

NutriGuard™, Topazium’s AI tool to harness the healthy benefits of food, has been selected as a finalist for the Awards category: BEST HEALTH DATA-DRIVEN INNOVATION at #DES2023*! NutriGuard™ purpose is to promote and preserve health by using deep learning techniques applied to different sources of information. On the one hand, it takes all available information about…

Artificial intelligence in drug discovery: combining clinical and genomic data from cancer patients to identify genetic biomarkers and potential novel targets

Drug discovery is a costly process affected by a high attrition rate. The huge investment from pharma industry in past years has generated a vast wealth of information in the field that constitutes a great opportunity if it is conveniently exploited. Topazium is a company fully committed to creating a new collective intelligence that enables…

Nutraceutical & functional food research & development webinar

NutriGuard is a machine learning framework designed and developed by Topazium to harness the potential of food components for promoting and preserving health. It is inspired by the need to understand the physiological effects exerted by food components from a well-grounded rationale based on scientific evidence. NutriGuard utilizes different sources of information to achieve its goal and…

Finding a needle in a haystack: virtual screening, an artificial intelligence approach to drug discovery

Artificial intelligence (AI) is a technology well suited for dealing with large amounts of information and has long been considered a promising tool in drug discovery. It has made steady in roads in the field in the last decade by improving the probability of success and bringing greater precision, speed, and cost-efficiency to a process…

A machine learning (ML) approach for identifying genetic biomarkers and new molecular targets associated with impaired survival of breast cancer patients

BACKGROUND Machine learning (ML) tools are suitable to dive vast amounts of clinical and genetic information in order to identify genetic biomarkers of worse survival and potential new molecular targets. This study has investigated the ability of one such tool to identify genetic biomarkers associated with higher risk of mortality in breast cancer, biomarkers that…

Prospective evaluation of SkinGuard, a deep algorithmic framework for the classification of neoplastic skin lesions

Introduction. Diagnostic errors between nevic lesions and skin tumors are frequent for non-specialist physicians. Therefore, there is a need to create a simple and practical tool based on artificial intelligence to assists them in distinguishing potentially malignant lesions from benign ones, improving early detection of skin cancer. Objective. To evaluate the performance of SkinGuard, an…

Harnessing the power of AI and HTE, cloud lab and automation data to transform drug discovery

Drug discovery is a lengthy and costly process affected by a high attrition rate. The revolution in experimental sciences brought about by HTE, cloud labs and lab automation should represent an excellent opportunity to completely transform drug discovery and overcome the serious problems that hinder the process. But this transformation will not be possible without…