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AI in Drug Discovery Conference 2020

16 - 17 March 2020, London, UK.
SMi group presents the launch of the inaugural AI in Drug Discovery conference taking place in London. AI-empowered machine learning technologies hold the potential of reducing drug discovery associated costs by US$ 70 billion in the upcoming 10 years. With an estimated +39% CAGR, AI in drug discovery is

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Refining Breast Cancer Classification by Multiplexed Imaging

Breast cancer progression can vary significantly between patients. Even within the same tumor, different areas may be composed of different types of cells and characterized by different tumor structures. This heterogeneity makes it challenging to ascertain the severity of a tumor and assess its molecular subtype, thereby affecting the precision of diagnosis and the choice of the most effective treatment approach.

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Open Call SC1-HCO-19-2020: Reliable and Accessible Information on Cell and Gene-Based Therapies

Cell and gene-based therapies have the potential to treat many debilitating diseases and conditions. However, the pace of their clinical development does not meet public expectations. They face difficulties reaching patients because inter alia the complexity and costs of product development, regulatory hurdles and the non-harmonized procedures for reimbursements. In addition, there are concerns over patient safety due to the use of unproven treatments.

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Edible 'Security Tag' to Protect Drugs from Counterfeit

Manufacturing prescription drugs with distinct markings, colors, shapes or packaging isn't enough to protect them from counterfeiting, U.S. Drug Enforcement Administration reports have shown. Purdue University researchers are aiming to stump counterfeiters with an edible "security tag" embedded into medicine.

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Open Call SC1-HCO-20-2020: Coordination of Clinical Research Activities of the European Reference Networks

European Reference Networks (ERNs) have been established under the Directive on Patients' rights in cross-border health care in view of tackling complex or rare diseases and conditions that require highly specialised diagnostic tools and treatments. ERNs in collaboration with other European initiatives will gain major research potential due to their network structure bringing together highly specialised multidisciplinary expertise

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Man versus Machine: Can AI do Science?

Over the last few decades, machine learning has revolutionised many sectors of society, with machines learning to drive cars, identify tumors and play chess - often surpassing their human counterparts. Now, a team of scientists based at the Okinawa Institute of Science and Technology Graduate University (OIST), the University of Munich and the CNRS at the University of Bordeaux have shown that

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Artificial Intelligence (AI) can Detect Low-Glucose Levels via ECG without Fingerpick Test

A new technology for detecting low glucose levels via ECG using a non-invasive wearable sensor, which with the latest Artificial Intelligence can detect hypoglycaemic events from raw ECG signals has been made by researchers from the University of Warwick.

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Bolton NHS Foundation Trust Goes Live with Sunrise Acute Care

Bolton NHS Foundation Trust is now live with Sunrise™ Acute Care, following one of the most extensive initial deployments for the Allscripts electronic patient record in the UK.

The trust went live in A&E and across all of the wards at the Royal Bolton Hospital at the start of October, using a pathway approach.

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Bayer and Exscientia Collaborate to Leverage the Potential of Artificial Intelligence in Cardiovascular and Oncology Drug Discovery

Bayer and Exscientia Ltd., a UK-based Artificial Intelligence (AI)-driven drug discovery company, have entered into a three-year, multi-target collaboration. The partners will work on early research projects combining Exscientia's proprietary AI drug discovery platform and drug design know-how with Bayer's data and drug discovery capabilities.

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Smartphone Cameras can Speed Up Urinary Tract Infection Diagnosis

Biological Engineers at the University of Bath have developed a test that could help medics quickly diagnose urinary tract infections (UTIs), using a normal smartphone camera. Similar in principle to a pregnancy test, the process can identify the presence of harmful E. coli bacteria in a urine sample in just 25 minutes.

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