En Es
Categories

Industry News

AI Software Platform Aims to Synthesize Biomedical Knowledge

By HospiMedica International staff writers
12 Jun 2018

Image: The nference AI platform is designed to assist scientists’ abilities to generate holistic data-driven and unbiased hypotheses in a rapid manner (Photo courtesy of Shutterstock).nference (Cambridge , MA, USA), which focuses on artificial intelligence (AI)-powered life sciences, is developing an AI software platform to synthesize the exponentially growing biomedical knowledge.

The nference team, comprised of successful serial tech entrepreneurs and leading clinical, data and research scientists trained at Massachusetts Institute of Technology (MIT) and Harvard Medical School, works closely with pharmaceutical partners to solve the challenges in drug discovery and clinical research. This includes the identification of emerging targets and signaling pathways for disease processes with unmet need, stratification of patients in clinical trials, and prioritization of life-cycle opportunities for drugs in development. The nference AI platform plays a central role in augmenting the scientists’ abilities to generate holistic data-driven and unbiased hypotheses in a rapid manner.

nference uses state-of-the-art neural networks (shallow and deep learning models) for real-time, automated extraction of knowledge from the scientific, regulatory and commercial body of literature. The platform enables a diverse set of applications ranging from R&D to commercial strategy and operations in the life sciences ecosystem. nference is making biomedical knowledge computable, and building its AI platform to serve as the connective fabric for various silos of information that exist across health care enterprises.

“Natural language is the connective fabric across all therapeutic areas and support functions of large pharmaceutical companies,” said Venky Soundararajan, Ph.D., Founder and Chief Scientific Officer of nference and Qrativ. “Our AI platform leverages an ensemble of modern neural networks to decode the structure of literature. This kernel helps establish concordance between context-rich unstructured corpora and deep biological insights from structured databases spanning genomics to real world evidence. This presents a paradigm shift toward hypothesis-free scientific research and AI-augmented R&D decision-making.”

“The nference AI technology is enabling an important step forward in digitizing biology. nference’s approach reimagines big pharma R&D by enabling entirely novel hypotheses to emerge from the triangulation of insights across traditionally siloed structured databases and unstructured text documents,” said Diego Miralles, M.D., scientific advisor to nference and former Head of Johnson & Johnson Innovation. “This powerful platform establishes nference as a leader in the ongoing development of AI-powered drug discovery.”

“In addition to empowering drug discovery, the nference AI technology has the potential to transform both early and late-stage clinical development by allowing trialists and pharmaceutical companies to better guide patient selection and sooner anticipate side effects of novel therapies,” said Michael Gibson, M.D, scientific advisor to nference and Chief Executive Officer of the Baim Institute (Formerly Harvard Clinical Research Institute) and PERFUSE Research Institute at Harvard Medical School.

Related Links:
nference



E-mail Print
FaceBook Twitter Google+ Linked in

Additional news

18 May 2019
AI More Accurate at Predicting Heart Attacks than Physicians
Researchers from the Turku PET Centre have developed an algorithm that “learned” how imaging data interacts by repeatedly analyzing 85 variables in 950 patients with known six-year outcomes.
Read More
18 May 2019
New AI Method Predicts Breast Cancer Five Years in Advance
Researchers from two major institutions have developed a new tool with advanced artificial intelligence (AI) methods to predict a woman’s future risk of breast cancer.
Read More
18 May 2019
Weak AI security Exposes IoT Medical Devices to Risk of Cyberattacks
The proliferation of healthcare internet-of-things (IoT) devices, along with unpartitioned networks, insufficient access controls and the reliance on legacy systems has exposed a vulnerable attack surface that can be exploited by cybercriminals determined to steal personally identifiable information (PII) and protected health information (PHI), in addition to disrupting healthcare delivery processes.
Read More
18 May 2019
Disposable Anesthesia Device Demand Driven by Lower Risk of Transmitting Infections
The global anesthesia devices market is expected to register a CAGR of more than 6% during the period 2019-2023, driven by increasing demand due to advances in anesthesia technology and growing demand for disposable anesthesia devices.
Read More
18 May 2019
MRI Systems Market to Reach USD 11.72 Billion by 2025
The global Magnetic Resonance Imaging (MRI) systems market is expected to grow at a CAGR of 6.4% between 2018 and 2025 to reach USD 11.72 billion by 2025, driven by increased healthcare spending and sophisticated healthcare infrastructure in the developed nations, as well as recent technological advancements.
Read More
18 May 2019
New AR Patient Solution Applies VR to Thoracic Surgery
Surgical Theater, a provider of virtual and augmented reality healthcare services, has launched its first ever 360° Augmented Reality (AR) patient engagement solution that will allow thoracic surgeons to view patient-specific virtual reconstructions in AR.
Read More
08 May 2019
Technological Advancements and Multi-Modality Systems Driving X-ray Detector Market
The global healthcare X-ray detectors market is projected to grow at a CAGR of 6.14% during the forecast period 2018-2024, driven primarily by technological advancements and adoption of multi-modality imaging systems in hospitals.
Read More
08 May 2019
Primary Care Physicians to Drive Growth in Handheld Ultrasound Market
The global market for handheld ultrasound is projected to surpass USD 400 million by 2023. In 2018, sales of handheld ultrasound accounted for less than 2% of the USD 6.9 billion global ultrasound equipment market, with the relatively high cost and limited performance of early generation handhelds limiting growth.
Read More
03 May 2019
New Deep-Learning Model Could Help Predict Lung Cancer Outcomes
A team of researchers used serial image scans of tumors from patients with non-small cell lung cancer (NSCLC) to develop a new deep-learning model that predicted treatment response and survival outcomes better than standard clinical parameters.
Read More
Copyright © 2000-2019 TradeMed.com. All rights reserved. | Terms And Conditions