The Digital DNA series explores the role of large-scale genetic testing in science, industry and society. We aim to understand both the benefits and risks of this emerging technology and see what the future may hold. In the finale of our Digital DNA series we talked to Dr Ian Roberts, the Chief Technology Officer of […]
A new data analysis technique has shown success in identifying the faulty genes that cause rare genetic diseases. A Struggle for Diagnosis Despite advances in sequencing technologies, rare disease patients still struggle to receive a diagnosis. Only 30% of patients receive a diagnosis after whole genome sequencing, which is often used as a last resort […]
We talked to Laxmi Parida, Fellow and Computational Genomics Research Lead at IBM, to discuss her recent ground-breaking research paper on an AI algorithm that can distinguish blood cancer subtypes from dark matter DNA. Personalised Medicine for Cancer Patients The future of personalised medicine relies on quick and non-invasive diagnostics. Simple blood tests for tumour […]
Scientists have developed minimally invasive brain probes that can selectively deliver drugs in-vivo and stimulate cells with light. The probes can be wirelessly controlled from a smartphone. It is hoped that the probes will advance understanding of neurodegenerative disease by allowing the manipulation of brain circuits. Delivering drug infusions into the brain has previously been […]
Researchers have revealed the first vaccine purely designed by artificial intelligence (AI). This has the potential to revolutionise the drug discovery process by making it quicker, cheaper and producing more effective drugs. From target discovery to market, the drug discovery process takes on average nine years and millions of dollars. The majority of this time […]
Researchers have found a weakness in software used for genomics data storage, which could leave patients’ information vulnerable to cyber-attacks. The increasing speed and availability of genetic sequencing technologies has enabled personalised medicine to make significant progress over the last few years. Patient’s genetic profiles are considered when choosing chemotherapy treatment and cures are being […]
The amount of data captured by pharma companies today is fast outpacing best use for it. The ever-evolving scope of the field also means that many senior-level professionals do not fully understand the importance of getting data right in their business, or missing a potential opportunity that their rivals seize. Stemming from Front Line Genomics’ […]
Princeton University researchers have used AI techniques to uncover junk DNA mutations which can lead to autism. The findings are the first to link functionally link mutations in regulatory DNA with a disease like autism, and possibly prove that the changes affect how genes are expressed in the brain.
Out of a whole host of engaging and enjoyable moments at Front Line Genomics’ recent Data Driven Drug Development (D4) conference, held in Boston on 20-21 March, one of the most memorable was definitely the triumph of nQ Medical in our innovation showcase, beating out three other contenders for the claim to be “most innovative” of the technologies on display.
TEXLab, a mathematical AI software created by scientists at Imperial College London and the University of Melbourne can predict survival rates of patients with ovarian cancer more accurately than any current method, a trial published in Nature Communications has found.
With so many talks and panels occurring across our four stages and Live Lounge, we understand that it can be pretty hard to pick out the most unmissable discussions at the festival this year. Given the conundrum, we thought we’d help out! We’ve selected a couple of talks and panels occurring across the two days which we think will be incredibly interesting and enormously informative for a whole range of people.
A Boston biotechnology company has built a neural network which examines the overall elements of the human face and compiles a list of the ten genetic syndromes that person potentially has, possibly helping medical professionals narrow down the diagnosis for that individual.
A new AI program can predict the symptoms of a patient’s cancer and their severity of the course of treatment.
Machine learning can help healthcare workers predict whether patients may require emergency hospital admission, new study finds
AMP 2018: Decoding the Cancer Genome: Breakthrough AI Technology Quickly Identifies Actionable Mutations
Explosive advances in next-generation sequencing (NGS) have greatly improved the ability to identify actionable cancer mutations, both for solid and hematological malignancies, and sparked a new era of oncology care. But accurate analysis and proper interpretation of the complex genomic data produced by NGS remain key hurdles.