How CRISPR will guide the way to better cancer therapies
Posted 26th July 2019 by Jane Williams
This article was originally published on Open Targets and is republished with kind permission.
For many cancers we don’t have an effective treatment option, and worse still, a lot of the therapies that we use are just not good enough. We need better cancer therapies, and we need them now.
The reason we need new therapies is actually the reason why I got into cancer research. It goes back to when I was only 17 when my Mam was diagnosed with acute myeloid leukemia (AML). She went through her treatment, chemotherapy, with another 12 patients, and unfortunately she was the only one who survived.
Digital Revolution: Bring Your Cleverness and Wisdom
Posted 1st February 2019 by Joshua Sewell
We are lucky to be living in the middle of the digital revolution. Our access to information, products, and ability to change platforms and paradigms has never been better. Professionals shaping the digital revolution in pharmaceuticals and health care moved the leading edge further forward at the 2nd Global Pharma R&D Informatics and AI Congress.
Lab Data Automation, Optimizing R&D Workflows and Lead Discovery from Biologically Complex Bioassays
Posted 23rd January 2019 by Jane Williams
With an increasing amount of data being generated today, pharma and biotech companies need to develop new technologies and strategies in order to structure, analyse and integrate this big data. If you weren’t able to attend our Global Pharma R&D Informatics & AI Congress, we have made these slides from Ralph Haffner, Dana Caulder and Pierre Farmer available.
Human Genomic Evidence: Revolutionising the identification and prioritisation of targets for better medicines
Posted 17th October 2018 by Jane Williams
Nine out of 10 potential drugs that enter clinical trials never make it to the market. Failure often occurs because the biological target chosen is not well understood. However, it is hard to objectively select targets with a high chance of clinical success because the data required to predict efficacy and safety are complex, dispersed and incomplete. To address this challenge, Open Targets was founded in 2014 as a public-private partnership by GSK, EMBL-EBI and the Wellcome Sanger Institute. The consortium has grown since its launch, welcoming new partners Biogen in 2016, Takeda in 2017, and Celgene in 2018.
Transforming Drug Discovery by Accelerating the Development of More Effective Therapies
Posted 10th October 2018 by Jane Williams
This article was originally published by Technology Networks in August 2018 and is published here with permission.
John Baldoni currently heads up a drug discovery unit at GlaxoSmithKline. Since joining GSK in 1989, John has held numerous positions within the company and has led many significant cross-functional strategic initiatives. He has an impressive 37 years’ experience working within the biopharmaceutical industry.
The recently established Accelerating Therapeutics for Opportunities in Medicine consortium, was conceived by John, with a mission “to accelerate the development of more effective therapies for patients”. ATOM stemmed from the Cancer Moonshot, an initiative that aims to improve the availability of cancer therapies, enhance detection of cancer early on, and improve our ability to prevent cancer.
From data to discovery – the journey to digital innovation
Posted 3rd October 2018 by Jane Williams
Digital innovation in healthcare promises much. But potential and realisation are two very different things.
Researchers at Stanford in the US, for example, have developed an AI algorithm designed to diagnose skin cancer[1]. AI diagnosis was compared with that of 21 dermatologists and it matched the efficacy of its human counterparts. This has significant implications for patients, particularly those who find it difficult to access healthcare professionals. But the implications don’t stop there.
Cutting through the hype: Brandon Allgood talks AI and machine learning
Posted 28th September 2018 by Jane Williams
When we last spoke, Brandon Allgood told us about The Future of AI. This week, we caught up with Brandon and spoke about drug discovery and machine learning algorithms.
Analytics and Big Data in Pharma
Posted 17th September 2018 by Jane Williams
Drug discovery and development is a complex process that requires integration of multiple data points, experiments and calculated risk/benefit assumptions. It is therefore only natural that virtualization and big data analytics are a natural fit for implementations, expected to demonstrate significant cost-effective gains for the betterment of society, providing access to effective and safe medications.
